Global Climate Change: Resilient and Smart Agriculture [1st ed.] 9789813298552, 9789813298569

Table of contents :
Front Matter ....Pages i-xiii
Defining a Policy Nexus for Sustainable Agriculture and Food Security in the Caribbean Region (Wendy-Ann P. Isaac, Wayne G. Ganpat, Puran Bridgemohan, Marlene Attzs)....Pages 1-13
A Review of Climate-Smart Agriculture in Mauritius: Moving Towards a Landscape Approach (Shane Hardowar)....Pages 15-31
Climate-Smart and -Resilient Agricultural Practices in Eastern Dry Zone of Sri Lanka (V. Thadshayini, K. W. G. Rekha Nianthi, G. A. S. Ginigaddara)....Pages 33-68
Impact of Climate Change on Communities, Response and Migration of Insects, Nematodes, Vectors and Natural Enemies in Diverse Ecosystems (J. Sridhar, K. Kiran Kumar, R. K. Murali-Baskaran, Sengottayan Senthil-Nathan, Suraj Sharma, M. Nagesh et al.)....Pages 69-93
The Current Policies and Practices Behind Scaling Up Climate-Smart Agriculture in India (Dhanya Praveen, Andimuthu Ramachandran)....Pages 95-107
Building Resilience to Climate Change in Agriculture: Integrated Natural Resource Management and Institutional Measures (K. H. Anantha, Kaushal K. Garg, Sreenath Dixit)....Pages 109-136
Climate-Smart Small Millets (CSSM): A Way to Ensure Sustainable Nutritional Security (H. M. Vinaya Kumar, Naveenkumar Gattupalli, S. C. Babu, Anuj Bhatia)....Pages 137-154
Scope and Strategic Intervention for Climate-Smart Agriculture in North Eastern India (N. K. Patra, Suresh Chandra Babu)....Pages 155-186
Sustainable Livestock Management Systems for Indian Rural Livelihood: Mitigation of Climate Change (T. Thamil Vanan, D. Divya Lakshmi)....Pages 187-198
Precision Farming: A Step Towards Sustainable, Climate-Smart Agriculture (Trisha Roy, Justin George K)....Pages 199-220
Integration of Geospatial Technology and Simulation Modelling for Climate Change Studies (Himani Bisht, Shweta Gautam, Riki Sarma, A. K. Mishra, V. K. Prajapati)....Pages 221-247
Geospatial Applications in Modeling Climate Change Impact on Soil Erosion (Suresh Kumar)....Pages 249-272
Extension and Advisory Services for Climate-Smart Agriculture (Saravanan Raj, Saisree Garlapati)....Pages 273-299
Climate Services for Managing Climate Change Impacts on Agriculture (S. D. Attri)....Pages 301-314
Nanotechnology for Mitigation of Global Warming Impacts (K. S. Subramanian, V. Karthika, M. Praghadeesh, A. Lakshmanan)....Pages 315-336
Climate Policy (Javaria Nasir, Muhammad Ashfaq, Rakshanda Kousar)....Pages 337-358

Citation preview

V. Venkatramanan · Shachi Shah  Ram Prasad Editors

Global Climate Change: Resilient and Smart Agriculture

Global Climate Change: Resilient and Smart Agriculture

V. Venkatramanan • Shachi Shah • Ram Prasad Editors

Global Climate Change: Resilient and Smart Agriculture

Editors V. Venkatramanan School of Interdisciplinary and Transdisciplinary Studies Indira Gandhi National Open University New Delhi, Delhi, India

Shachi Shah School of Interdisciplinary and Transdisciplinary Studies Indira Gandhi National Open University New Delhi, Delhi, India

Ram Prasad Department of Botany, School of Life Sciences Mahatma Gandhi Central University Motihari, East Champaran, Bihar, India

ISBN 978-981-32-9855-2 ISBN 978-981-32-9856-9 https://doi.org/10.1007/978-981-32-9856-9

(eBook)

# Springer Nature Singapore Pte Ltd. 2020 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore

Preface

Global climate change affects people, ecosystems, and livelihoods across the world. The global warming trend in the recent past is unprecedented. The global mean surface temperature has increased about 1  C above pre-industrial levels and it is likely to reach 1.5  C between 2030 and 2052 if it continues to increase at the current rate. The occurrence of extreme weather events including but not limited to floods and droughts; heat and cold waves; super cyclones; and typhoons will not be uncommon in the future. Climate change-induced risks are already observed in human and natural ecosystems. Climate-sensitive agroecosystem is no exception. The complex agriculture production systems are constrained by a multitude of factors which are primarily the products of human actions. Global climate change will exacerbate the agricultural risks through their effects on crop ecology, crop geography, crop environment, crop production, agricultural resources, and agricultural supply chain and commodity prices. The panacea to the climate risks in agriculture lies in the transformation of agriculture into a resilient and smart agriculture production system. Smart agriculture emanates from the smart use of agriculture inputs—fertilizers and water; smart agriculture technologies and practices; application of agroecological principles; agro-advisory services and climate services; and decarbonizing of the agriculture economy. Further, linking the climate mitigation and adaptation in the agricultural production systems per se paves way for resilient agriculture. In effect, the resilient and smart agriculture endeavors to sustain the production and productivity, ensure global food and nutritional security, and decarbonize the agricultural production. The book attempts to present the intersection of global climate change and resilient and smart agriculture. The book targets the scientists, researchers, academicians, graduates, and doctoral students working on agricultural sciences and environmental science. It also caters to the needs of policymakers to frame policies on climate change, food, and nutritional security. We are deeply honored to receive chapters from leading scientists, and professors with rich experience and expertise in the field of global climate change, sustainable agriculture, and climate policy. The chapters cover a wide spectrum of resilient and smart agriculture—climate-smart agricultural practices in the Caribbean region, Mauritius, Sri Lanka, and India; landscape approach in climate-smart agriculture; policies to scale up climate-smart agriculture; building resilience in agriculture; precision farming; climate-smart millet production in climate-constrained v

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Preface

environment; sustainable livestock production; integrated natural resource management; geospatial technologies and crop simulation modelling in climate change studies; extension and advisory services for climate-smart agriculture; climate services for climate management; nanotechnology applications for climate change mitigation; and pest-natural enemy dynamics in the changing climate. Our sincere gratitude goes to the contributors for their insights on global climate change and climate-smart agriculture. We sincerely thank Dr. Naren Aggarwal, Springer, and Ms. Aakanksha Tyagi, Mr. Ashok Kumar, and Mr. John Martyn of Springer Nature for their generous assistance, constant support, and patience in finalizing this book. New Delhi, India New Delhi, India East Champaran, Bihar, India

V. Venkatramanan Shachi Shah Ram Prasad

Contents

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Defining a Policy Nexus for Sustainable Agriculture and Food Security in the Caribbean Region . . . . . . . . . . . . . . . . . . . . . . . . . . Wendy-Ann P. Isaac, Wayne G. Ganpat, Puran Bridgemohan, and Marlene Attzs

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A Review of Climate-Smart Agriculture in Mauritius: Moving Towards a Landscape Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . Shane Hardowar

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Climate-Smart and -Resilient Agricultural Practices in Eastern Dry Zone of Sri Lanka . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . V. Thadshayini, K. W. G. Rekha Nianthi, and G. A. S. Ginigaddara

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Impact of Climate Change on Communities, Response and Migration of Insects, Nematodes, Vectors and Natural Enemies in Diverse Ecosystems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 J. Sridhar, K. Kiran Kumar, R. K. Murali-Baskaran, Sengottayan Senthil-Nathan, Suraj Sharma, M. Nagesh, Pankaj Kaushal, and Jagdish Kumar

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The Current Policies and Practices Behind Scaling Up Climate-Smart Agriculture in India . . . . . . . . . . . . . . . . . . . . . . . . . Dhanya Praveen and Andimuthu Ramachandran

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Building Resilience to Climate Change in Agriculture: Integrated Natural Resource Management and Institutional Measures . . . . . . . 109 K. H. Anantha, Kaushal K. Garg, and Sreenath Dixit

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Climate-Smart Small Millets (CSSM): A Way to Ensure Sustainable Nutritional Security . . . . . . . . . . . . . . . . . . . . . . . . . . . 137 H. M. Vinaya Kumar, Naveenkumar Gattupalli, S. C. Babu, and Anuj Bhatia

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Contents

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Scope and Strategic Intervention for Climate-Smart Agriculture in North Eastern India . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155 N. K. Patra and Suresh Chandra Babu

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Sustainable Livestock Management Systems for Indian Rural Livelihood: Mitigation of Climate Change . . . . . . . . . . . . . . . . . . . . 187 T. Thamil Vanan and D. Divya Lakshmi

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Precision Farming: A Step Towards Sustainable, Climate-Smart Agriculture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 199 Trisha Roy and Justin George K

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Integration of Geospatial Technology and Simulation Modelling for Climate Change Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 221 Himani Bisht, Shweta Gautam, Riki Sarma, A. K. Mishra, and V. K. Prajapati

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Geospatial Applications in Modeling Climate Change Impact on Soil Erosion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 249 Suresh Kumar

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Extension and Advisory Services for Climate-Smart Agriculture . . . . 273 Saravanan Raj and Saisree Garlapati

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Climate Services for Managing Climate Change Impacts on Agriculture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 301 S. D. Attri

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Nanotechnology for Mitigation of Global Warming Impacts . . . . . . 315 K. S. Subramanian, V. Karthika, M. Praghadeesh, and A. Lakshmanan

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Climate Policy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 337 Javaria Nasir, Muhammad Ashfaq, and Rakshanda Kousar

Editors and Contributors

About the Editors V. Venkatramanan He is an Assistant Professor at the School of Interdisciplinary and Transdisciplinary Studies, Indira Gandhi National Open University, New Delhi. His interests include climate-smart agriculture, climate policy, biodegradation, and green technologies for environmental management. He has published more than 20 research papers in peer-reviewed journals, and book chapters.

Shachi Shah She is an environmentalist with nearly two decades of teaching and research experience at various reputed universities and institutes. She is an Associate Professor (Environmental Studies) at the School of Interdisciplinary and Transdisciplinary Studies, IGNOU, New Delhi. Her research interests include green technologies for waste management and energy generation, bioremediation, waste valorization, plant growth-promoting organisms, and biodiversity conservation. Moreover, she has authored more than 50 publications.

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Editors and Contributors

Ram Prasad, Ph.D. He is associated with Department of Botany, Mahatma Gandhi Central University, Motihari, Bihar, India. His research interest includes applied and environmental microbiology, plantmicrobe-interactions, sustainable agriculture, and nanobiotechnology. Dr. Prasad has more than 150 publications to his credit, including research papers, review articles, and book chapters and 5 patents issued or pending, and edited or authored several books. Dr. Prasad has 12 years of teaching experience and has been awarded the Young Scientist Award and Prof. J.S. Datta Munshi Gold Medal by the International Society for Ecological Communications; FSAB fellowship by the Society for Applied Biotechnology; the American Cancer Society UICC International Fellowship for Beginning Investigators, USA; Outstanding Scientist Award in the field of Microbiology by Venus International Foundation; BRICPL Science Investigator Award and Research Excellence Award, etc. He has been serving as editorial board member of several reputed journals including Series Editor of Nanotechnology in the Life Sciences, Springer Nature, USA. Previously, Dr. Prasad served as Assistant Professor, Amity University Uttar Pradesh, India; Visiting Assistant Professor, Whiting School of Engineering, Department of Mechanical Engineering at Johns Hopkins University, Baltimore, USA; and Research Associate Professor at School of Environmental Science and Engineering, Sun Yat-sen University, Guangzhou, China.

Contributors K. H. Anantha ICRISAT Development Centre, ICRISAT, Patancheru, Telangana, India Muhammad Ashfaq University of Agriculture Faisalabad, Faisalabad, Pakistan S. D. Attri India Meteorological Department, New Delhi, India Marlene Attzs Department of Economics, Faculty of Social Sciences, The University of the West Indies, St. Augustine, Trinidad and Tobago Anuj Bhatia Institute of Rural Management, Anand, Gujarat, India

Editors and Contributors

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Himani Bisht Water Technology Centre, ICAR-Indian Agricultural Research Institute, New Delhi, India Puran Bridgemohan Biosciences, Agriculture and Food Technology, The University of Trinidad and Tobago, Arima, Trinidad and Tobago Suresh Chandra Babu Capacity Strengthening Programme, IFPRI, Washington, DC, USA D. Divya Lakshmi Department of Livestock Production Management, Madras Veterinary College, Chennai, India Sreenath Dixit ICRISAT Development Centre, ICRISAT, Patancheru, Telangana, India Wayne G. Ganpat Department of Agricultural Economics and Extension, Faculty of Food and Agriculture, The University of the West Indies, St. Augustine, Trinidad and Tobago Kaushal K. Garg ICRISAT Development Centre, ICRISAT, Patancheru, Telangana, India Naveenkumar Gattupalli Department of Agricultural Extension and Communication, Anand Agricultural University, Anand, Gujarat, India Shweta Gautam School of Forestry and Environment Science, SHIATS, Allahabad, India Justin George K Indian Institute of Remote Sensing, ISRO, Dehradun, India G. A. S. Ginigaddara Department of Agricultural Systems, Faculty of Agriculture, Rajarata University of Sri Lanka, Anuradhapura, Sri Lanka Shane Hardowar Department of Agricultural Production and Systems, Faculty of Agriculture, University of Mauritius, Reduit, Mauritius Wendy-Ann P. Isaac Department of Food Production, Faculty of Food and Agriculture, The University of the West Indies, St. Augustine, Trinidad and Tobago V. Karthika Department of Nano Science and Technology, Tamil Nadu Agricultural University, Coimbatore, India Pankaj Kaushal ICAR-National Institute of Biotic Stress Management, Raipur, Chhattisgarh, India K. Kiran Kumar ICAR-Central Citrus Research Institute, Nagpur, Maharashtra, India Rakshanda Kousar University of Agriculture Faisalabad, Faisalabad, Pakistan Jagdish Kumar ICAR-National Institute of Biotic Stress Management, Raipur, Chhattisgarh, India

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Editors and Contributors

Suresh Kumar Agriculture and Soils, Indian Institute of Remote Sensing, Dehradun, India A. Lakshmanan Department of Nano Science and Technology, Tamil Nadu Agricultural University, Coimbatore, India A. K. Mishra Water Technology Centre, ICAR-Indian Agricultural Research Institute, New Delhi, India R. K. Murali Baskaran ICAR-National Institute of Biotic Stress Management, Raipur, Chhattisgarh, India M. Nagesh ICAR-National Bureau of Agricultural Insect Resources, Bengaluru, Karnataka, India Javaria Nasir University of Agriculture Faisalabad, Faisalabad, Pakistan N. K. Patra Department of Agricultural Extension, SASRD, Nagaland University, Medziphema, Nagaland, India M. Praghadeesh Department of Nano Science and Technology, Tamil Nadu Agricultural University, Coimbatore, India V. K. Prajapati Water Technology Centre, ICAR-Indian Agricultural Research Institute, New Delhi, India Dhanya Praveen Centre for Climate Change and Adaptation Research, Anna University, Chennai, India Saravanan Raj National Institute of Agricultural Extension Management (MANAGE), Hyderabad, India Andimuthu Ramachandran Centre for Climate Change and Adaptation Research, Anna University, Chennai, India K. W. G. Rekha Nianthi Department of Geography, Faculty of Arts, University of Peradeniya, Peradeniya, Sri Lanka Trisha Roy ICAR-Indian Institute of Soil and Water Conservation, Dehradun, India Garlapati Saisree National Institute of Agricultural Extension Management (MANAGE), Hyderabad, India Riki Sarma Water Technology Centre, ICAR-Indian Agricultural Research Institute, New Delhi, India Sengottayan Senthil-Nathan Division of Biopesticides and Environmental Toxicology, Sri Paramakalyani Centre for Excellence in Environmental Sciences, Manonmaniam Sundaranar University, Tirunelveli, Tamil Nadu, India Suraj Sharma ICAR-National Institute of Biotic Stress Management, Raipur, Chhattisgarh, India

Editors and Contributors

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J. Sridhar ICAR-National Institute of Biotic Stress Management, Raipur, Chhattisgarh, India K. S. Subramanian Tamil Nadu Agricultural University, Coimbatore, India V. Thadshayini Regional Directorate of Health Service, Ministry of Health Service, Trincomalee, Sri Lanka T. Thamil Vanan Department of Livestock Production Management, Madras Veterinary College, Chennai, India H. M. Vinaya Kumar Department of Agricultural Extension and Communication, Anand Agricultural University, Anand, Gujarat, India

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Defining a Policy Nexus for Sustainable Agriculture and Food Security in the Caribbean Region Wendy-Ann P. Isaac, Wayne G. Ganpat, Puran Bridgemohan, and Marlene Attzs

Abstract

Low food production, combined with a high dependency on food imports, vulnerability to external economic shocks and climate change in the Caribbean, exacerbates the food security challenge the region faces. To confront the challenges facing regional food security, this chapter suggests policies emphasising their interconnectivity and how they would impact sustainable development systems under the ambit of the new climate-smart agriculture. It focuses on transformative policies that ensure that all people have continued access to sufficient supplies of safe foods for a nutritionally adequate diet and in so doing achieve and maintain health and nutritional well-being of citizens in the Caribbean region. The case is made for policymakers to do more towards ensuring food and nutrition security at the household level, protect and strengthen the citizenry who feed the nation, and act assiduously towards stability and consensus on the way forward in a sustainable manner.

W.-A. P. Isaac (*) Department of Food Production, Faculty of Food and Agriculture, The University of the West Indies, St. Augustine, Trinidad and Tobago e-mail: [email protected] W. G. Ganpat Department of Agricultural Economics and Extension, Faculty of Food and Agriculture, The University of the West Indies, St. Augustine, Trinidad and Tobago P. Bridgemohan Biosciences, Agriculture and Food Technology, The University of Trinidad and Tobago, Arima, Trinidad and Tobago M. Attzs Department of Economics, Faculty of Social Sciences, The University of the West Indies, St. Augustine, Trinidad and Tobago # Springer Nature Singapore Pte Ltd. 2020 V. Venkatramanan et al. (eds.), Global Climate Change: Resilient and Smart Agriculture, https://doi.org/10.1007/978-981-32-9856-9_1

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Keywords

Sustainable agriculture · Food and nutritional security · Climate-smart agriculture · Agricultural policy · Climate policy

1.1

Food and Agriculture Foundations in the Caribbean

Historically, food and agriculture have always been integral to the economies of the Caribbean region (CARICOM). Williams and Smith (2008) characterised agricultural development strategies shaping the economies of the Caribbean as spanning four periods of colonial, immediate post-independence, structural adjustment programme and post-structural adjustment programme years. The current state of food security in the region is tied to its history and past priorities of plantation economies, created by colonialism and according to the report of the Moyne Commission, appointed by the British Government in 1938; the main focus of this strategy was the promotion of export-oriented agriculture on large-scale plantations as this was thought to be consistent with the comparative advantage of the region (Williams and Smith 2008). Historically, the Caribbean was basically a plantation economy for the export of traditional bulk primary products (sugar, rice, cocoa), and supported by preferential trade agreements (EU—Lomé Conventions and Cotonou Agreement). The colonial agrarian strategy in fact created a dual structure with the large-scale, export-oriented crop plantations existing with a large number of smallholder producers, cultivating domestic crops on marginal lands. The Moyne Commission proposed an agricultural diversification strategy based on mixed farming to reduce the inherent inequity pushed by the dual-agrarian structure through land settlement schemes, establishment of marketing boards to stabilise farm income and prices and extension services to farmers on improving agronomic practices (Demas 1987). The post-independence period which followed the colonial era aimed at promoting self-sufficiency in food and import substitution with the development of the meat industry for example and the promotion of macroeconomic and fiscal policies as well as tariff protection, tax holidays, credit schemes and industrial estates and industrial development corporations to facilitate industrial development. This period saw strategies aimed at the promotion of locally produced substitutes in meat and milk. In a nutshell, contemporary Caribbean agriculture has been forced to become a net importer of food and this has only increased food insecurity in the Caribbean region. Foreign imports which are high-valued goods cover every category from food to capital goods. The result was a large import bill and a disincentive to local production fostered by an attitude which maintained that foreign goods or anything with a foreign label was superior to the local products (Bridgemohan and Isaac 2019). According to the CARICOM Secretariat, the food import bill was estimated at some USD $5 billion (FAO 2018). Apart from Belize and Guyana, which produce more food than they import, all the other countries in the region are net importers of food. While the United Nations has announced that the Caribbean region is

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geographically unable to provide 100% food security, Belize, Guyana and Suriname, with comparatively larger land masses, can do a great deal to reduce the region’s vulnerability. There are however some small slivers of hope, as Governments of Guyana and Trinidad have planned for the establishment of facilities to increase agricultural and livestock production, thus reducing the dependence on foreign food imports. The basic problem associated with the import/export economy lies also with the nature of exports and imports. Caribbean agriculture is in the decline mainly due to: • • • •

Removal of preferential access based on quotas Reform of EU trading policies Increased globalisation pressures International competitiveness

The Caribbean people have moved away from the traditional foods and now they have gravitated to a North American diet. With this declining domestic production, there are growing concerns about the state of food security in the region, not to mention increasing nutritional related diseases, such as hypertension, cardiovascular diseases, certain types of cancers and diabetes mellitus, with the increased dependence on imported food spurring vulnerability in food security. Access to affordable and healthy food options is pivotal to contributing to the attainment of food and nutrition security and better health outcomes. Women are at an increased risk to food insecurity as it is reported that one in four women in the region is obese. Statistics suggests that about 44% of women in the Caribbean region are the heads of households. It is therefore reasonable that the gender dimensions should be mainstreamed into policies that address food and economic security (Venkatramanan and Shah 2020). The multidimensional nature of vulnerability in the Caribbean region requires that production systems for sustainable agriculture address issues of the environment, economic profitability and social and economic equity as plans and programmes are developed. The authors posit that there is an opportunity, therefore, to craft an appropriate nexus among the various policy options, thus setting the stage for an enabling framework for sustainable agriculture in the region. Such a policy should encourage agribusiness entrepreneurs, including farmers, to mitigate greenhouse gas emissions through the use of sustainable technologies; for example solar, wind, geothermal and biofuels should be integrated with appropriate adaptation systems, particularly for food production. This chapter also discusses some of the contemporary issues impacting food production and reviews and analyses food security in the CARICOM countries of the Caribbean using a conceptual framework. The chapter advocates the enhancement of domestic food production as the most appropriate way to improve the overall food security and discusses policy strategies for building capacity in local food production systems. One approach to confront the challenges facing regional food security is the development and implementation of policies which emphasise their

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interconnectivity and how they should impact the sustainable development of the new climate-smart agriculture. In effect, “converging demands from human population, food security, climate change mitigation and adaptation, biofuel and oil prices, food prices demand a new transformative, resilient agricultural approach called Climate Smart Agriculture” (Venkatramanan and Shah 2019). The new focus on transformative policies should be to ensure that all people have continued access to sufficient supplies of safe foods for a nutritionally adequate diet and in so doing achieve and maintain health and nutritional well-being of citizens in the Caribbean region. The case would be made for policymakers to do more towards ensuring food and nutrition security at the household level, protect and strengthen the citizenry who feed the nation, and act assiduously towards stability and consensus on the way forward in a sustainable manner.

1.2

Contemporary Issues Impacting Food and Nutrition Security in the Caribbean Region

Wuddivira et al. (2017) described the status of food and nutrition security in the Caribbean region as precarious, citing the “region’s increasing vulnerability to the high incidence of pests and diseases, poor human resource capacity, limited land resources, reliance on inefficient and outdated technologies in food production and processing, low investments in research, the lack of an enabling environment to foster innovation and entrepreneurship and high occurrence of tropical storms, hurricanes, floods, droughts and earthquakes”. These authors go further to say that the volatilities associated with food production and food prices including a high import bill, unsustainable high energy prices, some barriers to trade and the effects of climate change and its impacts further add to the challenges facing fragile Caribbean territories. Attempts to diversify Caribbean agriculture from the plantation system have had limited success and were not sustainable (Bridgemohan and Isaac 2019). There is a concerted shift to small farming, but the small farmers are either: • • • •

Undercapitalised Technologically conservative Sceptical about best practice Vulnerable to climate change

However, many innovative and entrepreneurial farmers and producers have amply demonstrated ways to promote competitiveness (Bridgemohan 2008) through: • Adoption of organic farming • Use of local resources • Non-chemical input

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• Farmer advice and support • Farmer organisation and marketing Industrial agriculture is energy intensive and has high demands on fossil-based fertiliser inputs. It has also been noted that the conventional practices in agriculture are associated with excessive use of agrochemicals, which have been proposed as a probable cause for the highest prostate cancer in the CARICOM countries (Claxton 2009). Therefore, the agricultural system requires a change, which can help to attain self-sufficiency in food production, to produce nutritious and safe food amidst the challenges posed by climate change. One such system, which addresses the concerns of agriculture, could be the practice of sustainable agriculture. The challenges impacting agriculture in the Caribbean region can be summarised as follows according to Isaac et al. (2019):

1.2.1

Technical Issues

• High occurrence of tropical pests and diseases • Lack of drainage and poor irrigation management technologies • Non-availability of local inputs, including seed and high-yielding planting material • Lack of research in the areas of animal and plant breeding • Inadequate market information/price model analysis • Inaccessibility of smallholders/farmers to high-end markets and agro-industries • Absence of regulation (policy) for seed and seedling production • Inappropriate smallholder mechanisation • Lack of post-harvest technologies and cold storage facilities • Minimal value addition and access to export market due to weaknesses in standards and certification capacity

1.2.2

Social Issues

• Aging farmers’ population • Praedial larceny • Lack of appreciation among youth towards the agricultural sector due to history of slavery • Lack of pride towards the agriculture sector that leads to scarcity of labour and high labour cost

1.2.3

Economic Issues

• Low profitability • Low economy of scale

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High cost of production Lack of credit to the land under tenure Lack of specialised credit facility to vulnerable communities Low commercial and financial viability Record-keeping Maximising resource efficiency Diversity of production and income sources

1.2.4 • • • •

Environmental Issues

Overuse of agricultural chemicals Improper pesticide disposal Natural hazards (forest fires and soil erosion) Ecological factors: – Bio-productivity per hour – Water count – Identifying ecosystem vulnerabilities

1.2.5

Policy and Institutional Issues

• Lack of transparency in land tenure and land-use policy • Poor coordination among national and regional organisations • Agricultural activities spread across ministries Development of a new policy should consider models that are tenable in long run; minimise dependence on expensive input; can supplement for fresh food and nutritional requirement; and earn income and forex. These factors have strongly affected the social, environmental and economic aspects of agriculture and have fashioned today’s systems of farming in the Caribbean region. Low food production, combined with a high dependency on food imports, vulnerability to external economic shocks and climate change in the Caribbean, exacerbates the food security challenge the region faces. In 2016, the region’s food import bill was estimated at US $5 billion and it continues to spiral upwards. Caribbean food and nutrition security is threatened by annual hurricanes, drought and floods and unpredictable weather changes. These cyclical natural events have increased in intensity over the recent past, thus making the region even less food secure. Food insecurity also has its impact on hunger and malnutrition as a result of poor food choices. The region has high levels of obesity as households with limited resources tend to spend less on healthy foods, which tend to be costlier. It is suggested that there must be a change in paradigm and systematic support, and that new projects be designed that will positively impact the agricultural industry and healthy population.

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Climate Change, Constraints, Vulnerability and Survival in Small-Scale Food Farming Systems in the Caribbean

Climate change refers to the change in weather patterns due to the build-up of greenhouse gases in the atmosphere, which trap the sun’s heat. Its impact has a devastating effect on “Small Island Developing States” (SIDS) and according to the Paris Agreement, global warming of 2  C is projected to further reduce crop yields and nutrition. The Intergovernmental Panel on Climate Change report highlights that global warming of 1.5  C may substantially reduce agricultural yield. The major effects of a changing climate include warmer temperatures causing rising sea temperatures, more natural disasters such as hurricanes, change in rainfall patterns and coastal erosion. Further, warmer temperatures may also result in the loss of species diversity and increased vegetation of noxious plant species which can adapt to warmer temperatures. The Caribbean has experienced several disasters within recent times, which have caused millions of dollars in damage to agriculture, seriously threatening food security. The destructive impacts of climate change— increasingly frequent and severe storms, droughts and floods—pose an ongoing threat to the region’s agricultural infrastructure and thus to its food and nutritional security. Underlining the need to build resilience to shocks, including through the development of climate-sensitive agriculture, water management programmes and drought- and flood-resistant seeds, is a critical mitigation strategy. In this regard, climate-smart agriculture technologies play a pivotal role in agricultural transformation and provide insurance against climate change impacts and achieve food security (Venkatramanan and Shah 2019). Significant losses are likely to continue if more is not done to identify what needs to be done to mitigate and lessen the negative effects of climate change. Climate change is causing “all kinds of challenges” for Caribbean farmers. Caribbean islands are the most vulnerable to climate change. The region may experience frequent severe storms, increased rainfall and flooding and also longer periods of drought. Climate change represents a clear and growing threat to food security in the Caribbean with differing rainfall patterns, water scarcity, heat stress and increased climatic variability making it difficult for farmers to meet the demand for crops and livestock. Many countries that have experienced prolonged drought during the dry season can sometimes expect prolonged rainfall posing significant challenges to food production. If the climate gets drier in some areas, this will ultimately affect crop production. Increased and efficient irrigation systems can mitigate against this, but the water for irrigation may not be available if rainfall decreases. With increased rainfall however, more flooding can be expected as well as hillside erosion in areas where natural forest cover has been removed for agriculture or other developments. Higher temperatures will also make more strenuous activities uncomfortable such that more energy consumption will be required through the use of air conditioning and refrigeration. Warmer temperatures may also lead to increased pest and disease occurrences as pest cycles are significantly reduced.

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Given the region’s vulnerability to the effects of climate change, and the threat it places on agricultural production and food security, there is an urgent need to protect Caribbean food systems, with research targeted at the areas under threat. Research must therefore identify the likely climate change scenarios and the production areas to be prioritised. For example, consideration should be given to the development of high-temperature-resistant and high-temperature-preference varieties; gene banks to preserve diversity; seed banks and securing of planting reserves to restart agricultural production after disasters; and ways to increase shelf life. Attention should also be focused on projects that encourage value addition of food commodities to enhance attractiveness over imported varieties; research to control invasive species and new pest and diseases; soil and water management studies; and investments and research on sustainable cropping systems. Urgent actions are needed to ensure sustainable food production systems, revitalise the agricultural sector, promote rural development and empower traditionally excluded groups, especially smallholder farmers and small-scale producers within local food systems. Nutrition is also in the spotlight as a key component of these efforts. Strengthening the resilience of rural communities and promoting the preservation and restoration of resources and ecosystems have key importance for ensuring the well-being of vulnerable segments of the population. Greater investment in the agriculture sector is needed to enhance food security and nutrition. Promotion of family farming with the support of government programmes for distribution of harvests, in coordination with the various regional actions on food security, is the need of the hour. Another priority is to guarantee that food is of a high quality and people make the right nutrition choices. Further, “climate-smart agriculture” measures to promote science-based farming augment the sustainability of agricultural production system. The measures include but are not limited to private sector collaboration, alternate water and waste management, ICT integration, promotion of agro-tourism and capacity building.

1.4

Sustainable Agriculture for Bolstering Food Security in the Caribbean

Agriculture must transform and focus on an ecological modernisation, which will bring new solutions for sustainable agricultural development in the Caribbean region. This can be achieved by increasing crop productivity, diversifying and expanding the range of crops while maximising the use of indigenous and underutilised foods, minimising post-harvest losses, improving the marketing and distribution of farm produce, promoting non-traditional approaches to crop production and increasing the participation of youth and women (Isaac et al. 2019). This transformative ecological modernisation is a system-based approach which looks to the interconnections between policy formation, economy and natural environment with the intention of transitioning operating systems to forms that are in line with the natural ecological process (Orssatto and Clegg 1999). It therefore becomes important

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that we change the whole philosophy of how food is produced, distributed, sold and consumed to address vulnerabilities created by the present agri-food economy. This ecological modernisation will make it possible for sustainable agriculture to become the new global standard, not the exception; the main factors resisting change are political will, lack of policy coherence at many levels, financing, governance and human behaviour. According to Isaac et al. (2019) and Campbell et al. (2016) some of the major initiatives needed to enhance the capacity of local producers to increase food quantity, quality, nutrition and affordability through sustainable climate-smart approaches include the adoption of improved water-smart practices such as rainwater harvesting, protected agriculture systems including greenhouse technology and shade houses, micro-irrigation, raised-bed planting, changes in crop establishment methods, utilisation of weather-smart activities such as ICT-based agro-advisories, crop varieties which can withstand drought and other stresses, nutrient-smart practices including site-specific nutrient management and precision fertilisers using drone technology, residue management using cover crops and green manures, carbon- and energy-smart practices such as agroforestry, silvo-pastures and conservation tillage, small livestock production (sheep and goats), Neotropical wildlife production and knowledge-smart activities including participatory approaches, farmer field schools, farmer-to-farmer sharing and learning, community-based exercises in capacity building, saving and sharing of seeds and community seed banks, crop diversification, market intelligence and off-farm risk management. In effect, technologies which are climate smart, resilient and transformative can provide impetus for the growth of sustainable agriculture; mitigation of and adaptation to climate change; and food and nutritional security (Fig. 1.1) (Venkatramanan and Shah 2019). Therefore, any policy towards sustainable agriculture should be based on agriculture investment, value chain and positive impact on environment, profitability and empowerment of farming community. There must be a paradigm shift towards regenerative protection systems, small-scale farmer productivity and conservation farming systems. Agriculture is inherently a risky undertaking; therefore the sustainable model is predicated on minimising risk, viz: • • • • • •

Unpredictable weather Pest and diseases High transaction cost Unreliable market prices Food safety and standards Discerning consumer and markets

1.5

Capacity Building and Research

“The empowerment of food producers in the Caribbean should focus on activities aimed at strengthening local food production and distribution systems while increasing the capacity through innovative education and extension to small

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Fig. 1.1 Matrix of climate-smart agriculture technologies (source: Venkatramanan and Shah 2019)

producers as well as its general citizenry to increase food production through sustainable systems and practices thereby increasing incomes and improving livelihoods” (Isaac et al. 2019). Such an approach should focus on “the development and implementation of an integrated and comprehensive strategy towards building the capacity of small-scale food producers so as to increase productivity and improve livelihoods and income through gender responsive-sustainable agricultural technologies and practices”. Isaac et al. (2019) explained that action research is urgently needed to address the climate risks to food security and the global challenge of reducing greenhouse gas emissions from all sectors, including agriculture in SIDS, an approach which fosters impactful connectivity among a range of

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stakeholders (e.g. different kinds of farmers, local service agencies and development agencies). Bekele and Ganpat (2015) also supported this approach and stressed that for education, extension and training interventions to be effective, new content must be taught and innovative methods must be embraced, beginning at the primary and secondary school levels (at the Caribbean Secondary Examination Certificate [CSEC] and Caribbean Advanced Proficiency Examination [CAPE] curriculum). These authors discuss that for this type of education to be effective, the following three components are required: • Locally relevant, adaptive, empowering and science-based curricula • A sustainable enabling educational environment • Community-based school activities driven and founded on the principle of equity Creative ways can be developed by governments to engage particular stakeholders to access funds and appropriate actions needed for future research and dissemination of knowledge to educate and train the population.

1.6

Policy Considerations for Strengthening Agriculture and Food Security

Most Caribbean agricultural policy frameworks have been reviewed as weak and fragmented (Bridgemohan 2008) due to: – – – – – –

Lack of strategy and direction Lack of prioritisation Understaffing and low budgetary allocations Weak science and technology as well as research and design Over-reliance on donors Marketing and trading system—geared for export and tourist markets

Given the current economic circumstances facing territories in the Caribbean region, it is a necessity for policymakers to do more towards ensuring food and nutrition security at the household level in order to protect and strengthen the citizenry who feed the nation and to act assiduously towards stability and consensus on the way forward in a sustainable manner. Policies must therefore ensure that citizens enjoy safe food in sufficient quantity and quality to satisfy their nutritional needs for optimal health (Isaac et al. 2019). To achieve this, Wuddivira et al. (2017) recommended the following policy considerations that: • Promote healthy eating • Promote low costs and clean energy • Foster technological innovation

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Build human resources Solve international trade issues Strengthen institutional settings Promote sustainable use and management of natural resources The agricultural policy framework should also consider:

• • • • • •

Views of all players in industry Organic farming policies and standards Legislation and regulation on import/export, toxic chemicals and training Budgets for small-scale farming Consultation with stakeholders Farmers association and clusters

To confront the challenges facing regional food security, this chapter suggests forward-looking policies emphasising their interconnectivity and how they would impact sustainable development systems under the ambit of the new climate-smart agriculture. These transformative policies will ensure that all people have continued access to sufficient supplies of safe foods for a nutritionally adequate diet and in so doing achieve and maintain health and nutritional well-being of citizens in the Caribbean region.

1.7

Conclusion

This chapter offered insights about the transformative policies in the Caribbean agriculture. To this end, it is suggested that the policy recommendations to ensure resilient and smart agriculture in the Caribbean must include the following: – Reducing the impact of climate change on food production – Developing climate resilience which focuses on adaptation as well as mitigation strategies for the food and agriculture sector – Enhancing the capacity of relevant institutions to provide climate-related information in collaboration with relevant regional bodies – Integrating climate management considerations – Promoting extension and capacity building as a key enabler for sustainable agriculture/climate/environmental/gender and economic policy in the Caribbean SIDS – Improving access to low-cost healthy foods, and creating supportive environments for healthy eating and adequate access to appropriate healthcare – Educating at all levels that promote sustainable food systems – Realigning national and regional agriculture research agendas to meet the new demand

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References Bekele I, Ganpat W (2015) Education, extension, and training for climate change. In: Ganpat W, Isaac W-A (eds) Impacts of climate change on food security in Small Island developing states. IGI Global, Hershey, PA Bridgemohan P (2008) Incubator farms as a sustainable approach for ‘Neo Farmers’. The 44th Caribbean food crop society conference, University of Florida, Institute of Agriculture and Food Sciences, 13–17 July 2008 Bridgemohan P, Isaac W-A (2019) Agricultural diversification—a strategy out of the economic difficulties of the sugarcane industry. In: Bissessar A-M (ed) Development, political and economic difficulties in the Caribbean. Palgrave Macmillan, Cham, Switzerland Campbell BM, Vermeulen SJ, Aggarwal PK, Dolloff CC, Girvetz E, Loboguerrero AM, Villegas JR, Rosenstock T, Sebastian L, Thornton PK, Wollenberg E (2016) Reducing risks to food security from climate change. Global Food Secur 11:34–43 Claxton M (2009) Ensuring food security; mitigating climate change—has CARICOM made the right policy choices?—Part 1: food security. https://www.alainet.org/images/claxton-hascaricom-made-the-right-policy-choices.pdf Demas WG (1987) Agricultural diversification in the Caribbean community: some issues. In: Caribbean development bank statement to Board of Governors. Caribbean Development Bank, Grand Anse FAO (2018) Food loss analysis: causes and solutions case study on the tomato value chain in the Republic of Trinidad and Tobago. http://www.fao.org/3/I9592EN/i9592en.pdf Isaac W-AP, Felix N, Ganpat WG, Saravanakumar D, Churaman J (2019) Sustainable climatesmart agricultural solutions to improve food and nutrition security in Trinidad and Tobago. In: Bissessar AM (ed) Development, political and economic difficulties in the Caribbean. Palgrave Macmillan, Cham, Switzerland Orssatto RJ, Clegg SR (1999) The political ecology of organizations: toward a framework or analysing business-environment relations. Organ Environ 12:263–279 Venkatramanan V, Shah S (2019) Climate smart agriculture technologies for environmental management: the intersection of sustainability, resilience, wellbeing and development. In: Shah S et al (eds) Sustainable green technologies for environmental management. Springer Nature Singapore Pte Ltd., Singapore, pp 29–51. https://doi.org/10.1007/978-981-13-2772-8_2 Venkatramanan V, Shah S (2020) Synergies between gender mainstreaming and food security. In: Leal Filho W et al (eds) Gender equality, Encyclopedia of the UN Sustainable Development Goals. Springer Nature, Cham, Switzerland. https://doi.org/10.1007/978-3-319-70060-1_18-1 Williams T, Smith R (2008) Rethinking agricultural development: the caribbean challenge. Paper presented at 40th Annual Monetary Studies Conference, St. Kitts Wuddivira MN, de Gannes V, Meerdink G, Dalrymple N, Henry S (2017) Challenges of food and nutrition security in the Caribbean. In: Clegg M, Bianchi E, McNeil J, Herrera Estrella L, Vammen K (eds) Challenges and opportunities for food and nutrition security in the Americas: the view of the academies of science. IANAS regional report. http://www.ianas.org/docs/books/ Challenges_Opportunities.html

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A Review of Climate-Smart Agriculture in Mauritius: Moving Towards a Landscape Approach Shane Hardowar

Abstract

Agriculture needs to be transformed into an effective instrument of climate change mitigation. Climate-smart agriculture (CSA) is a new concept that promotes best agricultural practices particularly integrated crop management, conservation agriculture, intercropping, efficient treatment and storage of manure, animal diversity, improved seeds, and fertilizer management practices among others. This chapter aims at reviewing climate-smart agriculture studies carried out in Mauritius and examines why a landscape approach is followed when moving towards CSA. The research methodology for this study includes a review of literature from Web-based publications, projects, and papers at regional and national levels. Locally available documents on climate change adaptation and mitigation and current practices in climate-smart agriculture in Mauritius have also been considered. It is found that CSA does not appear in the agriculturerelated strategy and action plans of Mauritius. Only few development plans contain elements of CSA. Moreover, very few efforts exist to elucidate the implementation of climate-smart landscapes in Mauritius. Farmers need to be encouraged to adopt climate-smart practices and policy makers should encourage an integrated approach of the climate-smart activities. To achieve a landscape approach, initiatives will require an integrated approach to land management which ensures sustainable policies that can help local farmers cope with the looming effects of climate change. This chapter concludes with recommendations to support the development and implementation of a landscape approach for CSA.

S. Hardowar (*) Department of Agricultural Production and Systems, Faculty of Agriculture, University of Mauritius, Reduit, Mauritius e-mail: [email protected] # Springer Nature Singapore Pte Ltd. 2020 V. Venkatramanan et al. (eds.), Global Climate Change: Resilient and Smart Agriculture, https://doi.org/10.1007/978-981-32-9856-9_2

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Keywords

Climate change · Climate-smart agriculture Mauritius · Mitigation · Adaptation · Landscape approach

2.1

Introduction

The Mauritian agriculture, excluding forestry, is dominated largely by sugarcane cultivation. In 2017, nearly 54,182 ha of agricultural land was devoted to sugarcane production, about 7780 ha to food crops, and nearly 622 ha to tea. The contribution of agriculture to the national GDP was estimated at 3.1% (2017) and the share of the sugar sector in GDP was estimated to be around 1.5% (Statistics Mauritius 2017). The farming community is organized as follows: The sugarcane farmers in Mauritius are normally smallholder farmers. These small farmers are around 12,000 and own less than 10 ha while corporate farmers (about 33) own more than 100 ha of land. Food crop production (106,621 tonnes) is dominated by small-scale farming (around 8000 planters) with an average holding of 0.25 ha and a few large farms that are greater than 10 ha. A wide range of crops including potatoes, onion, tomatoes, chilies, crucifers, garlic, and ginger are commercially cultivated whereas fruits mainly come from backyard production. Fruit production which consists of mainly banana, pineapple, and seasonal fruits such as litchi and mangoes is estimated at 42,000 tonnes produced form an area of about 3000 ha of land (Statistics Mauritius 2017). The ornamental sector regroups around 100 producers/nursery operators exploiting 90–100 ha of agricultural land, mainly in the north, central plateau, and south of the island. The livestock sector consists mainly of farmers involved in the breeding of cattle, goat, sheep, pigs, deer, and poultry. This sector is dominated by a large number of small-scale farmers, around 4000 farmers in the year 2017. The total extent of forest cover in Mauritius is estimated at 47,000 ha representing about 25% of the total land area in the year 2017. The native forests which originally covered most of the island have almost completely disappeared except for a few inaccessible areas, which have been spared the onslaught of deforestation. There are only two types of forest ownership in Mauritius: public and private. Around 22,103 ha are state owned and 25,000 ha are in private lands.

2.2

Climate Change and Agricultural Sector in Mauritius

Small Island Developing States (SIDS) such as Mauritius are more vulnerable to the vagaries of climate change and extreme weather events. Climate change poses a risk to the landscape agriculture in Mauritius. Projected air temperature increases for the Indian Ocean for the period 2010–2039 relative to the 1961–1990 period are estimated to be within the range of 0.51–0.98  C. Water resources are being seriously compromised having negative impacts on rain-fed agriculture, especially in the center-west region of the island. Climate change is affecting agricultural

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productivity and influencing food security as well as livelihoods of communities dependent on agriculture. A rise in atmospheric CO2 level and a corresponding rise in global temperatures will not only affect plant growth and yields, but also alter the regional patterns of precipitation and water availability as well as land erosion and fertility. Tropical regions are more likely to suffer from droughts, hence affecting agricultural production (Lotze-Campen et al. 2005). According to the Mauritius Meteorological Service (MMS), long-term time series of rainfall amount over the past century (1905–2010) shows a decreasing trend in annual rainfall over Mauritius. Furthermore, the duration of the intermediate dry months, the transition period between winter and summer, is becoming longer. In the 1960s, summer rains used to start in November while nowadays rain starts in late December. The number of rainy days has decreased but the frequency of heavy rainfall events has increased. Flash floods and severe droughts are more and more recurrent. All these disturbances in the atmosphere highly impact the microclimates in Mauritius, as the country’s agricultural sector is highly dependent on the El Nino Southern Oscillation (ENSO) for rainfall periods, amounts, and frequencies. This sensitivity explains why an ever-changing climate will have adverse impacts on agriculture.

2.3

Climate-Smart Agriculture (CSA)

The concept climate-smart agriculture (CSA) is gaining popularity as a unifying concept on climate change and agriculture. CSA is defined as “agriculture that sustainably increases productivity, resilience (adaptation), reduces or removes greenhouse gases (GHGs) (mitigation) and enhances the achievement of national food security and development goals (development) also referred to as Triple Wins” (FAO 2010). As coined, defined, and presented by the FAO at The Hague Conference on Agriculture, Food Security and Climate Change in 2010, climate-smart agriculture, forestry, and fisheries is a significant pathway to the achievement of sustainable development goals. It is an integration of the three dimensions of sustainable development (economic, social, and environmental) synchronically addressing food security and climate challenges. It is composed of three main pillars: • Increasing agricultural productivity and incomes sustainably • Adapting and building resilience to climate change • Reducing and/or removing greenhouse gas emissions (FAO 2010) CSA is a holistic and modern approach to developing the technical, policy, and investment conditions to bring about sustainable agricultural development for food security under climate change. Figure 2.1 shows the diagrammatic representation of what climate-smart agriculture encompasses.

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Fig. 2.1 Goals of climate-smart agriculture (source: Venkatramanan and Shah 2019)

2.4

Methodology of Research Work

A key challenge for policy makers and local actors is to understand the CSA strategies adopted by small farmers in their efforts to combat climate change. A review of literature on Web-based publications, projects, and papers at regional and local context was carried out. Locally available documents on climate change adaptation and mitigation and current CSA practices in agriculture in Mauritius from various stakeholders were also reviewed. Secondary research about past studies undergone with respect to climate change and agriculture and CSA in Mauritius was carried out and involved the summary, collation, and synthesis of existing research to identify and collect all relevant documentation available on climate change adaptation and mitigation in agriculture and climate-smart agriculture in Mauritius from various stakeholders.

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Climate-Smart Agriculture in Mauritius

With the increasing concern over the impacts of climate change and its whimsicality upon agricultural practices worldwide, various researchers and academia have researched thoroughly on this especially at international level. Food insecurity is the major pillar that alarms the whole global community on the impacts climate change can bring about in the following years to come. The potential impacts of climatic variability and instability upon agricultural production in developed as well as in emerging countries are extensively documented (Fisher et al. 2005). Some studies in fact show that if climate changes in an appropriate way for developing countries especially African countries in majority, it could eventually have a potential positive impact on agriculture and even be beneficial for the betterment of the known agricultural practices (Mendelsohn and Dinar 1999; Fisher et al. 2005). Facknath (2009) reported on the resilience of food security systems in Africa in the face of a changing climate, along with the challenges involved in estimating sustainable solutions for climate-smart crop protection. In May 2009, the Government of Mauritius devised a model of sustainable development through a visionary approach called the Maurice Île Durable (MID). Launched in 2008 and supported by the “Agence Française de Développement” (AFD), the United Nations Development Programme (UNDP), and the “Université de Technologie de Compiègne” (UTC), the Maurice Île Durable (MID) project consists of a number of policies and initiatives that promote sustainability and sustainable development. One of the objectives of the MID is to make Mauritius less dependent on fossil fuels by enhancing energy efficiency and go-green protocols and increasing the use of renewable energy sources like solar, wind, and tidal energy. Along with that, MID also promotes climate-smart agriculture (CSA) approaches to mitigate climatic impacts on the agricultural sector. A study entitled “The impact of climate change on agriculture in the Republic of Mauritius” investigated the impact of climate change in Mauritius through an econometric study based on a production function approach. It evaluated the impacts of different climatic variables on tomato yields and a socioeconomic survey analyzing small-scale and full-time Mauritian farmers. The survey results demonstrated that 92% of the interviewed Mauritian farmers noticed changes in weather patterns, where 87.8% of these farmers noticed changes in climate over the last 10 years which have affected their yields negatively. Furthermore, it was seen that farmers lacked the appropriate knowledge, capital, or technology to mitigate climate change impacts and adapt their agricultural practices for a more sustainable future (Jönsson 2011). In 2013, a project entitled “A Situational Analysis of Climate Change Adaptation and Mitigation for Agriculture in Mauritius” run by academia of the University of Mauritius clearly demonstrated the different activities in the area of agriculture and their respective relationship towards climate change. The report showed expectancy that the climate change division within the Ministry of Environment and Sustainable Development will coordinate, monitor, and implement activities pertaining to climate change in the multi-sectorial agriculture of Mauritius (Brizmohun-Gopaul et al.

