Food and Livelihood Securities in Changing Climate of the Himalaya 3031228162, 9783031228162

Table of contents :
Preface
Contents
List of Figures
List of Tables
1 Introduction
1.1 The Context
1.2 Definition of Problem
1.3 An Overview
1.4 Hypothesis and Objectives
1.4.1 Hypothesis
1.4.2 Objectives
1.5 Methodological Approach
1.5.1 Data Collection
1.6 The Study Area
1.7 Significance of the Study
1.8 Structure of the Book
References
2 Biophysical and Socio-economic Characteristics
2.1 Background
2.2 Physical Characteristics
2.2.1 Location and Extent
2.2.2 Topography
2.2.3 Slope
2.2.4 Drainage Pattern
2.2.5 Geology
2.2.6 Soils
2.2.7 Climate
2.2.8 Natural Vegetation
2.3 Cultural Characteristics
2.3.1 History
2.3.2 Demographic Characteristics
2.4 Infrastructure Facilities
2.4.1 Education
2.4.2 Health
2.4.3 Transport and Communication
2.4.4 Banking Facilities
2.4.5 Trade Flows
2.4.6 Hydropower Projects
2.5 Land-Use/Cover Analysis
References
3 Climate Variability and Farmers’ Perception
3.1 Introduction
3.2 Materials and Methods
3.2.1 IMD Data
3.2.2 Questionnaire Survey
3.3 Results and Discussion
3.3.1 Assessment of Climate Variability
3.3.2 Farmers’ Perceptions and Adaptive Capacity
3.3.3 Policy Initiatives to Raise Adaptive Capacity
3.4 Conclusion
References
4 Spatio-temporal Change Delineation and Forecasting of Snow/Ice-Covered Areas
4.1 Introduction
4.2 Materials and Methods
4.2.1 Data Source
4.2.2 Methods
4.3 Results and Discussion
4.3.1 Snow Cover Index (S3)
4.3.2 Normalized Difference Snow Thermal Index (NDSTI)
4.3.3 Perennial Snow Index
4.3.4 Time Series Analysis
4.3.5 Error Matrix
4.4 Conclusion
References
5 Agriculture System and Agrobiodiversity
5.1 Introduction
5.2 Agriculture Scenario of Sikkim
5.3 Agroecosystems of Sikkim
5.4 Analysis of Agrobiodiversity
5.4.1 Crop Diversity in Sikkim
5.5 Analysis of Cropping Patterns
5.5.1 Food Crops
5.5.2 Non-food Crops
5.6 Cropping Pattern in Sampled Households
5.6.1 Changes in Cropping Pattern
5.6.2 Farming Systems and Practices
5.6.3 Functions of Farming Practices
5.6.4 Agricultural Inputs
5.6.5 Reason Behind the Changing Pattern in the Yield
5.7 Crop Diversification
5.7.1 The Pattern of Crop Diversification
5.8 Conclusion
References
6 Analysis of Food Availability
6.1 Introduction
6.2 Methods
6.2.1 Gross Food Availability
6.2.2 Net Food Availability
6.2.3 Carrying Capacity of Land
6.3 Results and Discussion
6.3.1 Pattern of Consumption
6.4 Conclusion
References
7 Analysis of Livelihood Security
7.1 Introduction
7.2 Methodology
7.2.1 Logistic Regression Model
7.2.2 Multinomial Logistic Regression
7.3 Results and Discussion
7.3.1 Agricultural Diversities for Livelihood
7.3.2 Range of Livelihood Options
7.3.3 Factors Affecting the Livelihood Options
7.3.4 Econometric Analysis of Factors Affecting the Livelihood Options
7.4 Conclusion
References
8 Conservation of Agriculture for Sustainable Livelihood
8.1 Introduction
8.2 SWOT Analysis for Conservation Agriculture
8.3 Adoption of Conservation Agriculture
8.3.1 Minimum Mechanical Soil Disturbance
8.3.2 Permanent Soil Cover with Crop Residues and Live Mulches
8.3.3 Diversified Crop Rotation and Intercropping
8.3.4 Organic Farming
8.3.5 Soil Conservation
8.3.6 Integrated Pest Control and Management (IPCM)
8.4 Adoption of Conservation of Water
8.4.1 Low-Cost Micro-rainwater Harvesting Technology
8.4.2 Rooftop Rainwater Harvesting
8.4.3 Efficient Irrigation Method
8.5 Capacity Building Program
References
Summary
Bibliography