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2013). The study also revealed that even though impacts of climate change are being experienced in the agricultural sector, remedial actions to mitigate the problems are still on a go-slow phase and sometimes even nonexistent. Furthermore, the report stressed on the fact that limited research in the agricultural sector and CSA is a major cause for limited knowledge and poor counseling abilities to guide farmers on how to adapt to climate change. In 2013, the Food Agriculture and Natural Resources Policy Analysis Network (FANRPAN) conducted a program on CSA which covered the following countries: Angola, Botswana, Democratic Republic of the Congo, Kenya, Lesotho, Madagascar, Malawi, Mauritius, Mozambique, Namibia, South Africa, Swaziland, Tanzania, Uganda, Zambia, and Zimbabwe. The main objectives were to: 1. Conduct comprehensive analysis of CSA policies, programs, and institutional arrangements in focal countries 2. Generate CSA research-based evidence 3. Strengthen CSA institutional capacity and support capacity building of young professionals on CSA and food security research 4. Develop evidence-based institutional and substantive policy recommendations 5. Support advocacy campaigns for the development and implementation of responsive CSA policies 6. Support the uptake and up-scaling of CSA practices as best practice in Africa FANRPAN also initiated CSA initiatives such as Strengthening Evidence-Based Climate Change Adaptation Policies (SECCAP) and African Climate and EvidenceBased Policies for CSA (EPCSA). The comprehensive scoping and assessment study of CSA policies in Mauritius (Facknath et al. 2014) implemented by FANRPAN and the FOA reported on the policy framework including CSA-relevant policies where it was highlighted that CSA did not appear in Mauritius agriculture-related strategy and action plans but a number of development plans did contain elements of CSA. Recommendations for policies and programs for CSA as well as CSA-relevant farming techniques were highlighted. According to Facknath et al. (2014), several surveys were carried out on the perception of farmers on the impacts of climate variability and climate change on their production systems, and their adaptation mechanisms showed that about 92% of the farmers interviewed have noted changes in weather patterns over recent years, with more than 80% reporting reductions in quantitative and qualitative crop yields. Observations in the livestock sector included heat stress in the animals, lowered feed quality, lowered feed intake, lower productivity, lower milk production in cattle, reduction in live pig weight from about 100 pounds to 80–85 pounds per head, higher risk and incidence of swine flu and other diseases, higher risk of introduction of new diseases, disturbed younger animals resulting in poorer livestock production, physiological disturbances leading to delay in the onset of the reproductive cycle, slower growth rate of animals, dehydration in animals due to higher temperatures, lowering of meat quality and taste, emergence of diseases, and increased heat-related mortality in poultry. The increasing temperatures have also

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led to lower fodder productivity in the lowlands, resulting in a lowered carrying capacity for deer ranching (Brizmohun-Gopaul et al. 2013). Ramborun (2014) in their studies recommended that there was a need to promote CSA among farmers to become resilient to climate change and increase the adaptive capacity of the farming communities and CSA could be an indispensable tool for food security in Mauritius. Hardowar et al. (2015) reported that there was tremendous potential to support the local agriculture through the triple win of increased productivity, enhanced resilience, and greenhouse gas mitigation. According to the study, a comprehensive approach is needed to increase the resilience of agriculture and agro-food systems together with complementary policies, programs, and investments to mitigate extreme weather conditions and to protect the nutrition security of the poor. The Food and Agricultural Research and Extension Institute (FAREI) has a mandate to carry out agricultural research in Mauritius and has disseminated the following climate-smart technologies which have been adopted by farmers in Mauritius. Some examples include the adoption of new varieties of onions, beans, and Colocasia and new crops such as soya bean; adoption of cultural practices to conserve soil moisture and reduce water loss for example minimum tillage and use of manure, scum, and compost; rain water harvesting in ponds and from rooftops; water-saving technologies for example use of hydrogels (water-absorbent polymers) to retain moisture at root zone level (agrostockosorb applied at 12–15 kg/ha); growing drought-tolerant varieties for example eggplant (Zebrina), melon (Omega), and French beans (Long Tom); modification of environment to minimize heat stress in livestock such as cattle and pigs through cooling and shading; and lowering stocking density in poultry (less poultry head/square meter) to minimize mortality. Since the past decade, numerous climate-related pilot projects and programs have been introduced and run throughout the country. These projects have, as a matter of fact, contributed to a baseline knowledge database in climate change and its corelation to the local agriculture. Table 2.1 is a summary of database of all appertaining climate and agriculture programs which have been accomplished in Mauritius. From these documents, it is observed that CSA does not appear in the agriculture-related strategy and action plans of Mauritius and only a few number of development plans contain elements of CSA. Some climate-smart programs and projects in Mauritius (Facknath et al. (2014)) are as follows: “Under the African Adaptation Programme (AAP), funded by the Government of Japan and implemented by the Ministry of Environment and Sustainable Development, a number of implemented projects envisage the integration of climate change into sectoral plans and strategies, sustainable utilization of wastes for production of biofuels, strategies for reducing fertilizer use, and awareness-raising and capacity building for dealing with climate change. In 2008, the Government of Mauritius set up a Food Security Fund (FSF) to the tune of USD 33 million to assist the crop, livestock and fisheries sectors and to increase climate resilience through projects such as crop insurance schemes and capacity of farmers.

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Table 2.1 Review of existing programs, projects, and activities pertaining to climate change and agriculture, with particular reference to proposed research and training areas (Brizmohun-Gopaul et al. 2013) Title of document Climate change Action Plan (1998)

Salient features Highlighted the high vulnerability of the country to climate change as a SIDS

Initial National Communication to UNFCCC (1999)

Major impacts of climate change on agriculture were identified as: • Change in physiology of crop plants and weeds • Sea-level rise on agricultural land Various technologies are being adopted by the agricultural sector to attain sustainability

Technology Needs Assessment (2004)— Ministry of Environment

National Capacity SelfAssessment (2005)

The primary objective of the NCSA project was to identify national priorities and capacity building needed to address national as well as global environmental issues, in particular, to enhance the capacity of Mauritius to meet its commitments under the three Rio Conventions

Mauritius Meteorological Services (2009)

The science of climate change is followed by the Mauritius Meteorological Service (MMS)

UNFCCC (2010)

Adaptation measures put in place in the agricultural sectors: A Blueprint for a Sustainable Diversified Agri-food Strategy for Mauritius, 2008– 2015, addressing the food security by enhancing selfsufficiency status of a number of strategic crops in the short to medium term

Research/training areas and others The Action Plan highlighted the importance of reducing GHG emissions and increasing the sink capacity Adjustments will depend on the nature of impacts. The adoption of new technologies and management systems will play a key role in adaptation

• Research on CO2 fertilization effects • Research and capacity building are needed to focus on proper remedial measures • Research on the impact of climate change on hydrological cycle and on freshwater availability • Research to quantify vulnerability and adaptation of sugarcane and other non-sugar crops to climate change and the possible change in yield should be taken into consideration • Research on the diffusion of agrochemical and other nutrients Various climatic changes are being observed and research is required to better understand the changes occurring and better predict climatic changes Some of the key adaptation strategies/measures for agriculture include: • The need for introducing new varieties of cultivars • The shifting of regions where actual crops are grown to higher elevations with cooler temperatures

(continued)

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Table 2.1 (continued) Title of document Food Security Fund Strategic Plan (2008–2011)

Salient features The FSFSP has suggested a Risk and Catastrophe Insurance Scheme (RaCis). This scheme/insurance should cover losses of priority crops (already identified crops) as well as goat, cattle, and pigs

UNDP-African Adaptation Programme Project Document (2010): Supporting Integrated and Comprehensive Approaches to Climate Change Adaptation in Africa—The Republic of Mauritius

The AAP intends to build capacity to understand, analyze, and react to future climate change impacts within Mauritius

Mauritius Environment Outlook (2011)

Critical assessment of the environmental state and trends and links them to policy action to serve as a decision support tool The MID project is an opportunity to define a shared vision of sustainability and to develop strategies to reduce vulnerability to natural hazards

Maurice Ile Durable Project

Research/training areas and others All the measures proposed in the FSFC strategic plan aim at increasing the production of food commodities locally in order to strengthen the food system and decrease the net food import bill which is increasing drastically over the years The recent activities carried out by AAP are as follows: Trained ten representatives from ministries, the national meteorological agency, and academia on climate analysis Mainstreamed climate change in the development processes under the Capacity Building on Climate Resilient Policies Road Map Supported the development of the National Environmental Policy and Food Security Fund Strategic Plan, as well as water storage and water harvesting strategies Undertook economic evaluation of ecosystem services and socioeconomic assessment of climate change Increasing pressures on land resources along with unsustainable practices have led to overuse and degradation MID initiative will increase the preparedness of Mauritius to adapt to climate change as far as possible; this will involve mainstreaming adaptation to climate change at the policy level, leading to concrete actions at the operational level (continued)

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Table 2.1 (continued) Title of document The other migrants preparing for change, International Organization for Migration (2011)

Salient features Climate change will further increase uncertainty and exacerbate weather-related disasters, drought, biodiversity loss, and land and water scarcity and affects Small Islands Developing States (SIDS) disproportionately compared to the continents

Research/training areas and others The impacts of climate changes have already been felt in other countries such as Maldives, where communities had to be migrated to other parts of the archipelagos

The majority of policies for sustainable development include climate smart measures. Some of the adaptation actions are included in the following: (i) (ii) (iii) (iv) (v)

The Sugar Sector Strategic Plan (1999–2005). Non-Sugar Sector Strategic Plan (2003–2007). Strategic Options in Crop Diversification and Livestock Sector (2007–2015). The Food Security Strategic Plan (2008–2011). A Blueprint for a Sustainable Diversified Agri-Food Strategy for Mauritius (2008–2015).

Mitigation measures are embedded in (i) The National Environment Policy (2007) which establishes a clear policy framework and sets appropriate environmental objectives and strategies, including the conservation of habitats and ecosystems, protection of native fauna and flora, and enhancement of crop and animal production for food security. (ii) The Multi Annual Adaptation Strategy (2006–2015) which outlines action for the sugar industry for product diversification and energy cogeneration, and promoting agroforestry. (iii) The Environment Protection Act (2002) which has been amended to provide, inter alia, for the setting up of a Multilateral Environmental Agreement (MEAs) Coordinating Committee to ensure better mainstreaming of all MEAs into sectoral and national policies. This includes several climate change related issues, for instance banning of burning of agricultural residues to reduce CO2 emissions and to promote their conversion into composts which can be used in lieu of inorganic fertilizers. (iv) The National Forest Policy (2006) which includes measures to enhance sink capacity through reforestation and better management of existing forests. This can also contribute to preventing soil erosion, maintaining soil fertility through nitrogen fixation and nutrient recycling, etc. and hence contributing to agricultural productivity and climate-smartness. (v) The Long Term Energy Strategy (2009–2025) which sets a target of 35% of renewable energy sources in the national energy profile by the year 2025” (Facknath et al. 2014).

The National Climate Change Adaptation Policy Framework (NCCAPF) aims to integrate climate change in the future development of the country. The NCCAPF establishes national policy adaptation over 20 years, offering coping strategies and

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an action plan for the next decade and establishing a plan for financing for 3 years. It also contains forecasts on how climate change will affect the infrastructure and different sectors of the economy, including agriculture, tourism, fisheries, health, and water sector. The University of Mauritius has set up poles of research excellence (PRE). One of the poles of research excellence is the biofarming, climate change, and climate-smart agriculture hosted by the Faculty of Agriculture. The PRE on CSA is very active, with members undertaking major research projects such as the Global Climate Change Alliance (GCCA+) Flagship initiative to support climate-smart agriculture for smallholders in the Republic of Mauritius and the Development-Smart Innovation through Research in Agriculture (DESIRA) both funded by the European Union.

2.6

Discussion

2.6.1

Need for the Climate-Smart Agriculture Approach in Mauritius

The achievement of food security and agricultural development goals, adaptation and mitigation to climate change, and lower emission intensities per output are a must for the well-being of the future generation in Mauritius. Climate change is already crunching the agricultural sector and food security as a result of increased preponderance of extreme events like acute floods and droughts, and increased unpredictability of weather patterns like fluctuating temperatures and rainfall patterns. This can ultimately lead to reductions in agricultural production and lower incomes in vulnerable areas of Mauritius. The agricultural sector must ultimately become climate-smart to favorably tackle the current food security and climate change challenges ongoing from the past decades. This study has proposed a review of CSA practices and approaches in Mauritius. From the study, the desk review has tried to identify and report information contained in relevant documentation on CSA. The information collected formed the basis of a critical analysis of the actual situation of climate change and agriculture and CSA in Mauritius. It was observed that studies on climate change and agriculture related directly or indirectly to CSA are dispersed among several local institutions, with limited coordination among them. In Mauritius, strengthening and enhancing food security while simultaneously contributing to mitigate climate change and preserving the natural resource base and the vital ecosystem require a transition and transformation of more productive agricultural production systems, handling of inputs more efficiently and effectively, higher level of stability, and lower level of variability in outputs. According to FAO (2013a, b), higher productivity and greater resilient in agriculture require a major turnabout in the approach land, water, soil nutrients, and genetic resources that are allocated and managed to safeguard the efficient and effective usage of these resources.

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CSA is still considered as a new concept since its emergence in 2010. From the desk review of projects on CSA, it is observed that the majority are engaged in the discourse on agricultural practices for climate change adaptation and mitigation but they rarely include the climate-smart terminology. For a climate-smart agriculture to set footing in Mauritius, working at the landscape level with an ecosystems approach, combining forestry, fisheries, crops, and livestock systems is crucial for responding to the impacts of climate change and contributing to its mitigation. Furthermore, inter-sectoral approaches and consistent policies across the agricultural, food security, and climate change should be devised and implemented at all levels. Alongside, institutional and financial support would be needed for small farmers, fishers, and forest-dependent people so that the transition to climate-smart agriculture is effectively performed. To date, some effective climate-smart practices already exist and are already being implemented in Mauritius and this could even be further scaled up, but it would be only achievable with serious investments in building the knowledge base and developing alternate and new technologies. According to FAO (2013a, b), these investments in climate-smart agriculture must be the linkage of financial opportunities from public and private sectors and also incorporation of climate finance into sustainable development agenda. Climate-smart agriculture is the needed pathway for a sound development and food security built on the three pillars: increasing productivity and incomes, enhancing resilience of livelihoods and ecosystems, and reducing and removing greenhouse gas emissions from the atmosphere. Modifying the actual existing agricultural and CSA practices into climate-smart landscape practices in Mauritius at the management level will definitely be a major component in adapting agriculture to climate change. A spectrum of such adaptations for cropping and livestock has been outlined. However, adaptations at this level can be actively influenced by policy decisions to institute or reinforce conditions favorable for adequate adaptation activities through investment in new technologies and infrastructure. Concerning the cropping systems, there are potentially many alternatives of CSA management practices that could be adopted to directly or indirectly deal with forecasted climatic, environmental, and atmospheric changes. These alternate adaptations include: 1. The use of agroforestry with intermingling crops and trees 2. Revamping the structural systems, rates, and intensities of irrigation and other water management 3. Using emerging technologies to harvest water (rainwater harvesting) and conserve soil moisture (crop residue retention, humectants), and use of alternate water bodies (river, lakes) more effectively, when rainfall decreases 4. Administering good water drainage practices to prevent water logging, erosion, and nutrient leaching, when rainfall increases 5. Ensuring proper furrowing practices to have a good primary drainage system 6. Changing the timing or location of cropping activities 7. Diversifying income through altering integration with other farming activities such as livestock raising, aquaculture, agroforestry, and integrated agriculture

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8. High-level diversity of land use, land cover, species, and diversity of plants 9. Elaborating and improving on the effectiveness of pest, disease, and weed management practices through wider use of integrated pest and pathogen management 10. Developing and using varieties and species resistant to pests and diseases 11. Using climate forecasting to reduce production risk These adaptations when adopted in combinations will substantially reduce the negative effect of climate change on agriculture. For the livestock systems, the various climate-smart practices that could be incorporated are: 1. Ensuring additional care to continuously match stock rates with pasture production or grazing areas 2. Modifying rotation of pastures 3. Diversifying the use of forage and animal species and breeds 4. Using altered integration within mixed livestock/crop systems including the use of adapted forage crops 5. Using methane from livestock waste to replace fossil fuels Farmers and livestock keepers should be encouraged to adopt climate-smart practices ranging from conservational agriculture, that is, minimum tillage, to the retention of organic matter, crop rotation, and improved pasture and biogas production. This will help them reduce their carbon emissions, increase their yields, and cope with climatic variability. Developing climate-smart agriculture is thus important to achieve food security and climate change goals.

2.6.2

The Move Towards a Landscape Approach in Mauritius

It is noted that very few efforts exist to elucidate the implementation of climate-smart landscapes in Mauritius. Land use represents the largest climate mitigation potential through land-based carbon sequestration. Agricultural systems need to take a landscape approach and become climate-smart landscapes. A key challenge for landscaping planning will involve the design of land-use models to predict the location of growing crops and the most productive ones. To implement all these CSA practices within their landscapes, multi-stakeholder planning, institutional mechanism, and landscape governance are needed. Adapting to climate change requires an integrated approach, including socioeconomic development, environmental conservation, and disaster risk reduction. The purpose of undertaking climate-smart agriculture approaches based on landscape is to effectively set a baseline of knowledge, and manage and mitigate potential climate risks that will consequently affect our agricultural sector in the near future. An adaptive management approach or adaptation research will help inform decisions by farmers,

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agribusinesses, and even policy makers at governmental levels which may apply over a set range of timeframes from short-term tactical to long-term strategies. A landscape approach taking a holistic and integrated attitude towards land management helps establish sustainable development strategies to adapt to and mitigate climate change. An integrated approach to land management that ensures sustainable policies will help local farmers cope with the looming effects of climate change. The landscape approach should focus on improving livelihoods through an integrated set of activities including agroforestry, climate education, REDD+, and entrepreneurship development. This will benefit farmers economically and emission reductions will be observed. Research in climate-smart agriculture and climate-smart landscape approach must be a priority in the Mauritius Government’s agenda as it will definitely help all the stakeholders to understand how short-term replication strategies may link to longterm options to ascertain that, at a minimum, management and policy decisions implemented over the next decades do not undermine the ability to cope with potentially more sizably voluminous impacts later in the century. Based on the desk review, it was seen that institutions and farmers have developed some tactics and CSA strategies to adapt to climate change and it is understandable that climate change adaptation is largely being dealt with in isolation from other issues like new forms of pests and diseases. With time, however, this situation needs to evolve so that climate change is linked with a much broader set of policies. Climate-smart agriculture policies must inculcate the notion of sustainable development and natural resource management, and even regulatory protocols such as the regulation of genetically modified organisms (GMOs), human and animal health and welfare, and fostering of a good governance practice, among many others. Agricultural adaptation policy has been treated in isolation in a number of countries and research projects. A landscape approach is the ideal route to rural development so that farmers can adopt CSA policies and practices. The private sector should be engaged as a proactive partner in the implementation of agricultural policy. For example, the Medine Agribusiness in Mauritius can generate more credible and accessible climate information services. If Mauritius wants a sustainable transformation of the agricultural sector, a large-scale investment will be needed. It is imperative that small farmers engage in increasing on-farm carbon storage and reducing GHG emissions. CSA should thus be introduced at a landscape scale.

2.6.3

Institutional and Policy Options on Climate-Smart Agriculture

“Agriculture policy-making through the lens of climate change must factor in agricultural sustainability; vulnerability assessment of agro-based households; gender perspectives; policy measures to harmonize the demands of food production, feed and fodder production, and biofuel generation; strategies to improve the farmers or cultivators and other stakeholders through climate-smart adaptation practices like organic farming and agroforestry; capacitating the farmers in climate

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risk management, food value chain transformation; and provision of agricultural inputs and services that include weather-based automated agro-advisories, crop insurance, and social security” (Venkatramanan et al. 2020). Policies for a climate-smart landscape approach should be based on 1. 2. 3. 4.

Motivating farmers to adopt climate-smart practices Adoption of a multi-sectoral approach to policy making Provision of CSA financial incentives Investing in landscape approach research

From studies conducted, there are indications of an increase in awareness about climate change issues by diverse stakeholders including policy makers. However, few studies have covered CSA. Moreover, a lack of empirical evidence on overall impact at community scale and national level will hamper decision-making process towards the development of strategies and policies to support adaptation. Smart agriculture and green retailing projects (Switch Africa) are being undertaken which will accompany farmers and industries to develop sustainable and resilient farming systems in Mauritius.

2.6.4

Recommendations

Key policy recommendations for augmenting agricultural production in Mauritius, enhancing the climate resilience of agro-food system, and minimizing the greenhouse gas emissions from agricultural activity in Mauritius are stated below: The following are recommended: • Encouraging the production and transmission of quality climate information: Since access to information is a priority for most farmers, improving the use of climate science data for agricultural planning can reduce the uncertainties generated by climate change, and improve early warning systems for drought, flood, and pest and disease incidence. • Strategies and adaptation measures that take into consideration climate change scenarios and climate-smart agriculture need to be included in the national agricultural policy. • Design of farmer-friendly posters, pamphlets, and pictures on practices of CSA for instance pamphlets on conservation agriculture and rainwater harvesting can be distributed to farmers. • Promotion of policies that boost CSA by government: Climate-smart agriculture policies must inculcate the notion of sustainable development and natural resource management, and even regulatory protocols such as the regulation of genetically modified organisms (GMOs), human and animal health and welfare, and fostering of a good governance practice, among many others. • A multi-sectoral approach should be adopted to tackle the impact of climate change on food systems.

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• Promotion of financial incentives by policy makers that encourage CSA: Social safety nets could be introduced such as cash transfers, food distribution, and seed and tool distribution. • Encouragement of research in CSA by academia at national and regional levels (FANRPAN and UOM). • A Climate Field School could be set up at the Farmers Field Schools of FAREI with support from the MMS. • Land-use planning policies must be enforced and implemented. • Creating land-use models to plan future cropping patterns. • The Centre for Coordination of Agricultural Research and Development for Southern Africa (CCARDESA) and the UoM launched the Climate Proof Tool workshop in Mauritius in 2018. The tool could be useful to identify adaptation options and assess risks.

2.7

Conclusion

The project shows that there is tremendous potential to support the Mauritian agriculture through the triple win of increased productivity, enhanced resilience climate, and greenhouse gas mitigation. It is important for farmers to learn that there is a range of improved CSA technologies and management practices available which can lead to higher productivity, better water harvesting, improved efficiency in the use of water, and better yield. Such smart practices enable farmers to adapt to climate variability and change, address the increasing irregularity of rainfall patterns, and face climate change by sequestering carbon in soils. A comprehensive approach is needed to increase the resilience of agriculture and of agro-food systems together with complementary policies, programs, and investments to mitigate extreme weather risks and to protect the nutrition security of the poor. CSA holds significant promise for addressing hunger, increasing food production, and enhancing climate resilience. To achieve its full potential, it requires cutting-edge science and research, political commitment, adequate financing, policies, and environments that foster private investment along the value chain. In other words, CSA needs smart science and policies. A landscape approach and adoption of CSA policies and practices are thus important. A holistic landscape approach helps establish sustainable development strategies to adapt to and mitigate climate change. This will help local farmers cope with the looming effects of climate change. The Comprehensive Africa Agriculture Development Programme (CAADP) can also help in policy to support climate-smart landscapes since Mauritius is a signatory of the CAADP compact. Sustainable practices that conserve biodiversity, increase productivity, provide stability in the value chain, and increase profit of farmers are the need of the hour. This can be made possible through development of sustainable landscape. Institutions in Mauritius are already promoting CSA practices. A climate-smart village can be set up which involves researchers, extension officers, NGOs, and farmers so that all risks faced by them are incorporated in plans for land management.

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References Brizmohun-Gopaul R, Ruggoo A, Facknath S, Hardowar S (2013) A situational analysis of climate change adaptation and mitigation for agriculture in Mauritius. Research Project Report. University of Mauritius, Réduit; 72 pages Facknath S (2009) Climate change and resilience of food supply systems. Keynote address, international workshop of experts on global environmental change (including climate change and adaptation) in Sub-Saharan Africa, Pretoria, South Africa, 9–11 Feb 2009 Facknath S, Lalljee V, Boodia N (2014) A comprehensive scoping and assessment study of climate smart agriculture policies in Mauritius. Commissioned by FANRPAN FAO (2010) “Climate-smart” agriculture policies, practices and financing for food security, adaptation and mitigation. Food and Agriculture Organisation, Rome, Italy; 49 pp FAO (2013a) Climate smart agriculture. managing ecosystems for sustainable livelihoods FAO (2013b) Climate smart agriculture sourcebook. FAO Fisher G, Shah M, Tubiello FN, van Helhuizen H (2005) Socio-economic and climate change impacts on agriculture: an integrated assessment, 1990–2080. Philos Trans R Soc B 2005 (360):2067–2083 Hardowar S., Facknath S, Boodia N, Chooneea M (2015) A study of climate smart agriculture practices and technologies adopted by small farmers in response to climate change in Mauritius (Research project report). University of Mauritius, Mauritius, 91p Jönsson M (2011) Impact of climate change on agriculture in Mauritius: a socioeconometric study on Mauritian farming. Second cycle, A2E. SLU, Dept. of Economics, Uppsala Lotze-Campen H, Muller C, Bondeau A, Smith P, Lucht W (2005) How tight are the limits to land and water use? Combined impacts of food demand and climate change. Adv Geosci 4:23–28 Mendelsohn R, Dinar A (1999) Climate change, agriculture, and developing countries: does adaptation matter? World Bank Res Obs 14(2):277–293 Meteorological Services (2009) Climate change impacts on Mauritius. http://statsmauritius.govmu. org/English/Publications/Pages/Census-of-Agriculture-2014.aspx Ramborun (2014) Impact of climate change on farmers’ vulnerability and adaptability with a climate smart agriculture perspective: a case study in the western region of Mauritius. BSc (Hons) Agriculture, Dissertation (Specialization land and water management). University of Mauritius, Mauritius Statistics Mauritius (2017) Digest of agricultural statistics 2017. Statistics Mauritius, Ministry of Finance and Economic Development, Mauritius Venkatramanan V, Shah S (2019) Climate smart agriculture technologies for environmental management: the intersection of sustainability, resilience, wellbeing and development. In: Shah S et al (eds) Sustainable green technologies for environmental management. Springer Nature Singapore Pte Ltd., Singapore, pp 29–51. https://doi.org/10.1007/978-981-13-2772-8_2 Venkatramanan V, Shah S, Prasad R (eds) (2020) Global climate change and environmental policy: agriculture perspectives. Springer Nature, Singapore

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Climate-Smart and -Resilient Agricultural Practices in Eastern Dry Zone of Sri Lanka V. Thadshayini, K. W. G. Rekha Nianthi, and G. A. S. Ginigaddara

Abstract

The climate of Sri Lanka is mainly determined by rainfall, temperature, seasonal pressure, wind system, and humidity. Sri Lanka is a tropical island which is highly vulnerable to the adverse effects of climate change. Climate change in Sri Lanka is mainly characterized by the temporal and spatial variations of temperature as well as rainfall conditions. Sri Lanka is an agricultural country where agriculture is a key contributor to the national economy and the country’s food security. Since the agricultural sector is extremely dependent on natural resources such as water, soil fertility, temperature, and rainfall, it has a higher impact from climate change. Gradual climatic changes including extreme climatic events have already threatened Sri Lankan crop production including rice, livestock production, and the fisheries sector. Two-third of the agricultural areas in Sri Lanka are located in the dry zone, which covers the Northern, Eastern, and South-Eastern parts of the country where the Eastern provincial agriculture contributes significantly to the national agricultural production through both crop and livestock production. The higher degree of sensitivity of the major agricultural crops, livestock, and fisheries to climate change mainly for increased temperature and reduced rainfall and sudden climate vagaries may create both short-term and long-term adverse impacts on food production in eastern dry zone of Sri Lanka. Various mitigation and adaptation strategies for agriculture are adopted by the farming communities against climate change. Many of these climate-smart and V. Thadshayini Regional Directorate of Health Service, Ministry of Health Service, Trincomalee, Sri Lanka K. W. G. R. Nianthi (*) Department of Geography, Faculty of Arts, University of Peradeniya, Peradeniya, Sri Lanka G. A. S. Ginigaddara Department of Agricultural Systems, Faculty of Agriculture, Rajarata University of Sri Lanka, Anuradhapura, Sri Lanka # Springer Nature Singapore Pte Ltd. 2020 V. Venkatramanan et al. (eds.), Global Climate Change: Resilient and Smart Agriculture, https://doi.org/10.1007/978-981-32-9856-9_3

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-resilient practices are age-old and revamped against the present climate change to adopt in different production systems at different scales and intensities. This chapter describes the importance of eastern dry zone agriculture for the country’s economy and various climate-smart agricultural practices adopted by farming communities against climate change in Earthen dry zone of Sri Lanka including a case study done to investigate the influence of rainfall variation on paddy cultivation in the Eastern dry zone of Sri Lanka.

3.1

Introduction

The climate of Sri Lanka is tropical monsoonal with a marked seasonal rhythm of rainfall. It is mainly determined by rainfall, temperature, seasonal pressure, wind system, and humidity. The latitudinal extent of Sri Lanka (5 and 10 North latitude) provides the country with a warm climate, moderated by ocean winds and considerable moisture. The main factors influencing the climate of Sri Lanka can be identified as follows (Rekha Nianthi 2012): • Latitudinal extent and its influences on solar radiation received • The geographical position of Sri Lanka and influence of South Asian monsoonal regimes • Distribution of land and sea (island) • The insularity of Sri Lanka, together with the small area of the island, clearly illustrated by the fact that nowhere on the island is the coast further than 110 km distance • Location of global high- and low-pressure zones • Heat exchange from ocean currents • Relief of Sri Lanka characterized by the Central highlands and distribution of mountain barriers Climate change in Sri Lanka is mainly characterized by the temporal and spatial variations of temperature as well as rainfall conditions. The average yearly temperature for the country as a whole ranges from 26 to 28  C. The mean temperature ranges from a low of 15.8  C in Nuwara Eliya, Central Highland (frost may occur on some days in winter), to high temperature (average) of 29  C in Trincomalee and 37  C in the Northeast coast. Bright, sunny, warm days are common even during the height of monsoonal days and night temperature may vary from 4 to 7  C. Annual mean air temperature anomalies have shown significant increasing trends during the recent decades in Sri Lanka (Basnayake et al. 2002: www.meteo.gov.lk). The rate of increase of mean air temperature for the 1961–1990 period is in the order of 0.016  C per year (Chandrapala 1996: www.meteo.gov.lk). The rainfall distribution in Sri Lanka is influenced by many factors such as monsoonal winds, moving of Inter Tropical Convergence Zone (ITCZ), convections, orography, easterly waves, cyclonic wind circulations, and influences from trade

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winds. With respect to the rainfall, Sri Lanka has been divided into three main climatic zones, namely wet zone, intermediate zone, and dry zone. Further the boundaries of these three zones have been demarcated with consideration of present agricultural land use, distribution of forest species, rainfall, topography, and soils (Rekha Nianthi 2012). The climate in Sri Lanka is tropical monsoonal and consists of very distinctive dry and wet seasons. The seasons in Sri Lanka are first intermonsoonal season (March–April), Southwest monsoonal season (May–September), second inter-monsoonal season (October–November), and Northeast monsoonal season (December–February).

3.2

Climate Change and Sri Lanka

Wickramagamage (2016) has examined the spatial and temporal variation of rainfall trends of Sri Lanka. His study was based on daily rainfall data of 48 stations distributed over the entire island covering a 30-year period from 1981 to 2010 and the study revealed that half of the mean annual pentad series data show negative trends, while the rest show positive trends. By contrast, the rainfall trends of the Southwest monsoonal (SWM) season are predominantly negative throughout the country. The first phase of the Northeast monsoon (NEM1) displays downward trends everywhere, with the exception of the South-eastern coastal area. The strongest negative trends were found in the Northeast and in the Central highlands. The second phase (NEM2) is mostly positive, except in the Northeast. The intermonsoon (IM) period has predominantly upward trends almost everywhere, but still the trends in some parts of the highlands and Northeast are negative. The long-term data at Watawala, Nuwara Eliya and Sandringham show a consistent decline in the rainfall over the last 100 years, particularly during the SWM. There seems to be a faster decline in rainfall in the last three decades. The Northeast monsoon (December–February) is the major season that brings rainfall to the dry zone in Sri Lanka. The Northeast monsoon is predicted to decrease 34% (HadCM3: A2 scenario) and 26% (HadCM3: B2 scenario) in 2050. The Northeast monsoon rainfall in dry zone areas such as Jaffna, Manner, Vavuniya, Anuradhapura, Batticaloa, Trincomalee, and Hambantota is predicted to decrease (De Silva 2017). The highest decrease is predicted in Trincomalee and Batticaloa as 27% (A2) and 29% (B2) in 2050. According to the A2 and B2 scenarios for 2050s compared to the baseline (1961–1990) scenario, there is significant decrease in rainfall during the period from December to February mainly due to the significant decrease in rainfall during January and February months in 2050. In contrast, the Southwest monsoon rainfall is predicted to increase across the country. The average annual temperature is predicted to increase by 1.6  C (A2) and 1.2  C (B2). Highest increase in temperature is predicted in Anuradhapura by 2.1  C (A2) and 1.6  C (B2) which is situated in the dry zone area. The lowest annual average temperature increase is predicted in Nuwara Eliya by 1.1  C (A2) and 1  C (B2) (De Silva 2006). Various studies have predicted that the temperature increases and rainfall decreases

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will definitely create problems on the agricultural activities especially in the dry zone of Sri Lanka.

3.3

Sri Lankan Agriculture and Climate Change

Sri Lanka is a tropical island which is highly vulnerable to the adverse effects of climate change. On the other hand, Sri Lanka is an agricultural country where agriculture is a key contributor to the national economy. Climate change negatively affects the major sectors of Sri Lankan agriculture including plantation and non-plantation agricultural production, farm animal production, fisheries, and forestry. Plantation agriculture contributes to the production of tea, coconut, and rubber, and is mainly export-oriented. Food crop production for domestic consumption, including rice, other cereals, pulses, condiments, vegetables, and fruits, comes under non-plantation agriculture. Hence, the effects of climate change on Sri Lankan agriculture impose greater consequences on both the economy and the national food security. Several locations in Sri Lanka are experiencing a statistically significant longterm increasing trends for annual mean air temperature and decreasing long-term trends in annual precipitation (Chandrapala 1996; Domroes 1996; De Costa 2008). Since last few decades, the country has been experiencing significant changes in the climate system especially including drastic variations in monsoonal rain patterns (Malmgren et al. 2003), long-term drought conditions, and unexpected flooding conditions that are severely affecting the agricultural production in the country. At the beginning of 2016, Sri Lanka faced the worst drought in 40 years which lasted until the mid of 2018 and especially dryzone agricullture got affected. This situation was further worsened by severe floods in mid-2017 in the south-western parts of Sri Lanka. The impact of these continuing droughts and severe floods was disastrous for the country’s food production, economy, and human well-being.

3.3.1

Climate Change Impacts on Crop Production in Sri Lanka

Climate change and variability have been threatening Sri Lankan crop production including rice, which is a staple food crop. Climate change affects crop production mainly because of the gradual increase in temperature, rainfall variability, and elevation of atmospheric CO2 concentration. Crop production is highly sensitive to both short- and long-term changes in climate (De Costa 2010). It was found that paddy, tea, and coconut are the most sensitive crops to variations in temperature and precipitation (Wijeratne and Fordham 1996; Fernando 2000; Esham and Garforth 2013). For any crop, there is an optimum temperature range and the effect of increasing atmospheric temperature on crop growth will depend on the crops’ optimal temperature for growth and reproduction (Hatfield and Prueger 2015). However, sometimes in some areas, warming may benefit some types of crops but if the higher temperature exceeds the optimum temperature of that crop, it will

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definitely cause the reduction in crop yield. Researchers have found that for each 1  C increase in minimum temperature in the dry season, paddy yield declined by 10% (Peng et al. 2004). Increase of daily maximum temperature may decrease the rice spikelet fertility, which directly affects the yield, while increasing night-time mean temperature can cause a significant impact on rice yield (Peng et al. 2004; Venkatramanan and Singh 2009). Higher atmospheric CO2 concentration can affect crop yields. Though there are positive effects of increasing CO2 level on paddy yields, other factors such as temperature changes, atmospheric ozone (O3) concentrations, water, and other nutrient constraints may counteract this potential increase in yield (Wien 2007). Extreme weather conditions including long-term droughts and unexpected flooding conditions can destroy crop cultivations and it directly causes yield reduction. Paddy is a crop that requires a large quantity of irrigation water, especially during the early growing stages. Depending on the soil characteristics and the climate, rice requires 1500–2000 mm of water per season (Bouman 2001). Water stress during the early stages directly affects the reproductive stage by inhibiting pollen development, reducing grain formation, and consequently causing yield reduction. Since the majority of the farmers are totally dependent on rainfall, this situation is much common in dry zone of Sri Lanka especially during the Maha seasons of past few years because of changing monsoonal rain patterns. Grain development of rice is highly sensitive to temperature. During the reproductive stage, when the temperature increases beyond 34  C even for a few hours, a significant increase in grain sterility could be observed (Horie et al. 2000). In Sri Lanka, during the warmer, minor rainfall season (Yala season), increasing grain sterility has been reported from several rice-growing districts in the dry zone where the seasonal temperatures are highly likely to exceed the upper threshold of 34  C (De Costa 2010). For instance, during the last few decades, Sri Lanka has experienced a number of extreme rainfall events, especially in South-western regions during the Southwest monsoon season. At the same time, dry zone of Sri Lanka has experienced severe drought conditions during the paddy- and other field crop-growing seasons. Though dry zone farmers started their paddy cultivation onset of the northeast monsoonal rains, due to the inadequate rainfall their paddy and other field crop cultivations were severely damaged. As a result of long-term drought periods, the soil becomes much drier because of higher evaporation rates. During the severe drought periods, due to lack of irrigation water in natural water bodies, it is not practicable to irrigate crops in most of the areas in Sri Lanka. Further, since most of the weeds, pests, and fungi thrive during the warm moist conditions, severe pest attacks can be observable in both plantation and non-plantation sectors. Since the ranges and distribution of pest and weeds are likely to increase, farmers have to apply different pesticides to protect their yields and as a result of that human health is also threatened. Though higher CO2 levels can stimulate plant growth, it causes reduction in the nutrition value of most food crops. Scientists have observed that rising levels of atmospheric CO2 can cause reduction in the concentration of protein and essential

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minerals in most plant species including rice and it represents a potential threat to human health. Variability of rainfall patterns will not only affect the crop productivity but also cause to disturb the cropping calendar. As a result of delay in the onset of monsoon, shorter cultivation seasons are a common condition in the Sri Lankan context (Esham and Garforth 2013). Coconut, an important plantation crop in Sri Lanka, is also highly vulnerable to climate change. It was confirmed that changes in monsoonal rainfall patterns including reduction of rainfall amount per year and increase in maximum air temperature are the key factors that influence the variability of coconut yield in coconut triangle and other principal coconut-growing areas (Peiris et al. 2004). It is projected that coconut production in all the climate scenarios will not be sufficient to meet the local coconut demand (Peiris et al. 2004). Tea productivity is also affected by the climatic change. Similar to rice, tea also requires a well-distributed rainfall with a minimum of 200 mm per month (Watson 1986). It was shown that the reduction of monthly rainfall by 100 mm could reduce productivity by 30–80 kg/ha/month of made tea (Wijeratne et al. 2007). The initiation and expansion process of young shoots of tea is greatly affected by the vagaries of temperature, ultimately affecting the shoot yield of tea which is the economical part of the cultivation (De Costa and Wijeratne 2007). Sea-level rise poses another threat to coastal agriculture because of salinity development and inundation conditions. It affects the quality of irrigation water in coastal areas and it directly causes a reduction in cultivable land area in the coastal regions. Reduction of productivity of important sectors of agriculture representing rice, coconut, tea, and other agricultural crops directly affects the agricultural exports and hence the national economy of the country.

3.3.2

Climate Change Impact on the Livestock Sector in Sri Lanka

In the Sri Lankan context, impacts of climatic change are considerable in the poultry and dairy sectors as compared to the other livestock sectors. Temperature increase causes heat stress and it directly threatens livestock species especially high-yielding imported breeds and other crossbreeds. Heat stress reduces milk production and over time heat stress can increase vulnerability to severe disease conditions, decrease feed intake, and diminish fertility. Long-term droughts affect the livestock feed supply by decreasing the quality and quantity of forage available to grazing livestock. Since the past few decades, dry zone experienced more intense droughts and hence dry zone extensive dairy farming systems were highly affected because of lack of sufficient feed to the animals. As a result of changes in crop production during the drought, it has become a problem for animals that rely on different grains and their by-products. Climate change also causes changes in the composition of pastures such as the ratio of grasses to legumes and changes in herbage quality (Giridhar and Samireddypalle 2015). Increases in atmospheric CO2 may increase pasture productivity, but it decreases their quality. The quality of some of the forages found in pasturelands decreases with

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higher CO2 concentrations and as a result cattle would need to eat more to get the same nutritional benefits (Giridhar and Samireddypalle 2015). At the same time, higher temperature and warm, moist conditions may increase the prevalence of parasites and diseases that severely affect livestock production. The warmer climatic conditions allow parasites and pathogens to survive more easily and during the excessive rainfall periods there is prevalence of moisture-reliant pathogens CCSP 2008. With increasing use of parasiticides and other animal health treatments to maintain livestock health, the risk of pesticides entering the human food chains also increases (USGCRP 2014).

3.3.3

Climate Change Impact on Fisheries in Sri Lanka

Fisheries is an important economic activity in Sri Lanka. Climate change will affect fisheries and aquaculture mainly through increasing sea surface temperature, acidification, sea-level rise, and associated ecological changes. Especially fish feeding patterns, migration, and breeding behavior of both marine and freshwater fisheries are directly affected by climate change. Indirectly, changes in their physical environments will affect growth, mortality, and reproduction (Barange et al. 2018). In addition, the reduction of available dissolved oxygen content in water affects the productivity and the nutritional value of aquatic products. As a result of sea-level rise, changes in river salinity can be observed and it affects the productivity of freshwater fisheries because it negatively affects their reproduction and breeding behavior. Drought conditions mainly affect the inland fisheries which are dependent on seasonal tanks.

3.4

Overview of Eastern Province of Sri Lanka

Eastern province is one of nine provinces in Sri Lanka which has an area of 9361 square kilometers (Fig. 3.1), mid-year population of 1,677,000, and a population density of 179 (CBSL 2018). The province is surrounded by the Northern province to the North, the Bay of Bengal to the East, the Southern province to the South, and the Uva, Central, and North Central provinces to the West. Ampara, Batticaloa, and Trincomalee are the three districts of Eastern province. Eastern province can be identified as the most diverse province in Sri Lanka, both ethnically and religiously (Department of Census and Statistics, Sri Lanka 2019) (Fig. 3.2).

3.4.1

The Economy of the Eastern Province

Two-third of the agricultural areas in Sri Lanka are located in the dry zone, which covers the northern, eastern, and south-eastern parts of the country where the Eastern province agriculture contributes to a large portion of national agricultural production through both crop and livestock production. The Eastern province is basically an

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Fig. 3.1 Map of the eastern province (source: https://www.wikiwand.com/en/History_of_Eastern_ Tamils)

agriculture-based economy and is commonly known as the “Granary of Sri Lanka.” The GDP share of the Eastern province in 2017 was 5.7% while the contributions of agriculture, industry, and services to PGDP were 15.1%, 19.8%, and 55.8%, respectively (CBSL 2018). The 15.1% contribution of the province in the year 2017 was the highest among all the other provinces in the country which was led by the production of rice and marine fishing. With respect to agriculture, the province contributes 25% of national paddy production, 17% of national milk production, and 21% of national fish production. Maize cultivation in the province is becoming prominent. A large-scale maize cultivation with hybrid seeds and contractual

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Sinhalese

23.2% 36.9%

39.5%

41

Ethnic Group (C 2012)

Tamil

Sinhalese

360,738

Sri Lankan Moor

Tamil

614,184

Other ethnic group

Sri Lankan Moor

574,327 6,261

Other ethnic group

Religion (C 2012) 23%

Buddhist

Buddhist

357,052

Muslim

Hindu

540,153

Christian

Muslim

575,470

Other

Christian

Hindu

37% 34.7%

Other religion

82,683 152

Fig. 3.2 Ethnic group composition of the Eastern province in 2018 (Source: Department of Census and Statistics, Sri Lanka 2019) Table 3.1 Paddy cultivation and production in the Eastern province of Sri Lanka (source: Department of Census and Statistics, Sri Lanka 2019)

District Ampara Batticaloa Trincomalee

Total cultivated paddy land area (acres) Maha season, 2017/ Yala season, 2018 2017 200,887 114,415 160,114 59,829 96,251 22,183

Total paddy production (‘000 bushels) Maha season, 2017/ Yala season, 2018 2017 15,948 8945 8497 3224 6910 1917

marketing is reported in this province. The province’s target is to meet 25% of the country’s maize requirement. The province benefits from a large tourism industry with many seaside resorts and hotels situated mainly in lagoons as well as beaches such as Pasikudah, Nilaveli, Uppuveli, and Kalkudah. Historic sites and other natural attractions such as Pigeon Island and coral reefs contribute to the tourism industry as well. The Eastern province relies mainly on agriculture for food security, income generation, and employment of the population and the contribution of agriculture to the provincial GDP is about 50%. Even in the conflict era in the province, agriculture played a major role in the economy. About 65% of the population depends on agriculture for their livelihood. Moreover, about 30% of the population is engaged in farming on a full-time basis. There are 250,000 farm families in the province depending on crop farming for their livelihood. The region is fertile enough to produce one-fourth of the paddy out of total paddy production in the country. The

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Table 3.2 Cultivated land area (ha) of field crops and other vegetables in the Eastern province of Sri Lanka (source: Department of Census and Statistics, Sri Lanka 2019) Crop Green chilli Big onion Red onion Maize Finger millet Green gram Cowpea Black gram Gingerly Groundnut Beans Capsicum Pumpkin Snake gourd Tomato Cucumber Bitter gourd Okra Brinjal Luffa Mae

District Batticaloa 192 0.3 26 1331 15 174 253 141 10 1515 0 8 19 54 35.2 12 61 210 147 43 189

Ampara 316 0 0 12,226 76 85 218 6 25 398 15.2 26 80 74 33.8 54 70 130 119 65 185

Trincomalee 144 0.7 3 637 11 26 23 76 6 463 1.3 13 34 35 15.1 8 24 78 97 10 106

Total 652 1 29 14,194 102 285 494 223 41 2376 16.5 47 133 163 84.1 74 155 418 363 118 480

Table 3.3 Number of registered livestock farms and animal population in Eastern province—2017 (source: Livestock Statistical Bulletin 2017)

Number of registered livestock farms Animal population

Cattle (#) 71,783

Buffalo (#) 11,088

Goat (#) 19,091

Swine (#) 40

Poultry (Mn) Commercial 5007

Backyard 36,713

282,348

123,499

145,379

2522

36.2

1.10

region has an average rice yield of 5 metric tons. Paddy production is significant among other cereals in the Eastern province (Tables 3.1 and 3.2). Livestock production in the Eastern province gets an important place. Cattle, buffalo, goats, and poultry are the main livestock types reared in the province (Table 3.3). Nearly 15% of the national cattle population and about 15% of the total milk production are from Eastern province. All the necessary resources such as grasslands and water resources are available in the province. However, inadequate veterinary services is a severe constraint to livestock development in the province. When considering the cattle farm management system distribution in Eastern province in 2017, 13% were intensive cattle farms while 29% were semi-intensive and 58% extensive. Three

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Table 3.4 Milk production (liters) in Eastern province for the year 2017 (source: Livestock Statistical Bulletin 2017) Cow milk production Buffalo milk production Total milk production

40,740,692 21,179,046 61,919,738

major types of cattle breed found in the Eastern province are Indian breeds and crosses; European breeds and crosses; and local breeds. Among them, 26% were Indian and crosses while 16% were European and crosses and 58% were local breeds (LSB 2017). The milk production details are presented in Table 3.4. As regards the fisheries sector, fishing is a significant economic activity as the province contributes one-fifth of country’s fish production. Many varieties of dried fish are on sale and transported to other areas of the country. However, underutilization of marine resources in the province led to the poor livelihood of fishing communities.

3.5

Smart and Resilient Agriculture

Climate change has become a major problem for the sustainability of livelihood. The direct effects include but are not limited to income-generating issues and food security. There will be a lack of availability, access, and utilization of food. Agricultural crop production, which is vital to global food security, is being affected by climate change all over the world. However, the impact is being felt more severely in the more impoverished communities. It has been predicted that over the next decades, billions of people, especially those living in developing countries, will face shortages of water and food and greater risks to health and life because of climate change. With fewer social, technological, and financial resources for adapting to changing conditions, developing countries are the most vulnerable to the impacts of climate change (UNFCCC 2007). Further, agriculture is a significant source of greenhouse gas emission. Increase in the atmospheric concentration of CO2, CH4, and N2O is primarily due to the fossil fuel combustion, land-use changes, and agricultural activities (Venkatramanan and Shah 2019). However, the world population is increasing gradually and food production has to be increased for feeding increasing population. Together with the climate change impacts, degradation of available agricultural lands is a cause of concern. The higher degree of sensitivity of the major agricultural crops, livestock, and fisheries to climate change may create both short-term and long-term adverse impacts on food production. Mitigation and adaptation are the two principal pathways to minimize the adverse impacts of climate change. Addressing the causes of climate change such as anthropogenic emission of greenhouse gases, unclean energy generation, and deforestation comes under mitigation strategies. The mitigation alone cannot fully reverse the atmospheric processes causing climate change (Dai et al. 2001). Therefore, adaptation measures are to be adopted while pursuing

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the mitigation practices. Munasinghe and Swart (2005) mentioned that adaptation practices are capable enough to reduce the impact of climate change. Climate-smart agriculture (CSA) is an approach for transforming and reorienting agricultural systems to support food security under the new realities of climate change. There are many other terms related to agricultural development, but CSA is novel in its focus on a range of climate actions. According to the Food and Agriculture Organization (2010), CSA is defined as “agriculture that sustainably increases productivity, enhances adaptation and reduces GHGs emission and enhances the achievement of national food security and development goals.”. Present-day food systems have higher negative impacts with respect to greenhouse gas emissions. Therefore, these manageable practices have to be regulated to mitigate greenhouse gas emission and global warming. Climate-smart agriculture is an approach to address these challenges in a comprehensive manner (Fig. 3.3). (a) Sustainably increasing agricultural productivity and incomes: CSA aims to sustainably increase agricultural productivity and income from crops, livestock, and fish, without having a negative impact on the environment. This will

Augmenting the resilience of agricultural system and rural livelihoods

Climate change integration into agricultural planning

Spatial Scale

Temporal Scale

Tapping the synergies of mitigation and adapatataion

CSA APPROACH

Reducing the risks of global food insecurity

• Sustainable Intensification • Diversified agricultural system • Integrated Crop Managment • Landscape approaches • Low emission pathways

Sustainable agricultural strategies

Trade offs Country Perspective

Fig. 3.3 Dissection of climate-smart agriculture approach (Venkatramanan and Shah 2019)

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improve the food and nutritional security. This is a key concept related to raising productivity through sustainable cultivation practices parallel to the reduction of climate impacts and greenhouse gas emission. (b) Reducing and/or removing greenhouse gas emissions: CSA helps to reduce and/or remove greenhouse gas (GHG) emissions. This indicates how much of gas is released to the environment through the process of food production. Through CSA, reduce emissions of fuel per each calorie or kilo of food, and the fiber that is produced. With CSA, deforestation is avoided. Soils and trees are managed in ways that maximize their potential to act as carbon sinks for atmospheric CO2. (c) Adapting and building resilience to climate change: CSA aims to reduce farmers’ exposure to short-term risks, like food price changing and status imbalance, while also strengthening their livelihood pattern. The short-term goals are improving their capacity to adapt to and face the shocks and longer term stresses with cultivation practices. Particular attention is given in protecting the ecosystem services which ecosystems provide to farmers and others. These services are essential in maintaining productivity in the agricultural fields and the ability to adapt to climate changes.

3.5.1

Smart and Resilient Agricultural Practices in Eastern Dry Zone of Sri Lanka

Imports of food crops, livestock products, and fish are the three key components of domestic food availability in Sri Lanka. Eighty-five percent of the food requirement is provided by domestic agriculture. The production of domestic crops including rice has been affected by gradual changes in climatic conditions while extreme climate events threaten to worsen this. Reduced agriculture production, income, and also higher food prices due to climate change have limited access to food by households. In Sri Lanka, traditional and modern climate adaptation strategies coexist. As a response to climate variability, the ancient rulers in Sri Lanka constructed reservoirs for collecting and storing rainwater for supplementing the irrigation water requirement of crops and animal consumption during the dry season. These reservoirs are also providing the same facility for present-day agriculture. Similarly, they practiced various other agricultural practices to face changes in the climate. With the need for adaptation strategies to the present-day climate change and unexpected climate extremes, the age-old practices have been reintroduced by farming communities in the form of smart and resilient agricultural practices; conservation of genetic diversity and indigenous crop varieties and livestock breeds; introduction of high-quality, genetically improved varieties of rice, tea, and maize; adapting planting times; water and soil conservation techniques; intercropping and agroforestry; shade management; mulching; manure production and organic fertilization; crop diversification; and home gardening for increased food security. Various

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climate-smart and -resilient practices have been adopted in different production systems at different scales and intensities in Sri Lanka including eastern dry zone of the country (Table 3.5).

3.6

Influence of Rainfall Variation on Paddy Cultivation in the Eastern Dry Zone of Sri Lanka

The Eastern Province is primarily an agriculture-based economy. It contributes 25% of national paddy production, 17% of national milk production, and 21% of national fish production. Despite the constraints of water scarcity, rice production must rise dramatically over the next decades. Producing more rice with less water is a formidable challenge for food, economic, social, and water security of the region. Sri Lanka is relatively well endowed with water resources, but water resources per inhabitant are only slightly above half of the world’s average. Rice is the staple food in Sri Lanka. Across Sri Lanka, paddy is mostly cultivated meeting the domestic demand. In Trincomalee district, farmers are also doing paddy cultivation in large scale in Maha as well as Yala seasons. Rainfall is one of the major factors that affect the yield of paddy in Yala season. Due to the climate variability, the low rainfall in Yala season and high rainfall in Maha season influence the paddy production. In the recent past, paddy acreage varies due to the rainfall variation. Many researchers have been studying about paddy production from the perspective of climate change. Finding out how rainfall variability influences the paddy farmers at the village level (especially in the dry period) is important because the farmers’ income is mainly dependent on the seasonal variation of rainfall. Bottom-up approach helps to get the real reasons and the farmers’ suggestions and their adaptations from the ground level. For that reason, Thambalagamuwa village was chosen to represent the Trincomalee district for the study. Paddy is highly susceptible to rainfall variability. Water management is a challenge particularly in the dry zone in the east, southeast, and northern parts of the country. The paddy lands are distributed in three main production systems: major irrigation schemes 4808 ha, minor irrigation schemes 4072 ha, and rain-fed schemes 185 ha in Trincomalee. The major rice-growing areas are the dry and intermediate zones. In dry zone, nearly 70% of the paddy is cultivated. Rainfall is a key indicator of the agricultural practices. Sri Lanka gets two monsoon periods and two intermonsoon periods. The southwest monsoon is from May to September while the northeast monsoon is from December to February. In between these two monsoon periods, two inter-monsoon periods exist: first inter-monsoon, March–April, and second inter-monsoon, October–November. Rainfall varies in amount, intensity, frequency, and type over the years and decades. High intensity of rainfall causes flooding and low rainfall causes drought in some months. Trincomalee district consists of 11 Divisional Secretary’s Divisions (DS Divisions) and 230 Grama Niladhari Divisions (GN Divisions). In Yala season, farmers mainly depend on tank irrigation and in Maha season on north-east monsoon rainfall. Trincomalee’s average rainfall is 1569 mm/per year. The total district land extent is 2728 km2

Agricultural production system • Coconut production systems • Small-scale field crop production systems • Home gardening

• Small-scale field crop production systems • Home gardening

Climate-resilient/smart practice Live mulching

Dry mulching

• Reduces soil erosion • Improves soil moisture conditions • Controls weeds • Increases carbon storage in soils • Reduces chemical fertilizer usage and hence GHG emission

Climate smartness and resilience • Water conservation (reduced evaporation) • Ameliorating the microenvironment • Ploughing into soil promotes carbon storage in soil • Reduces the requirement for nitrogen fertilizer of the crop and enriches soil fertility

Table 3.5 Climate-resilient/smart practices adopted in Sri Lanka

Photo credit: GAS Ginigaddara

Photo credit: GAS Ginigaddara

(continued)

3 Climate-Smart and -Resilient Agricultural Practices in Eastern Dry Zone of Sri. . . 47

Agricultural production system • Small-scale field crop production systems • Home gardening • Rice production systems • Upcountry vegetable production systems • Coconut production systems

• Rice production systems • Field crop production systems • Small-scale agriculture

Climate-resilient/smart practice Use of nutrients of organic origin

Planting with the onset of rains

Table 3.5 (continued)

• Rainwater supply can reduce energy needs for irrigation

Climate smartness and resilience • Enhances soil quality • Enhances water retention and soil functions • Enhances plant vigor and hence potential to overcome climate shocks • Reduces chemical fertilizer usage and hence GHG emission

Photo credit: Economy Next, 08.10.2018

Photo credit: GAS Ginigaddara

48 V. Thadshayini et al.

• Ameliorates microenvironment • Shade reduces the heat stress on soil • Increases soil carbon sequestration and storage

• Reduces water wastage • Increases water-use efficiency • Ameliorates microenvironment

• Improves energy-use efficiency due to use of animal draft power • Reduces burning of fossil fuel, contributing to minimizing GHG emission • Minimizes the use of chemical fertilizer • Increases soil C sequestration

• Home gardening • Field crop production systems • Plantation crop production systems

• Field crop production systems • Plantation crop production systems

• Home gardening • Small-scale subsistent agriculture

Agroforestry

Microirrigation

Crop-livestock integration

Climate-Smart and -Resilient Agricultural Practices in Eastern Dry Zone of Sri. . . (continued)

Department of Animal Production and Health of Sri Lanka Photo credit : FAO

Sunday Times, 29.10.2017

Photo credit: Daily mirror

3 49

• Greater resistance to diseases and heat stress

• Reduces the use of nitrogen fertilizer, thus reducing GHG emissions • Efficient use of crop residues/animal manures • Resilient to climate shocks • Increases soil C sequestration

• Small-scale livestock production systems • Crop livestock production systems

• Home gardening • Small-scale livestock production systems • Small-scale livestock production systems

Rearing and conservation of indigenous cattle

Composting and biogas production

Climate smartness and resilience

Agricultural production system

Climate-resilient/smart practice

Table 3.5 (continued)

Photo credit: Civil Security Department of Sri Lanka

50 V. Thadshayini et al.

• Reduces the use of nitrogen fertilizer, thus reducing GHG emissions. • Increases water-use efficiency • Resilient to climate shocks • Increases soil C sequestration

• Microclimate amelioration • Increases resource (water, nutrients) use efficiency • Resilient to climate shocks • Increases soil C sequestration

• Small-scale or subsistent crop production systems • Dry farming systems

• Perennial crop (coconut) production systems • Paddy production systems • Small-scale agricultural systems • Home gardening

Natural farming practices

Use of inter-cropping, multi-cropping

Climate-Smart and -Resilient Agricultural Practices in Eastern Dry Zone of Sri. . . (continued)

Photo credit: The Ministry of Plantation Industries of Sri Lanka

Photo credit: GAS Ginigaddara

Photo credit: Daily News, 2010.11.10

3 51

Agricultural production system • Paddy production systems • Home gardening Climate smartness and resilience • Microclimate amelioration • Natural pest and weed control • Soil C sequestration • Efficient resource usage

Source: Adapted from Marambe et al. (2015) and personal collection (2020)

Climate-resilient/smart practice Bund farming practices/ fence farming

Table 3.5 (continued)

Photo credit: GAS Ginigaddara

Photo credit: Janathakshan

52 V. Thadshayini et al.

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including water bodies. Water bodies cover an extent of 96 km2. The topography is mainly an undulating land with the long coastal belt of 350 km length which is associated with 10 bays and 15 lagoons. The district falls within the dry zone segment of Sri Lanka. The mean annual temperature of the district is 28.5  C (Department of Meteorology). The rainfall is not equally showered throughout the year and has a bimodal pattern having heavy intensity in Maha season with less shower rains in Yala season. The northeast monsoon brings major part of the rainfall with little variation within the district. Yala season cultivation is mainly based on tank irrigation in the Trincomalee district. The command areas for major, medium, and minor tanks are more than 1500 acres, 200–1500 acres, and less than 200 acres, respectively. This study analyzed the interrelationship between paddy cultivation and rainfall variability especially during the dry season in the Trincomalee district. The main objective of this study was to analyze the variability of rainfall and its influence on paddy cultivation during the dry season in Trincomalee and to study the Thambalagamuwa village from the perspective of rainfall variability, paddy cultivation, adaptation practices, and farmers’ suggestions.

3.6.1

Conceptual Framework of the Case Study

Rainfall is one of the major factors that affect the paddy cultivation in Maha season and Yala season in Sri Lanka. Moderate rainfall is well distributed throughout the year. But when the rainfall variability increases, the paddy production, extent, and yield also fluctuate accordingly. Decreasing rainfall creates the dry spells and drought and excess rainfall creates floods. Sown area of the paddy extent is damaged due to the lack of irrigation water. A high rainfall causes the flood and destroys the cultivated paddy areas. Flood and drought both affect the paddy extent, yield, and production and reduce the farmer’s income in both Yala and Maha cultivation seasons. These issues happen basically due to poor water management and lack of awareness among the stakeholders (farmers, government departments, societies, etc.). Excess water from the high rainfall can be stored in the tanks with proper management and can be provided during the drought period, so as to save the paddy crop. It is also necessary to strengthen the adaptation practices of the paddy farmers to increase their income level especially during the dry period. Proper water management will increase the paddy farming community resilience. Relevant authorities should focus on building the capacity of the paddy farming community and state institutions such as the department of agrarian development to address issues through diversifying livelihoods, income sources, and extension supports for sustainable paddy production (Fig. 3.4).

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Annual and Seasonal rainfall variation in Maha and Yala cultivation seasons

Decreased rainfall Create droughts and dry spells

Increased rainfall Effect to paddy cultivation

Decrease paddy extent Yield and production

Strengthening the adaptation practices Proper Water management

Create floods

Decrease the income of the paddy farmers Increase the paddy community resilience In the study area

Fig. 3.4 Conceptual framework of the case study

3.6.2

Methodology

Trincomalee district is located in the dry zone of Sri Lanka. Due to low elevation, the land belongs to low country dry zone. The alluvial soil and the agroecological conditions are favorable for the cultivation of paddy. The potential area under paddy in Trincomalee district is about 41,200 ha, which includes the Yala and Maha cultivation seasons. The actual area sown and harvested differs from the total potential paddy lands. Trincomalee district which is in the northern part of the Eastern Province is bounded in the north by Yan Oya, by Anuradhapura and Polonnaruwa districts in the west, and by Verugal Ganga in the south. The inland water coverage is 96.7 km2. There are 39 tanks including medium and minor tanks.

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Thambalagamuwa Divisional Secretariat division is located in the border part of the Trincomalee district and bounded by Town & Gravets, Kinniya, Kanthale, and Morawewa divisions and Anuradhapura district. This division comprises a total area of 244.45 km2 (694,600 ha) which accounts to 12% of the total area of the district and divided into 12 Grama Niladhari Divisions (GND). Thambalagamuwa division consists of 8500 acres of highland, 14,500 acres of cultivation land, and rest of the 3600 acres covered by mountains, lagoons, forests, homestead, and grassland. Thambalagamuwa is one of the rural villages which is predominantly an agricultural area. It has been analyzed and recorded in the historical notes that this division is one of the oldest villages and the best division with fertile soil and ancient tanks which are very necessary for cultivation. The main economic activities are agriculture and agricultural based industries. The majority of the people continue to depend on the agriculture sector (Fig. 3.5).

3.6.2.1 Data Collection Seventy paddy farmers from Thambalagamam village were selected to gather information for this study. The relevant information needed to investigate the farmer’s experience in paddy cultivation and adaptation practices was collected using a structured questionnaire. The study was carried out through questionnaire surveys with farmers and conducted focus group discussion with relevant stakeholders from Department of Meteorology, Department of Agriculture, Department of Irrigation, and officers of the Govijana Sewa and Grama Niladhari. Exercises were also conducted using tools such as seasonal calendar maintained by Department of Agriculture. Secondary data were collected from annual reports from Department of Statistics and Census, Department of Irrigation, Department of Meteorology, Department of Agriculture, Journals, internet, books, etc. Rainfall, temperature, paddy extent and production, tank storage, and other necessary data were collected. Thambalagamuwa village is near to the main meteorological station of Trincomalee. Rainfall and temperature data were collected from this Meteorology Department, since it is assumed that the study area climate is similar to the main meteorological station. Thambalagamuwa village was selected as a study area for farmers’ perception study. From monthly rainfall data, annual and seasonal rainfall variations have been calculated. The collected data was analyzed by the Microsoft Excel (2013), XLSTAT (version 2015.1), and SPSS.

3.6.3

Results and Discussion

3.6.3.1 Analysis of Rainfall and Temperature Data Thambalagamuwa village (in Thambalagamuwa DS division) is the study area which is near to the meteorological station of Trincomalee. Figure 3.6 represents the monthly average rainfall from 2005 to 2015. October-to-March rainfall is high and it belongs to Maha cultivation season. The rainfall is very less during the months of June and July. So, Yala cultivation season basically depends on the irrigation

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Fig. 3.5 Trincomalee district and the study area—Thambalagamuwa (source: prepared based on Department of Survey-Trincomalee District Map)

water facilities. As it is a dry zone, rainfall is high between December and February due to northeast monsoon (NEM) and comparatively less rainfall between May and September during the southwest monsoon (SWM) season. There was a significant rainfall in October and November in second inter-monsoon (SIM) also due to the disturbances and depression originated in the Bay of Bengal. More rain during Maha season emphasizes the need to store excess water and use during the Yala season (Fig. 3.7).

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Monthly Average Rainfall (mm)

450.0 400.0 350.0 300.0 250.0 200.0 150.0 100.0 50.0 0.0

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Fig. 3.6 Monthly average rainfall (mm) from 2005 to 2015 (source: data from Department of Meteorology, Colombo)

2500.0

Rainfall (mm)

2000.0 1500.0 1000.0 500.0 0.0

FIM

SWM

SIM

NEM

Fig. 3.7 Variability of seasonal average rainfall (mm) (2005–2015) (source: data from Department of Meteorology, Colombo)

Figure 3.8 shows the variability of annual average rainfall from 1911 to 2016. Annual average rainfall for this period was 1637 mm. Rainfall variability was higher in the recent decades (1980–1990 and 2000–2010). The negative trend of rainfall also accounts more in the recent decades. Figure 3.9 highlights the above- and below-average rainfall from 2005 to 2016. The year 2011 experienced a high rainfall of 1269 mm above the average rainfall. There was a significant drought in 2014 and 2015 especially in the dry zone. Total rainfall in 2010 was decreased by 218 mm from the average value. It shows that the drought period slightly affected the cultivation in Yala season of 2010. Compared to past years, in 2016, there was low rainfall in overall Sri Lanka including dry zone. The rainfall was well below the average value by 641 mm in 2016 and continued to first half of the 2017. In Trincomalee, the Kantale Tank which can hold up to 140 MCM has dropped to 38 MCM due to the drought of 2016/2017. In the Maha season, the 2010/2011

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3000

Rainfall (mm)

2500 2000 1500 1000 500

1911 1915 1919 1923 1927 1931 1935 1939 1943 1947 1951 1955 1959 1963 1967 1971 1975 1979 1983 1987 1991 1995 1999 2003 2009 2013

0

Fig. 3.8 Variability of annual average rainfall (mm) from 1911 to 2016 (source: data from Department of Meteorology, Colombo)

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Fig. 3.9 Variability of annual average rainfall (mm) from 2005 to 2016 (source: data from Department of Meteorology, Colombo)

recorded a high rainfall of 2326.8 mm and low rainfall in 2013/2014 as 653.8 mm. In the Yala season, 2006/2007 received 410.6 mm as high rainfall and 265.5 mm as low rainfall in 2011/2012 (Table 3.6). On an average, Maha season receives 80% of annual rainfall and Yala cultivation season receives 20% of annual rainfall. As regards the temperature data, the annual average temperature was 28.5  C from 1961 to 1990 in Trincomalee (Department of Meteorology). Figure 3.10 shows the variability of the annual average temperature from 2007 to 2015. In 2007 and 2008, the annual average temperature was below the average temperature but from 2009 onwards it increased up to 2012. In 2014, the average annual temperature increased by 3  C and in 2015 it increased slightly higher by 3.03  C.

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Table 3.6 Variability of rainfall in Maha and Yala cultivation seasons (2005/2006–2014/2015) (source: Department of Meteorology, Colombo) Rainfall (mm) Years 2005/06 2006/07 2007/08 2008/09 2009/10

Maha 323.1 410.6 288.1 299.2 380.0

1482.3 1034.3 1337.2 1351.9 1219.0

Rainfall (mm) Yala 2326.8 1397.2 2162.5 653.8 1347.4

Years 2010/11 2011/12 2012/13 2013/14 2014/15

3.50 Temperature variation in 0C

3.00

3.00

3.03

2014

2015

344.5 265.5 295.9 316.9 372.2

2.50 2.00 1.50 0.70

1.00

0.70

0.30

0.50

0.00

0.00 -0.50 -1.00 -1.50

-1.00

-1.00

2007

2008

2009

2010

2012

2013

Fig. 3.10 Variability of annual average temperature from the average district temperature— Trincomalee (source: data from Department of Meteorology, Colombo)

Dry zone receives rainfall mostly from northeast monsoon. The rainfall pattern of Trincomalee and the study area Thambalagamuwa village were matched with the dry zone. Time to time, dry zone experiences drought and dry spells. In 2016, there was low rainfall recorded all over Sri Lanka. It reflected in Trincomalee district too. Paddy land was severely damaged due to poor rainfall. Considering the temperature, it increased up to 3  C in 2014 and 2015 from the average temperature. Increasing temperature affected the water storage structures (tanks, reservoirs, small ponds) through increased evaporation rate (Figs. 3.11 and 3.12).

3.6.3.2 Relationship Between Rainfall and Paddy Cultivation In Yala season, extent of paddy cultivation is to be decided after the Farmers Organization (FO) meeting with Govijana Sewa officers who are engaged with paddy cultivation decisions. In the study area, Yala cultivation in 2017 was carried out by bethma1 practice (Yoshino and Suppaiah 1983). As the last Maha season 1 Traditional land-use system practice in dry zone villages during seasons of poor tank water supplies (Yoshino et al. 1983).

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31.0

Temperature 0C

31.0

31.0

30.6

30.9

30.0

30.0

29.4 28.6

29.0 28.0

31.4

27.5

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27.8 27.1

27.0 26.0 25.0 Jan Feb Mar Apr May Jun

Jul

Aug Sep Oct Nov Dec

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32.0

3000

31.0

2500

30.0

2000

29.0

1500

28.0

1000

27.0

500

26.0

0

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Total Rainfall (mm)

Fig. 3.11 Monthly average temperature of Trincomalee district (source: data from Department of Meteorology, Colombo)

25.0 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 Total RF Temperature

Fig. 3.12 Variability of annual total rainfall (mm) and average temperature in Trincomalee district from 2006 to 2015

(2016/2017) received low rainfall, water storage in the Kantale Tank was reduced. Maha season average water storage for the Kantale tank was 82.74 MCM for 2002–2012. In Fig. 3.13, storage from the average was high in the middle of February (34.33 MCM) in Kantale Tank and low from the average in early October ( 48.99 MCM2). Yala season average water storage for the Kantale Tank was 75.63 MCM for 2002–2012. Figure 3.14 shows that Kantale Tank water storage from the average was high in the middle of March (41.34 MCM) and low from the average in the middle of September ( 41.60 MCM). When the water level in the village tank is too low to cultivate the reasonable extent of the paddy fields, farmers resort to the 2

Negative value—storage variation from the average water storage calculated in 2002–2012.

(MCM)

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Variation from Average Storage

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40.00 30.00 20.00 10.00 0.00 -10.00 -20.00 -30.00 -40.00 -50.00 -60.00 -48.99

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34.33

(MCM)

Variation from Average Storage

Fig. 3.13 Water storage in Kantale Tank in Maha season compared with average water storage (MCM) 2002–2012

50.00 41.34 40.00 30.00 20.00 10.00 0.00 -10.00 -20.00 -30.00 -40.00 -50.00

-41.60

Fig. 3.14 Kantale Tank water storage in Yala season compared with average storage (MCM) 2002–2012

bethma system, under which a small extent of land near the tank is cultivated jointly by all the farmers in the village. This is the normal adaptation practice while the water for irrigation is low in dry season (Madduma Bandara 1983).

3.6.3.3 Relationship Between Rainfall and Paddy Extent Paddy extent, namely Asweddumized (land prepared for cultivation), sown and harvested on a complete enumeration basis was commenced in 1951. This method of data collection has been continued each season with the active cooperation of the Agricultural Research and Production Assistants (ARPO) and Grama Niladhari (GN) who are acting as primary reporters (Department of Statistics). Figure 3.15 highlights the total rainfall variability of Yala and paddy extent of Yala from 2005 to

25000

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15000

300

10000

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5000

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Yala Extent (ha)

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0

0 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 Yala Extent (ha)

Yala Rainfall (mm)

Yala Extent Variation from the Average (ha)

Fig. 3.15 Total rainfall variability and paddy extent in the Yala season (2005–2015). Source: Figure is prepared based on the data from Department of Meteorology and Department of Agriculture

11,031

12,000 9,065

10,000 6,000

8,769

6,728

8,000 4,920

10,792

6,039 4,198

4,000 2,000 (2,000) (4,000)

(891)(1,487) (3,159) 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 Yala Extent Variation (ha)

Fig. 3.16 Variability of paddy extent in Yala cultivation season compared with the average paddy extent from 1985 to 2015

2015. In the year 2011 and 2015, the paddy extent in the Yala season was comparatively higher due to relatively high rainfall. However, except for some years, the paddy extent has not shown significant variability vis-à-vis rainfall. It means that the paddy cultivation is undertaken, assuming to get enough rainfall. However, due to the rainfall variability, expected production may be varied. The average paddy extent of Yala cultivation from 1985 to 2015 was calculated as 12,529 ha. Even though some years recorded above the average extent, i.e., 2005, 2008–2013, and 2015, some years also reported below the average, i.e., 2006, 2007, and 2014. In 2013 and 2015 paddy extent (cultivated) was more than 10,000 ha (Fig. 3.16). In 2014, cultivated area was below the average extent due to the low rainfall and production also reduced due to the low rainfall.

Climate-Smart and -Resilient Agricultural Practices in Eastern Dry Zone of Sri. . .

Yala Extent Variation (ha)

3

8,000 6,000 4,000 2,000 (2,000) (4,000) (6,000) (8,000) (10,000)

5,940 3,974

5,700

3,678

1,637 (171)

63

948 (894)

(5,982)(6,578)

(8,251) 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 Yala Extent Variation (ha)

Fig. 3.17 Variability of paddy extent in Yala cultivation season as compared to the average extent from 2005 to 2015

Average paddy extent of Yala cultivation from 2005 to 2015 was calculated as 17,621 ha. There is a difference of about 5000 ha between the averages of 1985–2015 and 2005–2015. There was high fluctuation in the paddy extent (Yala cultivation season) in these two average periods (1985–2015: 12,529 ha and 2005–2015: 17,621 ha). Figure 3.17 shows that only in 2006, 2007, and 2014 paddy extent was less than the average paddy extent. For example, in 2014, cultivation area was less than the average by 3159 ha. Observation of the paddy extent in Yala cultivation season showed year-to-year fluctuations.

3.6.4

Public Perception on Paddy Cultivation and Rainfall

This section highlights the public perception on rainfall variability, paddy cultivation (extent, production, and yield), and adaptation practices that are being adopted by the paddy farmers especially in the dry season. A case study was carried out in the Thambalagamuwa village of Trincomalee belonging to the Thambalagamuwa DS division. Farmers in the Thambalagamuwa village of Trincomalee practice paddy cultivation in Maha season with enough irrigation water. In Yala season, cultivation was based on irrigation from the tank because most of the times, rainfall was not sufficient for the paddy cultivation. All of the respondents agreed that the rainfall has been decreasing in the recent past. The farmers opined that the causes of low rainfall in the Yala season are mainly climate change and deforestation. During the highrainfall period, the excess water from the tank is drained. However, during the low-rainfall period, tank’s water storage greatly reduced. Further, siltation is another factor affecting tank storage. The Kantale Tank siltation caused the decrease in water storage capacity, affecting the cultivation activities. In the recent past, farmers cultivated their land under the “bethma” practice and in the study area the maximum land extent was utilized for the paddy cultivation. In the focused group interview, the agrarian officers stated that the study area is vulnerable to flooding in Maha season, when the rainfall is above

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the average. Flooding is caused due to heavy rainfall and tank overflows. The impacts of flooding include paddy land inundation, damage of channel system, and low drinking water quality. The Thambalagamuwa village study area in the past experienced flooding (2010–2011; 2012–2013) and drought conditions (2013–2014; 2016–2017) during the Maha season. The farmer opined that the rainfall variability, delay in irrigation water distribution, and lower tank storage are the main reasons for delay in paddy cultivation. Due to variability of the rainfall, farmers faced difficulties to predict their cultivation activities on time. Nevertheless, the paddy yield in the study area is between 3 m and 5 m/acre. Famers suggested measures to increase paddy production: increasing the water storage capacity of tanks through proper tank management strategies, timely availability of irrigation water, alternative irrigation system, efficient water-use techniques, and drought/flood-tolerant paddy varieties. In direct interviews officials mentioned that the paddy varieties adopted by the famers include BG367, BG370, BG352, and BG366. In Yala season, farmers were mostly cultivating white rice and in Maha season red rice. The farmers opined that the Samba rice gave good yield. Farmers practiced some of the adaptation techniques to maximize the use of irrigation water. Farmers puddled the land to retain the water and stored the water in the paddy land up to 4–5 cm in crop establishment period. It helped for weed control too. To reduce the water usage, they used common bed for seeding and rearranged the channel system according to the water use. Other than the present system (Kantale Tank), 68% respondents suggested to build small tank system for managing water on proper time. Twenty-three percent suggested establishing common/agro well for irrigation purpose. Nine percent preferred to build the sprinkler system for cultivated area less than 1 acre. Farmers listed out some of the major reasons for weakness of water management: lack of knowledge of tank management, no proper estimation of water demand, no proper maintenance of main and field channels, and poor rehabilitation and maintenance of minor irrigation schemes. Farmers preferred, in addition to paddy cultivation, animal husbandry and curd production to increase their income. During drought period, men used to find labor work on a daily basis to manage their household income.

3.7

Conclusion

Sri Lanka is a tropical island which is highly vulnerable to the adverse effects of climate change. Sri Lanka is an agriculture-based economy. Climate variability and climate change are threatening Sri Lankan crop production including rice, livestock production, and the fisheries sector. Further, two-third of the agricultural areas in Sri Lanka are located in the dry zone, which covers the northern, eastern, and southeastern parts of the country where the Eastern Provincial agriculture contributes significantly to the national agricultural production. Nevertheless, mitigation and adaptation strategies for agriculture are adopted by the farming communities against

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climate change. This chapter has provided a glimpse of climate-smart and -resilient practices adopted in Sri Lankan agriculture. Further, this chapter delved on the importance of eastern dry zone agriculture for the country’s economy and climatesmart agricultural practices. A case study was conducted to investigate the influence of rainfall variation on paddy cultivation in the eastern dry zone of Sri Lanka. Paddy extent, production, and yield have relationship with rainfall. In both cultivation seasons, Maha and Yala, the extent of paddy cultivation was decided by the FO and Govijana Sewa (Kanna3 meetings). In this meeting, farmers decided to cultivate assuming to get enough rainfall. But due to the rainfall variability, expected production might be varied. In the study area, paddy production in Yala season was high compared to that in Maha season. Maha season is mostly influenced with flood in Trincomalee (Eastern Province) due to the northeast monsoon rainfall. But in Sri Lanka, in most of the districts of North Central Province in the dry zone, Maha is the main paddy cultivation season compared to Yala season. This shows the spatiotemporal differences of paddy cultivation within the dry zone areas. Bethma system is the normal adaptation practice in the study area during the dry season. Farmers prefer flood/drought-tolerant paddy varieties, advanced agro-techniques, and irrigation management as part of adaptation to climate change. In Thambalagamuwa village, farmers cultivated Samba rice in Yala season and red rice in Maha season. At the village level, Samba is getting more unit price compared to red rice. Therefore, reasonable control price for the red rice should be maintained by the Govijana Sewa department. Farmers preferred, in addition to paddy cultivation, animal husbandry and curd production to increase their income. As paddy is cultivated on a major scale, it is suggested to produce rice flour as a value-added product to the local market. The paddy FO of the Thambalagamuwa village and the officers of the Kantale Tank water management together managed water distribution during the cultivation periods. This corporation should be improved and strengthened in the future to manage the Kantale Tank water for the paddy cultivation. Further, the village administration has been actively taking the decisions on selection of paddy seeds, time of the cultivation, bethma practice, etc. Indigenous practices like bethma system are still practiced by the farmers in Thambalagamuwa village. This practice should be carried out in the future in dry season as a best practice. However, preparedness for the dry spells and drought needs to be strengthened. Therefore, the prediction on rainfall, drought, and dry spells from relevant government authorities is to be reached to ground level, on the period of pre-growing, growing, and harvesting of paddy through the village-level organizations.

3 Formal meeting of the FO before the beginning of cultivation seasons to determine cultivation schedule, water issues, and related matters.

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Yoshino MM, Suppaiah R (1983) Climate and paddy production: a study on selective districts in Sri Lanka, In: Yoshino MM, Kayane I, Bandara M (eds), Climate, water and agriculture in Sri Lanka. Sri Lanka. Tsukuba University, Tsukuba Yoshino MM, Ichikawa T, Urushibara K, Nomoto S, Suppiah R (1983) Climatic fluctuations and its effects on paddy production in Sri Lanka. Climatol Notes 33:9–32

Further Reading www.dailymail.co.uk/sciencetech/article-2403631/Control-weather-shoot-lasers-clouds.html www.doa.gov.lk www.meteo.gov.lk www.statistics.gov.lk www.sundaytimes.lk/170507/news/millions-of-mouths-run-dry-in-drought-without-end-239466. html

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Impact of Climate Change on Communities, Response and Migration of Insects, Nematodes, Vectors and Natural Enemies in Diverse Ecosystems J. Sridhar, K. Kiran Kumar, R. K. Murali-Baskaran, Sengottayan Senthil-Nathan, Suraj Sharma, M. Nagesh, Pankaj Kaushal, and Jagdish Kumar

Abstract

Global climate change, the current burning issue around the globe, is the change in climate for an extended period of time, due to either natural variability or human activities. It exerts a multitude of threats to human life in various forms. Global average temperature increased by 1.2
C since the industrial revolution. By the end of the twenty-first century, the global average temperature is projected to increase by 1.4–7.5
C and CO2 by 560 ppm, if the uncontrolled anthropogenic activities continue with the same speed to meet the demanding needs of growing population. Rising temperature directly affects the biology and physiology of insect communities by shortening the life cycle and increasing the number of generations which aggravate the pest problems. The feeding rate of the insect pests increases by 25% to meet their nutritional requirements in the form of amino acids under elevated CO2 (500 ppm). Global climate change also affects the migratory pattern and behaviour of insects like locusts, monarch butterflies and fruit flies. Recently in India, the pest scenario of cotton, rice and other ecosystems is being changed; with the minor pests becoming major pests, invasion of new pests and pest outbreaks under specific climatic conditions are true evidences of

J. Sridhar (*) · R. K. Murali-Baskaran · S. Sharma · P. Kaushal · J. Kumar ICAR-National Institute of Biotic Stress Management, Raipur, Chhattisgarh, India K. K. Kumar ICAR-Central Citrus Research Institute, Nagpur, Maharashtra, India S. Senthil-Nathan Division of Biopesticides and Environmental Toxicology, Sri Paramakalyani Centre for Excellence in Environmental Sciences, Manonmaniam Sundaranar University, Tirunelveli, Tamil Nadu, India M. Nagesh ICAR-National Bureau of Agricultural Insect Resources, Bengaluru, Karnataka, India # Springer Nature Singapore Pte Ltd. 2020 V. Venkatramanan et al. (eds.), Global Climate Change: Resilient and Smart Agriculture, https://doi.org/10.1007/978-981-32-9856-9_4

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changing climate besides the outbreaks of vector-borne diseases like malaria, dengue, chikungunya, filariasis and leishmaniasis. Mitigation activities from all sectors are essential in the form of increased use of alternative substances, energy efficiency improvements and short-term emission reduction steps to counteract the adverse effects of climate change in future. The development of pest management strategies to reduce insect pest population under changing climate is the challenging task ahead of the scientific community. In this chapter, we have discussed the impact of climate change on insect pests of forest, agriculture, nematodes and vectors of human diseases. Keywords

Climate change · Insect communities · Pest · Nematodes · Response · Migration

4.1

Introduction

Global climate change refers to an array of changes occurring in the environment due to natural as well as anthropogenic happenings as defined by IPCC. The global mean temperature increased by 0.6
C in the twentieth century and the decade 2000–2009 recorded the warmest. Extreme weather events in Asia were reported to provide evidence of increases in the intensity (about 3
C will be in the decade of the 2050s and about 5
C will be in the decade of the 2080s) or frequency on regional scales as a result of future increases in atmospheric concentration of greenhouse gases. The effects of global climate change on living organisms vary geographically and not all species have positive phenology in response to warming (Parmesan and Yohe 2003). Current projections point to a global increase of 1.4–7.5
C by 2100. This warming will have real consequences for the world, for with that warming will also come additional sea-level rise that will gradually inundate coastal areas and increase beach erosion and flooding from coastal storms, changes in precipitation patterns, increased risk of droughts and floods, threats to biodiversity and a number of potential challenges for public health. Climate change increases the potential consequences of many existing challenges associated with environmental, social or economic change (Keenan 2015), and the shift of interactions between herbivorous insects and invasive plants and the risks of biocontrol agents to non-target organisms under climate change are crucial for management of invasive plant species (Simberloff 2012; Chown et al. 2012; Sandel and Dangremond 2012). Some species respond to climate change, through both mitigation and adaptation, and may represent a paradigm shift for forest managers and researchers (Schoene and Bernier 2012). Insects and other arthropods have significant adaptive ability than other animals for examining the direct and indirect effects of climate change over time, since they are omnivorous, respond quickly to the subtle changes in habitat and have short generation time, which makes them candidate species for monitoring of changing climate. Insects have been considered as poikilotherms; hence their physiological

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parameters are directly related to ambient temperature (Beresford and Sutcliffe 2009; Beresford 2011). Climate variables, such as temperature, can influence both efficacy of the biocontrol agent by increasing the contact between biocontrol insects and populations of non-target plants previously isolated by high latitude or elevation (Ortega et al. 2012; Lu et al. 2013) and its safety to native species. Range expansion to higher latitudes or elevations depending on a species’ dispersal ability will be a key adaptive response of many species to global warming (Parmesan and Yohe 2003; Chen et al. 2011). The rate of development of insects may also be influenced by global warming (Karuppaiah and Sujayanad 2012). Forest pathogens are sensitive to temperature and moisture conditions. As a result of this sensitivity, these organisms will be directly affected by changing climate, in addition to being indirectly influenced via climate change impacts on other organisms, such as their host species (Hushaw 2015). Climate change-induced temperature and precipitation changes will provide generally favourable living conditions to free-living soil nematodes, which will result in an increase in their development and reproduction rates. The increase in development and growth rates will positively affect nutrient cycling rates and encourage plant growth (Munteanu 2017). The increase in atmospheric CO2 to 380 ppm, derived from the combustion of fossil fuels and changes in land use (Forster et al. 2007), accelerates the rate of plant photosynthesis, often causing reduced grain fill, increased crop water consumption, reduced nutrient-use efficiency and favouring of weeds over crops. However the increasing concentration of troposphere O3 typically has the opposite effect. Changes in the concentration of these gases in the troposphere also affect many aspects of leaf structure and chemistry that indirectly affect productivity by changing the relationship between plants and insect herbivores. The magnitude and direction of these indirect effects vary widely (Kopper et al. 2001). Understanding how insect feeding behaviour is altered by elevated CO2 and O3 will be important for predicting crop productivity as well as identifying insect species likely to become pests in the future (Baker et al. 2000).

4.2

Effect of Global Climate Change on Insects

4.2.1

Agricultural Insect Pests

Climate change affects the pattern of population dynamics of insects in different ways. Global warming not only leads to greater overwinter survival, early appearance in spring, an increase in the number of generations in a year, lengthening of the reproductive season, etc. but also affects their biotic associations as a result of change in interspecific interactions (Kiritani 2013). In general, warmer weather has direct effect on insect communities by increasing the metabolic rate, shortening the life cycle, and increasing the number of generations and rapid life histories which aggravate pest problems. Elevated CO2 has an indirect effect on insect communities, viz. changing of host plant phenology that will create serious imbalance in the insectplant relationships and tritropic interactions. Both warmer weather and elevated CO2 alter the bionomics of the insect pests under the changing climate (Hulle et al. 2008). Many insects are contributors to global warming because of the CO2 they emit. Bugs

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Table 4.1 Effect of climate change in geographical distribution of various insect pests (Sharma 2016) Insect pest Corn earworm, Helicoverpa zea (Boddie)

Host plant/s Maize

European corn borer, Ostrinia nubilalis (Hub.) Old world bollworm, Helicoverpa armigera

Maize

Pod borers, Helicoverpa armigera and Maruca vitrata (Geyer) Oak processionary moth, Thaumetopoea processionea (L.)

Tomato, cotton, pigeon pea, chickpea, rice, sorghum, and cowpea Cotton, pulses, vegetables

Oak, chestnut

Impact on insects/ behavioural response Range expansion to higher altitudes and northern Europe and USA, and increased overwintering Northward shifts with an additional generation per season Increased presence in southern Europe and outbreaks

Reference Diffenbaugh et al. (2008)

Porter et al. (1991) Cannon (1998)

Expansion of geographic range in northern Asia and Europe

Sharma (2014)

Northward range extension from southern Europe to Belgium, the Netherlands and Denmark. Poleward shift of geographic range

Cannon (1998); Paramesan and Yohe (2003)

and termites are major contributors to global warming. With every degree the global temperature rises, the life cycle of each bug will be shorter. The quicker the life cycle, the higher will be the population of pests (Deka et al. 2012). Table 4.1 depicts the changes in geographical distribution of different insect pests as a result of climate change (Sharma 2016).

4.2.1.1 Elevated Temperature Climate change due to increased temperature may affect the insect survival, development and geographical distribution either directly or indirectly through their physiological changes or existence of hosts. For example, cicadas take several years to complete one life cycle due to moderate temperature variability over the course of their life history (Abolmaaty et al. 2011). The rise in mean surface temperature by 1.0
C over the last 40 years in Japan showed northward range expansion of more than 50 butterfly species and establishment of 10 previously migrant butterfly species on Nansei Islands during 1966–1987. It also showed 15% reduction in winter mortality of adults of Nezara viridula and Halyomorpha halys and may be responsible for increase in abundance of H. armigera and Trichoplusia ni (Kiritani 2006). Under changing climate, the spiralling whitefly, Aleurodicus dispersus, an exotic insect, invades native crops and feeds on more than 150 plant

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species including teak plantation at elevated temperature. Native insects become invasive on native plant such as rhinoceros beetle in coconut plantations of South India. Teak defoliator, Hyblaea puera, periodic outbreak was observed in southern parts of India. Increase in temperature may alter the host physiology and resistance which breaks down the temperature-sensitive resistance. Increase in food quality due to increase in N content in plants under stress conditions caused by high temperature can result in sudden resurgence of insect pest populations. Moreover, the defensive system of plant is lowered under stress condition. The Myzus persicae flies in spring and early summer when crops are vulnerable under elevated temperature. A 2.0
C rise in temperature leads to increase in number of generations of M. persicae from 18 to 23 that starts flying 2 weeks early. The active period of pests is increased resulting in greater damage to crop plants. It has been told that the gender ratio of thrips may be changed at elevated temperature. The parthenogenetic population of aphid undertake sexual reproduction which increases virulence and wider host adaptability and become more polyphagous. A 50-year-old study in paddy fields in Japan indicated that the number of annual light-trap catches of rice stem borer, Chilo suppressalis, and green rice leafhopper, Nephotettix cincticeps, increases in summer with increasing temperatures in the previous winter. The increment is much larger for N. cincticeps than for C. suppressalis because of the more number of generations. Higher winter temperature has a negative influence on the abundance of brown plant hopper, Laodelphax striatellus (Yamamura et al. 2006). An increase in the number of generations of onion thrips per season is expected because of the big predicted increase in cumulative degree-days and the prolongation of the period with favourable developmental conditions. More generations could lead to larger populations and consequently more damage on host plants. The onion thrips also could become a serious threat in areas where it is not currently a problem (Bergant et al. 2005).

4.2.1.2 Elevated CO2 Exposure to elevated CO2 can alter the nutritional value of leaves, and some herbivores may increase consumption rates to compensate. The effects of O3 on leaf nutritional quality are less clear; however, increased senescence may also reduce leaf quality for insect herbivores. Additionally, changes in secondary chemistry and the microclimate of leaves may render plants more susceptible to herbivory in elevated CO2 and O3. Damage to soybean (Glycine max L.) leaves and the size and composition of the insect community in the plant canopy were examined in large intact plots exposed to elevated CO2 (550 μmol mol1) and elevated O3 (1.2 ambient) in a fully factorial design with a soybean free air concentration enrichment system. Elevated CO2 alone and in combination with O3 increase the number of insects and the amount of leaf area removed by insect herbivores across feeding guilds. Exposure to elevated CO2 significantly increased the number of western corn rootworm (Diabrotica virgifera) adults (foliage chewer) and soybean aphids (Aphis glycines; phloem feeder). No consistent effect of elevated O3 on herbivory or insect population size was observed. Increased loss of leaf area to herbivores was

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associated with increased carbon-to-nitrogen ratio and leaf surface temperature. Soybean aphids are invasive pests in North America and new to this ecosystem. Increased concentrations of CO2 may increase herbivory in the soybean agroecosystem, particularly by recently introduced insect herbivores (Dermody et al. 2008). Despite predictions that elevated CO2 might mitigate reductions in yield caused by high temperatures based on increasing of the optimum temperature for photosynthesis (Lobell and Field 2007; Bishop et al. 2014), a study on early-season soybean grown under elevated CO2 resulted in 57% more damage primarily due to Japanese beetles, potato leafhopper, western corn rootworm and Mexican bean beetle than the crop grown in today’s atmosphere. This may be due to increased levels of sugars in the soybean leaves that favoured the additional insect feeding (Hamilton et al. 2005). Elevated CO2 had resulted in doubling of BPH population in rice compared to the crop grown under ambient CO2 (Prasanna Kumar et al. 2012). Chen et al. (2005) reared larvae of H. armigera on milky grains of spring wheat grown in ambient CO2 concentration, at 550 ppm and at 750 ppm. The results show that the larvae developed quite similarly under all CO2 concentrations, even though the larvae under elevated CO2 consumed much more than those under ambient CO2. Bollworm (H. armigera) larvae feeding on elevated CO2-grown pea plants at 700 ppm were significantly smaller than those grown on ambient-grown plants.

4.2.1.3 Rainfall Frequency of rainfall would decrease but its intensity would increase. Aphids on wheat will be affected as they are washed away and small insects will be reduced. Heavy rainfall causes outbreak of armyworm.

4.2.2

Forest Insects

4.2.2.1 Elevated Temperature Climate change due to increase in seasonal temperature may alter the phenology of trees, which results in phenological asynchrony between insects and their host tree. Insect species such as two-spotted oak buprestid, Agrilus biguttatus, having restricted range cause increase in declining of oak trees at elevated temperature in UK forests (Wainhouse and Inward 2016) (Table 4.2). The onset of flight and dispersal are the major phenological factors which play an important role in host finding, colonisation and brood establishment. For example, the dispersal of epidemic populations of mountain pine beetle, Dendroctonus ponderosae, might have resulted in the spread of outbreaks in British Columbia. Further, day length and threshold temperature are important factors in insect emergence and first appearance after hibernation. For example, the spring swarming of the European spruce bark beetle, Ips typographus, can be predicted by accumulated temperature above photoperiod threshold level and specific thermal threshold for flight activity (Baier et al. 2007). Insects find optimum temperature conditions for their growth and development. As long as the temperature exceeds, the positive

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Table 4.2 Effect of climate change on various forest insect pests in the UK (Wainhouse and Inward 2016) Risk of increased Forest insect pest Host damage Aphids, scale insects and related species Elatobium abietinum, Spruce Very high Green spruce aphid

Cryptococcus fagisuga, Beech scale

Beech

Low

Bark beetles, weevils and wood-boring beetles Dendroctonus micans, Spruce High great spruce bark beetle Pine Low

Likely effects on populations and damage in a warmer, more unstable climate Multiple generations in warm weather result in rapid population increase, exacerbated by increased winter survival. Drought stress of host trees favourable to population growth Reduced importance of beech in a warmer, more drought-prone climate likely to reduce importance of beech scale Reduced generation time may increase abundance. Drought stress of host trees decreases resistance to attack. Range extension resulting in more widespread damage Reduced generation time increasing population size but reducing period of risk, especially in northern forests Wind blow in stormy weather increases breeding material. Sister broods increase abundance. Host stress through drought or defoliation reduces resistance of living trees to attack Availability of declining oaks and warmer weather likely to increase both abundance and geographical range Availability of declining oaks and warmer weather likely to increase abundance and damage to timber Wind blow in stormy weather increases breeding material. Sister broods increase abundance. Host stress through drought or defoliation by sawflies reduces resistance of living trees to attack. Range extension likely to increase area of damage

Hylobius abietis, large pine weevil

Spruce Pine

Moderate Moderate

Tomicus piniperda Common pine shoot beetle

Pine

High

Agrilus biguttatus Two-spotted oak buprestid Platypus cylindrus oak pinhole borer

Oak

Moderate

Oak

Moderate

Ips cembrae larch bark beetle

Larch

Moderate

Oak

High

Range extension likely to increase significance of this pest

Pine

Moderate

Spruce Oak

Moderate Moderate

Reduced rainfall on vulnerable sites has potential to trigger outbreaks Phenological synchrony with oak may be disrupted as the climate warms, reducing the likelihood of outbreaks in the short to medium term. Exposure to novel hosts during afforestation can result in local outbreaks

Lepidoptera Thaumetopoea processionea oak processionary moth Bupalus piniaria pine looper moth Operophtera brumata winter moth

(continued)

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Table 4.2 (continued)

Forest insect pest Lymantria dispar gypsy moth

Host Oak

Risk of increased damage Low

Panolis flammea pine beauty moth

Pine

Low

Zeiraphera diniana larch budmoth

Spruce Pine Larch

Low Low Low

Spruce

Moderate

Pine

Low

Larch

Low

Sawflies Gilpinia hercyniae European spruce sawfly

Neodiprion sertifer European pine sawfly Cephalcia lariciphila web-spinning larch sawfly

Likely effects on populations and damage in a warmer, more unstable climate A newly established pest may increase its range as the climate warms resulting in localised defoliation Has the potential to cause outbreaks on exotic pines introduced as an adaptation to climate change Disruption of phenological synchrony with host tree likely to reduce the risk of outbreaks in short to medium term Increased number of generations extends seasonal occurrence of damage and may increase abundance. Range extension may result in local damage Possible increased risk of damage on dry nutrient-poor sites Range extension may result in localised defoliation, depending on the future importance of larch

response of enhanced reproductive potential is expected in insects (Jönsson et al. 2009). Due to shortened egg and larval periods, where insects are most susceptible to predation and parasitism, probabilities of survival and higher abundance will increase. Temperature and humidity change can influence insects indirectly by changes in host plant metabolism and physiology (Netherer and Schopf 2010). Emerald ash borer (Agrilus planipennis), an introduced pest of ash trees (Fraxinus) in North America and western Russia probably with wood packaging material, is considered as a minor pest in its native range in Northeast Asia. However, in the introduced areas, it causes serious damage to all the native species of ash trees (Ramsfield et al. 2016).

4.2.2.2 Diapause and Winter Mortality Recent studies show that the effects of day length on the induction and termination of diapause may be modified by rising temperatures both in positive and negative ways for insect development. Battisti (2004) refers to the spruce web spinning sawfly, Cephalcia arvensis, which enters extended pupal diapause below a soil threshold temperature of about 12.8
C. Abnormally high temperatures at pupation time may cause a switch to annual life cycles and increase fecundity and damage potential of populations. On the other hand, a disruption of the maintenance of diapause by lacking low temperatures may also lead to high winter mortality and very low abundance in spring, as was observed for the larch budmoth, Zeiraphera diniana, in the Swiss Alps.

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A study was conducted to find the effect of elevated temperatures (15, 20 and 25
C) on the larval survival rate and duration of development of Lymantria monacha (L.) on needles of Pinus sylvestris (L.) and in Lymantria dispar (L.) on leaves of Quercus robur (L.), respectively. Results revealed that an increase in temperature caused a significant shortening of the duration of development (DD) of larvae of both these closely related Lymantria species. With increasing temperature, the survival rate of larvae declined in L. monacha, but increased in L. dispar. The rearing of larvae of L. dispar at higher temperatures (25 and 3.5
C above ambient) significantly shortened the time needed for larvae to reach the pupal stage (by about 15 and 8 days, respectively). Therefore, it is possible that under global climate change these differences may lead to changes in distribution of both insect species. Most likely the outbreak of L. dispar would occur at elevated temperature in Missouri (Karolewski et al. 2007). Higher temperatures have also been found to result in shortening of the larval period in other insect species (Leather and MacKenzie 1994). To address how multiple, interacting climate drivers may affect plant–insect community associations, insects were sampled that naturally colonised a constructed old-field plant community grown for over 2 years under simultaneous CO2 (660 ppm), temperature (3
C above ambient temperature) and water manipulation (25 mm). Insects were sampled using a combination of sticky traps and vacuum sampling, identified to morphospecies and insect community with respect to abundance, richness and evenness quantified. A total of 35,622 insects from 10 orders were collected with sticky traps, with order Thysanoptera (thrips) representing 86% of the total insects sampled followed by Hymenoptera: 2155, Diptera: 1512 and Coleoptera: 619. Elevated temperature significantly increased (123%) the abundance of thrips compared with ambient temperature. It was observed that temperature, more so than CO2 or water, was responsible for changing insect community composition via effects on morphospecies diversity and feeding guild composition. A common herbivore taxon of plants responded strongly to warming with increases in abundance and overall insect species richness and evenness decreased at an elevated air temperature, likely due to effects on morphospecies that responded both positively and negatively to this climate factor. The results provide insight into changes that could arise within insect communities as the climate warms and could stimulate the development of more targeted experiments examining specific plant–insect associations in multifactor experiments (Villalpando et al. 2009).

4.2.2.3 Elevated CO2 The elevated CO2 mediates its effect on herbivores indirectly via host plant. The foliar N typically decreases by 10–30% causing an increase in the C/N ratio. The mature leaves will be less nutritious for herbivores. The dilution of foliar N under elevated CO2 may be eliminated in plants associated with nitrogen-fixing symbionts. The carbon/nutrient balance hypothesis states that resources in excess of growth demands are shunted into secondary metabolites. Hence excess carbohydrate that becomes available under elevated CO2 should cause increase in carbon-based

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defensive compounds such as terpenes and phenolic compounds while decrease in N-based defences such as alkaloids (Williams et al. 1994). Higher CO2 also results in higher starch content of leaves and increased tissue water content because of increased water-use efficiency. Finally, plants grown in higher CO2 conditions are hypothesised to have leaves with higher specific weight and greater toughness, although the latter phenomenon has been reported in only one experimental study.

4.3

Effect of Global Climate Change on Nematodes

Nematodes are the most abundant and diversified group of organisms on the earth. They are found in different habitats ranging from aquatic, marine and freshwater to terrestrial environments (van Megen et al. 2009). Bacterial and fungal feeding nematodes play a major role in nutrient availability to crop plants and also help in maintaining soil health. Predatory nematodes have the potential for biocontrol of plant parasitic nematodes (Ahmad and Jairajpuri 2010). However, entomopathogenic nematodes act as biocontrol agents of various soil-borne insect pests in crop ecosystems (Kaya et al. 2006). In contrast to this, others act as parasites on plants and animals. The rise in atmospheric CO2 and surface temperature levels will significantly affect both natural and managed ecosystems by interacting with biotic and abiotic components on the earth which may cause alterations in temporal and spatial distribution, abundance, biology and infectivity of nematodes (IPCC 2007; Singh and Prasad 2016). However, climate change has both positive and negative impacts on the abundance of nematodes (Mueller et al. 2016).

4.3.1

Agricultural Ecosystem

4.3.1.1 Elevated Temperature Field experiments and lab studies indicated increase in population density of Radopholus similis and greater root damage in banana as the anticipated temperature increases (Reddy 2013). The prevalence of Radopholus and Hoplolaimus spp. infestations was seen in connection to decrease in total annual rainfall and increasing trends of annual temperature in Cameroon (Neba et al. 2013/14). Climate change in pertinence to increased soil temperature brought about increased hatching and population density of Globodera rostochiensis and G. pallida on potato in the UK (Kaczmarek et al. 2014). It also resulted in increasing of nematode species diversity by ~36% in complex plant communities and decrease in simple plant communities by ~39% compared to ambient temperature in Minnesota, USA (Thakur et al. 2017). However, a field infrared heating experiment showed significant decrease in nematode density using daytime warming and diurnal warming modes, whereas nighttime warming showed marginal effect on the soil nematode density in the western Songnen Plain, Northeast China (Yan et al. 2017). The analyses on the impact of increased soil temperature in controlled environment conditions revealed increased survival to female maturity of G. pallida and G. rostochiensis for Scotland followed

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by Wales and England (Skelsey et al. 2017). The theoretical results on increment of 1
C ambient temperature would result in the spread of virus-transmitting nematodes, viz. Longidorus elongatus, L. leptocephalus, L. macrosoma and Xiphinema diversicaudatum, from south to north Europe (Boag et al. 1991; Neilson and Boag 1996).

4.3.1.2 Elevated CO2 Studies on elevated CO2 reported increased number of bacterivorous, fungivorous and herbivorous nematodes, while the number of carnivorous nematodes was not changed in winter wheat and sugar beet (Sticht et al. 2009). The experiments conducted by ICAR-IIRR, Hyderabad, India, showed no adverse effect of elevated CO2 (up to 700 ppm) on the abundance of rice root knot nematode, M. graminicola, on rice (Somasekhar and Prasad 2010). In contrast to this, crop residue incorporation inhibited the plant parasitic nematode response and stimulated structure index to the elevated CO2 in wheat in China (Li et al. 2009). The investigations on the effect of climate change on the spatial distribution of coffee nematodes (races of Meloidogyne incognita) and leaf miner (Leucoptera coffeella), using geographical information system (GIS) in future decades of the 2020s, 2050s and 2080s (scenarios A2 and B2) (IPCC 2014) compared to normal climate from 1961 to 1990, brought about increased number of generations and infestation of M. incognita races 1, 2 and 4 and L. coffeella on coffee plants in Brazil (Ghini et al. 2008). The geographical distribution of soybean cyst nematode, Heterodera glycines, has expanded more rapidly since 1970s and now spreads to main soybean-growing regions in the USA (Rosenzweig et al. 2001; Niblack 2005).

4.3.2

Forest Ecosystem

4.3.2.1 Elevated Temperature The studies on global climate warming in response to increased temperature brought about significant increase in ratio between microbial feeding and plant parasitic nematodes in both closed and open canopy forest in the temperate-boreal ecotone of Minnesota, USA (Thakur et al. 2014). However, in Switzerland, strong climatic warming was presumed to be the indirect cause for dying of Scots pine (Pinus sylvestris L.) and these high temperatures favoured the conditions for pinewood nematodes (Bursaphelenchus mucronatus) and bark beetle development and the trees were susceptible to the attack by secondary pathogens (Rebetez and Dobbertin 2004). 4.3.2.2 Elevated CO2 Fumigation of forests with elevated CO2 resulted in increase of maturity index, diversity and occurrence of nematode genera in loblolly pine (Pinus taeda) than sweet gum (Liquidambar styraciflua) forests in the UK and the identified nematode genera responded differentially to elevated CO2 in both the forests (Neher and

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Weicht 2013). However, previous reports suggest that fungivores are the only trophic group affected by elevated CO2 in forest soils (Neher et al. 2004).

4.3.3

Grassland Ecosystem

4.3.3.1 Elevated Temperature Papatheodoroua et al. (2004) reported that the impact of large-scale and small-scale seasonal fluctuations on soil temperature (1.4
C) has no synchronised response between bacterivorous nematodes and their bacterial food resources. A field experiment on temperature-induced changes in semi-arid grassland reported a significant increase in population density of Cephalobus, Helicotylenchus, Paratylenchus and Tylenchorhynchus species (Bakonyi and Nagy 2000). 4.3.3.2 Elevated CO2 The response of nematodes to CO2 enrichment varies among species. Yeates et al. (2003) reported increased abundance of plant parasitic nematode, Longidorus, and no effect on the abundance of Paratylenchus, Trichodorus and Hoplolaimidae. However, the relative abundance of all nematode feeding groups (predators; omnivores; fungal feeders; plant associated; root feeders; bacterial feeders) increased significantly in soils subjected to elevated CO2 after 5 years of CO2 enrichment in pasture plots in New Zealand. In contrast to this, Yeates et al. (1997) reported neutral effect on the abundance of herbivorous nematodes in grassland turfs in New Zealand. The experimental studies by Ayres et al. (2008) revealed the increased abundance of Anguinidae and decreased abundance of Hoplolaimidae. However, it was observed that elevated CO2 did not influence the herbivorous nematode community in grassland ecosystem at three locations, Colorado, California (USA) and Montpellier, France. Based on the results, it is presumed that the response of nematode taxa to elevated CO2 may be influenced by soil factors (Yeates et al. 1999). The combined in situ effects of both elevated CO2 (~600 ppm) and temperature of ~1.5
C during the day and 3
C during the night for about 7–8 years throughout all seasons bring about decreased abundance of plant parasitic nematodes and increased level of bacterial and fungal feeding nematodes in semi-arid, mixed-grass prairie in Wyoming, USA (Mueller et al. 2016).

4.4

Effect of Global Climate Change on Natural Enemies

Climate change may alter the interactions of herbivores and their natural enemies, resulting in potential changes in levels of natural control and dynamics of the herbivore. The potential for seasonal asynchrony between herbivores and natural enemies is apparent. The potential for increased exposure of overwintering hosts to parasitism with rising temperature is seen with Ooencyrtus kuvanae (Howard), an egg parasitoid of the gypsy moth. Gypsy moth overwinters in diapauses during the

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egg stage from about July until April each year (Brown 1984). The parasitoid attacks host egg masses during the fall and early spring, often inflicting high levels of parasitism depending upon the size of an egg mass (Williams et al. 1990). Ooencyrtus kuvanae females are not generally active during the winter months but are not in diapause. As a result, numbers of fall generations of the parasitoid have been reported to vary from two to five over the range in North America, apparently in response to climatic differences (Brown 1984). Increase in fall and winter temperatures clearly may permit additional generations in a specific location, resulting in higher levels of parasitism. Climatic limitations to natural control of herbivores are generally appreciated but some natural enemies, such as insect pathogens, may be more definitively limited by critical dependence of their life cycles on temperature and humidity. An example is Entomophaga maimaiga Humber, Shimazu and Soper, a fungal pathogen of gypsy moth larvae, whose epizootics decimated host populations over wide areas of the North Eastern USA in 1989 and 1990. Those epizootics were associated with higher than average rainfall in May, and infection levels of the fungus increased with additional moisture in controlled studies (Hajek et al. 1996). The fungus continues to increase its range, but its ability to produce epizootics under changed climatic conditions likely will depend upon relative levels of temperature and rainfall. The studies on quantifying the effect of climate change on the activity of natural enemies against insect pests will be a major concern in future pest management programmes due to the population control of insect pests through interspecific interactions with their natural enemies (parasites and predators). For example, oriental armyworm, Mythimna separata (Walk.), populations increase during prolonged period of drought which is detrimental to natural enemies, followed by heavy rainfall. Therefore, it is necessary to devise appropriate methods to study the interaction between insect pests and their natural enemies in pest management (Table 4.3) (Sharma 2016).

4.5

Effect of Global Climate Change on Insect Migration

Any increase in temperature is bound to influence the distribution of pests and diseases. It is predicted that 1.0
C rise in temperature would enable species to spread 200 km northwards or 140 km upwards in altitude (Parry et al. 1989). The areas which are not favourable at present due to relatively low temperature may become congenial with rising temperatures, causing a shift of pest density from South to North. Cabbage butterfly migrates from hills to plains in winter and back to hills in summer. Locust, Robinia pseudoacacia, swarms produced in the Middle East usually fly eastward into Pakistan and India during summer season and they lay eggs during monsoon. Changes in rainfall, temperature and wind speed pattern may influence the migratory behaviour of the locust. The migratory behaviour of oriental fruit fly, Bactrocera dorsalis, is well studied and is distributed in tropics and subtropics, and extends to warmer temperate areas such as southern Mediterranean Europe under

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Table 4.3 Effect of climate change on insect pest–natural enemy interactions (Sharma 2016) Climatic variability Decreased rainfall in September and October Increased rainfall Variability Decrease in rainfall in June– September

Stage of insect Eggs

Potential impact Increase

Eggs

Decrease

Eggs Larvae

Decrease Decrease

Eggs

Decrease

Campoletis chlorideae

Larvae

Decrease

Tetrastichus spp.

Eggs

Up to 100% increase

Crop Sorghum

Insect pest Stem borer Chilo partellus (Swin.)

Natural enemy Trichogramma spp.

Castor

Semilooper, Achaea janata Leaf-eating caterpillar, Spodoptera litura Leaf miner, Aproaerema modicella S. litura Pod borer, Helicoverpa armigera (Hub.) Yellow stem borer, Scirpophaga incertulas

Trichogramma chilonis Telenomus remus Cotesia flavipes T. chilonis T. remus

Soybean

Increase in rainfall events

Groundnut

Dry weather conditions

Chickpea, pigeon pea

Decrease in August rainfall

Rice

climate change (Stephens et al. 2007). It is projected to extend further polewards as cold-stress boundaries recede. A species of dragonfly, the globe skimmer or wandering glider, is a remarkable dragonfly that has been revealed to travel an amazing 12,000 miles every winter using a tropical weather system to flit between India and Africa. The fall migration flyways of monarch butterflies in eastern North America from Canada and the USA to overwintering sites in Mexico is one of the world’s most amazing biological phenomena revealed by citizen scientists, although recent threats make it imperative that the resources needed by migrating monarchs be conserved. The 3-year data was used to elucidate the flyways on a continent-wide scale that revealed two distinct flyways, but only one appears to lead directly to Mexico. This main ‘central’ flyway begins in the American Midwest states and southern Ontario; then continues south-southwest through the states of Kansas, Missouri, Oklahoma and Arkansas; and finally passes through Texas and northern Mexico. The number of monarchs migrating to Mexico has been significantly reduced due to loss of habitat in their overwintering grounds, illegal logging, loss of breeding habitat due to climate change, urbanisation and agriculture, especially genetically modified crops and chemical spraying for insect pest control (Howard and Davis 2009). Recently severe desert locust outbreaks were witnessed during 2020 in Africa, India, Pakistan due to unseasonal heavy rains caused by climate change which have played the most crucial role in the worst locust attack that India has ever witnessed in decades. The locusts have invaded new areas of Indian states, Madhya Pradesh, Uttar Pradesh, Chhattisgarh and Maharashtra (FAO 2020).

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Effect of Global Climate Change on Pollinators

Global climate change will affect the phenology (growth and reproduction) of plants and the abundance of insect pollinators which result in altering of plant-pollinator networks (Naga et al. 2015). The population of insect pollinators is under threat because of the changing climate. There has been tremendous reduction in the pollinators in various countries since the past 15–20 years which ultimately affects the agricultural production. The bee population has been reduced by 50% and other pollinators as well. The possible causes are change in land-use practices, indiscriminate use of agrochemicals, parasites and diseases, and changing climate could also contribute to decline of pollinators.

4.7

Effect of Global Climate Change on Insect Vectors

Dhiman et al. (2008) reported that India is afflicted with six major vector-borne diseases (VBDs), namely malaria—Anopheles culicifacies, dengue—Aedes aegypti, Chikungunya—Aedes aegypti, filariasis—anopheles mosquito, Japanese encephalitis—culex mosquitoes, leishmaniasis—Phlebotomus papataci. Vector-borne infectious diseases infect over a billion people each year, contributing to over a million deaths globally (World Health Organization 2014). Recent resurgences in vectorborne diseases and concerns of global climate change have together prompted questions regarding their potential relationship (Medlock and Leach 2015). The rate of increased digestion of blood meal leads to reduced time taken for vector populations to breed, for ovarian development and for egg laying as well. The biting behaviour of the vector increases. They also produce smaller adults which may require multiple blood meals in order to reproduce, increasing the probability of pathogen transmission and decreasing the incubation period of the pathogen. Mosquitoes need access to stagnant water in order to breed. Heavy rain can create as well as wash away breeding sites. Drought conditions can increase breeding sites by causing stagnation of water. The minimum temperature required in anopheles mosquitoes to multiply is 14.5–16.5
C for Plasmodium vivax and 16.5–19
C for Plasmodium falciparum. The best conditions exist between 20 and 30
C temperature and 60% relative humidity. The completion of sporogony of parasite at 16
C takes 55 days, at 18
C takes 29 days and at 28
C takes 7 days. The anopheles survives for 4–5 days at 35
C while all die within 24 h at 40
C.

4.8

Global Climate Change and Insect Pests: Indian Scenario

Elevated atmospheric CO2 expected in the near future as a consequence of increasing emissions will alter the quantity and quality of plant foliage, which in turn can influence the growth and development of insect herbivores. Feeding trials with two foliage feeding insect species, Achaea janata (Table 4.4) and Spodoptera litura

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Table 4.4 Effect of elevated CO2 on A. janata CO2 conc. (ppm) 550 700 Ambient CO2 in OTC Outside (355) LSD ( p ¼ 0.05)

Weight of leaf ingested (g) 3.071 3.284 2.020 2.138 0.524

Larval weight (g) 0.171 0.170 0.154 0.157 0.013

Larval duration (d) 16.11 16.29 14.33 14.33 0.18

Larval weight (g) 0.137 0.137 0.117 0.118 0.011

Larval duration (d) 18.27 18.22 16.11 16.13 0.261

Table 4.5 Effect of elevated CO2 on S. litura on castor CO2 conc. (ppm) 550 700 Ambient CO2 in OTC Open (355) LSD ( p ¼ 0.05)

Weight of leaf ingested (g) 0.820 0.869 0.594 0.588 0.166

(Table 4.5), were conducted using foliage of castor plants grown under four concentrations of CO2, viz. 700 ppm CO2 inside open top chamber (OTC), 550 ppm CO2 inside OTC, ambient CO2 (350 ppm) inside OTC and ambient CO2 in the open. Biochemical analysis of foliage revealed that plants grown under elevated CO2 had lower N, and higher C, C/N ratio and polyphenols. The consumption rate of castor semilooper increased by 44% when elevated CO2 foliage offered for consumption and more larval weight and slower development were observed (Srinivasa Rao et al. 2009). Compared to the larvae fed on ambient CO2 foliage, the larvae fed on 700 and 550 ppm CO2, foliage exhibited greater consumption. Larval duration also increased by 2 days. The 700 and 550 ppm CO2 foliage was more digestible with higher values of approximate digestibility. The relative consumption rate of larvae increased whereas the efficiency parameters, viz. efficiency of conversion of ingested food (ECI), efficiency of conversion of digested food (ECD) and relative growth rate (RGR), decreased in case of larvae grown on 700 and 550 ppm CO2 foliage. The consumption and weight gain of the larvae were negatively and significantly influenced by leaf nitrogen, which was found to be the most important factor affecting consumption and growth of larvae. The larvae of S. litura consumed more (39%) elevated CO2 foliage which led to more larval weight and slower development (Table 4.5). The feeding rate of S. litura increased significantly when fed on mung bean leaves grown under elevated CO2 of 600 ppm and this experiment was conducted at IARI (Srivastava et al. 2002). India during the last decade has witnessed severe outbreaks of different insect pests in many crops of economic importance. Some outbreaks related to crops in India are the following: Outbreak of sugarcane woolly aphid Ceratovacuna lanigera Zehntner in sugarcane belt of Karnataka and Maharashtra states during 2002–2003 resulted in 30% yield losses (Table 4.6) (Joshi and Viraktamath 2004; Srikanth 2004, 2007; Tripathi et al. 2008; Rafee 2010). The widespread outbreaks of rice plant

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Table 4.6 Insect pest outbreaks in relation to climate change in India (Sharma 2016)

Plant hoppers, Nilaparvata lugens Sogatella furcifera Mealybug, Phenacoccus solenopsis

Rice

Region/ location Karnataka and Maharashtra during 2002–2003 North India

Cotton, vegetables

Punjab, Haryana

Papaya mealybug, Paracoccus marginatus

Papaya

Tamil Nadu, Karnataka, Maharashtra

Insect pest Sugarcane woolly aphid, Ceratovacuna lanigera

Host plant/s Sugarcane

Probable reason/s Abnormal weather conditions; insecticide misuse Abnormal weather conditions; insecticide misuse Hot and dry weather; insecticide misuse Abnormal weather conditions; misuse of insecticides

Impact 30% yield losses; reduced cane recovery Crop failure on >33,000 ha

Reference Joshi and Viraktamath (2004), Srikanth (2007) IARI News (2008)

30–40% loss

Dhawan et al. (2007)

Significant yield loss

Tanwar et al. (2010)

hoppers, namely Nilaparvata lugens (Stal) and Sogatella furcifera (Horvath), due to recent abnormal weather patterns coupled with insecticide misuse led to crop failure over more than 33,000 ha paddy area in North India (Fig. 4.1a) (IARI News 2008; IRRI News 2009). Tanwar et al. (2010) have reported that the papaya mealybug Paracoccus marginatus is a major pest and caused havoc in papaya and other horticultural crops of economic importance during 2007–2009 in the parts of Tamil Nadu, Karnataka and Maharashtra states. Choudhary et al. (2013) reported an outbreak of stink bug Tessaratoma javanica (Tessaratomidae) on litchi crop in Chotanagpur region of Jharkhand state, resulting in approximately 80% yield loss to agricultural and horticultural crops and weeds (Fig. 4.1b) and litchi fruits (Fig. 4.1c). Severe incidence of leaf-eating caterpillar S. litura (Fabricius) in soybean (Fig. 4.1d) and pod borer H. armigera (Hubner) in pigeon pea and chickpea due to abnormal weather during kharif season is a regular feature in semi-arid cropping regions of the country (Fig. 4.1).

4.8.1

Changing Cotton Pest Scenario in India in Response to Climate Change

The pest scenario is changing fast and is assailed by multitude of pests as it evolves through various production levels. American and spotted bollworms attained secondary pest status and Spodoptera, pink bollworm, mirids and mealy bugs are emerging as major pests. Sap-sucking pests like aphids, jassids, thrips, whiteflies and mites are major pests and also economically important. Grey weevil, chaffer

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Fig. 4.1 Emerging pest problems in economically important agri-horticultural crops in India (Fand et al. 2012). (a) Suddenly broken out plant hopper infestation on rice (inset) in North India during 2008 leading to hopper burn symptoms (photograph by M. Sujithra, Scientist (Entomology), IARI, New Delhi). (b) Severe infestation of Phenacoccus solenopsis on pomegranate fruit (photograph by Babasaheb B. Fand, Scientist (Agril. Entomology), NIASM, Baramati). (c) Outbreak of litchi stink bug in Jharkhand; photo in inset shows litchi flowers and tender fruits attacked by stink bug (source: Choudhary et al. 2013). (d) Spodoptera litura larvae feeding gregariously on soybean foliage (photograph by Mahesh Kumar, Scientist (Plant Physiology), NIASM, Baramati)

beetle and pollen weevils are found infesting cotton crop. In recent past the mealy bugs, Phenacoccus solenopsis and Maconellicoccus hirsutus have attained major pest status. Adoption of Bt cotton has changed not only the cultivation profile, but also the pest scenario. While there is decline in the pest status of bollworms, the sap feeders are emerging as pests (Vennila 2008). In north zone, among the sucking pests, jassids alone were severe, spotted bollworm was moderate and pink bollworm was high; however H. armigera is negligible. In central zone, moderately high level of jassids population was seen; higher population of thrips and whitefly was recorded; spotted bollworm was moderate; and pink bollworm larval population was very high; H. armigera was higher at Akola centre. In south zone, higher population of aphids, jassids and thrips was recorded; however other sucking pests were low. Mealy bug was found in almost all zones. Low temperature and high humidity favoured the build-up of pests. In southern Punjab, mealy bug and tobacco caterpillar emerged as major pests on Bt cotton and attained economic status (Sarode

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et al. 2009). The climate change influenced crop growth, pathogens that cause diseases and insects that occur in the cotton ecosystem. CICR (Central Institute for Cotton Research) showed that the leaf-eating cotton caterpillar S. litura consumed 30% more leaves of cotton plants under elevated CO2 compared to control plants. Furthermore, the insect laid more eggs after feeding on the CO2-exposed plants. Among various sap-sucking pests, the whitefly B biotype causes serious yield losses to cotton, vegetable and ornamental crops not just as a direct pest but also as a vector of the cotton leaf curl virus in India and Pakistan. Elevated temperatures can have serious effects on increasing populations of the whitefly and the cotton leaf curl virus disease. Elevated CO2 in the atmosphere could result in increased ratio of carbon to nitrogen in leaf tissues which could decrease the nutritional value for insects. Reports indicate that elevated CO2 levels resulted in decline in the levels of Cry toxins in Bt cotton. Higher temperatures resulted in a decline in the efficacy of insecticides such as the synthetic pyrethroids and Spinosad. The vulnerability of cotton in North India also extends to the possibility of higher levels of whitefly infestation and transmission of the leaf curl virus disease due to increase in temperature (Kranthi 2014).

4.8.2

Changing Rice Pest Scenario in North Eastern India in Response to Climate Change

Spreading of insect pests to the newer areas due to climate change is reported, which may be due to their ability to survive in the changed climatic condition. In the northeastern region, there are certain reports on the emergence of new pests. Singh (1981) reported for the first time Parasa bicolour infesting rice in Ukhrul district of Manipur. Krishnasamy et al. (1982) first observed flea beetle Chaetocnema basalis during transplanting and at tillering stages in Assam during 1980. In the major ricegrowing districts of Manipur in September–November, 1986, four species of bugs were recorded in the milky stage. These were the pentatomids: Dolycoris indicus, Menida histrio and Scotinophora coarctata and coreid: Cletus signatus; stink bug, C. signatus, was predominant with 10–40% grain infestation; Menida sp. and Cletus sp. were also reported from the neighbouring Bhutan. Whorl maggot, Hydrellia sasakii, and brown plant hopper became major pests. Gundhi bug, hispa and D. armigera became most dreadful insects in Tripura, Meghalaya and Assam. Development of Biotype 6 of gall midge in Manipur was also reported. Changes in temperatures or rainfall patterns will have profound influence on pest scenario. Leaf mite and panicle mite which were not considered even as minor pests in rice during 1980s have now assumed major pest status mainly because of rise in temperatures and changes in climate. The winter mortality of adults of Nezara viridula is predicted to be reduced by 15% with each rise of 1
C (Kiritani 2006). Sometimes rising temperatures have negative effect on delicate natural enemies. For example, BPH is found to be 17 times more tolerant than its predator Cyrtorhinus lividipennis at 40
C, and subsequently resulting in rise in BPH populations (Krishnaiah and Varma 2013).

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In north eastern India, upland rice cultivation is common and only one crop is taken in a year. However, in Assam, wet land cultivation involves three crops in a year, viz. Ahu (March–April), Sali (July–August) and Boro or winter (December– January). The climate in this region with high rainfall and humidity is conducive for pest incidence and multiplication. Hispa is an important pest of this area and it is reported that increase in temperatures had an impact on the biology of the pest (Hazarika et al. 2009).

4.9

Conclusion

Climate change is the greatest challenge in the twenty-first century. As regards the pest dynamics, the pest problems will be more under elevated temperatures and CO2 in near future, as there are evidences in the form of changing pest scenario in various agroecosystems in India. The minor pests becoming major pests. Pest migration towards north may cause threat to the crops in North India. The insect vectors of medical importance may also pose great danger under changing climate, provided that if favourable breeding sites are available to them. The pest management tactics may be modified to manage pest population under changing climate which is a challenging task ahead for the entomologists.

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The Current Policies and Practices Behind Scaling Up Climate-Smart Agriculture in India Dhanya Praveen and Andimuthu Ramachandran

Abstract

Rainfed farming systems in India are severely wedged by climate change, variability, and extremities. A developing country like India faces multitudes of challenges in addressing current and future climate risks. Projections made up by the latest IPCC AR5 reports also reiterate that frequency and length of dry spells may likely be increased in future due to global warming, the consequences of which include increased heat and water stress for agriculture ecosystems. This may adversely impact the livelihoods of resource-poor farmers of this country. As the changing weather patterns pose serious threats to the traditional agriculture systems, climate-smart agriculture (CSA) is recognized as the future of farming in our country. With this backdrop of understanding, initiatives to scale up climatesmart agriculture (CSA) are underway. Moreover, India’s Intended Nationally Determined Contribution (INDC) and National Action Plan on Climate Change pay particular attention to the inclusion of sustainable agriculture action plans and also enhance resilience among smallholders. CSA practices require local specific dialogue with key stakeholders. As an initial step forward, climate change communication can play a critical role in enabling this dialogue. This chapter proposes to discuss about the current practices and model frameworks present in the implementations and scaling up of CSA in India as a part of strengthening the resilience of Indian agriculture sector and advancement in applied research. Regional variations are apparent in our country as far as cropping patterns are considered. Geo-climatic parameters like altitude, rainfall pattern, evaporation, soil type, and topography together evolve distinct agronomic environments wherein a distinct cropping pattern flourishes in a village, block, district, or state. This chapter would also like to discuss how science, policy, and community interface at every level from local to regional in India for D. Praveen (*) · A. Ramachandran Centre for Climate Change and Adaptation Research, Anna University, Chennai, India # Springer Nature Singapore Pte Ltd. 2020 V. Venkatramanan et al. (eds.), Global Climate Change: Resilient and Smart Agriculture, https://doi.org/10.1007/978-981-32-9856-9_5

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the effective implementation and maintaining its sustainability. Participatory and action research play a major role in its implementations and way forward. In order to create a win-win situation for CSA activities, India may necessitate a rigorous determination to capitalize on any synergies within spatial units and sectors, government departments, NGOs, research organizations, farmers, and all other stakeholders. Keywords

Climate-smart agriculture · Agricultural policy · Sustainable agriculture

5.1

Introduction

It is a major concern for the entire humanity to sustain the pace of agricultural growth to meet the rising demands of the large population of the world. Climate change has aggravated the already existing constraints of agriculture growth such as deteriorating soil health conditions, diminishing crop yields, groundwater depletion, declining size of operational holdings, and labor shortages. It is now a widely known fact that diversified options for adaptation across different regions and agricultural systems across the world have to be utilized to foster the agricultural transformation in order to address climate change. Climate-smart agriculture (CSA) was initially introduced by FAO in the Hague Conference on Agriculture, in 2010. Under a climate change scenario, it is an approach to evolve the technical, policy, and investment conditions to achieve sustainable agricultural development for food security. This also helps to transform agricultural systems to sustain food security and support rural development in a changing climate (FAO 2018; FAO 2014; Neufeldt et al. 2015). Agriculture and land-use change are considered as an adaptation priority and also a mitigation opportunity to limit global warming below 2  C by many developing countries in their Intended Nationally Determined Contributions (INDCs) under the Paris Agreement. The recent United Nations Climate Change Conference (COP24) held in Katowice, Poland, also focused on the fact that the world must scale up potential responses to climate change especially in the agriculture sector. In order to achieve Sustainable Development Goals 2: Zero Hunger, it is necessary to limit warming well below 1.5  C. “Climate smart agriculture provide a pathway to achieve sustainable development goals which focuses on poverty reduction, food security and environmental health” (Venkatramanan and Shah 2019). Further, “the SDGs are well connected as evidenced in the connection of SDG 2 with SDG 13 (climate security), SDG 6 (water security), SDG 15 (soil security), SDG 7 (energy security), and SDG 5 (gender equality)” (Venkatramanan and Shah 2019). Positive climate outcomes from the agriculture sector require the identification of climate-smart, context-specific, and investment-ready opportunities for farmers, investors, and policy makers. The main potential of it lies in the fact that transformative actions can be adopted to reorient food systems and have to be mainstreamed as an integrated approach responsive of the local contexts.

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Regional Crop Simulation studies conducted by the Indian Council of Agricultural Research (ICAR) under the Network Project on Climate Change (NPCC) indicate that food production could reduce by 4.5–9% during 2010–2039 and it could further decrease by nearly 25% in the long term (2070–2099). Because agriculture makes up roughly 14% of India’s GDP, a 4.5–9% loss of production due to climate change could translate into a loss of approximately 1.5 GDP per year (Tripathi and Mishra 2017; Geethalakshmi et al. 2011). Studies have also indicated that irrigation requirement in arid and semiarid regions is estimated to increase by 10% with every 1  C rise in temperature. District-level simulation studies under the RCP 4.5 scenario also indicated a decrease in the major C3 and C4 crop yields for South India (Ramachandran et al. 2017). This would affect not only the local food security, but the livelihood security as well. Based on this understanding, ICAR has launched a major project on Climate Resilient Agriculture in India, i.e., National Initiative on Climate Resilient Agriculture (NICRA) (http://www.nicra-icar.in/). NICRA has the twin objectives of generation of appropriate climate-resilient technologies for crops, horticulture, livestock, fisheries, and poultry and their demonstration on farmers’ fields through more than 150 Krishi Vigyan Kendras (Naresh Kumar et al. 2012). Institutions like CRIDA and ICRISAT are working in the states like Telangana, Andhra Pradesh, and Bihar with specific climate-smart agriculture (CSA) practices and identified synergies to design and promote local-level CSA implementation plans. They have taken initiatives in prioritizing CSA practices that are adaptable and location specific, factoring in diversity at grassroots level. In Indian contexts, many states are implementing CSA activities and establishing climate-smart villages. It requires coordinated actions among science, community, and government policies to bring in desired outcomes at the grassroots level. CSA brings together practices, policies, and institutions which are otherwise unfamiliar to farmers. Mahatma Gandhi National Rural Employment Guarantee Act (MNREGA) program in India also supports the promotion of CSAs and mainstreaming of climate considerations into developmental programs at local level.

5.2

Climatic Risks in Indian Farming Systems

Indian agriculture as it is predominantly rainfed has a high stake on the success and failure of monsoon systems. Most of our agriculture land has gone through severe degradation due to spatial variability of rainfall availability, water scarcity, poor soil conditions, etc. Agriculture ecosystems are highly influenced by climate variables such as precipitation, temperature, humidity, solar radiation, etc. According to IPCC, the arid and semiarid regions may be impacted severely through heavy land degradations, loss of biodiversity, and food insecurities. Indian agriculture is frequently faced with varying onset and termination dates of rainfall (e.g., delayed monsoon, early withdrawal of rainfall), intermittent dry spells, high-intensity wet spells, and heat/cold stresses which will have profound adverse effects on plant growth, phenology, and grain setting in crops. The change in the per capita area of arable land in India from the period 1950–1955 to 2000 is 0.9–0.15 ha and projected

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to decline further to 0.08–0.07 ha by the year 2025. It is projected that consecutive dry days may be increased by 5–10 days for the period 2081–2100 for India as per RCP 8.5 emission pathways (IPCC 2013). The rate of wheat senescence changes due to exposure to a temperature greater than 34  C was studied by Lobell (Lobell et al. 2012). The results revealed that there is statistically significant hastening of senescence from extreme heat. This result implies that warming presents a greater challenge to wheat growers. (Venkatramanan and Singh 2009a, b: Venkatramanan and Shah 2019). This observation is supported by Bapuji Rao et al. (2014), who found a decline in paddy yield by about 411–859 kg/ha due to a rise in temperature by 1  C. Auffhammer et al. (2011) also noted stronger adverse impact of climate change on rice crop due to rising temperatures. It is noted that arid and semiarid tracts of India have been suffering from acute water scarcity due to increasing temperature and higher evaporation rates than water availability (Agrawal et al. 2009; Aryal et al. 2018; Venkateswarlu 2017; Ramarao et al. 2013). In this case, early adoption of proper land, water, and agriculture management practices is crucial for a country like India. Concrete mitigation and adaptation efforts have to seep in to our agriculture systems in order to have sustainable agriculture development with less environmental footprints. In order to achieve the 2030 agenda for Sustainable Development and Climate Change, the UN has envisaged transformed agriculture ecosystems with a change in modes of production and consumption. In India, farmers’ lack resources, information, and capacity to adapt; hence they are unable to respond well with the climate stimuli. Apart from all these, farmers are also faced with fragmented land holdings, low income, and basic amenities.

5.3

CSA as Mitigation and Adaptation Option in India

Government of India has taken strong steps to have sustainable agriculture production systems with programs like Paramparagat Krishi Vikas Yojana—organic farming, Pradhan Mantri Krishi Sinchayee Yojana—efficient irrigation, Neeranchal— watershed development, National Initiative on Climate Resilient Agriculture (NICRA), reduction in fossil fuel subsidies, and National Adaptation Fund. Since climate change poses a threat to agricultural sustainability, smart options play a significant role both as a mitigation and adaptation option. Climate-smart agricultural technologies endeavor to enhance productivity sustainably, enhance resilience to climate change, and reduce greenhouse gas emissions (Fig. 5.1). Further, climatesmart agricultural technologies provide a pathway to achieve the goals of climatesmart agriculture (Venkatramanan and Shah 2019). It is a well-known fact that crop and livestock production systems are a significant source as well as a sink of greenhouse gases (GHGs). So there is a need to modify agricultural practices in a more sustainable way to overcome these problems. Evaluating the local scenario of the drawbacks with respect to GHG emissions, inefficiency of age-old farm operations, and declining soil fertility has to be considered on a serious note. Mitigation pathways always aim to have a sustainable

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Fig. 5.1 Matrix of climate-smart agriculture technologies (source: Venkatramanan and Shah 2019)

production with low energy-, water-, and input-intensive cultivation. Based on the purpose, time, form, and space scales adaptations can be divided into various types (Fig. 5.2). Changes in farm operations like modifying planting, harvesting, and fertilizing practices for crops, changing crops under cultivation, using tolerant varieties of seeds, micro-irrigation facilities, agroforestry, seed and fodder banks, farm ponds, and soil conservation measures may come under both planned and autonomous adaptation measures. Developing new crop and livestock varieties and providing agricultural subsidies on the input cost, insurances and credit facilities, etc. come under planned adaptation measures.

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• Passive/ Active • Planned/ Autonomous

•Ecosystem / Community based •Social/ technological/ economical

• Anticipatory/ Responsive • Proactive/ Reactive

Purpose

Time

Form

Space •Local/ Regional/Widesprea d •Native /Indigenous/ Exogamic

Fig. 5.2 Types of adaptation (source: Dhanya and Ramachandran 2016)

5.4

Science, Policy, and Community Interface

It is likely that by 2050, we need to increase our food grain production by 50% more to meet our food demand (FAO 2013). Receiving timely information is highly significant for taking informed decisions especially in the purview of climate change and weather aberrations. Agriculture has always had to cope with variability in the weather, but climate change will likely produce more permanent shifts in temperature and precipitation that will require more robust actions (Neufeldt et al. 2015). There needs to be a science, policy, and community interface at every level from local to regional in India for effective implementation and maintaining its sustainability (CSA Guidelines 2018; Ngara 2017). Participatory and action research plays a major role in its implementations and way forward. Sustaining CSA activities and its effective implementation require integration of highly committed workforce at all necessary levels. Conscious efforts are expected from all actors to maximize any synergies within and outside of all spatial units and sectors, nonprofit organizations, public and private sectors, research organizations, and all stakeholders. The CSA projects in our country go through different processes such as understanding the context including identification of major problems/barriers and opportunities; developing and prioritizing solutions and designing plans; implementation; and finally monitoring and evaluation (Fig. 5.3). Institutional mechanism research institutes have to take care of the latest scientific advancements as far as climate change adaptations and mitigations are concerned. As far as climate-smart agriculture policies are concerned, Government of India has formulated National Mission for Sustainable Agriculture (NMSA) as one of the eight national missions embodied under National Action Plan on Climate Change

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Fig. 5.3 Steps involved in CSA implementation

(NAPCC), which aims at enhancing agricultural productivity by integrated farming, water-use efficiency, soil health management, and synergizing of resource conservation. There is another major program, Pradhan Mantri Krishi Sinchayi Yojana (PMKSY) which focuses on “per drop more crop” for promoting micro-irrigation systems which are proven to save 50% water in irrigation activities. Strengthening of the livelihood is done through doubling of the farmers’ income initiative by the Government of India. More than 27 big-budget projects (approximately 660 crores) have been sanctioned for various states of India under NAPCC and NABARD has been designated as National Implementing Entity (NIE) for implementation of adaptation projects under NAFCC by Govt. of India. Most of it aims at climatesmart agriculture adaptation interventions. Widespread mainstreaming of CSA in India requires critical appraisal of ongoing and promising practices for the future, and extensive institutional and financial support for its adoption (Fig. 5.4). Initiatives are sprouting up from the government agencies to make agriculture ecosystems smarter in future. One of such notable initiatives is from the mission of the Indian Meteorological Department (IMD) which aims to provide crop- and location-specific agromet advisories for the farmers through technological innovations by establishing high-end operational agrometeorological advisory services even at village level by 2030. Weather advisories will be disseminated through a wide network of multichannel systems like radio, Doordarshan, private TV, mobile phone, social media, NGOs, Krishi Vigyan Kendra (KVK), Kisan Call Centers/ICAR and other related institutes and universities, and extension centers/ agriculture departments.

Innovations technological, ICTs, Agronomy based adaptations

Livelihood Security Climate Smart Villages

Actors: Actors :ICRISAT,CRIDA,

ICAR, State Agriculture Universities

Regional- local administrative units, Farmers welfare associations, Seld Help Groups, NGOs Actors Stakeholders

SDGS-Food security INDCs NAPCC-NMSA SAPCC Incentives, Loans wave off Weather based insurances Actors Central state governments ,District administrations, Department of Agriculture, Rural Development institutes etc

Finance & Policies

Basic, applied and action research

Community

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Science

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Fig. 5.4 Framework diagram of various levels and actors involved in climate-smart agriculture implementation—a science, community, and policy interface

The combined efforts put forward by science, policies, and government alone can have the convincing power among the primary stakeholders to shift themselves from conventional farming methods to adopt CSA practices.

5.5

Success Stories of CSA

CSA has a major role in enhancing farm productivity and resilience to weather extremes and decreasing GHG emissions to a large extent (Steenwerth et al. 2014). It should be the prerogative of both private and public sectors to identify and promote technologies and practices that can increase farm productivity and farmers’ adaptive capacity and, as a co-benefit, ability to mitigate (Thapa et al. 2015). To help the state mitigate such climate-associated risks in agriculture, ITC Limited, a leading multibusiness enterprise has devised scalable approaches to bring about climate smartness in the state’s agriculture system in three states, i.e., Madhya Pradesh, Maharashtra, and Rajasthan, with the support from CGIAR Program on Climate Change, Agriculture and Food Security (CCAFS). The venture is being implemented by ITC along with its civil society partners through the climate-smart village (CSV) approach which promotes the identified sites as multi-stakeholder learning platforms for testing technological and institutional options to build resilience. In India, climate-smart villages (CSVs) have been set up in many parts of the country, as they are significant for putting climate-smart agriculture into action. Almost 500 CSVs have been launched and functioning in Haryana’s rice-wheat

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systems. In Maharashtra as well efforts are underway in setting up more climateproof villages giving focus on sustainable agriculture, water management, and ecosystem-based disaster management programs for the vulnerable districts. This is with the support of TERI. As part of this initiative, promotion of crops that are drought hardy will sustain in the changing climate, with promotion and preservation of traditional varieties being planned along with more public–private participation in water conservation. Integrated agriculture, which comprises animal husbandry, fisheries, and agroforestry, will be adopted. Government of Madhya Pradesh is also setting up more than 1000 climate-smart villages under the National Agriculture Development Programme (NADP) and Indian National Mission on Sustainable Agriculture. The smart practices are not confined to farm operations, but they also opt for smart weather forecast services, mobile applications, smart apps, climate-smart villages, information and communication facilities, social media, advisories and alerts on index-based insurance in the event of extreme weather conditions, etc. CGIAR has conducted a research study with the small and marginal farmers of Indo-Gangetic Plains (IGP) of India. They have indicated that among the CSA practices and technologies including use of improved crop varieties, laser land levelling, zero tillage, residue management, site-specific nutrient management, and crop diversification, a majority of the farmers prefer to use improved crop varieties, crop diversification, laser land levelling, and zero tillage practice in their fields. It is interesting to note that farmers in these areas can earn net return of INR 15,712/ha/ year with the usage of improved crop varieties, INR 8119/ha/year with laser levelling, and INR 6951/ha/year with zero tillage in rice-wheat system (Sapkota et al. 2015; Khatri-Chhetri et al. 2016; Jat et al. 2014). Through most of these studies, it is revealed that most of the climate-smart agricultural practices (CSAPs) have clear economic (Aryal et al. 2015; Khatri-Chhetri et al. 2016; Sapkota et al. 2015) and climate change adaptation benefits (Aryal et al. 2016; Sapkota et al. 2015). Majority of the farmers in Bihar adopt these CSAPs as complements and substitutes. The gender of the farmer, caste, education, social and economic status, farm land characteristics, access to the market, extension services, and training are found to be some of the crucial factors affecting the decision to adopt the latest CSA technologies in Bihar. Knowingly or unknowingly various adaptation measures are being implemented at farm level in our country which may not be under the name of CSA implementation. It is important to create more evidences, document the successful practices and autonomous adaptations in various agroecological zones in India, and make rational decisions that promote and upscale the sustainable and climate-smart practices in a region. However, there are lots of regional disparities attached to its field-level implementation. Deliberate microlevel studies are the need of the hour to design planning at local level where CSA is not yet practiced. There is a dire need to have strong public–private partnerships programs especially for financing adaptation actions at various levels.

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Constraints for Scaling Up and Way Forward

Willingness to adapt and support is a significant factor in CSA adoption. Science should be able to create a real-time situation wherein primary stakeholders lay faith in adopting the advisories. For this, our research, institutional, and technological capacities need to be increased further. When the complex monsoon systems of our country get smarter every year with more number of unanticipated extreme events, there is a need to enhance stakeholder capacities and we become at least smart enough to adapt to the changing situations. From the research and development perspective there is a growing need to provide smart cultivars/seeds which are drought, salt, and flood tolerant based on the forecasts given by Indian Meteorological Department for each growing season. Not only dry spells and drought, but we are not equipped with proper proactive measures to tackle flash floods and storm surges as well. Report issued by National Institute of Disaster Management (NIDM) shows that hydrometeorological disaster has increased by 78.4% in the past 100 years. There are research publications revealing that sea level of Chennai coasts may rise by 0.92 m above MSL under moderately strong emission reduction scenario of IPCC AR5 under RCP 4.5. It shows then to have aggressive cuts in the carbon pollution, through energy-efficient ways (Dhanya et al. 2018). It is the need of the hour to put more focus on research and development which will pave the way forward for wider development of halophyte crops that can grow successfully in salt-affected soils of our coastal wetlands. Research outcomes show similar cases with the entire coastal stretch of India; however the research happens in silos and the practitioners or catalysts of grassroots-level interventions are aware of these outcomes in our country. Even after realizing the terrible situation of water shortages, poor and marginal farmers in our country are neither willing nor capable of adopting the water-efficient cultivation practices such as alternative wetting or drying (AWD) in paddy cultivation and System of Rice Intensifications. Field studies revealed that rural poor is extracting the groundwater lavishly without understanding the ill effects. Thus, the seepage of awareness to adopt water-conserving technologies and reduce, reuse, and recycle the available water to the grassroots level still needs to be enhanced in our country. There should be a climate leader at each district to instill a climate lens to each and every developmental activity that happens in the district. He/she should have the responsibility to provide information and advisories to the local authorities on (a) what is happening around us internationally, nationally, and state-wise; (b) what a district can possibly do; and (c) how it can be accomplished or what are the possible solutions. Planned implementation of the CSA tools lies in the hands of the public sector, by enhancing and mobilizing finance, human resources, capacity building, etc. There are success stories from various districts of India which can be spread across on a mission mode. Members from the local Panchayat also need to be made accountable for the smooth adoption and implementation of CSA at farm level. Sensitizing the local youth and inviting more participation from NGOs and self-help groups may also help in wider acceptance of CSA.

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There are positive vibes noted from the recent flash floods (with 69 years’ recordbreaking rainfall of 951.4 mm for the month of August, 2019) which occurred in various parts of our country in terms of adaptation. The stories of post-disaster resilience created by the social media networks especially in Kerala are a remarkable one. It showed that real smart ways of adaptation happen in the minds of people and lie in the power of networking. Social media groups through Facebook or WhatsApp were doing excellent reactive or responsive adaptations in smart ways to revive the farmers from loss and damage due to unprecedented floods, landslides, and crop loss. They are found to be supporting each other with hardened seeds, saplings, farm implements, and financial support. This area is an emerging topic of discussion, as to how media and social groups can facilitate smart adoption of agriculture production in a synergistic way. Farmers will have faith in the advisories only if we can give reliable forewarnings, which can sustain their crops and livelihood. At present almost all the agricultural universities and research organizations are working relentlessly to achieve the desired outcomes. Modeling communities and researchers should put in constant efforts to minimize uncertainties and biases in their forecasts. At present, with almost 80% of rural households having marginal landholdings of 1 ha and just 20% holding more than 2 ha, technological adaptation intervention has a major role to play in order to make it smart. The success stories of CSA practices with international and national importance have to be well documented scientifically and widely spread by social and print media. Better availability of information on the success and profitability of CSA practices from reliable sources would support its greater adoption over larger spatial extent in our country. With the backdrop of understanding that there may be likely increase in temperature by 2  C by the end of this century, CSA has a promising role to play in order to improve the agriculture situation of our nation.

References Agrawal A, Kononen M, Perri N (2009) The role of local institutions in adaptation to climate change. World Bank, social development working paper no 118. World Bank Group, Washington, DC Aryal, J.P., Sapkota, T.B., Jat, M.L. and Bishnoi, D.K. (2015), “On-farm economic and environmental impact of zero-Tillage Wheat: a case of North-west India”, Experimental Agriculture, Vol. 51 No. 1, pp. 1–16. Aryal, J.P., Sapkota, T.B., Stirling, C.M., Jat, M.L., Jat, H.S., Rai, M., Mittal, S. and Sutaliya, J.M. (2016), “Conservation agriculture-based wheat production better copes with extreme climate events than conventional tillage-based systems: a case of untimely excess rainfall in Haryana, India”, Agriculture, Ecosystems & Environment, Vol. 233, pp. 325–335 Aryal J, Jat M, Sapkota T, Khatri-Chhetri A, Kassie M, Rahut D, Maharjan S (2018) Adoption of multiple climate-smart agricultural practices in the Gangetic plains of Bihar, India. Int J Clim Change Strat Manag. https://doi.org/10.1108/ijccsm-02-2017-0025 Auffhammer M, Ramanathan V, Vincent JR (2011) Climate change, the monsoon, and rice yield in India. Clim Change 111(2):411–424

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Bapuji Rao B, Santhibhushan Chowdary P, Sandeep V, Rao V, Venkateswarlu B (2014) Rising minimum temperature trends over India in recent decades: implications for agricultural production. Global Planet Change 117:1–8. https://doi.org/10.1016/j.gloplacha.2014.03.001 CSA Guidelines (2018). https://csa.guide/csa/practices. Accessed 19 Apr 2018 Dhanya P, Ramachandran A (2016) Farmers’ perceptions of climate change and the proposed agriculture adaptation strategies in a semi arid region of South India. J Integr Environ Sci 13 (1):1–18. https://doi.org/10.1080/1943815X.2015.1062031 Dhanya P, Andimuthu R, Palanivelu K (2018) Constructing local sea level rise scenarios for assessing possible impacts and adaptation needs: insights from coasts of India. In: Zhang Y, Hou Y, Yang X (eds) Sea level rise and coastal infrastructure, vol 2. IntechOpen, Rijeka. https:// doi.org/10.5772/intechopen.74325 FAO (2013) Climate-smart agriculture source book. Food and Agriculture Organization of the United Nations, Rome. http://www.fao.org/docrep/018/i3325e/i3325e.pdf. Accessed 8 July 2016 FAO (2014) The state of food insecurity in the world (SOFI): strengthening the enabling environment for food security and nutrition. Food & Agriculture Organization of the United Nations (FAO), Italy, p 206 FAO Report (2018). http://www.fao.org/news/story/en/item/1174811/icode/. Accessed 7 Jan 2019 Geethalakshmi V, Lakshmanan A, Rajalakshmi D, Jagannathan R, Gummidi S, Ramaraj AP et al (2011) Climate change impact assessment and adaptation strategies to sustain rice production in Cauvery basin of Tamil Nadu. Curr Sci 101(3):10 IPCC (2013) Summary for policymakers. In: Stocker TF, Qin D, Plattner G-K, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, Midgley PM (eds) Climate change 2013: the physical science basis. Contribution of working group I to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge/New York Jat RK, Sapkota TB, Singh RG, Jat ML, Kumar M, Gupta RK (2014) Seven years of conservation agriculture in a rice-wheat rotation of eastern Gangetic plains of south Asia: yield trends and economic profitability. Field Crop Res 164:199–210 Khatri-Chhetri A, Aryal JP, Sapkota TB, Khurana R (2016) Economic benefits of climate-smart agricultural practices to smallholder farmers in the Indo-Gangetic Plains of India. Curr Sci 110 (7):1244–1249 Lobell DB, Sibley A, Ivan Ortiz-Monasterio J (2012) Extreme heat effects on wheat senescence in India. Nat Clim Chang 2(3):186–189 Ngara T (ed) (2017) Climate-smart agriculture manual for agriculture education in Zimbabwe. Climate technology centre and network, Denmark, Copenhagen. https://www.ctc-n.org/system/ files/dossier/3b/climate-smart_agriculture_manual_final.pdf. Accessed March 2018 Naresh Kumar S, Singh AK, Aggarwal PK, Rao VUM, Venkateswaru B (2012) Climate change and Indian agriculture salient achievements from ICAR network project. Indian Agricultural Research Institute Publications, New Delhi Neufeldt H, Negra C, Hancock J, Foster K, Nayak D, Singh P (2015) Scaling up climate-smart agriculture: lessons learned from South Asia and pathways for success, ICRAF Working Paper No. 209. World Agroforestry Centre, Nairobi. https://doi.org/10.5716/WP15720.PDF Ramachandran A, Dhanya P, Jaganathan R, RajaLakshmi D, Palanivelu K (2017) Spatiotemporal analysis of projected impacts of climate change on the major C3 and C4 crop yield under representative concentration pathway 4.5: Insight from the coasts of Tamil Nadu, South India. PLoS One 12(7):e0180706. https://doi.org/10.1371/journal.pone.0180706 Rama Rao CA, Raju BMK, Subba Rao AVM, Rao KV, Rao VUM, Ramachandran K, Venkateswarlu B, Sikka AK (2013) Atlas on Vulnerability of Indian Agriculture to Climate Change. Central Res Inst Dryland Agric Hyderabad 116 Sapkota TB, Jat ML, Aryal JP, Jat RK, Khatri-Chhetri A (2015) Climate change adaptation, greenhouse gas mitigation and economic profitability of conservation agriculture: some examples from cereal systems of Indo-Gangetic Plains. J Integr Agric 14(8):1524–1533

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Steenwerth K, Hodson A, Bloom A et al (2014) Climate-smart agriculture global research agenda: scientific basis for action. Agric Food Secur 3:11. https://doi.org/10.1186/2048-7010-3-11 Thapa K, Gautam S, Chaudhary P, Khattri-Chherti A, Bhatta KP, Gurung KD, Bhattarai B, Rijal D, Gurung DD (2015) Scaling-up climate smart agriculture in Nepal: inception report. LIBIRD and CCAFS, Kaski Tripathi A, Mishra AK (2017) Knowledge and passive adaptation to climate change: an example from Indian farmers. Clim Risk Manag 16:195–207 Venkateswarlu B (2017) Climate smart agriculture: are we poised to outsmart climate change impacts? Curr Sci 112(5):10. http://www.indiaenvironmentportal.org.in/files/file/Climate% 20smart% 20agriculture.pdf. Accessed Feb 2018 Venkatramanan V, Shah S (2019) Climate smart agriculture technologies for environmental management: the intersection of sustainability, resilience, wellbeing and development. In: Shah S et al (eds) Sustainable green technologies for environmental management. Springer Nature Singapore Pte Ltd., Singapore, pp 29–51. https://doi.org/10.1007/978-981-13-2772-8_2 Venkatramanan V, Singh SD (2009a) Differential effects of day and night temperature on the growth of rice crop. Pusa Agric Sci 32:57–62 Venkatramanan V, Singh SD (2009b) Differential effects of day and night temperature on the growth of wheat crop. Ann Agric Res 30(1&2):49–52

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Building Resilience to Climate Change in Agriculture: Integrated Natural Resource Management and Institutional Measures K. H. Anantha, Kaushal K. Garg, and Sreenath Dixit

Abstract

Available evidences from natural resource management suggest that building resilience into ecological ecosystems is the ideal way to deal with future shocks as well as emerging climate risks especially in drylands. However, there are diverse views on how these evidences have implications for policies and strategies for responding to climate change. We attempt to address this gap by using different case studies on natural resource management (NRM) interventions in drylands. Drylands are characterized by water scarcity, land degradation, and poor crop and livestock productivity. Increasing uncertainty in rainfall behavior/ other meteorological parameters increases the challenges of the region further. Despite such challenges, large scope exists for bridging yield gaps through various land, water, nutrient, and crop management interventions. This chapter shows how these NRM interventions have helped different stakeholders in different agroecological regions for building system resilience through positive impact on land- and water-use efficiency. Moreover, the chapter also describes different institutional approaches for achieving the system-level outcomes. Keywords

Natural resource management · Drylands · Resilience · Scaling-up · Ecosystem services · Climate resilient agriculture

K. H. Anantha · K. K. Garg (*) · S. Dixit ICRISAT Development Centre, ICRISAT, Patancheru, Telangana, India e-mail: [email protected] # Springer Nature Singapore Pte Ltd. 2020 V. Venkatramanan et al. (eds.), Global Climate Change: Resilient and Smart Agriculture, https://doi.org/10.1007/978-981-32-9856-9_6

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Introduction

Agriculture is one of the important sectors of the Indian economy. It contributes nearly 14% to the GDP of India and about 12.55% of its total exports (Government of India 2017). About 54.6% Indian population still relies on agriculture as its principal source of income and agriculture serves as a source of raw material for a large number of industries. India accounts for only about 2.4% of the world’s geographical area and 4% of its water resources, but it supports about 17% of the world’s human population and 15% of the livestock. Accelerated growth of agriculture production is therefore necessary, not only to achieve higher contribution towards GDP and meet the rising demand for food, but also to increase farmers’ income to ensure their inclusiveness. Out of 141 million ha arable land, 54% land is rainfed and remaining irrigated. More than 80% of 137 million farm households are small farm holders and they together account for only 45% of the total area under operation (Government of India 2014). Rainfed agriculture supports an estimated 40% of population and has a large share of cropped area under rice (42%), pulses (77%), oilseeds (66%), and coarse (nutritious) cereals (85%). Further, rainfed agriculture supports about 78% of cattle, 64% of sheep, and 75% of goats that cater to most part of the meat market in the country. However, agriculture is affected by natural disasters and these disasters are compounded by the outbreak of epidemics and human-made disasters which severely affect farm production and income which are beyond the control of farmers. Further, increasing fragmentation of holdings, frequent climatic variations (Boomiraj et al. 2010; Kesava Rao et al. 2013), and rising input costs and postharvest losses pose an enormous challenge to sustaining agricultural growth. With commercialization of agriculture, the magnitude of loss due to unfavorable eventualities is increasing. The strong trends in climate change already evident, the likelihood of further changes occurring, and the increasing scale of potential climate impacts give urgency to addressing agricultural adaptation more coherently. There are many potential adaptation options available for marginal change of existing agricultural systems, often variations of existing climate risk management. We show that implementation of these options is likely to have substantial benefits under moderate climate change for some cropping systems. However, there are limits to their effectiveness under more severe climate changes. Hence, more systemic changes in resource allocation need to be considered, such as targeted diversification of production systems and livelihoods. Several market and policy instruments have been evolved and established to address compounded risks in the agriculture sector. In order to minimize price risks associated with market, Government of India introduced Minimum Support Price (MSP) for different crops. However, the benefit of MSP is not uniform across regions as it depends on the procurement policy of the government and most of the crops such as horticulture crops are not in the ambit of MSP. Similarly, crop insurance has been the major risk management strategy of the government to minimize agricultural risks and protect farmers from natural disasters such as

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drought, frost, cyclones, and flood. In recent years, contract farming also has emerged as one of the mechanisms by which small farmers can supply high-value crops to urban and international markets while benefiting from assured higher incomes (Government of India 2018). With this background, this chapter addresses the risk-mitigating strategies in agriculture.

6.2

Land Degradation, Water Scarcity, Nutrient Deficiency, and Climate Change

Climate change has added a new dimension to future agricultural growth, which is a major concern. Rising temperature, altered rainfall patterns, and frequent extreme events will increasingly affect crop production. In India, average temperature has increased by +0.65  C between 1901 and 2001 (Fig. 6.1) (IMD 2017). Climate aberrations impact all small farm holders, especially those in rainfed and marginal production areas. Therefore, investment options arise for both adaptation and mitigation, and policies and technology to reduce the risk and impact of climate change for farmers. Impact of climate change at regional level and measures needed to adapt crops and agricultural systems to that change are critical and urgent. Kesava Rao et al. (2013) found that the semiarid area increased by 8.45 Mha in India (mainly in Madhya Pradesh, Bihar, Uttar Pradesh, Karnataka, and Punjab) and decreased by 5 Mha in 11 states between 1971–1990 and 1991–2004, an overall increase of 3.45 Mha (Fig. 6.2). In addition, there has been a net reduction of 10.71 Mha in the dry subhumid area pointing to dryer and wetter production zones in India that replace more moderate climates (Kesava Rao et al. 2013; Jalota et al. 2012).

Fig. 6.1 Annual average temperature of India: 1901–2016 (source: IMD 2017)

Fig. 6.2 Changes in climate types in India between 1971–1990 and 1991–2004 (source: Kesava Rao et al. 2013)

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Water Scarcity and Land Degradation

India will be required to produce more food with less land and water. Per capita water availability, in India, has declined from 5177 m3 in 1951 to 1545 m3 in 2011 due to the rise in population from 361 million in 1951 to 1.21 billion in 2011 (Government of India 2014). Water resources in most of the river basins have been allocated and/or utilized among various sectors (domestic, agriculture, industry, energy, ecosystems) and only limited scope exists to further harvest freshwater. Irrigated regions are near their productivity plateau and the challenge is how to sustain yields in irrigated areas as land and water degradation continues. Rainfed regions bypassed for development in the past are now looking at how to harness innovation to close future increases in food production while sustaining production levels in irrigated regions. Agriculture is the biggest user of water, accounting for about 80% of the water use and mounting pressure for diverting water to other sectors. It is projected that availability of water for agricultural use in India may be reduced by 21% by 2020, resulting in a reduced production of irrigated crops, especially rice, and associated food price increases. Climate change will exacerbate water scarcity by threatening the scope of rainfed agriculture (Wani et al. 2009). Policy reforms to adapt include the establishment of secure water rights to users, decentralization and privatization of water management functions to appropriate levels (including communities for watersheds), pricing reforms, markets in tradable property rights, and introduction of appropriate water-saving technologies. Water scarcity is already a problem in many parts of the world, and an increasing number of regions are reaching the limit at which reliable water services can be delivered. An estimated 2.7 billion people are living in river basins that experience severe water scarcity during at least 1 month of the year, and almost half a billion people experience severe water scarcity for at least 6 months of the year (Fig. 6.3) (Hoekstra and Mekonnen 2011). Globally, land degradation, freshwater scarcity, and soil nutrient loss are on the rise which reduce the quality and quantity of natural resources available for food production. Worldwide, agriculture accounts for about 70% of global freshwater withdrawals, although there is wide regional variation (Hoekstra and Mekonnen 2011). It is estimated that water use has been growing at more than twice the rate of population increase globally, and competition for freshwater resources is increasing between sectors, i.e., agriculture, industries, domestic, and ecological uses (Palaniappan and Gleick 2009). Further, it is expected that 17% more water will be required by 2020 to meet food production needs as populations grow and diets continue to shift towards high-water-demanding crops and animal products (Palaniappan and Gleick 2009). Currently, 40% of the world’s food production is grown on irrigated land (Siebert and Döll 2010). This clearly implies that rainfed agriculture plays a major role in ensuring food security to rapidly growing population across the world. Recent data show a general increase in the global food production. This can be attributed to both the expansion of cultivated area and technological progress, leading to increased crop yields (FAO 2010). This yield gain has been achieved

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Fig. 6.3 Water scarcity status in major river basins of India from 1996 to 2005 (source: adapted from Hoekstra and Mekonnen 2011)

largely due to heavy reliance on fertilizers and pesticides, thereby putting pressure on the environment. According to Fyles and Madramootoo (2016), although N and P are often replenished, other nutrients are not replenished. Thus, nutrient removal from agricultural soils through erosion, leaching, and crop uptake needs to be balanced through external inputs. Similarly, Bossio et al. (2010) reviewed various studies and identified that in many Asian and Latin American countries, current rates of soil nutrient depletion are unsustainable. Likewise, in India, soil nutrient deficiencies have significantly reduced the effectiveness of N and P fertilizers and limit crop yields. Significantly, the amount of grain grown per kg of nutrient applied declined from 13.4 kg of grain in 1970 to 3.7 kg of grain (Jones et al. 2013). It is estimated that soil erosion removes 23–42 million tons of N and 12–22 million tons of inorganic P from agricultural fields each year and loss of nutrients through erosion also wastes expensive nutrients added as fertilizer (Quinton et al. 2010). Food production at the global scale can cater to the needs of growing population. Nevertheless, a web of factors challenges the various dimensions of food security (Fig. 6.4). Among the challenges that are confronting global agricultural landscape, climate change is quite significant as it has the potential to reduce agricultural food production (Venkatramanan and Shah 2020). Climate change drives food security at both global and regional scales. There is a wide range of predicted impacts on crop production due to regional variations in growing length, minimum and maximum temperatures, frequency and intensity of precipitation, and spread of crop pests and diseases (IPCC 2007). Climate change impacts on crop yields will also vary widely with the number of biophysical and socioeconomic factors, viz. soil texture, nutrient and organic matter levels, and ability of farmers to mitigate precipitation and temperature changes. Use of agrochemicals, supplemental irrigation, improved crop varieties, and altering farm management techniques such as timing of field

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Fig. 6.4 Challenges to food security (source: Venkatramanan and Shah 2020)

operations and use of conservation agriculture are some of the factors which can help to withstand climate change risks in agriculture. According to different studies, drought and extreme rainfall over the last 50 years in India have already reduced rainfed rice yields by about 6%, and wheat yields have not increased in 10 years (Auffhammer et al. 2012; Lobell et al. 2012). Further, increases in day and night temperature are reported to negatively affect the growth and development of rice and wheat crops, which are the staple food crop in South Asia (Venkatramanan and Singh 2009a, b). An estimation of crop production changes in South Asia to 2050 under climate change suggests that daily per capita food availability will drop from 2424 to 2241 kcal (Nelson et al. 2010).

6.3

Current Yield Gap and Technologies for Bridging the Gap

In order to meet increasing demands of food due to increasing population and income, food production in India needs to be increased. The production of food grains in India increased considerably since 1960s due to increase in arable area, large-scale cultivation of high-yielding semidwarf varieties, and increased applications of irrigation, fertilizers, and pesticides. India became food secure in the last three decades, at gross level, because of increase in food production. The food security of India is, however, now at risk due to increase in population. By 2050, India’s population is expected to grow to 1.6 billion people from the current

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level of 1.2 billion. This implies a greater demand for food. “The cereal requirement of India by 2020 will be between 257 and 296 million tons depending on income growth” (Kumar 1998; Bhalla et al. 1999). The demand for rice and wheat is expected to increase to 122 and 103 million tons, respectively, by 2020 assuming a medium income growth (Kumar 1998). This will have to be produced from the same or even shrinking land resource. Thus, by 2020 the average yields of rice and wheat need to be increased by about 60%. Similar is the scenario for many other crops. “A linear relationship is generally assumed between biomass growth and vapor flow (ET), which describe water productivity (WP) in the range between 1,000 and 3,000 m3 ton 1 for grain production” (Rockström 2003). “It is recognized that this linear relationship does not apply for the lower yield up to 3 t ha 1 which exactly coincide with yield level at small and marginal farmers in dryland/rainfed areas. The reason is that improvements in agricultural productivity, resulting in yield increase and denser foliage, will involve a vapor shift from nonproductive evaporation (E) in favor of productive transpiration (T) and a higher T/ET ratio as transpiration increases (essentially linearly) with higher yield” (Stewart et al. 1975; Rockström et al. 2007). Huge scope for improving water-use efficiency by green water management especially at lower yield range exists and can help in reducing water-stress situation. “Evidence from water balance analyses on farmers’ fields around the world shows that only a small fraction, less than 30% of rainfall, is used as productive green water flow (plant transpiration) supporting plant growth (Rockström 2003). In arid areas typically as little as 10–15% of the rainfall is consumed as productive green water flow (transpiration), 85–90% flows as non-productive evaporation, i.e., no or very limited blue water generation” (Oweis and Hachum 2009). In temperate arid regions, such as West Africa and North Africa, a large portion of the rainfall is generally consumed in the farmers’ fields as productive green water flow (45–55%) that results in higher yield levels (3–4 t ha 1 as compared to 1–2 t ha 1) and 25–35% of the rainfall flows as nonproductive green water flow and remaining 15–20% generate blue water flow. Agricultural water interventions in the watershed in Indian semiarid tropics (SAT) reduced runoff amount by 30–50% depending on rainfall distribution and converted it more into green water (Garg et al. 2012). There is vast untapped potential in rainfed areas with appropriate soil and water conservation practices (Rockström and Falkenmark 2000; Wani et al. 2003a, 2009, 2011a, b, 2016; Rockström et al. 2007, 2010; Anantha and Wani 2016). “Even in tropical regions, particularly in the sub-humid and humid zones, agricultural yields in commercial rainfed agriculture exceed 5–6 t ha 1 (Rockström and Falkenmark 2000; Wani et al. 2003a, b). At the same time, the dry sub-humid and semi-arid regions have experienced the lowest yields and the weakest yield improvements per unit land. Here, yields oscillate between 0.5 to 2 t ha 1, with an average of 1 t ha 1 in sub-Saharan Africa, and 1–1.5 t ha 1 in South Asia, Central Asia and West Asia and North Africa under rainfed agriculture” (Rockström and Falkenmark 2000; Wani et al. 2003a, b; Oweis and Hachum 2009).

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Fig. 6.5 A comparison of harvested grain yield by implementing IWRM techniques in BW1 Vertisol Heritage watershed at ICRISAT with traditional farmer’s practices at BW4C; results are shown since 1976 onwards

Data obtained from long-term experiment conducted at ICRISAT’s heritage watershed site (Fig. 6.5) has explained that due to integrated IWRM interventions average crop yield is fivefold higher compared to traditional farmer’s practices (Wani et al. 2003a, 2011a). Similar results are also recorded at Adarsha watershed, Kothapally, Southern India, where implementing IWRM interventions enhanced crop yields almost 2–3 times compared to baseline situation (Wani et al. 2003a; Sreedevi et al. 2004; Karlberg et al. 2015). Yield gap analyses carried out for major rainfed crops in semiarid regions in Asia and Africa and rainfed wheat in West Africa and North Africa revealed large yield gaps being a factor of 2–4 times lower than achievable yields (Fig. 6.5). In countries in Eastern and Southern Africa, the yield gap is very large (Fig. 6.6). Similarly, in many countries in West Asia, farmers’ yields are less than 30% of achievable yields, while in some Asian countries, the figure is closer to 50%. Historic trends present a growing yield gap between farmers’ practices and farming systems that can benefit from advances in management practices (Wani et al. 2003b, 2009).

Syria

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Fig. 6.6 Examples of observed yield gap (for major grains) between farmers’ yields and achievable yields (100% denotes achievable yield level, and columns actual observed yield levels) (source: Rockström et al. 2007)

6.4

Climate-Resilient Practices

6.4.1

Agriculture Water Management Interventions

Rainfall in dry lands is highly erratic and nonuniform which often leads to longer duration dry spells. Various land and water interventions alleviate water-stress situation to a certain extent but supplemental irrigation sometimes is highly essential to save the crop. Crop intensification with the help of supplemental irrigation is also an important option for better use of available water resources and enhancement of income in rainfed regions. Sharma et al. (2010) showed that the rainfed districts in India receiving rainfall in the range of 400–1600 mm covering 39 Mha generate on an average 115 km3 y 1 surface runoff in a normal year. Twenty percent of harvested runoff can provide 100 mm of supplemental irrigation for 25 Mha rainfed lands and remaining 80% would contribute to meet river/environmental flow and other requirements for downstream locations. Several studies indicated an average increase of 50% in total production through increased water productivity with one supplemental irrigation and improved management compared to the traditional practice (Joshi et al. 2005, 2008; Wani et al. 2008, 2011a, b; Sreedevi et al. 2007; Pathak et al. 2009, 2011; Sharma et al. 2010). Rainwater harvesting in watersheds is a basic activity and clear impacts of runoff harvesting through various types of structures in terms of increased groundwater availability, increased irrigated area, and increased cropping intensity are well documented in a meta-analysis of 636 case studies reported by Joshi et al. (2008).

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Similar results from number of watersheds in India, Thailand, Vietnam, and China are also reported (Wani et al. 2003a, 2008, 2009, 2017a, b). The mean annual rainfall in most rainfed regions is sufficient for raising one or, in some cases, two good crops in a year. However, the onset of rainfall and its distribution are erratic and prolonged droughts are frequent. A large part of rain occurs as high-intensity storms, resulting in sizeable runoff volumes. In most rainfed regions, harvesting of excess runoff and storage into appropriate structure as well as recharging of groundwater are very much feasible and a successful option for increasing and sustaining the productivity of rainfed agriculture through timely and efficient use of supplemental irrigation. In the areas with annual rainfall >500 mm, this approach could be widely adopted to enhance the cropping intensity, diversify the system into high-value crops, increase the productivity and incomes from rainfed agriculture, and at the same time create assets in the villages (Pathak et al. 2009, 2011; Sharma et al. 2010). Different types of runoff harvesting and groundwater-recharging structures are currently used in various regions. Some of the most commonly used runoff harvesting and groundwater-recharging structures are earthen check dam, masonry check dam, farm ponds, tank, sunken pits, recharge pits, loose boulder, gully checks, drop structure, and percolation pond. Designing these structures requires estimates of runoff volume, peak runoff rate, and other hydrological parameters, which are generally not available in most of the rainfed regions. Due to nonavailability of the data, many times, these structures are not properly designed and constructed resulting in higher costs and often failure of the structures. A significant effort is to be given towards hydrological monitoring of field and microscale watersheds to understand rainfall-runoff relationships of various soil, rainfall, and other ecological regions. The information generated will be helpful in developing strategies for rainwater harvesting, designing structure capacity, and supplemental irrigation particularly in cases where more than one drought occurs during the cropping season.

6.4.2

Conservation Agriculture

Intercropping or mixed cropping systems are more resilient compared to mono cropping system in rainfed areas due to efficient and better utilization of resources such as green water and soil nutrients. These systems are also stable under adverse weather and pest/disease situations. Land smoothening and forming field drains are basic components of land and water management for conservation and safe removal of excess water in a guided manner. Broad bed and furrow (BBF) system is an improved in situ soil and moisture conservation and drainage technology for clayey soils with low infiltration rate as soil profile gets saturated and waterlogged with the progression of rainy season (El-Swaify et al. 1985). Data from long-term research trials at ICRISAT show that management of Vertisols with improved management options/interventions improved soil physical, chemical, and biological properties of micro-watersheds. Field-scale intervention of improved management comprises sowing of crops on graded broad bed and furrow

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(BBF) of 45 cm practice for in situ soil and water conservation and safe disposal of excess runoff during heavy downpour. The rainy season crops (sole and intercrops) along with pigeon pea/maize/sorghum/soybean/green gram were sown in the dry bed prior to the onset of monsoon rains, and two crops were grown annually in a rotation. The fertilizer management involved the application of 80 kg N and 40 kg P2O5 per ha. Under the traditional practice, the seedbed was kept flat, and one crop, either sorghum or chickpea, was grown during the post-rainy season utilizing the stored soil moisture in the profile. No mineral fertilizers were added, and farmyard manure was added at 10 t ha 1 every 2 years. Results show that improved management significantly increased soil porosity, infiltration rate, and carbon content compared to traditionally managed fields Khan et al. 2005; Olaposi et al. 2013. Such changes in biophysical properties also led to change in hydrological cycle as runoff was reduced in BBF fields and stored more rainfall into green water form. Significant amount of total rainfall is used in productive transpiration; therefore crop yield in BBF fields was found consistently higher than 4.5 t ha 1, irrespective to several deficit and surplus water years (Wani et al. 2003a, 2011a; Pathak et al. 2005). On the other hand, average crop yield in traditionally managed field was found as 0.9 t ha 1. Average crop water productivity of BBF fields was found to be 0.65 kg m 3 compared to 0.15 kg m 3 in traditionally managed field. “On-farm trials on land management of Vertisols of central India revealed that BBF system resulted in a 35% yield increase in soybean during rainy season and yield advantage of 21% in chickpea during post-rainy season when compared with the farmers’ practice. Similar yield advantage was recorded in maize and wheat rotation under BBF system. Yield advantage of 15% to 20% was recorded in maize, soybean, and groundnut with conservation furrows on Alfisols over farmers’ practices at Haveri, Dharwad, and Tumkur watersheds in Karnataka. Yield advantage in rainfall-use efficiency (RUE) were also reflected in cropping systems involving soybean-chickpea, maize-chickpea, soybean/maize-chickpea under improved land management systems. The rainfall use efficiency (RUE) ranged from 10.9 to 11.6 kg ha 1 mm 1 under BBF systems across various cropping systems compared with 8.2 to 8.9 kg ha 1 mm 1 with flat-on-grade system of cultivation on Vertisols” (Singh et al. 2009).

6.4.2.1 Rainy Season Fallow Management Vertisols and associated soils which occupy large areas globally (approximately 257 Mha, Dudal 1965) are traditionally cultivated during post-rainy season on stored soil moisture due to waterlogging-associated risks during the rainy season due to poor infiltration rates. The practice of fallowing Vertisols and associated soils in Madhya Pradesh, India, was perceived to be decreased after the introduction of soybean; however, 2.02 Mha of cultivable land is still kept fallow in Central India, during kharif season (Wani et al. 2002; Dwivedi et al. 2003). However, the survey indicated that soybean replaced sorghum; rainy season fallows remained as fallows as rainy season crop delays the sowing of post-rainy (rabi) crop forcing farmers to keep the cultivable lands fallow which reduces water-use efficiency (WUE) as well as enhances soil erosion.

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ICRISAT demonstrated on-farm participatory research trials on landform management in Vertisols. “On-farm soybean trials involving improved land configuration (BBF) and short-duration soybean varieties along with fertilizer application (including micronutrients) showed a yield increase of 1,300 to 2,070 kg ha 1 compared with 790 to 1,150 kg ha 1 in Guna, Vidisha and Indore districts of Madhya Pradesh. Increased crop yields (40%–200%) and incomes (up to 100%) were realized with landform treatment, new varieties, and other best-bet management options” (Wani et al. 2008; Singh et al. 2009).

6.4.2.2 Rice Fallow Management for Crop Intensification Considerable amount of green water is available after the monsoon especially in rice fallow systems which could easily be utilized by introducing a short-duration legume crop with simple seed priming and micronutrient amendments (Subbarao et al. 2001; Kumar Rao et al. 2008, Wani et al. 2009, Singh et al. 2010; Gumma et al. 2016). About 14.29 Mha (30% of rice-growing area) rice fallows are available in IndoGangetic Plains (IGP) spread in Bangladesh, Nepal, Pakistan, and India, out of which 11.4 Mha (82%) are in the states of Bihar, Madhya Pradesh, Chhattisgarh, Jharkhand, West Bengal, Odisha, and Assam in India (Subbarao et al. 2001). Taking advantage of sufficient available soil moisture in the soil after harvesting rice crop, during the cool season in eastern India, growing of early-maturing chickpea in rice fallow areas with best-bet management practices (zero tillage for chickpea, seed priming of chickpea, 4–6 h with the addition of sodium molybdate to the priming water at 0.5 g L 1 kg 1 seed and Rhizobium inoculation at 5 g L 1 kg 1 seed, micronutrient amendments, and use of short-duration rice cultivars during rainy season) showed chickpea yields of 800–850 kg ha 1 (Kumar Rao et al. 2008; Harris et al. 1999). An economic analysis has shown that growing legumes in rice fallows is profitable for the farmers with a benefit:cost (B:C) ratio exceeding 3.0 for many legumes. Also, utilizing rice fallows for growing legumes could result in the generation of 584 million person-days employment for South Asia. In a number of villages in the states of Chhattisgarh, Jharkhand, and Madhya Pradesh in India, on-farm farmers’ participatory action research trials sponsored by the Ministry of Water Resources, Government of India, showed significantly enhanced resource-use efficiency (RUE) through cultivation of rice fallows with a total production of 5600–8500 kg ha 1 for two crops (rice + chickpea) benefiting the farmers with increased average net income of INR 51,000–84,000 (USD 1130–1870 ha 1) (Singh et al. 2010). 6.4.2.3 Direct Seeded Rice (DSR) The productivity and sustainability of rice-based systems are threatened because of (1) the inefficient use of inputs (fertilizer, water, labor); (2) increasing scarcity of resources, especially water and labor; (3) changing climate; (4) emerging energy crisis and rising fuel prices; (5) rising cost of cultivation; and (6) emerging socioeconomic changes such as urbanization, migration of labor, preference of nonagricultural work, and concerns about farm-related pollution (Ladha et al. 2009). Further, a grim water scenario in agriculture together with the highly inefficient

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Table 6.1 Mean yield, net return, and benefit:cost ratio of direct seeded rice under Bhoosamrudhi program in Karnataka, India

District Dharwad Udupi Davanagere Raichur

Mean yield (t h 1) DSR TPR 2.8 2.6 5.9 5.3 4.8 4.0 5.8 5.4

% Change over TPR 7.7 11.3 14.3 7.4

Net return from DSR (INR ha 1) 37,600 87,200 85,375 69,500

B:C ratio 1.1 2.7 2.4 1.6

rice production technologies currently adopted by a majority of farmers globally warrants the exploration of alternative rice production methods, which inherently require less water and are more efficient in water use. DSR provides some opportunities for saving water. Both dry and wet DSR are more water efficient and have an advantage over transplanting under conventional tillage (CT-TPR) (Bhuiyan et al. 1995; Dawe 2005; Humphreys et al. 2005; Tabbal et al. 2002). However, with increasing shortage of water, dry DSR with zero tillage in which potential savings of both labor and water can be much higher appears to have the greatest potential, especially in rainfed ecologies of India. The DSR was popularized under Bhoosamrudhi program in Karnataka by the consortium of CGIAR institutes, state agricultural universities, and line departments. Paddy seeds were sown using zero-till multi-planter. Zero-till multi-planter facilitated to sow seeds without any seed bed preparation, without puddling which reduced significant amount of energy, cost, and labor. Zero-till machine makes a 4–5 cm sharp cut on surface soil, places seed and fertilizer appropriately, and covers it with soil. As surface soil layer is not disturbed, available moisture in topsoil is also protected from nonproductive evaporation losses. Recommended dose of preemergent weedicide was applied to control the weeds. Fields were irrigated once in a week or in 10-day interval as per need. Recommended dose of fertilizers was applied as per defined protocol. Crop cutting studies showed that the crop yield obtained from DSR was found to be ranging between 2.8 and 5.8 t ha 1 compared to 2.6 and 5.4 t ha 1 in transplanting system (TPR) (Table 6.1). Direct seeding avoids nursery raising, seedling uprooting, and transplanting, and thus reduces the labor requirement. DSR also avoids puddling operations, and thus further saves labor use. Since land preparation is mostly mechanized, there is more savings in machine labor than in human labor in this operation. Short- to medium-term on-station studies reported 34–46% savings in machine labor requirement in DSR compared with transplanting system (TPR) (Bhushan et al. 2007; Sahrawat et al. 2010). In addition to labor savings, the demand for labor is spread out over a longer period in DSR than in transplanted rice. Conventional practice requires much labor in the critical operation of transplanting, which often results in a shortage of labor. The spread-out labor requirement helps in making full use of family labor and has less dependence on

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Fig. 6.7 (a): Comparing cost of field operations between DSR method and transplanted paddy; (b) comparing economics of the DSR method with transplanted paddy under Bhoosamrudhi program in Tumakuru, Karnataka

hired labor. As a result, the net return under DSR was significantly higher with benefit:cost ratio more than 1 indicating the profitability of the technology. A comparison of DSR and transplanted methods of rice cultivation revealed that yield in DSR method of cultivation is higher than transplanted method. The data obtained from field demonstrations in Karnataka clearly showed that nearly 7.5 t ha 1 is possible with DSR method under rainfed conditions (Fig. 6.7a, b). In addition, DSR generally requires one or two passes of the machine and can also be practiced under zero tillage, offering considerable time, cost, and energy savings for

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farmers. The DSR paddy was economically beneficial compared to transplanted paddy as the net income obtained from DSR paddy was almost three times higher than the transplanted paddy although yield was almost equal in both the systems (Fig. 6.7a, b). Similarly, irrigation cost for transplanted paddy was double that for DSR paddy, which indicates that water scarcity issues can be effectively addressed by adopting DSR system.

6.4.2.4 Zero Tillage Due to fragmented and small land holdings and variable farmer typology, it is not affordable to purchase many machines for the planting of different crops by the same farmer. The multi-crop planter can plant different crops with variable seed size, seed rate, depth, spacing, etc., providing simple solution to this. In addition to adjustments for row spacing, depth, gears for power transition to seed, and fertilizer-metering systems, the multi-crop planters have precise seed-metering system using inclined rotary plates with variable grove number and size for different seed size and spacing for various crops. This provides flexibility for use of these planters for direct drilling of different crops with precise rate and spacing using the same planter which does not exist in fluted roller metering drills. Hence, the same multi-crop planter can be used for planting different crops by simply changing the inclined plates. The planter can also be used to make the beds and simultaneously sow the crop just by mounting the shovels and shapers which can be easily accomplished due to the given provision in the machine. Moreover, farmers generally keep their land fallow in Rabi despite huge soil moisture after paddy harvesting. This machine provides opportunity to sow seeds without ploughing operation. 6.4.2.5 Broad Bed and Furrow (BBF) System The BBF system consists of a relatively flat bed or ridge approximately 105 cm wide and shallow furrow about 45 cm wide and 15 cm deep. The BBF system is laid out on a grade of 0.4–0.8% for optimum performance. The BBF system of land management can be adopted in semiarid tropics with deep black soils and for groundnut crop in red soils with a reduced gradient along the BBF (0.2–0.3%) with an average rainfall of 600–800 mm. The BBF system is most effectively implemented in several operations or passes. After the direction of cultivation has been set out, furrow making is done by an implement attached with two ridgers with a chain tied to ridgers or a multipurpose tool carrier called “Tropicultor” to which two ridgers are attached or any other suitable implement. If opportunity arises (after showers) before the actual beginning of the rainy season, another cultivation is done to control weeds and improve the shape of the BBF. Thus, at the beginning of the growing season this seed is receptive to rainfall and, importantly, moisture from early rains is stored in the surface layers without losing in deep cracks in black soils. The broad bed and furrow system is an effective method of soil and water conservation in different rainfall regions. In addition to soil and water conservation, the yield advantage of BBF is significant as the results showed that the yield increment was ranging between 10% and 17% over farmers’ practice covering different crops (Table 6.2).

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Table 6.2 Yield of major crops under broad bed and furrow (BBF) system under Bhoosamrudhi in Vijayapura, Karnataka, during 2016–2017 Crop Green gram Green gram Pearl millet Pigeon pea

Cultivar DGGV-2 IPM-02-14 Dhanashakthi ICPL–88039 ICPL–161 ICPL–85063

BBF (kg/ha) 250 210 1020 300 520 1500

Non-BBF (kg/ha) 220 180 921 266 460 1300

% Change over, non-BBF 13.6 16.7 10.7 12.8 13.0 15.4

Fig. 6.8 Farmers’ participatory climate-resilient crop variety evaluation in Vijayapura, Karnataka

6.4.3

Climate-Smart Crops and Cultivars

With climatic aberrations, the availability of length of growing period is changing. This change requires suitable crop cultivars as per soil moisture-supplying capability of an agroecological system. To cater to the needs of changing climatic situations, a number of universities and research institutes are engaged in developing climatesmart crop cultivars. Huge efforts and time are being invested for developing new cultivars by national and private institutes. The adoption of improved varieties always generates significant field-level impact on crop yield and stability (Wani et al. 2016). The yield advantage through the adoption of improved varieties has been recognized undoubtedly in farmers’ participatory trials across India under rainfed systems. For example, farmer participatory demonstrations undertaken in one of the Bhoosamrudhi pilot sites in recent years showed the advantage in crop yield ranging from 12 to 55% in crops like pigeon pea, pearl millet, and chickpea with the use of high-yielding varieties (Fig. 6.8). Despite having developed, timely availability of the improved variety/cultivar is the major bottleneck as they have not

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reached mainstream seed supply chain. Therefore, seed replacement rate is less than the required rate.

6.5

Institutional Mechanism

6.5.1

Crop Insurance

Crop insurance is a mechanism to protect farmers against the uncertainties of crop production, due to natural factors, beyond farmer’s control. It is also a financial mechanism, which minimizes the uncertainty of loss in crop production, by factoring in a large number of uncertainties, which impact crop yields distributing the loss burden. In a country like India, where crop production is subjected to the vagaries of weather and large-scale damage due to the attack of pests and diseases, crop insurance assumes a very vital role. In order to protect farmers against crop failure due to natural calamities, pests and diseases, and weather conditions, Government of India had introduced the National Crop Insurance Programme (NCIP) with component schemes of Modified National Agricultural Scheme (MNAIS), Weather Based Crop Insurance Scheme (WBCIS), and Coconut Palm Insurance Scheme (CPIS). They have been modified as and when required to address operational issues. The present credit-linked Insurance Scheme (NAIS) has proven its worth as crucial risk intervention mechanism but it suffers from several limitations such as low indemnity levels, high prices, no coverage for all horticulture crops, poor servicing and awareness level, and inadequate loss coverage (Fig. 6.9). Further, the levels of indemnity are 60%, 80%, and 90% corresponding to high-, medium-, and low-risk areas. Currently, the National Agricultural Insurance Scheme is implemented on the basis of “homogeneous area”

Fig. 6.9 Farmers insured and benefited from WBCIS in Kharif and Rabi seasons in India (source: Raju et al. 2016)

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approach, and the insurance unit at present is the Mandal/Taluk/Block or equivalent unit, in most instances. These are large administrative units with considerable variations in yields and impact of natural calamities. Therefore, these schemes have recently been reviewed in consultation with various stakeholders and as a result a new scheme “Pradhan Mantri Fasal Bima Yojana” has been approved for implementation from Kharif 2016 along with restructured pilot Unified Package Insurance Scheme and weather-based Crop Insurance Scheme. Given the poor penetration and benefits of existing crop insurance schemes in India, the following strategies are proposed to minimize the risks and enhance the efficiency in crop insurance sector: • Among the 70 million non-loanee farmers, only about 3% have access to crop insurance due to lack of affordability, lack of awareness, and unsureness about the benefits of insurances, and have remained extremely poor (Parchure 2013). Thus, incentives should be provided to non-loanee farmers to avail crop insurance. • The administrative cost of implementation is also very high in case of traditional crop insurance scheme. So, an alternative insurance mechanism with quick settlement, low cost, and transparency is essential. • India has more than 60% of the rainfed agriculture; yield and price uncertainties often reduce the incomes of the rainfed farm households. Thus, the insurance products need to be developed encompassing the factors such as deficit rainfall, excess rainfall, frosting, and high temperature. • To minimize the risk of high claim ratios arising out of adverse selection, multiple season/year insurance contracts should be promoted wherein farmers are encouraged to buy insurance for a couple of seasons/years, in advance. This will also help in discounting the premiums to some extent (Parchure 2013). • Owing to the structural complexities of index-based weather insurance that ensures long-term sustainability of these models, special emphasis on education and awareness to find widespread favor with the farmers about index-based insurance products is critical. In this context, farmer producer organizations (FPOs)/producer companies (PCs), Ministry of Agriculture, state agriculture departments, and agri-insurance providers would pool in resources to create a special-purpose vehicle (SPV) to (i) provide training and certification to business correspondents/extension workers/NGOs; (ii) provide training and certification to farmers that would make them eligible to secure additional benefits; and (iii) be a central repository of extension services being offered by the government, private sector, and institutions across the country. • The unit for determining the claim should be a village or cluster of villages as increasing evidences of climate change events have shown considerable variations in yields and impact of natural calamities with large administrative units. To support this, large-scale automatic weather stations have to be established at the cluster village level. • Bank assurance can also be promoted to mitigate the risks for both voluntary loanees and nonvoluntary loanees.

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• An integrated app needs to be developed which can act as proxy extension agent in disseminating the information relating to production, weather, markets, etc. • Several agencies and organizations are involved in crop insurance programs and coordinated efforts are critical for effective implementation of crop insurance schemes. There is a need for a comparative statistical analysis of different insurance products. Enhanced consumer protection legislation for indexed insurance products is required. Research on better understanding of methods to combine the information from different indices is to be promoted so that farmers can rely on timely claim payments in bad years. • High science tools/technologies like remote sensing and drones can be promoted to monitor crop growth and losses. This provides better understanding of the extent of risks and immediate processing of claims.

6.5.2

Remunerative Prices

The price effects in the market for farm output determine the income effect of increased output for farm households. These price effects also send feedback to the producer that determines future desired output levels. However, farm harvest prices in India show high inter- and intra-year volatility. In the absence of perfect market information, farmers tend to produce agricultural goods which are having lower market demand by incurring high cost of cultivation. Although the minimum support price (MSP) is being announced as a measure of boosting incomes of small farm holders, controlling price, and minimizing the exploitation of middlemen, majority of farmers are not aware of the existing prices and selling mechanism (Government of India 2016a, b). Further, it is important that market information and intelligence are crucial to enable farmers to make informed decisions about what to grow, when to harvest, to which markets produce should be sent, and whether to store it or not. The most important marketing intelligence need of the farmer is price intelligence. In India, owing to poor educational status as well as infrastructure facilities, most of the farmers still lack a good understanding and capacity to use market intelligence in guiding their production and marketing decisions. Hence, dissemination of market information such as demand, production, and prices plays an important role in the functioning of the market, by harmonizing the competitive marketing process. Helping ensure that produce goes to markets where there is a demand for it shortens marketing channels and cuts down on transport costs. It helps to ensure that each marketing transaction is a fair one, and that all participants share the risks and benefits.

6.5.3

Agriculture Markets

An occasional paper by NITI Aayog (Government of India 2015) has reviewed the existing marketing system in the country and observed that given the vastness and

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diversity of Indian agriculture, the country requires multiplicity of instruments including the model APMC Act, scaling up of successful experiences like cooperative milk marketing, and organized retail to impart efficiency, competitiveness, and modernization of agricultural marketing. Agricultural marketing suffers from fragmentation resulting from a large number of intermediaries and poor infrastructure, lack of vertical integration, and policy distortions. A consequence of this fragmentation is that the farmer often receives a small fraction of the final price paid by the consumer. Therefore, urgent reforms are needed in agricultural marketing so as to enable farmers to receive a larger proportion of the final price paid by the consumers. Following are key strategies: • Encouraging contract farming under which the buyer can provide the farmer access to modern technology, quality inputs, other support, and a guaranteed price. • Promoting producers’ association, producers’ companies, and cooperative marketing societies to improve the bargaining power of producers. • Trading platforms like NCDEX and eNAM need to be publicized to add more members from farming community to ensure remunerative prices to farmers from the open market and to reduce the demand for price support mechanism. • It is disheartening to note that the agricultural produce marketing systems in the country suffer from major distortions and multiplicities of levies and mandi taxes (Patnaik 2011; Subramanian 2014). These are neither transparent nor uniform across the states and are a major barrier to farmers realizing remunerative prices. There remain serious restrictions on the movement of agricultural commodities even within states. In this context, a model has been developed by Karnataka which has integrated a number of markets into a single licensing system with a joint venture of state government agency and NCDEX spot exchange, which offers automated auction and post-auction facilities (https://www.ncdex.com/). • Further to enhance the market efficiency and to ensure farmers’ welfare, the availability of adequate infrastructure plays a crucial role. Currently, road networks in the country lacking all-weather approach roads as well as adequate transport facilities result in inability of the farmer to take their produce to the appropriate market and they are unable to receive a fair price for the product. • Further, due to lack of storage facility, the farmer is unable to keep their product safely until it can fetch a fair price, and they are forced to sell the product at a low price. Therefore, adequate road, transport, and storage infrastructure need to be given priority with public-private partnership. • Further, no/poor value addition which is the result of lack of standardization and grading affects fixing of scientific price for the product. Due to lack of proper standardization and grading, the customers have problem in purchasing the product. Further, appropriate mechanization needs to be promoted for grading, processing, and packing through women SHGs or unemployed youths by following the model of collective action.

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• The farmers do not have sufficient information and knowledge about the market. Thus, proper tools should be developed and promoted such as mobile advisories, community radios, and television advisories for information dissemination. • The current demand pattern of agricultural commodities has been shifting towards high-quality and processed products. These changes favor integrated supply chain, assured market, and specific produce. Such supply chains also offer considerable scope for cutting the margins of middlemen and are beneficial to smallholders. A well-functioning supply chain can reduce the cost of marketing by linking farmers more closely to processing firm and consumers.

6.5.4

Contract/Commercial Farming

Contract farming is an important price risk mitigation tool and has many more direct benign impacts on farm incomes. Market risks are large in specialty crops and vegetables that deter most farmers from investing in them. Through price insurance, credit, and technological inputs, contract farming could be an important mechanism by which small farmers can supply high-value crops to urban and international markets while benefiting from assured higher incomes. Contract farming can reduce the load on the central- and state-level procurement system and increase the private sector investment in agriculture. The contract farming provides opportunity to select crops with a market focus to benefit and act as a steady income source at the individual farmer level. To some extent, contract farming also helps to generate gainful employment in rural communities particularly for landless labor and reduce rural-urban migration. Ministry of Agriculture and Farmer Welfare, Government of India, has drafted Agriculture Produce and Livestock Contract Farming (Promotion and Facilitation) Act, 2018. The act will regulate contract farming activities while protecting and promoting the interest of the farmers. Farmers will also get benefit through coverage of market risk and better resource-use efficiency. Moreover, there will be provision to get bonus if the contracting firm gets more benefit out of contracted produce.

6.5.5

Agriculture Extension System

India has the world’s largest extension system, capable of addressing the needs of all sections of the farmers. However, the role of the extension institutions in acting as a conduit between the scientists and users is not very effective. Rather, the inability of Indian agriculture to respond and adjust to the changing environment in the postliberalization period can be attributed to a large extent to inadequate support of the extension system. The efficacies of the existing extension mechanism remain much to be desired in terms of lower outreach and poor coverage, as large segments of the farmers continue to remain deprived of the new ideas and access to market and price intelligence support (NSSO 2013). The public extension service is constrained by many factors including inadequacy of finances and human resources and poor roads

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to rural areas. As a result, many farmers have not benefited much from public extension services in terms of information relating to new technologies. It is critical to revitalize advisory services, complementing the investments being made in agricultural research. Our experience highlighted the importance of research and extension systems, which should be more demand driven, multi-stakeholder, and multi-sector. To reshape agricultural education by abolishing long-established traditions of academic isolation, increasing collaboration between scientists and line departments, and emphasizing research and extension through innovative teaching is necessary. Further, as trained human resource is a major constraint in agriculture extension system, various information communication tools (ICT) are available which can bridge the gap between farmer and knowledge generator. There is a need to develop appropriate training modules for the agricultural extension staff on the science of climate change and the various adaptation and mitigation strategies available in the universities, research institutes, and government departments. The other dimension of extension system is knowledge delivery pathways (KDP). The traditional ways to delivery information are through announcements, infographics (wall writing or banners), and scheduled programs on television and radio, which still are effective options for mass communication. Information communication tools have provided a wide range of options to assist extension agents as well as farmers for getting up-to-date knowledge. Government of India and private companies are transforming the AES. There are several technologies that are being used for information dissemination. For example, Government of India has Kisan Call Center (KCC) facility to satisfy information request as per farmers’ demand in 22 local languages. Karnataka State Natural Disaster Management Center is a provider of service to its subscribers in the state to receive daily weather update including alert about abnormalities in weather. In addition to government, private companies are also providing innovative solutions for agriculture extension. For example, IFFCO Kisan Sanchar Limited has introduced voice messages for agro-advisory system and Thomson Reuters introduced mobile-based integrated agro-advisory system “Reuters Market Light.” Information updates obtained from such advisory system allow farmers to take decision regarding various farm operations, which eventually helps farmers to cope to climate change or changes in weather.

6.6

Conclusion

The preceding discussion revealed that despite climate change impacts, a large untapped potential exists for crop intensification by adopting various NRM interventions, suitable crop cultivars, and mechanization along with institutional backstopping. The current water management regime emphasizes largely on optimizing blue water but overlooks the utilization of green water management. To unlock the potential of dryland agriculture, in situ interventions need to be promoted in large scale. A mass-scale awareness building is required among various stakeholders including researchers, development agencies, and policy makers along

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with farming community. To address increased climate change risks, a large-scale farmer participatory cultivar demonstrations are critical which are helpful in (i) increasing awareness among stakeholders about the potential of climate-smart cultivars and (ii) suitable cultivar selection as per the length of growing period/local resource availability. In addition, there are new innovative methods of land and water management such as direct seeded rice and laser land leveler for enhancing land- and water-use efficiency. These interventions not only enhance crop yield but also significantly reduce cost of cultivation resulting in higher net income. Moreover, building awareness towards innovative government programs (e.g., PMFBY) can further cover the risks of crop failure to some extent. To strengthen the current extension system, government agencies, development organizations, research organizations, and private institutes should work in tandem towards achieving system-level outcomes.

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Climate-Smart Small Millets (CSSM): A Way to Ensure Sustainable Nutritional Security H. M. Vinaya Kumar, Naveenkumar Gattupalli, S. C. Babu, and Anuj Bhatia

Abstract

Sustainable management of water resources is critical to address the challenges of climate change, environmental degradation, poverty and malnutrition. India’s green revolution enabled food security but at the cost of environmental degradation and unsustainable development. Water, a scarce resource, was used extensively during the green revolution to cultivate rice-wheat cropping system. However, paddy processing in India involves removing the husk, as well as polishing process in which the proteins, dietary fibre and other vital minerals are lost, rendering consumption of starch or carbohydrates leading to malnutrition due to low protein, crude fibre, minerals, calcium, phosphorous and iron. In this context, the climate-smart small millets (CSSMs) such as kodo millet, proso millet, foxtail millet, little millet, pearl millet, barnyard millet and finger millet which have originated from India play a crucial role in addressing the scarcity of water as well as issues of malnutrition, obesity and diabetes as there is a growing demand for millets in urban areas including export demand. This will benefit the resource-poor and rainfed farmers who can reap the multiple benefits of cultivating millets due to a reduction of crop duration by almost 30 days and water requirement by nearly 75%, meeting nutritional and fodder security and the challenges of climate change as they can withstand drought and extremities. Due to its balanced amino acid profile, fibre and minerals coupled with high protein content, CSSMs are superior to wheat and rice in nutrition; besides providing H. M. V. Kumar (*) · N. Gattupalli Department of Agricultural Extension and Communication, Anand Agricultural University, Anand, Gujarat, India S. C. Babu Capacity Strengthening Programme, IFPRI, Washington, DC, USA A. Bhatia Institute of Rural Management, Anand, Gujarat, India # Springer Nature Singapore Pte Ltd. 2020 V. Venkatramanan et al. (eds.), Global Climate Change: Resilient and Smart Agriculture, https://doi.org/10.1007/978-981-32-9856-9_7

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nutritional security, especially to women and children, it ensures forage safety for livestock. By upscaling the cultivation and enhancing consumption of CSSMs, anaemia (iron deficiency), B-complex vitamin deficiency and pellagra (niacin deficiency) can be contained. CSSMs can also help to combat health challenges such as noncommunicable diseases as they are gluten free with low glycaemic index and rich in antioxidants. CSSMs can address in unison some of the vital global issues such as poor diet, health and environmental degradation, and rural and urban poverty. Keywords

Climate change · Nutritional security · Small millets · Sustainability · Potable alcohol · Bioethanol · Malt

7.1

Introduction

Millets are important “nutritional reservoirs”, essential for human health and wellbeing. Millets such as pearl millet and sorghum are important food and fodder crops in the semi-arid tropical regions on account of its tolerance and adaptability to climatic conditions (Cobley 1976; Purseglove 1985). Further, its importance has increased in the era of climate change. Although they are the oldest foods in the world, they were discarded in favour of consumption of wheat and rice mainly due to rapid urbanisation and change in consumer taste and preferences. The high protein content of millets contributes to a lack of energy in the vegetarian diet. Due to its high grain yield potential with a short growing period, prolonged shelf life coupled with nutritional security makes them commercially sound superfoods for the present and future generations, particularly in the rainfed areas. The challenge is to develop tasty, novel and ready-to-eat foods in millets to match the consumer preferences (Dewet 1986; Doggett 1986).

7.2

An Overview of Small Millets

Crops that are grown on short and slender grassy plants for their small grains are called as small millets. The millets include finger millet (Eleusine coracana), proso millet (Panicum miliaceum), foxtail millet (Setaria italica), little millet (Panicum sumatrense), barnyard (Sawa) millet (Echinochloa colona), kodo millet (Paspalum scrobiculatum), etc (De Wet et al. 1983, 1984). Small millets are popularly referred to as minor millets and their role is significant. Millets such as Japanese millet, barnyard, proso and foxtail millets have long been cultivated, especially in Asia, and continue to play an important role today. Finger millet is an old, still widely cultivated tropical cereal in East Africa and South Asia (Cobley 1976; Purseglove 1985). The millets have always been grown in situations where there is a risk of hunger and assures a low yield but more promising harvest than other crops grown in low-rainfall regions. Kodo millet is traditionally stored in temples so that seed in

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times of crisis is available. Hence an in-depth study is needed to know about the potential of these millets. Storing of millets as food and seed is important to ensure feed for livestock in dry areas. These small millets can be developed as good grain and forage as they can be produced with low water consumption from any source of irrigation water.

7.3

Area, Production, and Productivity of Millets in India and World

Global millet production is estimated at around 27.83 million tons (FAO, 2014), where India is the world’s leading producer accounting for 41.04% of total production, followed by Niger accounting for 11.94% of the world production. The importance of millets as staple food has declined in the recent past due to urbanisation, rising income levels and increasing preference for rice and wheat. Nevertheless, the demand for millets was observed in the domain of feed and fodder, and starch and alcohol production. According to FAO statistics (2009), millet production increased significantly by 13.00% over 7 years (2002–2009) from 23.3 to 26.7 million metric tons, covering an area of 33.3 and 33.6 million hectares, respectively. In the year 2009, Africa was the world’s highest millet producer (20.6 million metric tons), followed by Asia (12.4 million metric tons) and India (10.5 million metric tons). Sorghum is the fifth largest cereal produced and planted after rice, wheat, maize and barley, accounting for 5% of the world’s total cereal production (Dayakarrao et al. 2015). Global pearl millet production decreased by 13.00%, from 32.8 million tons in 2010 to 28.4 million tons in 2014. Asia and Africa contribute more than 98.00% of the world’s total pearl millet production. Africa’s contribution of 49.22% of global millet production in 2010 declined to 43.72% in 2014, while Asian countries increased their production from 48.72 to 52.25% in the same period. According to FAO (2017) statistics, sorghum is the fifth largest cereal crop in the world after paddy, maize, wheat and barley, and its production has increased significantly by 14% from 60 million tons in 2010 to 68.9 million tons in 2014. Africa was the largest sorghum producer in 2014, with 42% of global production, followed by America (39.75%) and Asia (14.04%). India was the leading millet producer in the world. Out of the total sown area of 141.0 mha in India, the rainfed region accounts for 85.0 mha which constitutes about 60% of the total farming area distributed over 177 districts. Rainfed agriculture accounts for 44% of the country’s total food grain production, producing 75% pulses and over 90% sorghum and millet. Despite the fact that rainfed regions were neglected for almost a half century, they provide livelihoods for nearly 50% of the total rural labour force and support 60% of the country’s livestock (Satish 2010). Sorghum production in India has declined by 40% from 7 million tons (2010–2011) to 4.2 million tons (2015–2016) over a period of 5 years. The production of bajra also reduced by 20% from 10.4 to 8.1 million tons, and ragi production has decreased by 18% from 2.2 to 1.8 million tons during the same period.

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“Millets are cultivated in India on an area of 15.48 million hectares producing 17.2 million tons with a productivity of 1111 kg/ha” (Economics and Statistics Directorate, 2015). Maharashtra, Rajasthan and Karnataka are the leading cultivation states in India for millets. The contribution of millets to India’s total food grain production has decreased from 22.17 to 6.94% in the last six decades from 1950–1951 to 2011–2012. The area under millet production has declined sharply in the last five decades although they possess extraordinary qualities, since the crops like rice and wheat were promoted in the selected resource-rich areas under irrigated conditions. An unnatural promotion of maize due to their demand for biofuel and poultry feed leads to the invasion of maize in different parts of the country which leads to a major threat to millet cultivation (Malathi et al. 2016). The amount of rainfall and growing habits determine the spatial distribution of millets. While sorghum is normally grown in the areas receiving annual rainfall above 400 mm, pearl millet is preferred in areas receiving an annual rainfall of 350 mm. In the southern and central part of India where the annual rainfall is below 350 mm, small millets namely finger millet, foxtail millet, barnyard millet, little millet and proso millet are normally cultivated (Dayakarrao et al. 2015). Millets are grown as sole crop or mixed or intercropping in combination with legumes, oil seeds, spices and condiments. In the desert regions of Rajasthan, pearl millet and sorghum are cultivated as sole crop. As regards Tamil Nadu and Gujarat, the ragi or finger millet is mainly grown as a sole crop (Behera 2017). In effect, small millets include “finger millet, foxtail millet, kodo millet, little millet, barnyard millet and proso millet”. Small millets are known for long period of existence; they are cultivated in dry lands and hilly areas; they provide food, feed and fodder. The acreage, production and productivity of small millets in India (2015–2016) are presented in Table 7.1.

7.4

Consumption Pattern of Millets in India and World

The role of sorghum and millets as aggregate food staples has declined since 1980. The per capita consumption of sorghum and millets has reduced drastically from 5.7 to 1.9 kg per year in case of sorghum, while in case of millets it was declined to 2.9 kg per year from 5.2 kg. The per capita availability of all cereals in Asia decreased marginally from 164 to 156.4 kg per capita per year during the same period. In all countries, including China, India, and Pakistan, the per capita availability of sorghum and millets declined. In India, the availability of sorghum per capita was reduced by more than half for millets and by less than a third for millets. Although the availability of sorghum and millets in the aggregate is low and they have a decreasing per capita, their importance as food crops cannot be underestimated (Dayakarrao 2015). It was observed that there was a decline in the demand for direct consumption of millets both in rural and urban regions over the years from 1973 to 2014 (Table 7.2). The sorghum consumption has declined more than 75% in case of rural and urban population, while in case of coarse cereals it was reported that there was a decline in

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Table 7.1 State-wise area, production and productivity of small millets in India (2015–2016) State Andhra Pradesh Arunachal Pradesh Assam Bihar Chhattisgarh Gujarat Himachal Pradesh Jammu and Kashmir Karnataka Madhya Pradesh Maharashtra Meghalaya Nagaland Odisha Rajasthan Sikkim Tamil Nadu Telangana Tripura Uttar Pradesh Uttarakhand West Bengal India

Area (in ‘000 hectare) 51.0 27.5 6.6 1.8 94.8 18.0 4.2 5.9

Production (in ‘000 tons) 49.0 27.6 4.4 1.3 15.0 20.0 3.0 2.3

Productivity (kg/ha) 961 1002 674 756 158 1111 728 395

28.0 180.0 76.0 2.9 8.7 25.4 13.9 3.6 31.3 1.0 0.1 8.0 59.0 2.3 649.9

10.0 73.3 31.0 2.8 9.8 12.7 6.7 3.5 36.4 1.0 0.1 5.0 74.3 1.7 390.9

357 407 408 950 1122 501 482 980 1164 1000 820 625 1259 233 602

Source: Ministry of Agriculture and Farmers Welfare, Govt. of India (ON1394); http://www. aicrpsm.res.in/Downloads/Reports/ICAR-AICRP%20reports-2017-18/1-Introduction.pdf

consumption by more than 70% in both rural and urban regions (Thakur and Sharma 2018). The main reasons for the decline in consumption of millets are due to rapid urbanisation, change in their livelihood patterns and industrialisation; the rise in income levels and change in food habits of consumers over these periods led to the drastic reduction in consumption of millets (Annual Progress Report 2017–18). If same trend of consumption continues to occur, after the next two decades the coarse cereals such as small millets and sorghum will completely replace by rice and wheat (Dayakarrao 2015).

7.5

Reasons to Undertake Cultivation of Millets

• Millets require less water for production. Hence, it places less demand on irrigation and power. It can be cultivated in the low-rainfall areas also. So these millet crops will be preferred during climate crisis (Table 7.3).

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Table 7.2 Trends in direct consumption of cereals and food grains Commodity 1973–1974 1983–1984 Rural consumption kg/person/year Rice 84.0 80.7 Wheat 42.8 54.3 Sorghum 19.0 12.5 Coarse cereals 56.8 45.1 Total cereals 183.6 180.1 Food grains Urban consumption kg/person/year Rice 65.5 64.7 Wheat 52.6 58.6 Sorghum 11.0 6.0 Coarse cereals 19.7 14.1 Total cereals 137.7 137.5 Food grains

1993–1994

2003–2004

2013–2014

85.4 53.5 9.7 24.1 163.0 172.8

82.7 51.7 5.7 16.5 151.6 162.2

83.80 51.13 3.9 13.2 148.59 159.9

64.2 57.4 4.9 7.7 129.3 140.4

59.4 56.8 3.3 6.0 122.4 135.1

60.11 53.42 2.5 5.4 119.37 134.3

Source: Various NSSO reports, GOI and Dayakar Rao et al. (2014) Table 7.3 Comparative rainfall requirement of various crops

Crop Sugarcane Banana Rice Sorghum Bajra Ragi

Rainfall requirement (mm) 2000–2200 2000–2200 1200–1300 400–500 350–400 350–400

Source: FAO, http://www.fao.org/docrep/W1808E/w1808e0c.htm

• Millets are rich source of nutrients. They are rich in mineral content, fibres, calcium (finger millets), iron (fox tail and little millet) and beta carotene. Hence these crops can provide nutritional security. • Millets can be cultivated in the low-fertile soils and problem soils. Millets possess resilience capacity and demonstrate the ability to survive in difficult conditions. • Millets do not require chemical fertilisers. Farmers’ can cultivate these crops using organic manures. • Pest and disease attack are minimum in the millet crops. The grains can be stored for longer period of time without pest attack. • Millets are mainly grown as an intercrop or mixed crop. • Millets provide food and nutritional security and livelihood security and improve soil fertility.

In effect, millets are climate change-compliant crops. Millets continue to be our agricultural response to the global climate crisis. We are expected to face three challenges in climate change, viz. temperature increase up to 2–5  C, water stress

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and severe malnutrition. Millets have already been acclimatised to drought conditions, with higher temperatures and low rainfall conditions ranging from 200 to 500 mm even in non-irrigated water-stress conditions.

7.6

Nutrient Content of Millets

The millets contain 7–12% protein, 2–5% fat, 65–75% carbohydrates and 15–20% dietary fibre in general. It has significant amounts of amino acids and fat content. Further, calcium, dietary fibre, polyphenols and protein present in the millets make millets nutritionally important. On account of lysine in fox tail millet, it is used as a protein supplement for most of the cereals. Finger millets are unique for their sulphur-rich amino acids and protein and lipid composition. It was reported that the dry matter amount and amino acid concentration in proso millet are higher than the rice and wheat crop. Further, millets are rich in carbohydrate and dietary fibres which helps in the lowering of blood cholesterol, and slow release of sugar in blood. Millets are also rich in phytochemicals, polyphenols, phytases, tannins and roughages (Tables 7.4, 7.5, 7.6, 7.7, 7.8 and 7.9) (Wafula et al. 2018; Jaybhaye et al. 2014; Malleshi and Dayakarrao 2015).

7.7

Health Benefits of Millets

The demand for food will increase as the world population grows. Currently, around 50% of the total calorie intake in the world is derived directly from cereals. Rice, wheat and maize have become the main staple cereals with a smaller sorghum and millet content. Sharma (2016) reported that an increase in the area of crops with intense water requirements such as rice, sugarcane (Saccharum officinarum) and cotton (Gossypium) resulted in an increase of 0.009% in the distance between the ground level and the groundwater table, which is equivalent to a loss of 7191 L of groundwater per hectare. There is a smaller chance of increasing the production of major staple cereals, as the world already faces the challenges of increasing drylands and deepening groundwater levels. According to the National Rainfed Area Authority (NRAA) report, even after full irrigation potential has been realised, approximately half of the net sown area remains rainfed. This alarms the need to move to the current grain staple alternative. There are several health disorders and chronic diseases in the world. According to the Global Nutrition Report (2016), 44% of the population in 129 countries (countries with available data) have severe levels of undernutrition, overweight for adults and obesity. An unbalanced nutrient diet causes most of these diseases. According to the UN Food and Agriculture Organization estimates, approximately 795 million people (10.9% of the world population in 2015) have been undernourished, while more than 1.9 billion (39% of the world’s population) adults 18 years of age were overweight and 13% were reported to be obese. The world population average body mass index (BMI) was reported to be 24 kg/m2 in 2014, higher than the

Carbohydrates (g) 72.0 66.9 70.4 60.9 67.0 65.5 72.6 67.5 71.2 78.2

Protein (g) 7.3 8.3 12.5 12.3 7.7 6.2 10.4 11.6 11.8 6.8

Fat (g) 1.3 1.4 1.1 4.3 4.7 2.2 1.9 5.0 1.5 0.5

Energy (kcal) 328 309 341 331 341 307 349 361 346 345

Crude fibre (g) 3.6 9.0 2.2 8.0 7.6 9.8 1.6 1.2 1.2 0.2 Mineral matter (g) 2.7 2.6 1.9 3.3 1.5 4.4 1.6 2.3 1.5 0.6

Source: Nutritive value of Indian foods, NIN, 2007; MILLET in your Meals, http://www.sahajasamrudha.org/

Food grain Finger millet Kodo millet Proso millet Foxtail millet Little millet Barnyard millet Sorghum Bajra Wheat (whole) Rice (raw, milled)

Table 7.4 Nutrient composition of millets compared to fine cereals (per 100 g) Ca (mg) 344 27 14 31 17 20 25 42 41 10

P (mg) 283 188 206 290 220 280 222 296 306 160

Fe (mg) 3.9 0.5 0.8 2.8 9.3 5.0 4.1 8.0 5.3 0.7

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Thiamin (mg) 0.59 0.41 0.42 0.3 0.33 0.15 0.38 0.38 0.41 0.41

Niacin (mg) 3.2 4.5 1.1 3.2 4.2 2.0 4.3 2.8 4.3 5.1

Riboflavin 0.11 0.28 0.19 0.09 0.1 0.09 0.15 0.21 0.04 0.1

Vit A (carotene) (mg/100 g) 32 0 42 0 0 0 47 132 0 64

Vit B6 (mg/100 g) – – – – – – 0.21 – – 0.57

Folic acid (mg/100 g) 15.0 – 18.3 9.0 – 23.1 20.0 45.5 8.0 36.6

Source: Nutritive value of Indian foods, NIN, 2007; MILLET in your Meals, http://www.sahajasamrudha.org/)

Millet Foxtail Proso Finger Little Barnyard Kodo Sorghum Bajra Rice Wheat

Table 7.5 Vitamin profile of millets and major cereals Vit B5 (mg/100 g) 0.82 1.2 – – – – 1.25 1.09 – –

Vit E (mg/100 g) 31.0 – 22.0 – – – 12.0 19.0 – –

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Arginine 220 290 300 250 270 240 300 480 290

Histidine 130 110 130 120 120 160 140 130 130

Lysine 140 190 220 110 150 150 190 230 170

Tryptophan 60 50 100 60 50 70 110 80 70

Phenyl alanine 420 310 310 330 430 300 290 280 280

Tyrosine – – 220 – – 180 200 290 180

Methionine 180 160 210 180 180 100 150 150 90

Cystine 100 – 140 90 110 90 110 90 140

Source: Nutritive value of Indian foods, NIN, 2007; MILLET in your Meals, http://www.sahajasamrudha.org/

Millet Foxtail Proso Finger Little Barnyard Sorghum Bajra Rice Wheat

Table 7.6 Essential amino acid profile of millets compared to fine cereals (mg/g of N) Threonine 190 150 240 190 200 210 140 230 180

Leucine 1040 760 690 760 650 880 750 500 410

Isoleucine 480 410 400 370 360 270 260 300 220

Valine 430 410 480 350 410 340 330 380 280

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Table 7.7 Micronutrient profile of millets compared to fine cereals (mg/100 g) Cereals/millets Foxtail Proso Finger Little Barnyard Kodo Sorghum Bajra Rice Wheat

Mg 81 153 137 133 82 147 171 137 90 138

Na 4.6 8.2 11.0 8.1 – 4.6 7.3 10.9 – 17.1

K 250 113 408 129 – 144 131 307 – 284

Cu 1.40 1.60 0.47 1.00 0.60 1.60 0.46 1.06 0.14 0.68

Mn 0.60 0.60 5.49 0.68 0.96 1.10 0.78 1.15 0.59 2.29

Mb 0.070 – 0.102 0.016 – – 0.039 0.069 0.058 0.051

Zn 2.4 1.4 2.3 3.7 3 0.7 1.6 3.1 1.4 2.7

Cr 0.030 0.020 0.028 0.180 0.090 0.020 0.008 0.023 0.004 0.012

Su 171 157 160 149 – 136 54 147 – 128

Cl 37 19 44 13 – 11 44 39 – 47

Source: Nutritive value of Indian foods, NIN, 2007; MILLET in your Meals, http://www. sahajasamrudha.org/ Table 7.8 Fatty acid composition of millets compared to fine cereals Cereals/millets Foxtail Proso Finger Little Sorghum Bajra Rice Wheat

Palmitic 6.40 – – – 14.0 20.85 15.0 24.50

Palmeolic – 10.80 – – – – – 0.80

Stearic 6.30 – – – 2.10 – 1.90 1.00

Oleic 13.0 53.80 – – 31.0 25.40 42.50 11.50

Linoleic 66.50 34.90 – – 49.0 46.0 39.10 56.30

Linolenic – – – – 2.70 4.10 1.10 3.70

Source: Nutritive value of Indian foods, NIN, 2007; MILLET in your Meals, http://www. sahajasamrudha.org/ Table 7.9 Amylose and amylopectin content of millets

Cereal grain Proso millet Foxtail millet Kodo millet Finger millet Sorghum Bajra Short grain rice Wheat

Amylose (%) 28.2 17.5 24.0 16.0 24.0 21.1 12–19 25.0

Amylopectin (%) 71.8 82.5 76.0 84.0 76.0 78.9 88–81 75.0

Source: Nutritive value of Indian foods, NIN, 2007; MILLET in your Meals, http://www.sahajasamrudha.org/

WHO standards for optimum health (21–23 kg/m2). Complications associated with obesity, such as cardiovascular disease and diabetes, have already been declared an epidemic by the World Health Organization. India is the home of the world’s largest undernourished population. Approximately 194.6 million people, 15.2% of India’s

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total population, are undernourished. India was ranked 100th out of 119 countries in the 2017 Global Hunger Index report. India’s scores are even worse than Nepal, Sri Lanka, and Bangladesh. Protein-energy malnutrition (PEM) has resulted in 469,000 deaths and 84,000 deaths from the lack of other vital nutrients such as iron, iodine and vitamin A. Obesity is also a significant health concern in India, with 11% prevalence in men and 15% in women. Millets are the sixth largest producer of cereal grains in the world and are still a staple food in many parts of the world. They are a rich source of many vital nutrients and therefore represent an additional advantage in the fight against nutrient deficiencies in the Third World (Kumar et al. 2018). Millets with rich nutrient content have potential health benefits. It is reported that the consumption of millets improves digestion; protects against cardiovascular diseases, degenerative diseases and diabetes; and detoxifies the body (Malleshi and Dayakarrao 2015).

7.8

Factors Limiting the Productivity of Millets

• Millets are normally cultivated on marginal and problem soils, under semi-arid conditions. • Broadcasting method of sowing impedes farm operations like weeding and other intercultural operations. • Use of traditional varieties and minimum/no use of chemical fertilisers reduce farm returns. • Inadequate research and development and lack of adequate extension support reduce the productivity of millet crops. • Socio-economic constraints of famers coupled with instability in market prices earn only limited returns to the farmers (Stanly and Shanmugam 2013).

7.8.1

Casual Factors for Decline in the Consumption of Nutritious Cereals

• Rapid urbanisation. • Change in consumer preferences and food habits. • Nutritious cereals are socially less valued, which means that their consumption decreases compared to increasing per capita incomes. • Easy access to cereals like rice and wheat at cheaper prices than nutritious cereals under public distribution system. • Tedious and time-consuming process in the food preparation.

7.8.2

Measures for Increasing the Demand of Nutritious Cereals

• Public awareness building of nutritional supplements. • Nutritious cereals supply through public distribution system at cheaper prices.

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• By providing value addition to nutritious cereals. • By integrating the supply of millet foods with mid-day meal scheme, Adolescent Girl Nutrition Scheme and Integrated Child Development Programme.

7.9

Approaches to Improve Millet Cultivation

As discussed in the factors limiting the productivity of millets, the millet cultivation is carried out by resource-poor farmers under resource-limiting environments. Nevertheless, the millet cultivation must be recognised for reasons such as low water consumption, nutritional content and quality. • Millet cultivation must be popularised through proactive extension activities such as result demonstration, training programmes and adaptive trials. • Agronomic research should be undertaken to develop cost-effective technologies. • Measures to supply quality seeds of new high-yielding varieties. • Distribution of millets through public distribution system (Anonymous 2010). • Development of rainfed agriculture through integrating it with programmes like MGNREGA, watershed development programmes and employment generation programmes. • Value addition and development of instant foods must be encouraged through training programmes. • Recognition of millets as climate-smart millets. Millet cultivation must be preferred to cope with climate change as millet cultivation is possible in water-scarce and arid environment. • The marginal lands, fallows and wastelands should be reclaimed and used for millet cultivation. By doing so, millet grain production and fodder production can be increased. In this regard, awareness campaign and training programmes must be encouraged to promote millet cultivation (Stanly and Shanmugam 2013).

7.10

Value Addition of Millets

• Millet production is viewed positively by the policy makers from the perspective of national food security. Attempts are required in the area of millet processing, value addition and production of ready-to-eat foods, and healthy and bakery foods. • Refinement of the millet grains to improve the grain quality: The processed millet products are used for making flour, sprouting and fermentation. • Hydrothermal treatment to decorticate the millets augments the edibility and appearance of food. • Modern milling methods including disk sheller, rice huller and centrifugal sheller aid greatly in the value addition of millet grains.

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• The value-added products from millets include multigrain flour, fermented foods, papad, millet flakes, ready-to-use food, noodles-vermicelli, bakery products, etc. (Kulkarni et al. 2018).

7.11

Way Forward and Future Plan for Reviving the Demand of Millets

• Identification of product-specific varieties in millets. • Nutritional assessment of millet foods and use of laboratory data highlighting nutritional characteristics. • Shelf-life improvement through improved packaging to meet modern dietary habits by providing balanced nutrition. • Standardisation of millet-rich multigrain flour and food products. • Changes from commodity-based on-farm production to market-driven end product-specific farm production and market assurance for millet farmers through buyback. • Public-private partnership (PPP) model of holistic farm extension services for seed supply, fertilisers, plant protection chemicals, crop management and capacity building. • Ready-to-eat and convenient foods to overcome cumbersome and timeconsuming food preparation of millets. • Setting up more links with government-line departments and NGOs. • Identifying and standardising designer foods intended for school children’s mid-day meals. • Branding millets as health foods by adding value through evaluation and certification of nutrition and implementation. • Innovative popularisation approaches such as road shows, wet sampling and millet tables for the Republic Day or Independence Day parade and important public spaces and functions. • Coalition building with other research groups and private groups working on millets elsewhere in the world through exchange visits, national seminars and workshops on millets and further global meetings on mills. • Recognition and value addition to land races that have long been nurtured by farmers, possibly also securing IPR for local innovation. • “Model support” for dry-land farmers by linking to government schemes such as the pilot-scale mid-day meal scheme in one district of Andhra Pradesh, Maharashtra and Karnataka under INSIMP, in order to extract value and make the public welfare system more efficient and locally relevant for educating on the nutritional use of millets.

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Utilisation of Millets for Alternative Uses

Traditionally millets are used to make fermented food and drinks. Grains with high starch (65–72%) and low protein (8–12%) may be used for alcohol production. Kharif sorghum is used mainly as a raw material for different industries, because it is much less used for human consumption. Pearl millet is most recently used as a low-cost substitute for maize in poultry and animal feed. • The grain can be used in the preparation of protein-rich foods because of its rich protein content. • Due to its richness in oil content in the bran, it can be used as a complementary to rice bran oil. • Pearl millet may also be used for brewing in favourable areas where the factories are located with a market surplus. • Since it is gluten free and has high fibre content, it can be used in the preparation of health products. In India, the main industries currently using sorghum and millets are poultry feed, animal feed, potable alcohol distilleries, etc. The poultry feed industry currently uses approximately 2.0 million tons of sorghum per year; the dairy feed industry uses approximately 0.60 million tons of sorghum followed by alcohol distillers (approximately 0.49 million tons).

7.12.1 Poultry Feed/Animal Feed The poultry feed industry is progressing well in India. Most of the studies conducted on feeding trials carried out on layer and broiler birds could demonstrate conclusively that sorghum and pearl millet are as good as maize, although the latter is marginally higher in total energy. In layer birds, sorghum and millet-based feed must be supplemented with carotene to ensure the yellow colour of the egg yolk. Moulded Kharif grain is also found as an acceptable grain component in goat and swine feed. Sorghum is used as a supplement to maize when the prices of maize rise and during the period of its scarce availability.

7.12.2 Starch In view of processing problems and starch yield, sorghum is rarely used by the starch industry, as the machinery for extracting starch is adapted to the larger grain size of maize. While the recovery of starch from sorghum can be improved by modified extraction, selective breeding and use of specially adapted machinery, starch production from the current sorghum cultivars is only economically viable if the grain price is 20% lower than that of maize. Sorghum grain is found to be more suitable for glucose and liquid glucose production.

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7.12.3 Potable Alcohol The grain of sorghum offers excellent ethanol and a high alcohol recovery rate of 422–448 L/ton. This allows the use of rain-damaged blacked and sorghum grain with a lower market value as a raw material for malting and production of high-quality drinking alcohol. More than ten distilleries currently use sorghum grain (mostly blacked) as the raw material for drinking alcohol. The Maharashtra Government has announced incentives for distilleries based on sorghum grain that are an alternative to sugarcane molasses. The establishment of such an industry in potential areas would benefit farmers by contract farming to secure a market with a remunerative price.

7.12.4 Malt Another potential area in the brewing industry could be the use of ragi and sorghum malt. In Ghana and Nigeria, malted sorghum is used to brew beer. The comparative advantage of sorghum would be its low output price, especially in rainy sorghum production regions in India over existing raw materials.

7.12.5 Bioethanol Sweet stalked and high-energy sorghum can become a significant bioenergy crop for industrial alcohol, gasoline and even electricity production. While national sweet sorghum tests showed potential productivity of 50–60 tons of stalk and 2–3 tons of grain/ha in 125–130 days, reports from China indicate a high productivity rate of 90 tons of stalk and 6 tons of grain/ha from the crop in 140–150 days. This potential for productivity gives the crop an advantage over sugarcane or molasses at their ruling prices for ethanol production. Due to its high productivity and relatively low fertilisation and irrigation levels, sweet sorghum is more efficient than sugarcane. In this context, sweet sorghum could be used effectively as an energy crop. IIMR and ICRISAT and many R&D organisations have been actively involved in sweet sorghum fine-tuning technology to develop it as an alternative feedstock for the production of bioethanol. Other possibilities of sweet sorghum are the production of jaggery and brown or colourless syrup or high fructose. These diversifications could be carried out as small enterprises at village or farm level.

7.13

Limitations with Storage and Consumption of Millets

Although millets are highly nutritious and beneficial to other cereals, their awareness among producers and consumers is very low. Small-sized seeds, instability, non-remunerative prices, and lack of postharvest operation such as cleaning, grading

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and value addition before placing in the market fetch low price. Also, rainfall at maturity/harvest also results in poor product quality. Its high fat, fibre and inert matter content coupled with high humidity and moisture lead to fungal attack during storage. Grains which are stored at high humidity often develop mycotoxins which are detrimental for the health of humans and animals. The shelf life of millet flour is also low due to the high-fat content of the grains. The colour of some millet’s dark seed coat, such as ragi and bajra, also has problems accepting food products from these commodities. The improvement of shelf life could, therefore, be an essential challenge in the processing of grain into products and in the marketing of its sustainability.

7.14

Conclusion

In the wake of climate change and depleting surface water and groundwater resources, large-scale cultivation of millets ensures employment and income of marginal and small farmers who are resource poor. Currently, in India, over 70% of agriculture is supported by groundwater irrigation and policy support of free and subsidised electricity supply. Severe overexploitation of groundwater is taking place due to the crop pattern dominated by high-water low-value crops such as paddy, sugarcane and other crops. With the cultivation of millets, the invaluable groundwater resource is indirectly conserved. However, the postharvest processing of millets in rural areas certainly deserves policy support from the government to encourage its cultivation by marginal, small and medium farmers. Millets offer opportunities for the processing sector to develop consumer-friendly, ready-to-use and economically accessible food products. This calls for field and lab-oriented research, R&D of millet cultivation and value chain in addition to policy support such as remunerative prices and procurement. There is a dire need for the policy makers and other stakeholders to augment climate-resilient millet crop production through proactive policies.

References Annual Progress Report (2017–18) ICAR-AICRP on small millets, Bengaluru, p 1–3 Anonymous (2010) National food security act: an introductory primer on the legal guarantees demanded by the right to food campaign, Right to Food Campaign Secretariat, vol 1. Capital Printers, New Delhi, pp 1–24 Behera MK (2017) Assessment of the state of millets farming in India. MOJ Ecol Environ Sci 2 (1):1–5 Cobley LS (1976) Introduction to the botany of tropical crops, 2nd edn. Longman, London Dayakar Rao B, Patil JV, Nirmal Reddy K, Soni VK, Srivatsava G (2014) SORGHUM: an emerging cash crop consumer acceptability of processed RTC/RTE health foods. Cambridge University Press India Pvt. Ltd., pp 20–30 Dayakarrao B (2015) Utilization pattern of millets. In: Tonapi VA, Patil JV (eds) Millets ensuring climate resilience and nutritional security. Daya Publishing House, New Delhi, pp 541–549

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Dayakarrao B, Malleshi NG, Annor GA, Patil JV (2015) Nutritional and health benefits of millets. In: Dayakar Rao B et al (eds) Millets value chain for nutritional security: a replicable success model from India. CABI, Wallingford, Oxford, pp 24–48 De Wet JMJ, Rao KEP, Mengesha MH, Brink DE (1983) Domestication pf Sawa millets (Echinochloa colona). Econ Bot 37:283 De Wet JMJ, Rao KEP, Brink DE, Mengesha MH (1984) Systematic and Evaluation of Eleusine coracana. Am J Bot 71:550 Dewet JMJ (1986) Origin Evolution and systematics of minor cereals. In: Riley KW, Harinarayana G (eds) Small millets in global agriculture. Oxford and IBH, New Delhi, pp 19–29 Doggett H (1986) Small millets a selective overview. In: Riley KW, Harinarayana G (eds) Small millets in global agriculture. Oxford and IBH, New Delhi, pp 2–17 Economics and Statistics Directorate (2015) DACNET: directorate of economics and statistics, department of agriculture, cooperation and farmers welfare, ministry of agriculture and farmers welfare, Govt. of India. http://eands.dacnet.nic.in/ FAO (2014) Food and Agriculture Organization, Rome. http://faostat3.fao.org/home/E FAO (2017) World food situation; 2017. http://wwwfaoorg/worldfoodsitua tion/csdb/en/. Accessed 30 Oct 2018 Global Nutrition Report (2016) From promise to impact: ending malnutrition by 2030. IFPRI—led food security portal, p 1–182 Jaybhaye RV, Pardeshi IL, Vengaiah PC, Srivastav PP (2014) Processing and technology for millet based food products: a review. J Ready Eat Food 1(2):32–48 Kulkarni DB, Sakhale BK, Giri NA (2018) A potential review on millet grain processing. Int J Nutr Sci 3(1):1–8 Kumar A, Tomer V, Kaur A, Kumar V, Gupta K (2018) Millets: a solution to agrarian and nutritional challenges. Agric Food Secur 7(1):13989547 Malathi B, Chari A, Rajender G, Dattatri K, Sudhakar N (2016) Growth pattern of millets in India. Indian J Agric Res 50(4):382–386 Malleshi N, Dayakarrao B (2015) Creating demand of millets through value addition. In: Tonapi VA, Patil JV (eds) Millets ensuring climate resilience and nutritional security. Daya Publishing House, New Delhi, pp 551–574 Purseglove JW (1985) Tropical crops, monocotyledons. Longman, London Satish PV (2010) Millets: future of food and farming. Towards Ecological Sanity, Deccan Development Society, Issue April-June, 2010. http://archive.wizardconcepts.com/bhoomima/article/ millets-future-food-and-farming Sharma CP (2016) Overdraft in India’s water banks: studying the effect of production of water intensive crops on groundwater depletion. Master Thesis, Georgetown University, Washington, DC Stanly JP, Shanmugam A (2013) A study on millets based cultivation and consumption in India. Int J Market Financ Serv Manag Res 2(4):49–58 Thakur SS, Sharma HO (2018) Trend and growth of small millets production in Madhya Pradesh as compared to India. Int J Agric Sci 10(1):4983–4986 Wafula WN, Korir NK, Ojulong HF, Siambi M, Gweyi-Onyango JP (2018) Protein, calcium, zinc, and iron contents of finger millet grain response to varietal differences and phosphorus application in Kenya. Agronomy 8(24):1–9. https://doi.org/10.3390/agronomy8020024

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Scope and Strategic Intervention for Climate-Smart Agriculture in North Eastern India N. K. Patra and Suresh Chandra Babu

Abstract

Agriculture is the key player of the economy of North Eastern Region (NER), India, and mainstay of most of the people of NER, India. However, environmental factors and climate change influence the production, productivity and regional food security. Climate-smart agriculture (CSA) is the concept of sustainable augmentation of agricultural production and productivity to ensure the food security and restore or protect the environment by reducing the emission of greenhouse gases (GHGs). Therefore, sustainable production and productivity of important food items or crops without or reduced emission of GHGs and building resilience to climate change are the challenges to the agriculture sector. This chapter is an attempt to assess the scope of CSA and propose a strategic intervention to achieve the CSA in the region. All the existing agricultural crops and some important practices in the region are assessed with special reference to CSA. We also assess the existing stakeholders in the implementation of CSA and mitigation and adaptation of climate change and propose a suitable strategy to accelerate the implementation of CSA and the mitigation and adaptation of climate change. Keywords

Climate-smart agriculture · Sustainable agriculture · North Eastern India · Resilient agriculture

N. K. Patra (*) Department of Agricultural Extension, SASRD, Nagaland University, Medziphema, Nagaland, India S. C. Babu Capacity Strengthening Program, IFPRI, Washington, DC, USA # Springer Nature Singapore Pte Ltd. 2020 V. Venkatramanan et al. (eds.), Global Climate Change: Resilient and Smart Agriculture, https://doi.org/10.1007/978-981-32-9856-9_8

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Introduction

North Eastern Region (NER) of India is under the Eastern Himalayan Region and includes eight states, namely Arunachal Pradesh, Assam, Manipur, Meghalaya, Mizoram, Nagaland, Sikkim and Tripura. The NER spans between 22.50
and 29.34
north latitudes and 88.00
and 97.30
east longitudes. The region is strategically very important and borders with another five South Asian countries, namely Bangladesh, Bhutan, China, Myanmar and Nepal (www.wikipedia.com). West Bengal is the bridging state between Central India and NER. Assam is in the core of the NER and all the states are situated around it and Sikkim is isolated. The total population is 45 million (3.75% of country’s population) (Census India 2011) and the region is a residence of around 483 different tribes and native of more than 50% of the total recognised and resident tribes of the country. The total geographical area of the region is 262,379 square km (7.9% of the geographical area of the country) and out of this 28.3% has an elevation of more than 1200 m, 17.9% between 600 and 1200 m, and about 10.8% between 300 and 600 m above mean sea level. Around one-fourth of the forest area of the country is nurtured by this region. NER is one of the world famous biodiversity hotspots and abodes more than one-third of the country’s total biodiversity, and one of the largest river systems (the Brahmaputra) of India passes through this region (IGFC 2011 and www.wikipedia.com). The Brahmaputra river originated from Himalayan highland; passes through three densely inhabited countries of South Asia, namely China, India and Bangladesh; and is the seventh largest tropical river (Hovius 1998; Latrubesse et al. 2005; Tandon and Sinha 2007) of the world and one of the largest river systems in India. This river passes through Arunachal Pradesh and Assam of NER and reaches the Bay of Bengal via Bangladesh. The Fourth Assessment Report of Intergovernmental Panel on Climate Change (IPCC) (IPCC 2007) highlighted that “the Himalayan Highlands will face some of the highest increases of global warming and consequently flow of rivers is already changed” (IPCC 2007). Millions of people from India and Bangladesh depend upon this river as a direct source of livelihood (IPCC 2007). According to Goswami (2008), Assam is vulnerable to climate change in several ways and one of the most flood-prone areas of the world, having 40% of its geographic area flooded yearly. Approximately, 80% of the population of the region stays in rural areas and mainly depends on agriculture and allied activities for their livelihood and survival (Government of India 2015). The economy of the region is mainly based on agriculture. Agriculture in NER includes crops, livestock, forestry, fisheries, apiculture and sericulture. It is the most important sector of the region and the main source of livelihood and survival of 80% of the population. Shifting (locally known as jhum cultivation) cultivation and rainfed cultivation are predominant and farmers of the region are continuing mixed cropping. Farmers are growing various crops according to the domestic requirement and suitable climatic condition for the specific crop. Major cereal crops of the region are rice and maize; major tuber crops in the region are tapioca, Colocasia and potato; important spice crops are ginger, turmeric, chilli, black pepper and cardamom, and fruit crops are pineapple, orange, kiwi, banana,

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jackfruit and apple. Apart from shifting cultivation, terrace cultivation, lowland rice cultivation, and livestock rearing and forest product (both timber and non-timber forest product) collection are the alternatives for the survival and livelihood of the people. Agriculture in NER is characterised by traditional practices with low productivity and unable to meet the food grain requirement and mostly depends on import from other states of the country. Therefore, the region is food and nutrition insecure and food insecurity is related to several factors, like non-adoption or inadequate adoption of improved technologies in the farming sector; lack of policy intervention; inadequate supply or availability of contributing inputs like quality seeds, nutrients, fertilisers and extension services and crop field; non/less accessibility of resources; and vagaries of climate—erratic and unpredictable rainfall and temperature. The climate of NER corresponds with topographical variation, humid subtropical with hot and humid summer, severe monsoons and mild winters. But the climatic condition of Arunachal Pradesh and Sikkim is mountain climate with cold, snowy winters and mild summers (IGFC 2011). The altitudinal differences give rise to varied types of climate, ranging from near tropical to temperate and alpine. The average rainfall of the region is 2450 mm and temperature ranges from 0 to 42
C. The topography of more than two-third of the region is undulating, hilly (IGFC 2011) and erosion prone. According to World Bank (2007), climate change will have far-reaching consequences for agriculture that will disproportionately affect poor and marginalised groups who depend on agriculture for their livelihoods and have a lower capacity to adapt. It is predicted that the common impact of climate change in NER and in India will be seen as follows: an additional increase in CO2 concentration due to jhum burning and deforestation, increase in average temperature by 2–4
C, change in distribution and frequency of rainfall, water stress and less availability of fresh water, increase in frequency and intensity of cyclonic storm, threat to agriculture and food security, threat to human health due to increase and frequent outbreak of diseases and threat to natural ecosystem. A recent study estimates the annual costs of adapting to climate change in the agricultural sector to be over US$ 7 billion (Nelson et al. 2009). In this juncture, climate change and agriculture have intersected each other and impact of agriculture without proper concentration on the issues of climate change is more shocking and it hastens the process of climate change. Agriculture is estimated to account for about 15% of global greenhouse gas (GHG) emissions and for about 26% if the emissions from deforestation in developing countries—where agriculture is the leading cause of forest conversion—are included (World Bank 2007). Accordingly, the concept of “climate-smart agriculture” (CSA) has emerged to address the issue of anti-relationship of climate change and agriculture. CSA practices are defined as those that sustainably increase agricultural productivity and income, build resilience and capacity of agricultural and food systems to adapt to climate change, and reduce and remove GHGs while enhancing national food security (Neufeldt et al. 2013).

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To address the issues and negative impacts of climate change, different initiatives started as per the requirement. The National Environment Policy (Government of India 2006) was the most appropriate initiative and offered the foundation and basis for the integration of environmental issues and considerations in the policies of all sectors. The process of climate change mitigation and adaptation involves various sectors and stakeholders. After the implementation of the NEP, all development initiatives must be assessed for their sensitivity to climate concerns. The importance of institutional mechanism for implementation of the policy process and CSA practices has always been underemphasised. The policy is a set of interrelated decisions concerning the selection of goals and the means of achieving them within a specified situation (Jenkins 1978). The key institutional and policy mechanism to address the issues and impact of climate change is mainly state-level action plan on climate change, and the National Action Plan on Climate Change (NAPCC) (Government of India 2012). The NAPCC focuses on climate change adaptation as well as mitigation across all the major sectors. Under NAPCC (Government of India 2012), eight missions and North East Climate Change Adaptation Programme have been launched and which form the foundation for climate change policy of the Government of India. Extension functionaries of agriculture and allied departments of the region are promoting the adoption of CSA practices and climate adaptation concurrently with their main assignment. It is also important to highlight that large number of initiatives and strategies have already been initiated in response to actual climate change or expected climate change and/or to cope up with its devastating effects or impacts. Similarly, different studies have been conducted to estimate or predict the impact of climate change at the international, national and regional levels, but studies related to the institutional and policy-making process of climate change with reference to agriculture were less emphasised and relatively very less studies have been done. In this regard, Godfray et al. (2010) viewed that feeding the projected 9 billion people in 2050 requires a radical transformation of agriculture over the next four decades, growing more food without exacerbating environmental problems and simultaneously coping with climate change (CCAFS 2011). In connection with the above discussion, a study has been initiated with the following objectives: 1. To study the profile and existing farming system of NER, India 2. To examine some existing practices to recognise as smart climate practice 3. To study the involvement of different stakeholders in CSA and climate change mitigation 4. To propose a strategic measure to implement the CSA in the region

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159

Methodology

In this study, primary and secondary data were collected from various reliable sources related to CSA and analysed to bring pertinent inferences. More specifically, the study involves desk review of relevant information sources. Desk review includes reports and documents related to CSA, research reports on climate change and CSA, NER database and internet. Based on the desk review, the profile and existing farming system of the region, involvement of different stakeholders in CSA and climate change mitigation have been explored. Based on the earlier research initiatives (Patra 2017; Patra and Babu 2017) and review work a tool was developed to assess different practices or technologies aligned to CSA and recognise the practice or technology as climate smart. Finally, a strategic measure has been proposed for smooth implementation of CSA in the region. For identification of climate-smart practices, a list of sustainable and environmentally friendly practices was prepared based on experiences and views of the researchers, extension workers, farmers and experts and review of literature. These identified practices were validated and judged by experienced extension functionaries of different line departments and subject matter specialists of Krishi Vigyan Kendra (KVK) or Farm Science Centre with the help of questionnaire for data collection. Altogether, 35 respondents were included in the assessment of technologies and only four technologies were included in this chapter. The questionnaire was designed to collect the information related to existing climate-smart practices based on the “CSA Tech Index” of World Bank (2016) to measure and recognise the practice or technology as a climate smart or not in the earlier research work (Patra 2017). Three main themes, namely productivity, resilience and mitigation of GHGs of a practice/technology, were emphasised and taken into consideration to assess the climate smartness of a practice/technology. Altogether, 31 indicators were included for all themes of CSA to achieve the maximum accuracy. All the indicators included in the questionnaire were presented with the options of 5-point scale to perceive by the respondents in the form of highly unsatisfactory, unsatisfactory, satisfactory, highly satisfactory and extremely satisfactory with a weight of 1, 2, 3, 4 and 5, respectively. The themes and indicators in respect of existing crop production are presented in Table 8.1. With the help of collected data from 35 respondents, a “Climate Smart Index” (CSI) was developed. The mean value of all the responses against each indicator was considered as a score of that indicator. Similarly, the mean value of all the scores against all indicators was considered as CSI of practice, i.e. the degree of climate smartness of the practice or technology. Practice or technology with CSI value greater than 3 is considered as climate-smart practice/technology (Patra 2017).

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Table 8.1 Indicators for identification and validation of existing crop production practices with reference to CSA Themes Productivity

Resilience

Mitigation

Indicators The technology/practice (T/P) has the potential to increase yield. The T/P has the potential to lead the diversification of livelihood of the farming community. The T/P has the potential to reduce the area under erosion. The T/P is suitable for high altitude. The T/P is suitable for low altitude. The T/P is suitable for the steep slope. The T/P is suitable for rainfed cultivation. The T/P is suitable for high-rainfall area. The T/P is drought tolerant. The T/P is suitable in high temperature. The T/P is suitable at low temperature. The T/P has the potential to enhance soil fertility. The T/P has the potential to increase water (irrigation) use efficiency. The T/P has the potential to reduce the withdrawal of underground water for irrigation. The T/P has the potential to reduce the use of energy in the agriculture sector. The T/P has the potential to adopt IPM for pest control. The T/P has the potential to adopt INM. T/P has the potential to improve livestock diversification in existing farming systems. The T/P has the potential to improve feed production in existing farming systems. The T/P has the potential to lead the diversification of livestock production in existing farming systems. The T/P has the potential to address the issue of food security. The T/P has the potential to increase income. The T/P has the potential to promote crop diversification. The T/P has the potential to foster local and regional production and supply chains. The T/P has the potential to reduce gender inequality. The T/P has the potential to increase the resilience of the cropping system to drought. The T/P has the potential to reduce GHG emission. The T/P has the potential to enhance carbon sequestration. Use of T/P is possible without much disturbance (zero tillage) of soil. Crop residue/biomass is suitable for fodder. Crop residue not producing GHGs.

Source: Patra (2017)

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161

Results and Discussion

The results of the research are discussed and presented in this chapter according to the specific objectives of the study.

8.3.1

Profile and Existing Farming System of North Eastern Region, India

North Eastern Region (NER) of India is a beautiful and adventurous place due to hilly topography and green coverage. The majority (around 80% of the rural population) of the people of the region are surviving with agriculture and allied livelihood activities. Forest-based livelihood activities are also playing a prominent role in the area. A considerable portion of the population is also surviving with riverbased livelihood activities. Valley of Brahmaputra is accommodating around 22% of the people of the region (www.wikipedia.com). Mines and ores-based livelihood activities are also continuing by a considerable portion of the population of NER of India. Government and corporate and third sector’s job, business and cottage industry are even playing an essential role in the economy and livelihood of the region. The farming system in NER of India can be classified into different categories based on different dimensions. Based on topography and altitude, it can be classified into very high hill farming, high hill farming, foothill farming, plain land farming and lowland farming. According to the farming system, it can be classified into shifting cultivation, terrace cultivation, permanent cultivation, orchard and plantation, “char and diara” land cultivation and lowland waterlogging rice cultivation. Agriculture is characterised as traditional with low productivity and that is unable to meet the food grain requirement and mostly depends on import from other states of the country (Government of India 2015). Therefore, the region is food and nutrition insecure and food insecurity is related with several factors, like non-adoption or inadequate adoption of improved technologies in the farming sector; lack of policy intervention; inadequate supply or availability of contributing inputs like quality seeds, nutrients, fertilisers and extension services and crop field; non/lees accessibility of resources; and vagaries of climate—erratic and unpredictable rainfall. The climate of NER has corresponded with topographical variation, but mainly humid subtropical with hot, humid summer, severe monsoons and mild winters but the climatic condition of Arunachal Pradesh and Sikkim is mountain climate with cold, snowy winters and mild summers. The altitudinal differences give rise to varied types of environment, ranging from near tropical to temperate and alpine. The average rainfall of the region is 2450 mm, and temperature ranges from 0 to 42
C. The topography of more than two-third of the area is undulating and hilly (Table 8.2).

Districts Blocks Area under cultivation Forest area

Population/sq km Literacy rate (%) Geographical area (sq km) Longitude, latitude and altitude

Population (million) Male Female Major tribes (no.)

States NER Demography

78,438

Latitude 24
8 N to 28
2 N 89
42E and 96
E Longitude 45– 1960 meters

83,743

Between 260 300 N and 290 300 N and longitude 910 300 and 970 300 east Altitude 213 and 7090 m from the mean sea level 24 140 –

67,248 (80.30%)

72.19

65.38

37%

33 239 56.84

398

14

15,939,443 15,266,133 18

713,912 669,815 26

Assam

311,69,272

1.4

Arunachal Pradesh

17,418 sq km

9 41 231.19 sq km

22,327 sq km Longitute 93
580 E Latitute 24
440 N Altitude 748– 2994 m or 2572 feet

76.94

130

1,438,586 1,417,208 02

2,855,794

Manipur

23.1645
N, 92.9376
E 2210 m

25.4670
N, 91.3662
E Altitude between 450 and nearly 6000 feet (137– 1829 m) above sea level 11 46 Approx. 10% 14157.42 (63%) 1,594,000 ha (90.68%)

8 26

21,087

91.58

52

552,339 538,675 14

1,091,014

Mizoram

22,429

74.43

132

1,491,832 1,475,057 5

2,966,889

Meghalaya

Table 8.2 Demographic and agricultural details about NER, India

11 74 Approx. 10% 862,930

26.1584
N, 94.5624
E 2438 m (3841 m)

16,579

79.55

119

1,024,649 953,853 16

1.98

Nagaland

7811 (74%)

4 32 –

27.5330
N, 88.5122
E Altitude 280 m (920 ft) to 8586 m (28,169 ft)

7096

70.5

86

323,070 287,507 3

610,577

Sikkim

5745 (54%)

8 58 1,45,389

23.5360
N, 91.4870
E Altitude within 939 m (3,081 ft)

10,491

87.22

350

1,874,376 1799,541 7

3,673,917

Tripura

11 46 Approx. 10% 14157.42 (63%)

21.57
and 29.30
N latitude 89.46 to 97.30
Altitude almost sea level to 7000 m

262,230

170

23,212,792 22,273,992 220

45,486,784

NER

708,273 sq km (21.54%)

725 5500 60.45%

6
440 and 35
300 N latitude and 68
70 and 97
250 E longitude

3,287,263

74.04

623,724,248 586,469,174 705 (and 10.4 tribal population) 401.5

1,210,854,977

India

162 N. K. Patra and S. C. Babu

Banana, mandarin orange, kiwi, pear, papaya, pineapple, spices and vegetables Cattle, poultry, pig buffalo, mithun and yak

Banana, tea, mandarin orange, pineapple, kiwi, spices and vegetables Cattle, poultry, pig buffalo and mithun

Banana, mandarin orange, pineapple, spices and vegetables

Cattle, poultry, pig buffalo and sheep

Banana, mandarin orange, pineapple, spices and vegetables

Cattle, poultry, pig buffalo and mithun

Banana, mandarin orange, pineapple, spices and vegetables

Cattle, poultry, pig buffalo and mithun

Tea, banana, mandarin orange, pineapple, spices and vegetables

Cattle, poultry, pig buffalo and sheep

Apple, kiwi, mandarin orange, pineapple, spices and vegetables

Cattle, poultry, pig buffalo, mithun and yak

Important horticultural crops

Important livestock

Source: Authors’ compilation

Rice, maize, pulse

Rice, maize, pulse

Rice, maize, pulse

Agriculture, horticulture, livestock, forest and tourism based

Rice, maize, pulse

Agriculture, horticulture, livestock and forest based

Rice, maize, pulse

Agriculture, horticulture, livestock and forest based

Rice, maize, pulse

Agriculture, horticulture, livestock and forest based

Rice, maize, millet, pulse

Agriculture, horticulture, livestock, timber and tourism based

Important field crops

Agriculture, horticulture, livestock, river, forest and tourism based

Agriculture, horticulture, livestock, river, forest and tourism based

Major livelihood activities

Cattle, poultry, pig buffalo and sheep

Rice, maize, sugarcane, cotton Mandarin orange, pineapple, jackfruit, spices and vegetables

Agriculture, horticulture, livestock and forest based

Cattle, poultry, pig buffalo, mithun, sheep and yak

Khasi mandarin

Rice, maize, millet, pulse

Agriculture, horticulture, livestock, forest, river and tourism based

–

–

Agriculture, horticulture, fishery, marine fishery, livestock, forest based, industry and construction work based More or less all crops

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8.3.1.1 Arunachal Pradesh Arunachal Pradesh is the largest state in NER, India, and bounded by Myanmar to the east, China to the north-east, Bhutan to the west and Assam at the south. The state is the residence of 24 major tribes. The state is situated in the Eastern Himalayan Region between latitudes 26
300 N and 29
300 N and longitudes 91
300 E and 97
300 E with a geographical area of 83,743 km2. The altitude of the state extremely varied in nature and ranges from 50 m to above 7000 m from mean sea level. The important hill systems in the state are Kangto Massif and Namcha Barwa Massif. The Brahmaputra is the major river in the state and remaining rivers are Changlang, Dibang, Kameng, Lohit, Subansiri, Papum Pare, Tawang, Tirap and Siang (Govt. of Arunachal Pradesh 2011 and www.wikipedia.com). The state encompasses about 82% of Brahmaputra basin. About 157 glaciers are found in the state and mainly distributed in the Kameng, Subansiri and Dibang basin (Govt. of Arunachal Pradesh 2011 and www.wikipedia.com). In the state five agroclimatic zones are present, namely alpine zone, mid tropical hill zone, mid tropical plane zone, subtropical hill zone and temperate sub-alpine zone. The arable land (the net sown plus current and fallow lands) is estimated at 0.25 million hectares. Around 61% of the total geographical area is under forest and plays an essential role in livelihood and survival of sizeable tribal population living in proximity with timber. Farmers of the state are continuing traditional shifting cultivation which negatively influences the forest conservation. It is evident that the area under forest is declining (Government of India 2007). The state is the home of the second highest level of genetic resources. The state occupies only 2.5% of India’s geographical area but is the centre of origin of various animals, plants, orchids and angiosperms. In the year of 1995, the International World Conservation Union recognised this state as one of the significant centres of plant diversity (Govt. of Arunachal Pradesh 2011, www.wikipedia.com). Agriculture and Horticulture Agriculture is the backbone of the state economy, and many people depend upon agriculture and allied sectors for their livelihood and survival. Rice, wheat, maize millets, pulse and potato are commonly grown crops in the state. Traditional shifting cultivation (locally known as jhum cultivation) and terrace cultivation are predominant in the state. Shifting cultivation is characterised by slashing and burning which is accelerating climate change by adding CO2 to the environment. Productivity per unit area is very low (1.7–1.8—tonnes/hectare as compared to 3.7 tonnes/hectare at the national level) due to non-adoption of improved inputs and technologies. It has tremendous potential in respect of horticultural crop cultivation and production. The state has wide climatic variability in respect of high to low temperature, rainfall and humidity which is a prerequisite for a wide range of horticultural crop cultivation. Major horticultural crops in the state are apple, walnut, cardamom, pineapple, litchi, banana, ginger and chilli. Various livestock is also present in the state. Importantly, the state has a large population of yak, mithun, pig, poultry, goat and cattle.

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Climatic Condition and Impact of Climate Change The climate of the state is greatly influenced by a significant variation in elevation and Himalayan mountains all over the state. Areas under very high altitude experience alpine and tundra climates. A temperate climate prevails in the medium and middle Himalayan region. At the sub-Himalayan and foothill part, the weather is subtropical with hot summer and mild winter. Temperature ranges from ˂0
C to 40
C with the average temperature during winter in between 15 and 21
C and rainy season in between 22 and 33
C, and during summer month it reaches up to 37–40
C. The state was receiving high annual precipitation and reached up to 5700 mm, but average rainfall is 3500 mm. Rainfall is distributed around 9 months of the year and maximum is in between May and September, and decidedly less or absent in winter months. But the area under very high altitude experiences snowfall during peak winter months (Govt. of Arunachal Pradesh 2011, www.wikipedia. com). As per the IPCC (2007), the Himalayan region is highly vulnerable in respect of climate change. The entire state is under the Himalayan region and will experience a noticeable impact of climate change. Based on the rainfall statistics, annual rainfall will be decreased by 5–15% in 2030 (Govt. of Arunachal Pradesh 2011).

8.3.1.2 Assam Assam is the second largest state in the NER and lies in the middle of the region. The state occupies around 2.4% of India’s total geographical area, and river Brahmaputra passes through the state and reaches Bangladesh. The state is surrounded by West Bengal, Meghalaya and Bangladesh in the west; Arunachal Pradesh in the east; Bhutan and Arunachal Pradesh in the north; and Nagaland, Manipur, Mizoram, Meghalaya and Tripura in the south. The state is situated between latitudes of 24
500 N and 28
00 N and longitudes 88
250 E and 96
000 E with a geographical area of 78,438 km2. The altitude of the state is varied in nature and ranges from 50 m to above 7000 m from mean sea level. The temperature varies from 6 to 38
C. The state receives around 120 inches of rainfall per annum, but precipitation is higher in upper Assam and Brahmaputra valley and the surrounding region. The state is rich in biodiversity and climate is favourable for vegetation and plant growth (Govt. of Assam 2015, www.wikipedia.com). The state has 32.17 million population and around 2.58% of the country’s population (Census India 2011). Population density (398 per square km) is marginally higher than the national average. The state is blessed with fertile soil, congenial climate and abundant water sources, and these are favourable for better agriculture. Around 50% of the working population is engaged in agriculture and allied activities (Govt. of Assam 2015). Rice is the primary cereal and tea plantation plays a significant role in the state economy. Other important agriculture-based livelihood activities are bamboo curving, sericulture and forest-based activities. Climatic Condition and Impact of Climate Change The Himalayan mountains greatly influence the climate of the state. The temperate climate prevails in the state. At the sub-Himalayan and foothill region, climate is subtropical with hot summer and mild winter. Maximum temperature ranges from

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35 to 39
C at summer, and minimum temperature ranges from 5 to 8
C during winter. The climate is characterised by heavy monsoon rains which give relief from high temperature during summer. But spring (March–April) and autumn (September–October) period are very much pleasant with moderate temperature and rainfall (Govt. of Assam 2015, www.wikipedia.com). Based on the analysis of long-term meteorological data, it is proved that temperature is increasing per year and rainfall is also decreasing per year. The state is experiencing not only a reduced number of rainy days but also increased daily temperature. Occurrences of floods will increase due to the deposition of eroded soil in the river Brahmaputra (Govt. of Assam 2015).

8.3.1.3 Manipur Manipur is the fourth largest state of the NER, India, and bounded by Mizoram in the south, Nagaland in the north, Assam to the west and Myanmar in the east. The state is the residence of 2,793,896 people with 34% tribal population. The state is situated in latitudes of 23
830 N and 25
830 N and longitudes of 93
030 E and 94
680 E with a geographical area of 22,327 km2. The altitude of the state is extremely varied in nature and ranges from 50 m to above 7000 m from mean sea level. The state can be characterised as two separate physical regions, viz. rugged hills and narrow valleys, and plain area (Govt. of Manipur 2013; www.wikipedia.com). Principal crops grown in the state are rice, wheat, maize, beans, tree beans and different vegetables. Cattle, pig, poultry, mithun and goat are the valuable livestock that are reared by people of the state for their livelihood. Climatic Condition and Impact of Climate Change The climate of the state is greatly influenced by sizeable topographical variation. The lower foothills of western hills and Barak basin areas have a warmer climatic condition. The western part of the state experiences the humid climatic condition. The temperature ranges from 13.8 to 26.5
C. The state receives average annual precipitation, which ranges from 935 to 2636 mm per annum. Climate change will influence the amount, rate and frequency of rainfall. Crop yield will decrease, and the incidence of disease outbreak will be increased (Govt. of Manipur 2013).

8.3.1.4 Meghalaya Meghalaya is third largest state of the NER of India with hill ecosystem. The state is bounded by Assam in the north and east, and by Bangladesh in the south and west. The state is situated in latitudes of 23
830 N and 25
830 N and longitudes of 93
030 E and 94
680 E with a geographical area of 22,327 km2. The altitude of the state is extremely varied in nature and ranges from 50 m to above 7000 m from mean sea level (www.wikipedia.com). The economy of the state is much depended on agriculture, forestry tourism and ores. Agriculture is the backbone of the state rural economy, and many people depend upon agriculture and allied sectors for their livelihood and survival. Rice, wheat, maize millets, pulse and potato are commonly grown crops in the state like other NER states. Traditional shifting cultivation (locally known as jhum cultivation) and terrace

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cultivation are also continuing in the state and accelerating climate change by adding CO2 to the environment. Productivity per unit area is low (0.7–0.8 tonnes/hectare as compared to 3 tonnes/hectare) due to non-adoption of improved inputs and technologies (Govt. of Meghalaya 2013 and www.wikipedia.com). It has tremendous potential in respect of horticultural crop cultivation and production. The state has wide climatic variability in respect of high to low temperature, rainfall and humidity which is a prerequisite for a wide range of horticultural crop cultivation. Major horticultural crops in the state are lemon, guava, plum, pear, peach, cardamom, pineapple, litchi, banana, turmeric, ginger and chilli, medicinal and aromatic plants, orchid and fern. Further, the state importantly has a large population of cattle, pig, poultry and goat population. Climatic Condition and Impact of Climate Change The climate of the state is greatly influenced by a significant variation in elevation and Himalayan mountains all over the state. Areas under very high altitude experience alpine and tundra climates. The temperate climate prevails in the medium and middle Himalayan region. At the sub-Himalayan and foothill region, the climate is subtropical with hot summer and mild winter. Temperature ranges from ˂0
C to 28
C with a fall of temperature to 0
during winter. The state receives high annual precipitation, which reaches up to 12,000 mm in some areas (Govt. of Meghalaya 2012).

8.3.1.5 Mizoram Mizoram is a beautiful and fifth most extensive state of the NER, India. The state is a conglomeration of 21 major hills and is situated under Himalayan ecosystem. The state is highly forested and above 70% of the geographical area is under forest. The total geographic area is 22,081 square km and subdivided into 8 districts and 26 blocks. The state is a home of 1,091,014 people with a population density of 49 per square km. The state has a pleasant climatic condition with 11
C winter temperature and 20–30
C round the year. Temperature is hugely varied in nature with the altitude of the place. In a normal year, the state receives 3000 mm rainfall and monsoon period usually receives maximum (Govt. of Mizoram 2012 and www. wikipedia.com). Agriculture is the mainstay for more than 70% of the population and economy of the state is also based on agriculture. The agriculture sector is highly vulnerable, and productivity of important crops is very low. Out of the total geographical area, only 5% is under agriculture, and traditional shifting cultivation is practised in the state. In shifting cultivation and permanent cultivation, rice is the main crop and farmers used to grow early rice. Other important crops grown in the state are maize, sugarcane, cotton, tapioca, mustard, soybean, French beans and rice beans. Important horticultural crops in the state are orange, passion fruit, pineapple, jackfruit, banana, grapes, litchi and guava. Major vegetable crops, like tomato, peas, squash, mustard and cabbage, are also successfully grown in the state. The climate of the state is very much congenial for growing spices, like ginger, turmeric, cardamom and cinnamon. Farmers rear valuable livestock, like cattle, mithun, pig, poultry and goat.

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8.3.1.6 Nagaland Nagaland is also a mountainous state and sixth largest state of NER of India and is situated in the north-eastern Himalayan region. The state is highly vulnerable in respect of climate change, as it is located under the most vulnerable part of the northeastern Himalayan region. The state lies between 25
600 and 27
400 north latitude and 93
200 E and 95
150 E longitude. The state has a geographical area of 16,579 square km (www.wikipedia.com), and the total population is 1,980,602 (Census India 2011). The density of population is around 120 per square km. Average annual rainfall ranges from 2000 to 3000 mm, and temperature ranges from 4 to 31
C. The topography of the state is undulating, full of the hill range, which breaks into vast chaos of spurs and ridges (Patra et al. 2015). Climatic Condition and Impact of Climate Change The state has a humid tropical climate. The plain area and foothill area experience warm and subtropical climate. The topography of the state is undulating, and the climatic condition is varied according to the topography. The state is also a part of the eastern and north-eastern Himalayan ecology. The Himalayan mountains greatly influence the climate of the state. Monsoon is more prolonged, and annual rainfall varies from 1000 to 3000 mm. Based on the analysis of long-term meteorological data, it is proved that the temperature and rainfall magnitude is likely to increase by about 5–20% in the future as compared to the present and these will directly impact agriculture and allied sectors (Govt. of Nagaland 2012). Agriculture and Horticulture Agriculture is the mainstay for more than 75% of the population and economy of the state is also based on agriculture. In the state, shifting cultivation, terrace cultivation and permanent cultivation are in practice. In all types of cultivation practices, rice is the main crop. Other crops grown are maize, tapioca, Colocasia, French bean, mustard, soybean and rice beans. Major horticultural crops in the state are pineapple, orange, passion fruit, jackfruit, banana, litchi, guava, cardamom, tea, plum, medicinal and aromatic plant, orchid and fern. Major vegetable crops, like tomato, peas, squash, mustard and cabbage, are also successfully grown in the state. Further, spices like ginger, turmeric, cardamom and cinnamon are cultivated by farmers. Livestock population includes cattle, mithun, pig, poultry, duck, rabbit and goat.

8.3.1.7 Sikkim Sikkim state is situated between 27
040 S and 28
70 N and at the longitude of 88
000 W and 88
550 E. It is the smallest state of the NER of India with a geographical area of 7096 square km and is subdivided into four districts. The total population of the state is 610,577, more than 75% of the people stay in a rural area, and their livelihood and survival are based on agriculture and allied activities. It is one of the leading states in organic farming. The state has a wide variation in climate and extents from temperate and subalpine to alpine which makes the state one of the richest biodiversity hotspots. The state has the steepest landscape, and only 20% of the geographical area is habitable. The state has varied agroclimatic condition with a

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steep slope. Soil is generally acidic in reaction (Govt. of Sikkim 2011 and www. wikipedia.com). Terrace cultivation is the most prominent, and cardamom is the most important cash crop. Rice, millet and maize are commonly grown cereal crops, and other critical horticultural crops are pineapple, apple, orange, peach, guava, cardamom, tea, plum, medicinal and aromatic plant, orchid and fern. The livestock population also plays an essential role in the state to fulfil the need and livelihood of the rural community as well as protein and nutrition security of the state. Valuable livestock are cattle, buffalo, pig, sheep, goat and yak (Govt. of Sikkim 2011).

8.3.1.8 Tripura Tripura state covers about 10,491 km2 and is surrounded by Bangladesh to the north, south and west, and Assam and Mizoram to the east. The state is situated between latitudes of 22
560 N and 24
320 N and longitudes of 91
090 E and 92
200 E. The temperature varied from 13 to 36
C with mild winter. The state receives about 1980–2746 mm rainfall per year. The state is rich in biodiversity and climate is favourable for vegetation and plant growth (Govt. of Tripura 2011 and www. wikipedia.com). Around 75% of the population depends on agriculture and allied activities, and 60% of the area is under forest cover. Rice is the main cereal crop and tea plantation plays a major role in the state economy. Other important agriculturebased livelihood activities are bamboo curving, sericulture and forest-based activities (Govt. of Tripura 2011 and www.wikipedia.com). Climatic Condition and Impact of Climate Change The state has a tropical savannah climate with undulating topography. The state is a part of the eastern and north-eastern Himalayan ecology and the environment is greatly influenced by Himalayan mountains. Based on the analysis of long-term meteorological data, it is proved that the flood and drought magnitude is likely to increase by about 25% in the future as compared to the present (Ravindranath et al. 2011) and these will directly impact agriculture and allied sectors. Agriculture and Horticulture The state is an agrarian state and agriculture is the backbone of the state economy, and around 75% of the population depend upon agriculture, pisciculture and allied sectors for their livelihood and survival. Rice, pulse, potato, sugarcane, pineapple, tea, jackfruit, banana and vegetables are commonly grown crops in the state. Traditional shifting cultivation (locally known as jhum cultivation) and terrace cultivation are predominant in the state which are characterised by slashing and burning, which accelerate climate change by adding CO2 to the environment. Productivity per unit area is low to moderate. It has tremendous potential in respect of horticultural crop cultivation and production. The state has wide climatic variability in respect of high to low temperature, rainfall and humidity which is a prerequisite for a wide range of horticultural crop cultivation. Major horticultural crops in the state are pineapple, litchi, banana, ginger and chilli. Livestock population include cattle, goat, pig and poultry.

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Identification of Climate-Smart Practices

Climate-smart agriculture is defined as agriculture that “sustainably increases productivity, enhances resilience, reduces/removes GHG emissions, and enhances the achievement of national food security and development goals” (FAO 2010). CSA benefits smallholder farmers and vulnerable people in developing countries (FAO 2013). Further, “the agricultural production system requires resilient development pathways to increase the agricultural production, reduce greenhouse gases emissions from farm activities, and adapt agriculture to climate change” (Venkatramanan and Shah 2019). It is difficult to designate one component or practice as climate smart and another one as non-climate smart. In this chapter, some methods are identified as “climate smart” based on the individual assessment of exercises with the help of “Indicators for identification and validation of existing crop production practices concerning CSA”. It is essential to mention that based on the analysis, only four climate-smart practices identified from Nagaland, NER, are presented below.

8.3.2.1 Practice 1 Community Cultivation In Nagaland shifting cultivation is predominant and is commonly known as jhum cultivation. Slashing and burning is an important component of shifting/jhum cultivation and it contributes GHGs into the environment. As a result, jhum cultivation is not considered as climate friendly. But in this practice, farmers follow community/ village-based cultivation. All farmers of the village come together as a community and grow crop in an area/plot or more than one plot as per the requirement of food grains by the villagers. Villagers perform all the activities of cultivation as community work. After harvesting, farmers share the product proportionately among them. Individual farming requires field boundaries, which increases the requirement of land area and decreases productivity due to the ridges of the plot. On the other hand, community-based farming converts small areas/plots into a large plot and the responsibility of the entire plot is equally distributed to all the farmers. This reduces the scope of mismanagement and enhances the production from the same unit area. The CSI of community cultivation is 3.24 (Table 8.3). The perceived score of 14 indicators out of 31 has reached 3 or above. It has emerged that community cultivation has the potential for an increase in yield (mean score is 3.61); “community cultivation” has the potential to reduce the area under erosion (mean score is 3.51); “community cultivation” is suitable for high altitude (mean score is 3.54); “community cultivation” is ideal for low altitude (mean score 3.00); “community cultivation” is suitable for steep slope (mean score 3.22); “community cultivation” is suitable for rainfed cultivation (mean score 3.60); “community cultivation” is suitable for high-rainfall area (mean score 3.51); “community cultivation” is drought tolerant (mean score 3.11); “community cultivation” has the potential to improve feed production in existing farming systems (mean score 3.08); “community cultivation” has the potential to address the issue of food security (mean score 3.14); “community cultivation” has the potential to increase income (mean score 3.05);

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“community cultivation” has the potential to increase the resilience of the cropping system to drought (mean score 3.40); “community cultivation” has the potential to enhance carbon sequestration (mean score 3.14); “community cultivation” is possible without much disturbance (zero tillage) of soil (mean score 3.20); and crop residue/biomass from “community cultivation” is suitable for fodder (mean score 4.22). Based on the high mean score (>3) against above-mentioned 14 indicators and overall high mean score (>3) (Table 8.3), it can be concluded that the “community cultivation” is a smart climate practice. In effect, joint liability and common property management are the key concepts behind the idea. Community mobilisation is needed to achieve a better result.

8.3.2.2 Practice 2 Dibbling of Seed in Jhum Field In NER and Nagaland, shifting cultivation is predominant and commonly known as jhum cultivation. Slashing and burning are two integral components of shifting/jhum cultivation and contribute different GHGs to the environment. As a result, jhum cultivation has not been considered as climate friendly. But in this practice, sowing of seeds without disturbing the soil, i.e. dribbling of seed by digging a small hole as per the seed size in the soil, is an essential component. The soil surface is the vast reservoir of carbon (C) and soil disturbance leads to carbon emissions. Therefore, disturbing the soil surface for cultivation is not desirable and the concept of “zero tillage” or minimum tillage is appreciated for C-sequestration. Here the CSI is 3.00, and perceived score of 15 indicators (out of 31) has reached 3 or above (Table 8.4). It has emerged from the study (Table 8.4) that the practice of “seed dibbling” in jhum field has potential in respect of increase in yield (mean score 3.05); potential to reduce the area under erosion (mean score 3.51); potential to an increase of water (irrigation) use efficiency (mean score 3.60); potential to reduce the use of energy in the agricultural sector (mean score 3.28); potential to adopt INM (mean score 3.00); potential to improve feed production in existing farming systems (mean score 3.20); potential to lead the diversification of livestock production in existing farming systems (mean score 3.14); potential to increase income (mean score 3.08); potential to promote crop diversification (mean score 3.40); potential to reduce gender inequality (mean score 3.28); and potential to enhance carbon sequestration (mean score 4.14). Practice is suitable for high altitude (mean score 3.20), suitable for steep slope (mean score 3.68), suitable for rainfed cultivation (mean score 3.22), suitable for high-rainfall area (mean score 3.00), suitable in high temperature (mean score 3.11), and suitable in terms of cultivation without much disturbance (zero tillage) of soil (mean score 4.08) and crop residue/biomass is suitable for fodder (mean score 3.02). Based on the high mean score (>3) against the above-mentioned 15 indicators and overall high mean score (>3) (Table 8.4), it can be concluded that the seed dibbling is a climate-smart practice. Farmers are continuing this practice according to their traditional knowledge. They are sowing more than one seed in a hole to ensure germination. Depth of sowing is decided by their experiences and without

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Table 8.3 Climate-smart performance of community cultivation Indicators The “community cultivation” has the potential to increase yield The “community cultivation” has the potential to lead the diversification of livelihood of the farming community The “community cultivation” has the potential to reduce the area under erosion The “community cultivation” is suitable for high altitude The “community cultivation” is suitable for low altitude The “community cultivation” is suitable for steep slope The “community cultivation” is suitable for rainfed cultivation The “community cultivation” is suitable for high-rainfall area The “community cultivation” is drought tolerant The “community cultivation” is suitable in high temperature The “community cultivation” is suitable in low temperature The “community cultivation” has the potential to enhance soil fertility The “community cultivation” has the potential to increase water (irrigation) use efficiency The “community cultivation” has the potential to reduce the withdrawal of underground water for irrigation The “community cultivation” has the potential to reduce the use of energy in the agriculture sector The “community cultivation” has the potential to adopt IPM for pest control The “community cultivation” has the potential to adopt INM The “community cultivation” has the potential to improve livestock diversification in existing farming systems The “community cultivation” has the potential to improve feed production in existing farming systems The “community cultivation” has the potential to lead the diversification of livestock production in existing farming systems

Findings Mean SD 3.62 0.546

Minimum 3

Maximum 5

Sum 127

2.88

0.529

2

4

101

3.51

0.658

3

5

123

3.54

0.741

3

5

124

3.00

0.594

2

4

105

3.22

0.843

2

5

113

3.60

0.603

2

5

126

3.51

0.507

3

4

123

3.11

0.582

2

4

109

2.85

0.493

2

4

100

2.80

0.472

2

4

98

2.20

0.677

1

3

77

2.62

0.490

2

3

92

2.37

0.490

2

3

83

2.85

0.355

2

3

100

2.91

0.658

2

5

102

2.94

0.539

2

4

103

2.14

0.493

1

3

75

3.08

0.781

2

5

108

2.25

0.505

1

3

79

(continued)

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Table 8.3 (continued) Indicators The “community cultivation” has the potential to address the issue of food security The “community cultivation” has the potential to increase income The “community cultivation” has the potential to promote crop diversification The “community cultivation” has the potential to foster local and regional production and supply chains The “community cultivation” has the potential to reduce gender inequality The “community cultivation” has the potential to increase the resilience of the cropping system to drought The “community cultivation” has the potential to reduce the GHG emission The “community cultivation” has the potential to enhance carbon sequestration The “community cultivation” is possible without much disturbance (zero tillage) of soil Crop residue/biomass from “community cultivation” is suitable for fodder Crop residue from “community cultivation” not producing GHGs Overall score

Findings Mean SD 3.14 0.550

Minimum 2

Maximum 4

Sum 110

3.05

0.481

2

4

107

2.94

0.416

2

4

103

2.82

0.452

2

4

99

2.68

0.471

2

3

94

3.40

0.650

2

5

119

2.94

0.481

2

4

103

3.14

0.943

2

5

110

3.20

0.598

2

4

113

4.22

0.731

3

5

148

2.40

0.497

2

3

84

3.24

0.575

2.03

4.06

taking seed size into consideration and time requirement for germination. Scientific intervention is needed in respect of the depth of sowing to increase the rate of germination and reduce the seed rate.

8.3.2.3 Practice 3 Alder (Alnus nepalensis)-Based Cultivation Himalayan alder (Alnus nepalensis) is a leguminous forest tree species that provides shade to other shade-loving crops, like cardamom and tea. The timber of alder (Alnus nepalensis) tree is suitable for firewood and some of the vegetative parts are used as fodder for livestock. It is also used as shelter crop. In Nagaland, it is a potential component of agroforestry system and widely accepted throughout the state. Alder plant has wide adaptability, and it can grow well in high altitude and steep sloppy area and grows naturally on the landslide-prone areas. Thus, it has the potential to minimise landslides and is able to enrich the soil by nitrogen fixation.

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Research shows that sizeable cardamom-based agroforestry stored 3.5 times more carbon than the rainfed agriculture (Sharma et al. 2009). Therefore, the plant has the potential to mitigate GHGs and accelerate soil C-sequestration. This plant is capable of enhancing biomass production with other crops under agroforestry system. Alder plant can fix nitrogen at around 50–155 kg/ha (depending upon the age of the plant). The CSI is 3.00, and the perceived score of 17 indicators out of 31 has reached 3 or above (Table 8.5). Alder-based cultivation practice (Table 8.5) has the potential to increase the yield (mean score 3.31); potential to reduce the area under erosion (mean score 3.28); potential to enhance soil fertility (mean score 3.85); potential to reduce the use of energy in the agriculture sector (mean score 3.11); potential to adopt INM (mean score 3.28); potential to address the issue of food security (mean score 3.37); potential to promote crop diversification (mean score 3.31); potential to increase the resilience of the cropping system to drought (mean score 3.25); potential to reduce the GHG emission (mean score 3.51); and potential to enhance carbon sequestration (mean score 3.05). It has also emerged from the study that practice is suitable for high altitude (mean score 3.20); is suitable for steep slope (mean score 3.11); is suitable for rainfed cultivation (mean score 3.17); is suitable for highrainfall area (mean score 3.14); and is possible to use without much disturbing the soil (mean score 3.05) and crop residue is suitable for fodder (mean score 3.08). Based on the high mean score (>3) against above-mentioned 17 indicators and overall high mean score (>3) (Table 8.5), it can be concluded that the “Alder (Alnus nepalensis)-based cultivation” is a climate-smart practice. Though Alder (Alnus nepalensis)-based cultivation is very common in Nagaland, scientific intervention and standardisation are needed in respect of potentiality of the plant in GHG mitigation, C-sequestration, nitrogen fixation and biomass production.

8.3.2.4 Practice 4 Tissue Culture Sapling for Better Yield Micropropagation or tissue culture is an amalgamation of techniques to maintain or grow plant cells for clones of the plant. Planting materials from tissue culture are more authentic in terms of productivity, quality and disease resistance. In Nagaland cultivation of banana, ginger, turmeric and cardamom is widely practised. Farmers of the state are facing problems in terms of yield loss due to the disease infestation and poor quality of planting materials. Tissue culture is the most suited alternative for providing genuine planting material and assures income. The available literature reveals that tissue culture sapling can enhance the yield up to 30% as compared to the normal sapling. The CSI is 3.23, and the perceived score of 16 indicators out of 31 has reached 3 or above (Table 8.6). Adoption of tissue culture sapling (Table 8.6) has the potential to increase the yield (mean score 4.11); potential to lead the diversification of livelihood of farming community (mean score 3.14); potential to reduce the area under erosion (mean score 3.17); potential to increase water (irrigation) use efficiency (mean score 3.25); potential to reduce the use of energy in the agriculture sector (mean score 3.62);

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Table 8.4 Climate-smart performance of seed dibbling Indicators Overall score The technology/practice (T/P) has the potential to increase yield The T/P has the potential to lead the diversification of livelihood of the farming community The T/P has the potential to reduce the area under erosion The T/P is suitable for high altitude The T/P is suitable for low altitude The T/P is suitable for steep slope The T/P is suitable for rainfed cultivation The T/P is suitable for high-rainfall area The T/P is drought tolerant The T/P is suitable in high temperature The T/P is suitable in low temperature The T/P has the potential to enhance soil fertility The T/P has the potential to increase water (irrigation) use efficiency The T/P has the potential to reduce the withdrawal of underground water for irrigation The T/P has the potential to reduce the use of energy in the agriculture sector The T/P has the potential to adopt IPM for pest control The T/P has the potential to adopt INM T/P has the potential to improve livestock diversification in existing farming systems The T/P has the potential to improve feed production in existing farming systems The T/P has the potential to lead the diversification of livestock production in existing farming systems The T/P has the potential to address the issue of food security The T/P has the potential to increase income The T/P has the potential to promote crop diversification

Findings Mean SD 3.00 0.578 3.05 0.683

Minimum 2.03 2

Maximum 3.90 4

2.74

0.443

2

3

96

3.51

0.507

3

4

123

3.20 2.37 3.68 3.22

0.584 0.490 0.866 8.431

2 2 2 2

4 3 5 5

112 83 129 113

3.00 2.85 3.11 2.20 2.45

0.485 0.493 0.582 0.677 0.505

2 2 2 1 2

4 4 4 3 3

105 100 109 77 86

3.60

0.603

2

5

126

2.85

0.355

2

3

100

3.28

0.572

2

4

115

2.62

0.490

2

3

92

3.00 2.65

0.594 0.591

2 2

4 4

105 93

3.20

0.584

2

4

112

3.14

0.550

2

4

110

2.54

0.610

2

4

89

3.08

0.562

2

4

108

3.40

0.497

3

4

119

Sum 105.22 107

(continued)

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Table 8.4 (continued) Indicators The T/P has the potential to foster local and regional production and supply chains The T/P has the potential to reduce gender inequality The T/P has the potential to increase the resilience of the cropping system to drought The T/P has the potential to reduce the GHG emission The T/P has the potential to enhance carbon sequestration Use of T/P is possible without much disturbance (zero tillage) of soil Crop residue/biomass is suitable for fodder Crop residue not producing GHGs

Findings Mean SD 2.20 0.472

Minimum 1

Maximum 3

Sum 77

3.28

0.572

2

4

115

2.11

0.471

1

3

74

2.74

0.505

2

4

96

4.14

0.733

3

5

145

4.08

0.781

3

5

143

3.02

0.617

2

4

106

2.77

0.598

2

4

97

potential to adopt INM (mean score 3.25); potential to improve feed production in existing farming systems (mean score 3.22); potential to address the issue of food security (mean score 3.97); potential to increase income (mean score 3.88); potential to promote crop diversification (mean score 3.60); potential to foster local and regional production and supply chains (mean score 3.14); potential to increase the resilience of the cropping system to drought (mean score 3.28); potential to reduce the GHG emission (mean score 3.22); and potential to enhance carbon sequestration (mean score 3.14). Based on the high mean score (>3) against above-mentioned 16 indicators and overall high mean score (>3) (Table 8.6), it can be concluded that the adoption/use of “tissue culture sapling” is a climate-smart practice. Nevertheless, government intervention is needed to accelerate the adoption of tissue culture sapling in a farming system to enhance production, productivity and income.

8.4

Stakeholders in CSA and Climate Change Mitigation and Adaptation in NER

Various stakeholders are playing a role in climate change mitigation and adaptation and implementation of CSA in NER. All stakeholders can be subcategorised under the international, national, regional and third sector.

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Table 8.5 Climate-smart performance of Alder-based cultivation Indicators Overall score The technology/practice (T/P) has the potential to increase yield The T/P has the potential to lead the diversification of livelihood of the farming community The T/P has the potential to reduce the area under erosion The T/P is suitable for high altitude The T/P is suitable for low altitude The T/P is suitable for steep slope The T/P is suitable for rainfed cultivation The T/P is suitable for high-rainfall area The T/P is drought tolerant The T/P is suitable in high temperature The T/P is suitable in low temperature The T/P has the potential to enhance soil fertility The T/P has the potential to increase water (irrigation) use efficiency The T/P has the potential to reduce the withdrawal of underground water for irrigation The T/P has the potential to reduce the use of energy in the agriculture sector The T/P has the potential to adopt IPM for pest control The T/P has the potential to adopt INM The T/P has the potential to improve livestock diversification in existing farming systems The T/P has the potential to improve feed production in existing farming systems The T/P has the potential to lead the diversification of livestock production in existing farming systems The T/P has the potential to address the issue of food security The T/P has the potential to increase income The T/P has the potential to promote crop diversification

Findings Mean SD 3.00 0.550 3.31 0.582

Minimum 2.12 3

Maximum 4.09 5

Sum 104.93 116

2.88

0.403

2

4

101

3.28

0.518

3

5

115

3.20 2.71 3.11 3.17

0.478 0.518 0.631 0.452

3 2 2 2

5 4 4 5

109 95 109 111

3.14 2.48 2.91 2.82 3.85

0.733 0.658 0.445 0.513 0.733

2 1 2 2 3

5 4 4 4 5

109 87 102 99 135

2.77

0.645

1

4

97

2.37

0.689

1

4

83

3.11

0.471

2

4

109

2.68

0.471

2

3

94

3.28 2.68

0.458 0.471

3 2

4 3

115 94

2.97

0.568

2

4

104

2.82

0.452

2

4

99

3.37

0.598

3

5

118

2.74

0.443

2

3

96

3.31

0.529

2

4

116 (continued)

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Table 8.5 (continued) Indicators The T/P has the potential to foster local and regional production and supply chains The T/P has the potential to reduce gender inequality The T/P has the potential to increase the resilience of the cropping system to drought The T/P has the potential to reduce the GHG emission The T/P has the potential to enhance carbon sequestration Use of T/P is possible without much disturbance (zero tillage) of soil Crop residue/biomass is suitable for fodder Crop residue not producing GHGs

8.4.1

Findings Mean SD 2.88 0.582

Minimum 2

Maximum 4

2.68

0.471

2

3

94

3.25

0.610

2

5

114

3.51

0.562

3

5

123

3.05

0.725

2

4

107

3.05

0.591

2

4

107

3.08

0.507

2

4

108

2.45

0.560

1

3

86

Sum 101

International Stakeholders

The international contribution is enormous and multidimensional. The Paris Agreement of UNFCCC (2015) is a unique initiative to mitigate and adapt to the impact of climate change. UNDP is also directly implementing some activities with a significant concentration on climate change mitigation and adaptation. GIZ International is supporting different states of the region in policy and strategy formulation to combat climate change. IFAD has recently started the implementation of “Fostering Climate Resilient Upland Farming System in the North East Project” (FOCUS) (IFAD 2017) in the region. Asian Development Bank (ADB) is contributing in Brahmaputra river erosion control and supporting in livelihood improvement of erosion victims. International Potato Research Centre (CIP) has started climate-smart potato cultivation in collaboration with the Government of Assam. International Rice Research Institute (IRRI) has begun work on improved rice cultivation and world fish in the development of fish production in the region.

8.4.2

National, Regional and Third-Sector Stakeholders

At national level, Ministry of Agriculture and Farmers’ Welfare; Ministry of Environment, Forest and Climate Change; Ministry of DoNER; Ministry of Social Justice and Empowerment; and Ministry of Rural Development are playing a prominent role in the implementation of climate-smart approaches as well as mitigation and adaptation of climate change. At the regional level, the State Department of Agriculture and

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Table 8.6 Climate-smart performance of tissue culture sapling Indicators Overall score The technology/practice (T/P) has the potential to increase yield The T/P has the potential to lead the diversification of livelihood of the farming community The T/P has the potential to reduce the area under erosion The T/P is suitable for high altitude The T/P is suitable for low altitude The T/P is suitable for steep slope The T/P is suitable for rainfed cultivation The T/P is suitable for high-rainfall area The T/P is drought tolerant The T/P is suitable in high temperature The T/P is suitable in low temperature The T/P has the potential to enhance soil fertility The T/P has the potential to increase water (irrigation) use efficiency The T/P has the potential to reduce the withdrawal of underground water for irrigation The T/P has the potential to reduce the use of energy in the agriculture sector The T/P has the potential to adopt IPM for pest control The T/P has the potential to adopt INM The T/P has the potential to improve livestock diversification in existing farming systems The T/P has the potential to improve feed production in existing farming systems The T/P has the potential to lead the diversification of livestock production in existing farming systems The T/P has the potential to address the issue of food security The T/P has the potential to increase income The T/P has the potential to promote crop diversification

Findings Mean SD 3.23 0.698 4.11 0.832

Minimum 2.06 3

Maximum 4.48 5

Sum 113.38 144

3.14

0.429

2

4

110

3.17

0.452

2

4

111

3.08 3.54 3.22 3.57

0.612 0.741 0.843 0.698

2 2 2 2

4 5 5 5

108 124 113 125

3.51 3.48 2.85 3.05 2.20

0.658 0.817 0.493 0.723 0.677

2 2 2 2 1

5 5 4 4 3

123 122 100 107 77

3.25

0.700

2

4

114

2.62

0.490

2

4

92

3.62

0.770

2

5

127

2.74

0.657

2

5

96

3.25 2.11

0.780 0.471

2 1

5 3

114 74

3.22

0.942

2

5

113

2.20

0.472

1

3

77

3.97

0.890

3

5

139

3.88

0.676

3

5

136

3.60

0.881

2

5

126 (continued)

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Table 8.6 (continued) Indicators The T/P has the potential to foster local and regional production and supply chains The T/P has the potential to reduce gender inequality The T/P has the potential to increase the resilience of the cropping system to drought The T/P has the potential to reduce the GHG emission The T/P has the potential to enhance carbon sequestration Use of T/P is possible without much disturbance (zero tillage) of soil Crop residue/biomass is suitable for fodder Crop residue not producing GHGs

Findings Mean SD 3.14 0.648

Minimum 2

Maximum 5

2.68

0.471

2

3

94

3.28

0.893

2

5

115

3.22

0.910

2

5

113

3.14

0.943

2

5

110

3.20

0.759

2

5

112

3.85

0.772

3

5

135

4.40

0.553

3

5

154

Sum 110

Farmers’ Welfare; Ministry of Environment, Forest and Climate Change; Ministry of Social Justice and Empowerment; Ministry of Rural Development; and some allied departments of different state governments of the region are implementing climatesmart approaches as well as mitigation and adaptation of climate change. Simultaneously, various agricultural universities, research institutes of ICAR and other organisations, NGOs and KVK are also implementing climate-smart approaches.

8.5

Strategic Intervention for Implementation of CSA

Based on the review work and results of the study, a CSA implementation strategy is proposed in this section. CSA and climate-smart approach are a relatively new dimension of advanced agriculture. Identification, documentation, validation and calibration of existing practices/technologies that are climate smart are needed. Research system should be strengthened to develop more resilient and smart technologies in agriculture. Therefore, strategic intervention should be focussed on the identification of smart technologies from the existing system, research and development of new smart technologies and proper implementation strategy. Proper implementation and success of any implementation activity depend on various aspects and it is not an exception for CSA implementation. Various influential factors associated with CSA and its implementation are considered. The factors are policy, institutional, technical, productivity, resilience and mitigation. Strategic interventions in each respect for implementation of CSA are presented accordingly.

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8.5.1

181

Technical Interventions

Technical interventions for the implementation of CSA and climate-smart practices should be multifaceted and multidimensional. The strategic intervention should be focussed on all the subsectors of the agriculture that are responsible for GHG emission and climate change. Climate-smart approach and CSA edifice on the concept of maximum productivity with minimum resources and at the same time emission of GHGs should be less or minimum and ensure remunerative income for stakeholder or farmers. Therefore, the smart performance of various or all components of agriculture, namely input smart, water smart, energy smart, nutrient smart, market smart, demand smart, and postharvest and processing smart, is a prerequisite. Climate-smart performance of any practice or component can be quantified based on minimum input with maximum outcome or maximum productivity from per unit, adaptability of the practice or component under the stress or difficulty, bounce back, and resilience performance of method under biotic and abiotic stress, and minimum or reduced emission of GHGs from the practice and component. Among all subsectors of agriculture, livestock subsector plays a significant role in the GHG emission and climate change scenario of India. India is the home of the world’s largest livestock population (Government of India, MoAFW 2012). The livestock sector is responsible for climate change through the emission of GHGs by means of enteric emission from ruminant, and emission from manure or composting of animal dropping and exposing the carbon reservoir (the soil surface) through grazing. Therefore, five-prong strategies can be considered, namely less enteric and manure emission, less dependence on animal protein, less reliance on ruminant animal for milk and meat, and less exposure of earth surface through animal grazing. In order to minimise the GHG emissions from ruminants and to accelerate climate smartness of livestock sectors, the following alternatives may be adopted as strategic interventions: • • • • • • • •

Minimise the H2 production in the rumen of the ruminant Increase productivity (meat, milk per animal) per unit Feeding of starch-rich feed to reduce CH4 in the rumen Less feeding of roughage-rich feed to minimise the CH4 emission Proper feeds and feeding management Adequate nutrition management Use rumen modifiers to inhibit methanogens Feeding of ground and pelleted feed to reduce the CH4 emission (Johnson et al. 1996) • Adding external fats to dairy diets to increase milk production and to reduce enteric CH4 production (Ashes et al. 1997; Murphy et al. 1995) • Addition of ionophore to reduce enteric emission • Use of chemicals like bromoethanesulfonate (BES) for direct inhibition of methanogenesis so as to reduce enteric emissions (Mathison et al. 1998)

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Some interventions are also needed to be emphasised to reduce the emission of GHGs from manure and livestock dropping and to accelerate the climate smartness of the livestock sector: • • • • • •

Augmentation of productivity reduces the production of animal dropping. Increase feed-use efficiency to reduce the nutrient content in the animal dropping. Reducing anaerobic fermentation and ensuring aerobic fermentation of manure. Proper covering of manure heap to reduce the emission of GHGs. Biogas production and trapping of CH4 from the animal excreta. Proper collection and use of animal urine.

Emission of GHGs also takes place from rice cultivation and use of nitrogenous fertiliser. We need to propose some interventions to minimise and mitigate the emission from rice cultivation and application of nitrogenous fertiliser to the crop field. The following may be adopted: • Improve the productivity of rice from per unit of area. • Cultivation based on land capability, i.e. more suitable area as well as area not suitable for cultivation of other crops should be allocated for rice cultivation (Patra and Babu 2017). • Mid-season drainage and drying (also to increase water-use efficiency) of waterlogged rice fields are recommended to increase the yield by reducing sulphide toxicity (Stępniewski and Stępniewska 2009); this practice is also a climate change mitigation initiative (Tyagi et al. 2010) that reduces CH4 emissions from waterlogged rice fields (Patra and Babu 2017). • Emphasis on change in food habit from rice to wheat or maize-based food systems which reduce the rice production vis-à-vis GHG emission (Patra and Babu 2017). • Increase “N”-use efficiency to reduce the emission of N2O from rice or another crop field. • Increase the cultivation of leguminous crops. • Root zone placement of nitrogenous fertiliser to reduce the emission. • More emphasis on organic sources of nitrogen.

8.5.2

Institutional Intervention

Implementation of CSA and mitigation of emission of GHGs have remained on institutional arrangement and capacity of concerned institutions (Patra and Babu 2017). Based on the research by Patra and Babu (2017), we are proposing some appropriate institutional interventions for smooth implementation of CSA in the region: • Climate-smart technologies, inventory and database creation • Building capacity and upgrading skills of functionaries

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• Awareness creation among stakeholders and convergence of CSA in all development initiatives • Strengthening of the research system and generation of climate-smart technologies/practices • Strengthening of the extension system • Coordination among different stakeholders • Monitoring, evaluation and surveillance of activities

8.5.3

Policy Intervention

Successful implementation of any programme depends on the policy mechanism adopted for formulation and implementation of the application. Based on the research by Patra and Babu (2017), we are proposing some policy interventions: • • • • • • •

Use of authentic database in the policy process Formulation of policy for the national, regional and micro level of administration Inclusion of CSA in the state action plan of climate change Mass awareness creation The political environment should be taken into consideration in the policy process Sustainability and livelihood should be emphasised in the policy process Emphasis on budgetary strength and resource inventory of the region in the policy process • Emphasis on the involvement of public, private and non-profit sectors in the policy process

8.6

Summary

North-Eastern Region (NER) of India is under the Eastern Himalayan Region and includes eight states, namely Arunachal Pradesh, Assam, Manipur, Meghalaya, Mizoram, Nagaland, Sikkim and Tripura. The NER spans between 22.50
and 29.34
north latitudes and 88.00
and 97.30
east longitudes. The altitude of the region ranges from 45 m to as high as 8586 m (at Sikkim) from mean sea level. The region is strategically very important and borders with another five South Asian countries, namely Bangladesh, Bhutan, China, Myanmar and Nepal. The climate of NER corresponds with topographical variation, mainly humid subtropical with hot, humid summer, severe monsoons and mild winters. But the climatic condition of Arunachal Pradesh and Sikkim is mountain climate with cold, snowy winters and mild summers. The altitudinal differences give rise to different types of weather, ranging from near tropical to temperate and alpine. The Fourth Assessment Report of IPCC (Intergovernmental Panel on Climate Change) highlighted that “the Himalayan Highlands will face some of the highest increases of global warming and consequently impacting the flow of rivers” (IPCC 2007). To address the issues and negative impacts of climate change, different

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initiatives have started as per the requirement. The NEP, the NAPCC and state action plan on climate change are some of the important initiatives. The agriculture and allied sectors are highly vulnerable to climate change as well as responsible for climate change by the emission of GHGs. Further, additional production of 70% of present production from the proportionately decreasing agricultural land with less emission of GHGs is a paramount challenge to the agriculture sector. Concept of CSA is a befitting strategic intervention to meet the food demand with less or no emission of GHGs. Therefore, identification and R&D of climate-smart technologies or practices are prerequisites to accelerating the implementation of CSA. To identify the climatesmart technologies in the existing farming system, an assessment guide was adopted (Patra 2017) based on the CSA Tech Index of World Bank (2016). In the data collection guide, 31 issues were included with the rational weight of 1–5 and a “Climate Smart Index” (CSI) was developed. It has been reported that agriculture is diversified according to the climatic and environmental variation. Agriculture is traditional in nature and shifting (locally known as jhum) cultivation is a major component of the farming system. Adoption of technologies in the agriculture and allied sectors is in the nascent state, which results in low productivity, poor socio-economic status and nutrition, and food insecurity. But the region is very advanced and modernised in respect of tea cultivation. Approximately 80% of the population of the region stays in rural areas and mainly depends on agriculture and allied activities for their livelihood and survival. The economy of the region is primarily based on agriculture. Agriculture in NER includes crops, livestock, forestry, fisheries, apiculture and sericulture. Other relevant livelihood options are forest-based, river-based, and ores- and natural resource-based livelihood activities. In this chapter, four CSA practices, namely “community cultivation”, “dibbling of seed in jhum field”, “Alder (Alnus nepalensis)-based cultivation” and “tissue culture sapling for better yield”, were discussed in detail from the perspective of climate-smart practices.

References Ashes JR, Gulati SK, Scott TW (1997) New approaches to changing milk composition: potential to alter the content and composition of milk fat through nutrition. J Dairy Sci 80:2204–2212 CCAFS (2011) Climate change, agriculture and food security (CCAFS), proposal for research programme 7., CIAT, 2011 Census India (2011) Census data online. www.censusindia.gov.in. Accessed 5 Feb 2019 Food and Agriculture Organization of the United Nations (FAO) (2010) “Climate-smart” agriculture: policies, practices and financing for food security, adaptation and mitigation. Rome Food and Agriculture Organization of the United Nations (FAO) (2013) Climate-smart agriculture sourcebook. Rome Godfray HCJ, Beddington JR, Crute IR, Haddad L, Lawrence D, Muir JF, Pretty J, Robinson S, Thomas SM, Toulmin C (2010) Food security: the challenge of feeding 9 billion people. Science 327(5967):812–818. https://doi.org/10.1126/science.1185383 Goswami DC (2008) Managing the wealth and woes of the river Brahmaputra. J Ishani 2(4) Government of Arunachal Pradesh (2011) Arunachal Pradesh State Action Plan on Climate Change

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Government of Assam (2015) Assam state action plan on climate change (2015–2020). Draft Report. Department of Environment. Govt. of Assam, India Government of India (2006) National environment policy Government of India (2007) Forest survey report 2007: India state of forest report. Forest Survey of India Government of India (2012) National action plan on climate change, prime minister’s council on climate change. Govt. of India Government of India (2015) Basic Statistics of North Eastern Region (2015) Govt. of India, NECS, Shillong, India Government of India, MoAFW (2012) 19th Livestock census district wise report 2012. http://dahd. nic.in/documents/statistics/livestockcensus.NewDelhi Government of Meghalaya (2012) Meghalaya state climate change action plan. Govt. of Meghalaya Government of Mizoram (2012) State action plan on climate change (2012–17). Directorate of Science and Technology, Govt. of Mizoram Govt. of Manipur (2013) Manipur State Action Plan on Climate Change-2013 (MSAPCC-2013). Directorate of Environment, Imphal, Manipur, India. Government of Nagaland (2012) Nagaland state action plan on climate change—achieving a low carbon development trajectory. Govt. of Nagaland, Kohima Government of Sikkim (2011) Sikkim action plan on climate change (2012–2030), draft copy. Govt. of Sikkim, Gangtok Government of Tripura 2011. State action plan on climate change. Department of Science, Technology & Environment Hovius N (1998) Controls on sediment supply by large rivers. In: Shanley KW, McCaabe, PJ (eds) Relative role of eustasy, climate, and tectonism in continental rocks. SEPM Spec. Publ.59 Society for Sedimentary Geology, p 3–16 IFAD (2017) Fostering climate resilient upland farming system in the northeast (FOCUS), Asia and Specific Division programme Management Department, IFAD IGFC (2011) (Indian German Financial Cooperation). “North East Climate Change Adaptation Programme.” project document IPCC (2007) Climate change mitigation. In: Metz B, Davidson OR, Bosch PR, Dave R, Mayer LA (eds) Contribution of working group III to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, UK and New York, NY, XXX p Jenkins W (1978) Policy analysis. Pinter, London Johnson DE, Ward GW, Ramsey JJ (1996) Livestock methane: current emissions and mitigation potential. In: Kornegay ET (ed) Nutrient management of food animals to enhance and protect the environment. Lewis Publishers, New York, pp 219–234 Latrubesse E, Stevaux JC, Sinnha R (2005) Tropical rivers. Geomorphology 70:187–206 Mathison GW, Okine EK, McAllister TA, Dong Y, Galbraith J, Dmytruk OIN (1998) Reducing methane emissions from ruminant animals. J Appl Anim Res 14:1–28 Murphy JJ, Connolly JF, McNeill GP (1995) Effects of milk fat composition and cow performance of feeding concentrates containing full fat rapeseed and maize distillers grains on grass-silage based diets. Livest Prod Sci 44:1–11 Nelson GC et al (2009) Climate change- impact on agriculture and costs of adaptation. Food policy report. IFPRI, Washington, DC Neufeldt H, Jahn M, Campbell B, Beddinton J, DeClerck F, De pito A, Gulledge J, Hellin J, Herrero M, Jarvis A, LeZaks D, Meinke H, Rosenstock T, Scholes M, Scholes R, Vermeulen S, Wollenberg E, Zougmore R (2013) Beyond climate-smart agriculture: toward safe operating spaces for global food system. Agric Food Secur 2(12, 6) Patra NK (2017) Institutional and Policy Process on Climate Change and Formulation of Extension Strategy on Climate Smart Agriculture in Nagaland, India. PI, Department of Agril. Extension, SASRD, NU, Nagaland, India

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Patra NK, Babu SC (2017) Mapping Indian agricultural emissions: lessons for food system transformation and policy support for climate-smart agriculture. IFPRI, Washington, DC Patra NK et al (2015) Strategy for prevention of HIV/AIDS and drug abuse problems by non-government organizations in Nagaland, India. J Rural Dev:215–225. ISSN: 0970-3357 Ravindranath et al (2011) Climate change vulnerability profiles for north East India. Curr Sci 101 (3):384–394 Sharma et al (2009) Agroforestry: its relation with agronomy, challenges and opportunities. Indian J Agron 54(3):249–266 Stępniewski W, Stępniewska Z (2009) Selected oxygen-dependent process-response to soil management and tillage. Soil Tillage Res 102:193–200 Tandon SK, Sinha R (2007) Geology of large rivers. In: Gupta A (ed) Large rivers: geomorphology and management. Wiley, Chichester, pp 7–28 Tyagi L, Kumari B, Singh SN (2010) Water management—a tool for methane mitigation from irrigated paddy fields. Sci Total Environ 408:1085–1090 UNFCCC (United Nations Framework Convention on Climate Change) (2015) Paris Agreement. http://unfccc.int/files/essential_background/convention/application/pdf/english_paris_agree ment.pdf Venkatramanan V, Shah S (2019) Climate smart agriculture technologies for environmental management: the intersection of sustainability, resilience, wellbeing and development. In: Shah S et al (eds) Sustainable green technologies for environmental management. Springer Nature Singapore Pte Ltd., Singapore, pp 29–51. https://doi.org/10.1007/978-981-13-2772-8_2 World Bank (2007) Agriculture and food. www.worldbank.org/en/topic/agriculture/overview World Bank (2016) Climate smart agriculture indicators. World Bank Group report number 105162-GLB

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Sustainable Livestock Management Systems for Indian Rural Livelihood: Mitigation of Climate Change T. Thamil Vanan and D. Divya Lakshmi

Abstract

Livestock sector plays a significant role in food security. The livestock sector accounts for 40% of the world’s agricultural Gross Domestic Product (GDP) and about 1.3 billion people depend upon livestock husbandry for their livelihood. This sector alone contributes nearly 25.6% of value of output at current prices of total value of output in agriculture, fishing and forestry sectors. The total livestock population in India is about 536 million (2019). Nevertheless, the ruminants are an important source of atmospheric methane. In India, ‘49.1% of enteric methane was contributed by cattle, 42.8% by buffaloes, 5.38% by goat and 2.59% by sheep. Importantly, during 1961–2010, the increase in methane emissions (70.6%) from livestock population of India is much greater than the increase in methane emissions from livestock population of world (54.3%). It is reported that by 2050, about 15.7% of enteric CH4 emission at the global level will be contributed by the Livestock population of India’. However, the changing climate has potential impacts on livestock production and productivity. The surface air temperature is the single most important abiotic factor followed by humidity, radiation and wind velocity, which are known to have a great influence and negative impact on livestock productivity. The global average air temperature near the Earth’s surface rose by 0.74  0.18  C (1.33  0.32  F) during the 100 years ending in 2005. The elevated temperature and relative humidity will impose heat stress on all the species of livestock, and will adversely affect their productive and reproductive potential. Also, global climate change increases the vulnerability of livestock to various diseases. In this regard, there is a dire need for sustainable livestock production by factoring in both mitigation and adaptation strategies.

T. Thamil Vanan (*) · D. Divya Lakshmi Department of Livestock Production Management, Madras Veterinary College, Chennai, India # Springer Nature Singapore Pte Ltd. 2020 V. Venkatramanan et al. (eds.), Global Climate Change: Resilient and Smart Agriculture, https://doi.org/10.1007/978-981-32-9856-9_9

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Keywords

Climate change · Livestock management · Pasture management · Enteric methane emission · Mitigation · Adaptation

9.1

Introduction

Livestock sector plays a key role in food security which is an important strategy to alleviate poverty in India. This sector also has a significant economic and cultural influence on many communities throughout the world. The livestock sector accounts for 40% of the world’s agricultural Gross Domestic Product (GDP) and about 1.3 billion people depend upon livestock husbandry for their livelihood (FAO 2006). Over 70 million of small and marginal farmers including landless labourers depend on the livestock sector for alternate income to support their livelihood. This sector alone contributes nearly 25.6% of value of output at current prices of total value of output in agriculture, fishing and forestry sectors. But in the recent past the livestock sector’s productivity is greatly influenced by the environmental factors by several ways. The 19th Livestock Census reveals that the total livestock population consisting of Cattle, Buffalo, Sheep, Goat, pig, Horses and Ponies, Mules, Donkeys, Camels, Mithun and Yak in the country are 512.05 million numbers in 2012 and the same has decreased by about 3.33% over the previous census. But Livestock population has increased substantially in Gujarat (15.36%), Uttar Pradesh (14.01%), Assam (10.77%), Punjab (9.57%), Bihar (8.56%), Sikkim (7.96%), Meghalaya (7.41%) and Chhattisgarh (4.34%) which might be due to the influence of climate. The environmental temperature is the single most important abiotic factor followed by humidity, radiation and wind velocity, which are known to have a great influence and negative impact on livestock productivity. The global average air temperature near the Earth’s surface rose by 0.74  0.18  C (1.33  0.32  F) during the 100 years ending in 2005(IPCC 2007). Under this climate change scenario, ‘the elevated temperature and relative humidity will impose heat stress on all the species of livestock, and will adversely affect their productive and reproductive potential’ (Sejian et al. 2018), and increase the vulnerability to various diseases. Furthermore, the climate changes affect directly and indirectly supplies of feed and fodder and water resources to livestock. However, the global climate change scenario is a silent threat to not only sustainable animal agriculture but also other fauna and flora of the world.

9.2

Impacts of Climate Change on Livestock

Climate can affect animal husbandry in all regions both directly and indirectly. Climatic factors such as air temperature, humidity and wind speed directly influence the animal production and performance of economic traits. Indirectly the weather

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condition or climate change could affect the feed resources significantly which influence livestock productivity, the carrying capacity of available pasture land and the sustainability of agro-ecosystem. Climate change will affect livestock production significantly through their effects on feed production (availability and price of feed), feed quality and composition, pest and disease dynamics, and animal health and production. Impact of climate change will pose an additional burden on dairy farmers who operate on small profit margins. Countries which are in the tropical and sub-tropical regions are the major sufferers of global warming. However, the normal body temperature of livestock should be maintained under different climatic conditions. A slight deviation in body temperature has a great impact on animal production and activation of heat dissipation mechanism and thus diverting energy from production to maintenance. For example, the comfortable range of ambient temperature for better performance varies from 15 to 25  C for crossbred cattle and from 15 to 28  C for indigenous cattle (Upadhyay et al. 2009). Climate change, in particular global warming, likely affects animal health by influencing the host–pathogen–environment system both directly and indirectly. The direct effects are those associated with vector transmission, water or flood, soil, rodents, or air temperature and humidity (Abdela et al. 2016). The infectious diseases in animals and their transmission cycles represent complex interactions between hosts, pathogens and the environment and mainly occur following changes in the host–pathogen–environment system (Jones et al. 2009). Most of these diseases are zoonotic, that is, may be transmitted to humans, and can have serious consequences for public health, the economy of the livestock sector and biodiversity conservation. Indirect effects of climate change are more complex to disentangle and include those deriving from changes in land use and biodiversity and the attempt of animals to adapt to these climatic and environmental changes or from the influence of climate on microbial populations, distribution of vector-borne diseases and host resistance to infectious agents, feed and water scarcity, or food-borne diseases. In particular, prolonged droughts determine water and pasture shortages, which decrease livestock immunity against infectious diseases, as well as trigger livestock movements to areas at higher risk of animal diseases, determining the congregation of domestic animals around few available watering points and grazing areas in proximity to wildlife reserves. Here the risk of disease transmission is increased by the increased contact among domestic animals and between domestic and wild animals. Grazing areas resulting from deforestation and changes in land use may expose livestock to novel pathogens due to increased interface between livestock and wildlife (Lubroth 2012). These direct and indirect effects of climate change may be spatial, that is, affecting the geographical distribution of the pathogen, host or vector, or temporal, that is, affecting the timing of an outbreak and its intensity. However, not all organisms will respond similarly to climate change. In general, disease agents with external stages (e.g. non-host) of their life cycles, such as parasites, food, water and vector-borne diseases, are most influenced by climatic and environmental changes. For instance, temperature increases feeding intervals and development rates of blood-feeding arthropods, while rainfall increases

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the availability of habitat for breeding sites. In general, global warming and changes in rainfall patterns and intensity are expected to expand the geographical and altitudinal distribution of vectors, allowing them to cross mountain ranges that currently limit their distribution. Furthermore, climate change can also influence livestock health through the survival of pathogens in the environment. A pathogen may emerge in new territories and host landscapes become more aggressive, and perform a host species jump, possibly in relation to increased host species mixing or contacts (Lubroth 2012). Vector-borne diseases that are strongly associated with vector amplification due to climate variability include Rift Valley fever (RVF), West Nile Virus (WNV), Bluetongue (BTV) and Trypanosomosis. For instance, RVF in East Africa is strongly associated with extreme events, such as heavy rains and floods, caused by the El Nino Southern Oscillation events, which are expected to occur more frequently in future as an effect of global climate change. West Nile Virus (WNV), Bluetongue (BTV) and Trypanosomosis appear to be strongly influenced by rise in temperature (Paz 2015). Soil-borne diseases, such as Anthrax, are also affected by precipitation variability. Livestock and wildlife likely get infected with Anthrax while grazing and ingesting forage or soil contaminated with Anthrax spores, browsing on vegetation contaminated by carrion flies, or by percutaneous exposure from biting flies, and possibly spore inhalation. Anthrax outbreaks mainly occur after heavy rains and floods followed by a dry period or with the onset of rains ending a period of drought. These climatic conditions favour the concentration of spores in the upper level of the soil, increasing the risk of spore ingestion by herbivores. For instance, prolonged droughts can increase the risk of occurrence of foot and mouth disease, haemorrhagic fevers and tuberculosis (Abdela et al. 2016).

9.3

Livestock as Source of GHG

The ‘agriculture, forestry and other land use (AFOLU) sector release 10–12 Gt CO2e per annum. Greenhouse gases emissions from agricultural activity include land use changes; enteric methane emission from ruminants; lowland rice cultivation; N2O emissions from nitrogenous fertilizer use; and crop residue burning’ (Lipper et al. 2014; Smith et al. 2014; Venkatramanan and Shah 2019; Valli 2020). Nevertheless, the sources for ‘increases in CH4 concentration includes natural wetlands emissions (177–284 Tg CH4 year–1), agriculture and waste (187–224 Tg CH4 year–1), fossil fuel related emissions (85–105 Tg CH4 year–1), other natural emissions (61–200 Tg CH4 year–1), and biomass and biofuel burning (32–39 Tg CH4 year–1)’ (Venkatramanan and Shah 2019; Valli 2020). As regards the livestock production, methane is an important greenhouse gas. In effect, the ruminants are an important source of methane emission. In India, ‘49.1% of enteric methane was contributed by cattle, 42.8% by buffaloes, 5.38% by goat and 2.59% by sheep. Importantly, during 1961–2010, the increase in methane emissions (70.6%) from livestock population of India is much greater than the increase in methane emissions from livestock population of world (54.3%). It is reported that by 2050, about 15.7% of enteric CH4

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emission at the global level will be contributed by the Livestock population of India’ (Patra 2014; Valli 2020).

9.4

Mitigation and Adaptation Strategies

The mitigation and adaptation strategies are grouped into management strategies, feeding strategies, rumen manipulation and advanced strategies (Valli 2020). ‘Management strategies • Reducing ruminant livestock population • Breeding management • Manure management Feeding strategies • • • •

Pasture improvement Feed processing Increasing concentrates in ration Protein supplementation

Rumen manipulation • • • • •

Use of bacteriocins Use of ionophores Use of Fats/oils Use of prebiotics and probiotics Halogenated methane analogues

Advanced strategies • • • •

Precision Feeding Vaccines that target methanogens Genetic transformation of rumen bacteria Transferring rumen microbiome of low methane emitting ruminants’ (Valli 2020)

9.4.1

Livestock Rearing

Grazing can be optimized by finding the right balance among the different users of the land and adapting grazing practices accordingly. Optimal grazing leads to improved grassland productivity and delivers adaptation and mitigation benefits. However, the net influence of optimal grazing is variable and highly dependent on

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baseline grazing practices, plant species, soils and climatic conditions (Smith and Olesen 2010). One of the main strategies for increasing the efficiency of grazing management is through rotational grazing, in which the frequency and timing of grazing is adjusted to match the livestock’s needs with the availability of pasture resources. Through targeted temporal grazing exclusions, rotational grazing allows for the maintenance of forages at a relatively earlier growth stage. This enhances the quality and digestibility of the forage, improves productivity of the system and reduces methane emissions per unit of live weight gain. Rotational grazing is more suited to manage pasture systems, where the investment costs for fencing and watering points, additional labour and management that is more intensive are more likely to be recouped. In colder climates, where animals are housed during cold periods, there are also opportunities for controlling the timing of grazing to avoid grassland degradation and adapt the grazing to the timing of vegetation growth to optimize intake. Furthermore, increasing livestock mobility, a traditional strategy of nomadic and transhumant herders for matching animal production needs with changing rangeland resources, can significantly enhance the resilience of these livestock systems to climate change (drought in particular). The most clear-cut mitigation benefits perhaps arise from soil carbon sequestration that results when grazing pressure is reduced as a means of stopping land degradation or rehabilitating degraded lands. In these cases, enteric emission intensities can also be lowered because with less grazing pressure animals have a wider choice of forage, and tend to select more nutritious forage, which is associated with more rapid rates of live weight gain. By restoring degraded grassland, these measures can also enhance soil health and water retention, which increases the resilience of the grazing system to climate variability. However, if grazing pressure is reduced by simply reducing the number of animals, then total output (e.g. milk and meat) per hectare may be lower, except in areas where baseline stocking rates are excessively high.

9.4.2

Farming System Approach

Agricultural and livestock adaptation options are multiple and diverse and this presents challenges for the livestock production systems. A number of approaches to providing farmers with the knowledge and means to adapt and innovate have emerged. These operate against a backdrop of transition in the livestock production systems, with a shift away from pushing the adoption of technological solutions towards enabling adaptation through scientific research, remodelling and application. This has been in response to a growing recognition that challenges such as adapting to more sustainable and resilient systems require new approaches to engaging farmers. There has been an implication of mixed farming systems to mitigate climate change. Various mixed crop–livestock systems exist due to the diversity of culture, environment, plants, animals and microbes, economic activities and the rich history of agricultural production. In terms of the interactions between

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livestock production and other components and eco-regions of farming systems, especially between plant and livestock, five types of mixed crop–livestock systems have been identified in farming systems based on rangeland; farming systems based on grain crops; farming systems based on crop/pasture rotations; agrosilvopastoral systems; and farming systems based on ponds. Mixed farming based on grain crops is practised in the plains both in temperate and subtropical regions, where crop production is possible owing to favourable conditions of water. It is one of the most dominant regions for maize, wheat, cotton and soybean production in the world because of the high yields of maize, cotton and wheat and the third highest yield of soybean. Interaction between crop production and livestock production occurs mainly through the following ways: 1. Crop residues and grain are fed to livestock throughout the year. 2. Livestock supply manure and drought power for some crop production in the extensive systems of the developing regions, although there is an increasing level of mechanization in intensive crop production systems. 3. Livestock graze fallow cropland, stubble cropland and sparse rangeland. 4. The incorporation of small grain crops into grazing systems can overcome the feed gap of early spring and winter which commonly occurs in this type of farming system, and also provides the opportunity to exchange nutrient elements between different components of the farming system. Climatic factors play an important role in the productivity and distribution of crops and livestock. If the climate becomes warmer and drier, which has been identified as the main trend of global climate change in most areas of Asia, livestock with high adaptation to drought, such as goat, donkey, camel, deer, will extend their distributive areas, while other livestock with high susceptibility to climate change (such as horse, cattle, buffalo, sheep) will have their area of distribution reduced. If the climate becomes warmer and wetter, the changes in distribution of both the above types of livestock will be reversed. Global climate change will potentially affect the quality of animal products. Global climate change not only results in transforming the distribution, productivity and interaction of crop, rangeland and livestock but also affects the whole farming production system. Global warming with increased rainfall will raise the productivity of all types of farming systems, including both plant and animal production. All types of integrated farming systems can be characterized as part of a successional framework responding to the interactions among biotic factors (crops, livestock, etc.), abiotic (environmental) factors (precipitation, heat, etc.) and social factors. Global climate change is another factor exerting selection pressure on the succession of farming systems. If the climate becomes warmer, management of forage crops and of the interactions between herbivore and forage will determine the stable level of the integrated farming systems. However, increased frequency of dry and hot periods associated with global warming could be disastrous for farming

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systems. Global climate change is a slow and gradual process at a large timescale, so livestock and crops could adapt themselves slowly and simultaneously. However, global climate change will also induce a natural selection on the new breeds of livestock and new cultivars of crops; the influence of this is little known. It is generally recognized that both varieties of crops and breeds of livestock with high stress tolerance have more stable and higher productivity under global climate change; this provides more options to improving farm management. A number of studies have looked at the effects of climate change on forage and animal species, and on their potential to enhance adaptation both by traditional and genetic improvement. Furthermore, forage and livestock breeding can also contribute to climate change mitigation through reducing emissions of greenhouse gases (GHG) and raising carbon (C) sequestration in both grassland and livestock production. Asia has one of the most abundant germplasm resources of forage and domestic animals in the world, which can serve as the basis of new breeds. Improvements of forage and animal breeds will decrease GHG emissions and resource use per unit of animal product. High sugar ryegrass leads to a 7.5–21.0% increase in milk yield and a 7.1–25.7% decrease in excrement nitrogen (N). Re-seeding native grass species with those with higher productivity or C allocation to deeper roots, or introducing legumes into grazing lands, can all promote soil C in rangeland soils and reduce N emissions. In the face of global climate change, an adaptive farming system supplies opportunities, not only for new crop varieties and livestock breeds to manifest more sustainable productivity but also for more innovative management practices to be implemented. Integrated crop–livestock farming systems possess higher productivity and stability under conditions of global climate change through the coupling of plant production and animal production, promoting efficient use of biotic and abiotic resources, prolonging the economic chain and strengthening the interaction of all components. The inevitable evolution of agricultural systems towards enhanced productivity due to structural optimization or better application of existing breeds and technologies is generally associated with the integration of crop production and livestock production. However, with the largest and fastest growing population in the world, the increased demand in this region for animal products must be associated with decreasing emissions per unit of product, and by controlling the increase in emissions through establishing and improving mixed farming systems.

9.5

Climate-Smart Livestock Production Systems

Efficiency in the use of natural resources is measured by the ratio between the use of natural resources as input to the production activities and the output from production (e.g. kg of phosphorus used per unit of meat produced, or hectares of land mobilized per unit of milk produced). The concept can be extended to the amount of emissions generated by unit of output (e.g. greenhouse gas emissions per unit of eggs). Examples of opportunities that fall within this strategy are higher yields per hectare, higher water productivity, higher feed efficiency, improved management of manure

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and fertilizers and reduced losses along the food chain. Efficiency gains in the uses of resources can be achieved through improvements in management, technology, animal health, livestock breeds and feed crop varieties. Improving the feed-to-food conversion efficiency in animal production systems is a fundamental strategy for improving the environmental sustainability of the sector. A large volume of food is wasted even before it reaches the consumer. Along the animal food chain, reduction of waste can substantially contribute to lowering the demand for resources, such as land, water, energy, as well as other inputs, such as nutrients. The current prices of inputs (e.g. land, water and feed) used in livestock production often do not reflect true scarcities. Consequently, input costs do not provide disincentives for the overutilization of resources by the sector nor incentives to address inefficiencies in production processes. Any future policies to protect the environment will have to introduce adequate market pricing for natural resources. Ensuring effective management rules and liability, under private or communal ownership of the resources, is a further necessary policy element for improving the use of resources.

9.5.1

Risk Management in Production Systems

Traditionally, livestock producers have been able to adapt to various environmental and climatic changes. However, expanding populations, urbanization, economic growth, increased consumption of animal-based foods and greater commercialization have made traditional coping mechanisms less effective (Sidahmed et al. 2008). As a result, the identification of coping and risk management strategies has become very important. Livestock can produce edible food for people from a range of inedible vegetal products. They can also move to find feed resources and endure a certain level of food and water stress. As a consequence, livestock production and marketing can help stabilize food supplies and provide individuals and communities with a buffer against economic shocks and natural disasters. Particularly in pastoral and agropastoral systems, livestock are key assets held by poor people and fulfil multiple economic, social and risk management functions. Livestock are also a crucial coping mechanism in variable environments. In addition, keeping more than one species of livestock is a risk-minimizing strategy and provides farmers with a wider range of adaptive options against climate unpredictability than if only one species is kept: • An outbreak of disease may affect only one of the species, for example, the cattle, and specific species or animals of specific breeds are better able to survive droughts and thus help carry a family over such difficult periods. • Advantage can also be taken of the different reproductive rates of different species to rebuild livestock holdings after a drought. For example, the greater fecundity of sheep and goats permits their numbers to multiply quicker than cattle

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or camels. The small ruminants can then be exchanged or sold to obtain large ruminants. • Different animal species exploit different feed resources. In pastoral areas, camels can graze up to 50 km away from watering points, whereas cattle are limited to a grazing orbit of on average 10–15 km. Camels and goats tend to browse more, that is, to eat the leaves of shrubs and trees; sheep and cattle generally prefer grasses and herbs. Their differently shaped mouths allow them to graze different sources. • Different animal species supply different products. For example, cattle can provide milk, transport and draught power, whereas goats and sheep tend to be slaughtered more often for meat. Chickens often meet the immediate needs of household, sheep and goats are sold to cover medium expenditures, while larger cattle are sold to meet major expenditures. However, there are still problems to be addressed concerning the uncertainty of climate projections and projected impacts and how this uncertainty can be appropriately treated when determining response options (Wilby et al. 2009).

9.5.2

Barriers for Adopting Climate-Smart Livestock Production Systems

Overcoming these barriers requires specific policy interventions, including strengthening extension work and financing mechanisms, such as schemes for improving access to credit. Multi-sectoral and interdisciplinary collaboration and coordination in particular is required to mitigate the impact of animal diseases under changing climatic conditions. Policies for the adaptation of animal health systems should be implemented to strengthen animal disease surveillance programmes and risk analysis at the national level. This is needed to anticipate how climate change will facilitate the emergence of threats and alter the spread and distribution of animal diseases through ecosystems. Improved coordination should be fostered across all relevant ministries and organizations, including those dealing with environment, natural resources, wildlife and agriculture. There is still a lack of assessments of livestock production under climate constraints to support policies that aim at improving resilience in the sector (IPCC 2014). In particular, modelling and quantifying aggregated impacts on livestock production systems still need to overcome a number of challenges (Thornton et al. 2009). Firstly, more regional climate scenarios are becoming available, but they are still associated with significant uncertainties, which limit researchers’ capacity to model livestock productivity under climate change. Second, animal diseases are affected by climate change, but future patterns of distribution need to be modelled to understand their impact on scenarios and projections. Third, the impact on groundwater availability is also an area where more assessments are needed, in particular in grazing systems. Finally, research efforts are also required to identify additional combinations of adaptation and mitigation practices that are appropriate for specific

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production systems and environments (e.g. combined interventions addressing the management of feed, genetic resources and manure). The potential aggregated effects that multiple changes occurring within farming systems may have on food security and the use of natural resources at the regional level also need to be better understood.

9.6

Conclusion

Indian livestock are grazed on very poor quality tropical pastures or fed on crop residues having a very low nutritive value. Hence the productivity of animals is far below their genetic potential. Improving per-animal productivity is a potent tool in reducing enteric methane emission per unit of product produced (Valli 2020). Beyond doubt, livestock sector plays a significant role in the economy of developing and developed countries. Further, it plays a significant role in the nutritional security. However, livestock production is considered as the single most important source for atmospheric methane emissions. It must be recorded that the total livestock population in India is about 536 million as per the latest census. It has been further reported that in India, ‘49.1% of enteric methane was contributed by cattle, 42.8% by buffaloes, 5.38% by goat and 2.59% by sheep. Importantly, during 1961–2010, the increase in methane emissions (70.6%) from livestock population of India is much greater than the increase in methane emissions from livestock population of world (54.3%)’. Though the livestock are a source of GHG, livestock production per se is influenced by changing climate. The elevated temperature and relative humidity will impose heat stress on all the species of livestock, and will adversely affect their productive and reproductive potential. From this perspective, this chapter discussed the different mitigation and adaptation strategies including the farming system approach and climate-smart livestock production.

References Abdela N, Jilo K, Adem A (2016) Insufficient veterinary service as a major constraints in pastoral area of Ethiopia: a review. J Biol Agric Healthcare 6(9):94–101 FAO (2006) Livestock’s long shadow: environmental issues and options. FAO, Rome IPCC (2007) In: Parry ML, Canziani OF, Palutikof JP, van der Linden PJ, Hanson CE (eds) Climate change 2007: impacts, adaptation and vulnerability. Contribution of working group II to the fourth assessment report of the IPCC. Cambridge University Press, Cambridge, 976 pp IPCC (2014) In: Field CB, Barros VR, Dokken DJ, Mach KJ, Mastrandrea MD, Bilir TE, Chatterjee M, Ebi KL, Estrada YO, Genova RC, Girma B, Kissel ES, Levy AN, MacCracken S, Mastrandrea PR, White LL (eds) Climate change 2014: impacts, adaptation, and vulnerability. Part A: global and sectoral aspects. Contribution of working group II to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, 1132 p Jones PG, Thornton PK, Heinke J (2009) Generating characteristic daily weather data using downscaled climate model data from the IPCC’s fourth assessment

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Lipper L, Thornton P, Campbell B et al (2014) Climate-smart agriculture for food security. Nat Clim Chang 4:1068–1072. https://doi.org/10.1038/nclimate2437 Lubroth J (2012) Climate change and animal health. In: Building resilience for adaptation to climate change in the agriculture sector, vol 23, p 63 Patra AK (2014) Trends and projected estimates of GHG emissions from Indian livestock in comparison with GHG emissions from world and developing countries. Asian Aust J Anim Sci 27(4):592–599 Paz S (2015) Climate change impacts on West Nile virus transmission in a global context. Philos Trans R Soc B Biol Sci 370(1665):20130561 Sejian V, Bhatta R, Gaughan JB, Dunshea FR, Lacetera N (2018) Adaptation of animals to heat stress. Animal 12:1–14 Sidahmed AE, Nefzaoui A, El Mourid M (2008) Livestock and climate change: coping and risk management strategies for a sustainable future. In: Rowlinson P, Steele M, Nefzaoui A (eds) Proceedings livestock and global climate change international conference, 17–20 May 2008, Hammamet, Tunisia, pp 27–28 Smith P, Olesen J (2010) Synergies between the mitigation of, and adaptation to, climate change in agriculture. J Agric Sci 148:543–552. https://doi.org/10.1017/s0021859610000341 Smith P, Bustamante M, Ahammad H et al (2014) Agriculture, forestry and other land use (AFOLU). In: Edenhofer O, Pichs-Madruga R, Sokona Y, Farahani E, Kadner S, Seyboth K, Adler A, Baum I, Brunner S, Eickemeier P, Kriemann B, Savolainen J, Schlömer S, von Stechow C, Zwickel T, Minx JC (eds) Climate change 2014: mitigation of climate change. Contribution of working group III to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge Thornton PK, van de Steeg J, Notenbaert A, Herrero M (2009) The impacts of climate change on livestock and livestock systems in developing countries: a review of what we know and what we need to know. Agric Syst 101(3):113–127 Upadhyay RC, Ashutosh, Raina VS, Singh SV (2009) Impact of climate change on reproductive functions of cattle and buffaloes. In: Aggarwal PK (ed) Global climate change and Indian agriculture. ICAR, New Delhi, pp 107–110 Valli C (2020) Mitigating enteric methane emission from livestock through farmer-friendly practices. In: Global climate change and environmental policy, pp 257–273. https://doi.org/ 10.1007/978-981-13-9570-3_8 Venkatramanan V, Shah S (2019) Climate smart agriculture technologies for environmental management: the intersection of sustainability, resilience, wellbeing and development. In: Shah S et al (eds) Sustainable green technologies for environmental management. Springer Nature Singapore Pte Ltd., Singapore, pp 29–51. https://doi.org/10.1007/978-981-13-2772-8_2 Wilby RL, Troni J, Biot Y, Tedd L, Hewitson BC, Smith DM, Sutton RT (2009) A review of climate risk information for adaptation and development planning. Int J Climatol 29 (9):1193–1215

Precision Farming: A Step Towards Sustainable, Climate-Smart Agriculture

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Trisha Roy and Justin George K

Abstract

Climate change is one of the biggest challenges of our times, and we are steadily marching towards a climate catastrophe. Among the various sectors which is fuelling the climate change through emission of greenhouse gases (GHGs), the contribution of agricultural sector is 24%. Unscientific farm management practices like imprudent fertilizer and pesticide application, livestock management practices, land use changes etc. are the driving forces which have led to increased GHG emissions from agriculture. Thus, strategies to reduce the emission and its subsequent impact on the changing climate is the need of the hour, as agriculture besides being a contributor is also one of the most vulnerable sectors affected by climate change. Precision farming or precision agriculture (PA) is one such instrument which is effective in making agriculture more ‘climate smart’ by reducing its impact on the environment. This technique of farming employs right management practices at the right place and time by capturing the heterogeneity of the land at a minute scale. Thus, PA is a technology intensive system, which requires the assistance of Global Positioning System; different sensors for monitoring soil moisture, nutrients etc. and geo-referenced maps for different soil properties but when adopted at a large scale would help to improve the productivity, increase the saving of resources and reduce the environmental impact. PA is the modern-day climate-smart agriculture strategy, which could answer the problem of food insufficiency in developing countries and emerge as a powerful tool, as well as solution to the innumerable challenges faced by the agriculture sector.

T. Roy (*) ICAR-Indian Institute of Soil and Water Conservation, Dehradun, India J. George K Indian Institute of Remote Sensing, ISRO, Dehradun, India # Springer Nature Singapore Pte Ltd. 2020 V. Venkatramanan et al. (eds.), Global Climate Change: Resilient and Smart Agriculture, https://doi.org/10.1007/978-981-32-9856-9_10

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Keywords

Precision agriculture · Climate-smart agriculture · Variable rate technology · Sensors · Climate-smart technology

10.1

Introduction

Climate change is the biggest challenge faced by the globe in the twenty-first century and the biggest threat to various species and natural resources inhabiting the planet (Tercek 2018). A shift in the climatic parameters from the average atmospheric conditions is referred to as climate change. Generally, an average of 30 years data is considered for the climatic parameters (Kim 2008). The changes in climatic parameters are brought about either by natural forces like orbital motion of earth around the sun, volcanic activities, movement in the Earth’s crust or by several anthropogenic activities leading to increased emission of various greenhouse gases (GHGs) and aerosols. The Intergovernmental Panel on Climate Change (IPCC) in their fifth Assessment Report (IPCC-AR5 2014) reflects that during the last decade 2000–2010, the GHG emission rates have been twice than observed in any other decade since 1970. The present concentration of atmospheric CO2 has reached 408.9 ppm. This exerts huge pressure on the ratified countries to the Paris agreement on Climate Change to develop immediate strategies to curb emissions in order to achieve the global goal of restricting the Earth’s surface temperature between 1.5 and 2
C above the pre-industrial era by the end of this century (Victor et al. 2014). The global CO2 concentration has increased by 24% in present times since the first Earth day celebrated in 1970 (Climate Central 2017), which has increased the global surface temperature by 1
C, and if GHG emission is allowed in the business as usual scenario, the mean global temperature is likely to rise by 4.2
C (IEA 2011). Thus, strategies and policies to reduce the impact of global warming and working towards mitigation of climate change are being worked out at every level. However, in order to generate mitigation strategies to reduce the impact of climate change, the knowledge regarding sectoral contribution to GHGs is very essential, as it will help to create more efficient strategies and prioritize the focus on more immediate sectors where mitigation is an easier option. Of all the sectors contributing towards GHGs, the total contribution from agriculture sector is 24% (IPCC, AR5) (Fig. 10.1).

Fig. 10.1 Contribution of different sectors across globe towards GHG emission (IPCC 2014)

Electricity and Heat 9.6 25

6.4

Agriculture, Forestry, Land Use Transport

21

Industry 24

Buildings

14 Other Energy

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The agriculture sector not only contributes to climate change but is also affected by the extremities of climate and is susceptible to the phenomenon of climate change (EEA 2015). Thus, devising strategies to reduce the impact of climate change on one hand and reduce the vulnerability of the sector to the vagaries of extreme weather conditions on the other hand is the need of the hour. One of the major instruments which would help to achieve the dual purpose of reducing the climate change impact, as well as strengthen the agricultural system is the ‘precision agriculture’ or ‘precision farming’ (IFC 2017). Precision farming is based on the ‘four pillars with 4 Rs, i.e. doing the right thing in the right fashion at the right place and right time’ (IFC 2017). Precision farming aims at increasing the productivity with concurrent lowering of cultivation costs and reducing environmental impact of agriculture at the same time (National Research Council 1997; SKY-Farm 1999). This approach tries to capture the heterogeneity and variability in the farm at minute levels in order to tailor-make the management practices specific to the need of the area. Thus, it is more of a point approach of management of crops and inputs with assemblage of various technologies (Shibusawa 2001). This point approach of management helps to cut down on various agricultural inputs including water, nutrients, pesticides and animal rations. The optimum use of inputs in the true sense helps to reduce the emission of GHGs, improve soil health and plant nutrition, save precious inputs and thus, help to reduce the impact of agriculture on climate change. This chapter explains how precision farming can be adopted at every farm level with the help of various technical inputs to combat the phenomenon of climate change.

10.2

Precision Farming

Agriculture practice in general does not account for the on-farm variability and follow a traditional approach of equality with respect to application of majority of agricultural inputs like water, fertilizers, manures, pesticides, herbicides, soil amendments, growth hormones etc. This practice results in over or under application of inputs in many cases which have adverse impact on the environment, as well as economics of the farmers. Precision farming or precision agriculture tries to nullify the impacts of universal agriculture practices by considering the spatial and temporal heterogeneity in different growth parameters at the farm level. This consideration of variability optimizes the use of several inputs and helps to maximize the benefit/cost ratio on a long-term basis (Mandal and Maity 2013). ‘Precision farming’ can be defined as ‘managing variability at the sub-field level to best utilize resources and minimize environmental impacts’ (Mackay 2012). It involves the adoption of technologies for better managing the on-farm variability (Aziz et al. 2008), which helps to design Site Specific Crop Management (SSCM) practices. The SSCM refers to developing agricultural management systems that promote variable management practices within a field according to site or soil conditions (National Research Council 1997). The SSCM is an amalgamation of technologies which involves the following steps:

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• Collection of data at appropriate place and time • Data interpretation to take appropriate management decisions • Execution of the decisions at proper place and time All these steps in conjunction would determine the success of any precision farming system (Batte and Van Buren 1999). Though the process of precision farming is enlisted in three steps, it involves many specific and sophisticated technologies for its implementation at the field level. Thus, precision farming is something more than ‘Site Specific Farming’ and can be referred to as ‘Site Specific Farming Plus’ (Zhang 2015).

10.3

Components of Precision Farming

The major focus in precision farming is to account for the heterogeneity and on-farm variability existing in the natural system and act accordingly, so as to increase the productivity and reduce the environmental risks (Tran and Nguyen 2006). Therefore, the components involved in precision farming are mainly related to capturing the on-farm variability for better management. The boom in information technology during the 1980s has enabled the accounting of this variability through adoption of several technologies and tools. The modern precision farming system is an amalgamation of several techniques enlisted below. (a) (b) (c) (d) (e) (f)

Global positioning system Sensor technologies Geographic information system Variable rate technologies Grain yield monitors for mapping Crop management

These are essential tools or infrastructure which is needed for the establishment of precision farming in large areas. Though the initial cost of establishment might seem high, the positive impact on yield, savings on input, and better economics along with the intangible benefits of precision farming on the environment is much higher. All agriculture practitioners try to incorporate the idea of right amount of input at the right place and right time. The various components or tools used in precision agriculture also do the same things. The basic steps in precision agriculture thus involves precision soil preparation, precision seeding, precision crop management, precision harvesting and data analysis and evaluation to get precise results (Fig. 10.2).

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Data analysis and evaluation

Precision Soil Preparation

Precision Harvesting Precision Agriculture

Precision Crop Management

Precision Seeding

Fig. 10.2 The approach towards precision agriculture

10.3.1 Variable Rate Technologies Variable rate technology (VRT) is the process of controlling the amount of inputs such as fertilizers, seeds, irrigation water, pesticides, and other amendments according to the situation of the field or crop, unlike the uniform rate technology (URT) which follows uniform application of all inputs without considering the variability or heterogeneity of the system and surroundings. The major drawback of the URT is the over or under application of inputs, which decreases the yield, increases the cost and has negative impact on the environment (Bolotova 2006). These problems are taken care of with VRT which allows site specific management of the inputs at field level. Application of VRT at field level in turn is dependent on other tools or components of precision agriculture like the sensorbased monitoring of inputs, GPS-based maps and remote sensing data. Besides this, machineries capable of variable rate application of inputs (like sprayers, seed drills, etc.) are essential for successful employment of VRT. For VRT to be operational at field level, it can use either remote-sensing-based mapping technology or sensorbased detection units to understand the variability in the field. When remote sensing images or maps are used for VRT, the following steps are followed:

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(a) Status map of the entire area for different input elements to be used in agriculture is prepared (b) The maps/images prepared are interpreted thoroughly for capturing the variability (c) Delineation of the total area into management zones and rates of various inputs for each zone has to be worked out (d) Machinery or variable rate applicators for different inputs are to be deployed in the fields for application of different inputs

10.3.2 Sensor Technologies for Precision Agriculture Crookston (2006) highlighted precision agriculture as one of the top ten revolutions in the field of agriculture. However, due to intensive data usage and unavailability of cheap and rapid sensor technologies to detect the on-farm variability, precision agriculture still remains an unexplored area for many farmers particularly in the developing nations of South Asia and Africa. To obtain real-time data for monitoring and delivery of inputs, the sensors play a very important role. The sensors can be used to detect a wide array of soil properties like mechanical, chemical and physical properties (Adamchuk et al. 2004). The sensors developed for measurement of different soil properties can adopt different principles or detection mechanisms as listed below. 1. 2. 3. 4. 5. 6.

Electrical or electromagnetic sensors Optical or radiometric sensors Mechanical sensors Acoustic sensors Pneumatic sensors Electrochemical sensors

Standard soil testing procedure requires collection of representative soil samples from agricultural lands for deciding the quantity of inputs. This approach generally includes determination of routine parameters like available N, P, K, exchangeable cations, available micronutrients, pH, electrical conductivity (EC), soil organic C (SOC) etc. and is laborious and time consuming. On the contrary, the sensor-based approach tries to capture the location-specific values of different soil parameters which are processed further for decision-making on quantity of inputs in different locations. The use of sensors helps to reduce the time and labour for detection of different soil properties and allows more repetitive and accurate data acquisition. Different sensors use different principles for data acquisition and give information regarding wide array of soil properties. However, no single sensor is useful for getting information regarding all soil properties. Thus, many times, multiple sensorbased platforms are used to acquire data from a single point and derive information about different soil properties at the same time. The multiple sensor system provides us with more accurate, exhaustive and extended information about different soil

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Table 10.1 Multi-sensor devices for measuring different soil properties Soil property measured • Soil pH, apparent EC • Soil nitrate, soluble Na, K, soil pH • Soil mechanical resistance, optical reflectance, capacitance • Soil water, mechanical strength, electrical conductivity

Reference Lund et al. (2005) and Jonjak et al. (2010) Adamchuk et al. (2005) Adamchuk and Christenson (2005) Sun et al. (2008)

properties and hastens the decision-making process. Also, use of multiple sensors reduces the time of data acquisition, and more data are available within a short span of time. Multi-sensors have been developed by various researchers to measure more than one soil property at a time (Table 10.1).

10.3.2.1 Detection of Different Soil Properties Using Sensors Measurement of Soil Moisture Soil moisture is one of the most important parameter, which needs much focus for precision agriculture. Irrigation water management through soil moisture sensors gives immense opportunity to save water at field level and ensures optimal utilization of this precious resource. Detection of soil moisture at field level using moisture sensors can be broadly classified into contact and non-contact methods. Contact Methods

The contact method mostly employs determination of electrical conductivity, dielectric constant or thermal conductivity of soil, which gives an indirect measurement of the soil moisture content. The determination of electrical conductivity or resistivity measures the concentration and movement of ions rather than water itself, and the water content inversely affects the resistivity of the moisture sensors. Gypsum blocks or Nylon blocks used for detection of soil moisture through electrical resistivity measurement show reduced resistivity due to increased soil moisture content. A calibration curve is established between the resistivity and soil moisture content, and soil moisture is determined using the calibration curve. Since dielectric constant of water is the highest, many sensors employ detection of dielectric constant for measuring soil water. But the major flaw for such detection is that the dielectric constant of any medium not only depends on the soil moisture but also on the density, texture, temperature and gives inaccurate results for detection of soil moisture (Hellebrand and Umeda 2004). Most of the contact method-based sensors for soil moisture determination are not very much desirable for real-time monitoring and data acquisition of soil moisture in the field (Whalley 1991).

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Non-Contact Methods

Among the several non-contact methods used for detection of soil moisture, nuclear magnetic resonance (NMR) spectroscopy, visible and infrared spectroscopy (IR) and soil radar with IR spectroscopy are widely used. The NMR technique measures the concentration of proton in the soil system and gives direct measurement of moisture in the soil profile. The visible and infrared reflectance system generally interprets soil colour and soil temperature for determination of the soil moisture content. These indirect measurements lead to inaccurate detection of soil moisture. Combination of radar (3–10 cm wavelength) and IR reflectance can be a good device for measuring on-the-go soil moisture status of any field. Also, microwave sensors can be used for detection of soil moisture at field level. Mouazen et al. (2005) developed a visible and near-infrared spectrophotometer to determine the soil moisture content for site-specific irrigation. The sensor operated in the wavelength range of 306.5–1710.9 nm and was mounted on the rear-side of a subsoil chiseller to determine the soil moisture content. The data generated were used to prepare a map with a grid size of 10 m  10 m, which gives the spatial distribution of moisture in a particular field. This map is further interpreted to determine the amount of irrigation required in particular location. The authors observed good correlation with the oven-dried gravimetric soil moisture content and the data generated from the fibre-based VISNIR spectrophotometer. Soil moisture determination under precision agriculture can also be done using artificial neural network (ANN) along with spatial data obtained from unmanned aerial vehicle (UAV) for surface soil up to 10 cm depth (Esfahani et al. 2015). The UAV equipped with different types of sensors like visual, infrared, near infrared and thermal cameras are used for this purpose. The visual and infrared camera acquires data at 0.15 m resolution, while the thermal camera acquires data at 60 cm interval. Unlike the ground-based sensors like time domain reflectometry or frequency domain reflectometry, the remote sensing approach gives opportunity to obtain data for a large area which can be successfully employed for water management in precision agriculture. However, use of data mining algorithms like the ANN which uses highly correlated indices with soil moisture content like the Normalized Difference Vegetative Index (NDVI), the IR heating rate, and thermal images, etc. (Gillies and Carlson 1995) necessitates that ANN needs to be trained properly to reduce the errors and improve the output (Elshorbagy and Parasuraman 2008). Soil moisture sensor-based variable rate irrigation system (VRI) which is a part of the variable rate technology (VRT) used in precision agriculture also holds potential for moisture management at temporal and spatial scales. The placement of sensors is the most important criteria for optimal functioning of the VRI. Generally, for this purpose, the entire area is divided into management zones based on available water content and spatial distribution pattern of soil moisture over different time frame remaining same. This is referred to as temporal stability (Vachaud et al. 1985), which forms the basis for placement of the soil moisture sensors. The VRI using sensors helps in optimal use of water resources and maximizes productivity.

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Measurement of Soil Nutrients Achieving the goal of increased food production for the burgeoning population, as well as striking a balance between increased productivity while nullifying economic loses and environmental impacts, calls for enhanced management of the essential nutrient elements (Goulding et al. 2008). However, routine soil testing procedures often fails to address the optimal utilization of nutrients as majority of the recommendations follows the uniform application rate of fertilizers, thus overlooking the spatial heterogeneity of the land. This often leads to either overuse or under-use of the fertilizer resources, which has far-reaching consequences ranging from crop productivity to soil health and environmental quality. Adoption of advanced technologies in nutrient monitoring plays a decisive role in balancing the dual goals of optimizing production and economics along with maintenance of the environmental quality (Bah et al. 2012). The different technologies like the remote sensing and GIS, VRT, sensor-based nutrient monitoring all help to envisage and capture the temporal and spatial variability in the soil nutrient content, and thereby optimize resource utilization and productivity while enhancing the environmental quality. The variability in the soil nutrients can occur at varied scales starting from a field, an area, and region-wise and may even occur within few centimetres at the plot scale. Synchronization of the soil supplying capacity with the crop needs is a challenge in itself and necessitates the use of both temporal and spatial data at the same time to understand the variability and supply nutrients accordingly. The best possible way to detect the nutrients in the soil would be to have a complete analysis of the concentration of nutrients in the soil solution, which is directly related to the plant available nutrients. This can be accomplished through the nutrient sensors connected with GPS devices, which generate a map of the area concerned and divides it into different management zones. Such delineation helps in real-time monitoring and intervention of nutrients and allows more judicious use of fertilizer resources. Generally, the different sensors employ two major principles for nutrient detection in situ: (a) the diffusion controlled measurement of elements through ion-selective electrodes and solid-state electrochemical electrodes and (b) the chemical reaction controlled measurement (Hellebrand and Umeda 2004). Techniques like geo-statistics, neural network, regression trees and fuzzy-logic all help to understand and analyse the soil nutrient distribution and help in implementation of precision agriculture (Zhang et al. 2007; Liu et al. 2006; Park and Vlek 2002). Ion Selective Electrodes for Nutrient Measurement

The ion-selective electrodes work on the principle of measuring the difference in electrochemical potential of any particular ion in the soil solution to which it is sensitive with respect to a fixed concentration of the same ion in the electrode (Birrell and Hummel 2000). The electrochemical potential is a function of the ionic activity in the soil solution and is dependent on the concentration of ions, other ionic species in the soil solution, dilution of soil solution etc. Various ion-selective electrodes for soil pH, nitrate, potassium, phosphate, calcium and magnesium have been developed by several researchers, which can be applied for site-specific nutrient management

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under precision agriculture (Nielson and Hansen 1976; Artigas et al. 2001; Kim et al. 2006; Xiao et al. 1995). On-the-go soil nutrient sensors have been designed for nitrate detection by Adsett et al. (1999), where the ion-selective electrode was mounted on tractor for monitoring of the field. Laboratory results indicated that lab detected nitrate concentration was in 95% agreement with the results from the ion selective electrode. Several researchers have developed different sensors to monitor soil pH for precision agriculture. Soil pH, often referred to as the master soil property, is a very essential part of soil nutrient management and helps to guide the availability of all essential nutrients. The quantification of amendments for amelioration of problem soils like the acid, alkali soils, etc. also depends on soil pH. Rossel and Walter (2004) used 0.01 M CaCl2 buffer to determine the lime requirement of soil in the 17 ha field, and the pH was measured using an ion-sensitive field effect transistor (ISFET). However, the co-efficient of determination was not high (r2 ¼ 0.49). Adamchuk et al. (1999) developed a device for real-time monitoring of soil pH capable of sampling at a depth between 0 and 20 cm and output available every 8 s. Good correlation was observed between field data and laboratory estimates of soil pH (r ¼ 0.83), and this technology has been adopted commercially by Veris Technology, Kansas, USA, for developing a soil pH mapping system (Christy et al. 2004). Comparison between grid survey (1 ha grid, one sample every 100 m) and on-thego sensor with electrode for measuring soil pH revealed higher mapping accuracy with the latter (Lund et al. 2004). The use of on-the-go sensor improved the root mean square error of lime prescription to 1354 kg ha1 compared to 2506 kg ha1 obtained from the 1 ha grid survey. This kind of technology definitely helps in resource optimization and for properties like soil pH, which shows variation as high as 2 units within distance as low as 12 m (Bianchini and Mallarino 2002) grid survey or uniform rate application results in faulty farm management practices. Besides the detection of routine soil properties using ion-selective electrodes, techniques like the Donnan membrane technique (DMT) based on the principle of Donnan membrane equilibrium has been used for in situ measurement of trace elements in the paddy field (Pan et al. 2015). The DMT was capable of measuring the free metal concentration for trace elements like Ni, Pb, Cu, Zn and Cr. This can be explored for detection of heavy metals in contaminated soils for controlling soil pollution and effective remediation. Use of Reflectance Spectroscopy for Nutrient Management

In situ measurement of soil properties using visible-near infrared spectrophotometers (400–2500 nm) has been done by several researchers for assessing the variability in soil properties and precision input management (Kim et al. 2009). Presently, the global demand for accurate, inexpensive and reproducible soil data for the purpose of environmental monitoring, land use planning, various modelling and site-specific precision farming has increased manifolds. Reflectance spectroscopy analysis of soil is rapid, less expensive and non-destructive, which not only allows to derive large volume of information quickly but is also sometimes more accurate than the conventional soil analysis (Rossel et al. 2006). This tool for precision nutrient

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management and detection of other soil properties is very effective for catering to the global demand for soil data. The very first successful evidences of reflectance spectroscopy for detecting soil organic matter was done using a light emitting diode at 660 nm. The results were accurate for individual soil catena but were affected by variation in soil moisture content (Shonk et al. 1991). Rossel et al. (2006) used visible (VIS) (400–700 nm), near infrared (NIR) (700–2500 nm) and middle infrared (MIR) (2500–25,000 nm) individually and in combination to detect an array of soil properties. The combined use of VIS-NIR-MIR improved predictions of soil properties like sand, silt and clay content, while for properties like organic C, cation exchange capacity, lime requirement, pH, electrical conductivity, P, etc., the MIR region was more efficient. For exchangeable Al and K content, the NIR region was more accurate. NIR spectroscopy was found to be an effective tool for the prediction of soil pH, N and organic matter (OM) but was not very efficient for prediction of soil P and K. The spatial variability maps for soil pH, N and organic matter in combination with the geographic information system (GIS) serve as an effective tool for precision nutrient management (He et al. 2007). Though VIS-NIR spectroscopy is effective in reflecting the soil variability, often, it concentrates more on the soil surface neglecting the vertical distribution of nutrients which have an overall impact on the plant nutrition, more so with respect to C and N (Donovan 2012). The depth-wise mapping of nutrient from 0 to 20 cm or even deeper have been done by several researchers, and better calibration was obtained for the integrated results for the entire depth in comparison to individual soil layers (Baharom et al. 2015; Yang et al. 2011; Rossel et al. 2010). One important factor for the use of VIS-NIR spectroscopy for soil property determination is the selection of the wavelength for each parameter. For total N in soil, the VIS range was found to be more efficient, while for total C the VIS-NIR region was effective (Yang et al. 2011). However, the use of any kind of spectra and prediction of soil properties using different techniques like partial least square regression (PLSR), principal component analysis (PCA), boost regression trees (BRT), etc. needs to be validated before use in the real field situation for decision-making.

10.3.3 Application of GIS, GPS and Remote Sensing for Precision Agriculture The geographic information system (GIS) and the Global Positioning System (GPS) together form the two most important components of the precision agriculture system. Without the involvement of these two components, the real-time data acquisition becomes a futile exercise. The current GPS in use worldwide is the one developed by the United States Department of Defence, which has almost 24 satellites navigating the Earth at any time frame. The Navigation Satellite Timing and Range Global Positioning System, or NAVSTAR GPS is capable of giving the geographic coordinates of an object or location in three dimensions with its latitude, longitude and elevation.

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The GPS helps in gathering different spatial information about the land as geographic encoded data and determination of exact position on a continuous basis (Neményi et al. 2003). The information and data acquired through GPS is stored in the geographic information system (GIS), which helps to visualize and analyse the spatial data in a computer system and helps to create digital maps of the field or land area for designing different management practices. The GIS helps in gathering a huge amount of information, which is essential for making various precision agriculture decisions at farm level. Information related to weather forecast and monitoring; analysing yield trends; visualizing the land parameters like drainage, slope, depth, topography and status of soil nutrients; moisture and other physico-chemical properties related to crop growth and yield can be monitored and visualized in a GIS platform, which enables the farmers and managers to make precise management decisions for increasing the profitability and reduce the risk of crop losses. To facilitate farmers to adopt precision agriculture (PA), different government agencies like United States Department of Agriculture (USDA) and the European Union (EU) have websites dedicated to provide valuable information to the farmers to understand their land and soil in a better way for efficient decisionmaking (Yousefi and Razdari 2015). Remote sensing (RS) involves acquiring data about different objects without coming in physical contact with the object. This technique is one of the most essential components of precision agriculture as it helps to acquire large volume of data about soil properties, land features and plant/vegetation parameters, which can act as basic information for precision agriculture (PA). The use of RS for soil studies dates back to 1930s when black and white aerial photographs were used for preparing base maps for carrying out soil survey (Baumgardner et al. 1986). Following this with the development of different multi-spectral sensors, soil scientists began using RS data for studying a wide array of soil properties (Kristof 1971). Application of RS for PA has been generally done for investigation of various soil properties like soil texture (sand, silt and clay percentage), organic matter content, soil pH, N, P, K, EC, soil moisture, cation exchange capacity, etc. (Yufeng et al. 2011). Different wavelength and spectral region are involved in the process of RS and identification of different objects and soil characteristics on ground. Also, it involves different data analytical techniques like partial least square regression (PLSR), principal component analysis (PCA), principal component regression (PCR), multiple regression analysis (MLR), etc. for interpreting and analysing the RS data. The first ever instance of RS application in PA was by Bhatti et al. (1991) who predicted the spatial pattern of soil organic matter using Landsat imagery. These data were later used for estimating soil P and grain yield of wheat by Mulla (1997). Images of IKONOS satellite launched by USA have been successfully used to identify N deficiencies in crops like sugarbeet, performance efficacy of fungicide in wheat and determination of faulty artificial drainage pattern in wheat (Seelan et al. 2003). One of the important criteria for satellite RS to be useful for PA is its spatial resolution and the frequency of revisit of the satellite (Mulla 2013). Remote sensing

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Table 10.2 Different RS satellites suitable for precision agriculture Name of satellite Rapid Eye (Germany, 2008) Geo Eye (USA, 2008) World View 2 (2009) IKONOS (USA, 1999) Quick Bird (USA, 2001) a

Spectral bands and spatial resolution Ra, Ga, Ba, NIRa, red edge region (2.5 m)b R, G, B, NIR (40–60 cm)b R, G, B, NIR, Purple band (450–480 nm) (50 cm)b R, G, B, NIR (4 m)b R, G, B, NIR (0.6–2.4 m)b

Revisit frequency 1 day