Citation preview

Human-Environment Interactions 9

Suresh Chand Rai

Food and Livelihood Securities in Changing Climate of the Himalaya

Human-Environment Interactions Volume 9

Series Editor Emilio F. Moran, Michigan State University, Bloomington, IN, USA

The Human-Environment Interactions series invites contributions addressing the role of human interactions in the earth system. It welcomes titles on sustainability, climate change and societal impacts, global environmental change, tropical deforestation, reciprocal interactions of population-environment-consumption, large-scale monitoring of changes in vegetation, reconstructions of human interactions at local and regional scales, ecosystem processes, ecosystem services, land use and land cover change, sustainability science, environmental policy, among others. The series publishes authored and edited volumes, as well as textbooks. It is intended for environmentalists, anthropologists, historical, cultural and political ecologists, political geographers, and land change scientists. Human-environment interaction provides a framework that brings together scholarship sharing both disciplinary depth and interdisciplinary scope to examine past, present, and future social and environmental change in different parts of the world. The topic is very relevant since human activities (e.g. the burn of fossil fuels, fishing, agricultural activities, among others) are so pervasive that they are capable of altering the earth system in ways that could change the viability of the very processes upon which human and non-human species depend.

Suresh Chand Rai

Food and Livelihood Securities in Changing Climate of the Himalaya

Suresh Chand Rai Department of Geography Delhi School of Economics University of Delhi Delhi, India

ISSN 2214-2339 ISSN 2452-1744 (electronic) Human-Environment Interactions ISBN 978-3-031-22816-2 ISBN 978-3-031-22817-9 (eBook) https://doi.org/10.1007/978-3-031-22817-9 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 This work is subject to copyright. All rights are solely and exclusively licensed 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 Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

Preface

Climate variability/change is apparent from the observations of an upsurge in extreme weather events, average global temperature, melting of ice and snow, coastal flooding, and storm surge. It is a worldwide problem, and the Himalaya is subjected to it, due to its exceptional geophysical and hydro-climatic conditions. Climate change is expected to alter the existing vulnerability profile of the Himalaya. The Eastern Himalayan region of India is harboring the largest number of endemic and endangered species and is one of the significant biodiversity “hotspots” of the Indian subcontinent. Livelihood in the villages of the Himalayan region mainly depends on subsistence farming. “These farming systems have developed over the centuries as a comparative advantage to other livelihood options in the mountain areas.” Therefore, in the Sikkim Himalaya, upland farming is a traditional integrated land-use system comprising forest, agriculture, horticulture, agroforestry, bee farming, sericulture, poultry farming, and animal husbandry which will not only add to agricultural production but also improve the quality of food. Since there have been a lot of spatiotemporal variations in agriculture, there is a necessity for in-depth research in this direction. Therefore, the Sikkim Himalaya has been selected for the present study due to its heterogeneous geographical locations. This study is constructed on both primary and secondary databases. The secondary information was attained from published and unpublished records of the government and semi-government organizations and NGOs. The primary data was collected from the household surveys along an altitudinal gradient. The data have been processed and analyzed using appropriate statistical techniques and presented in tabular, diagrammatic, and map forms using GIS software. The whole study has been organized into eight chapters. Chapter 1 describes the context, statement of the problem, review of literature, objectives, hypothesis, methods of data collection and significance of the study, etc. Chapter 2 deals with the biophysical and socio-economic characteristics of the area. Chapter 3 deals with climate variability and farmers’ perception. Chapter 4 is about spatio-temporal change delineation and forecasting of snow/ice-covered areas. Agricultural systems and agrobiodiversity have been described in Chap. 5. Chapter 6 is about the analysis of food availability. Chapter 7 describes an analysis

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of livelihood security. Conservation of agricultural and sustainable livelihood has been discussed in Chap. 8. Based on the critical analysis of the facts and figures in the previous chapters, a summary and suggestions were given in the last. I express my sincere thanks to the Director, G. B. Pant National Institute of Himalayan Environment and Sustainable Development (An Autonomous Institute under the Ministry of Environment, Forest and Climate Change, Government of India) who has generously sanctioned this major project for me. I am thankful to Dr. R. C. Sundriyal, and Dr. G. C. S. Negi, the Scientists In-charge, of the ERP Project for their continuous support during the project period. I also express my thanks to the Head, Department of Geography, Delhi School of Economics, University of Delhi for providing facilities. Special thanks are due to Dr. Prabuddh Kumar Mishra, Assistant professor, Department of Geography, Shivaji College, University of Delhi for his continuous help and support. The entire fieldwork and collection of primary and secondary data have been done by project fellows, especially Miss Nikita Roy Mukherjee and Mr. Aman Rai. I place on record my thanks and appreciation for their painstaking study villages where they stayed for a considerable period and collected primary and secondary data. I am also thankful for my Ph.D. Scholars Dr. Pawan Kumar and Mr. Aakash Upadhyay for their continuous support to finish this task. A special thanks to all the farmers who supported us during fieldwork. Delhi, India

Prof. Suresh Chand Rai

Contents

1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 The Context . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Definition of Problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3 An Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.4 Hypothesis and Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.4.1 Hypothesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.4.2 Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.5 Methodological Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.5.1 Data Collection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.6 The Study Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.7 Significance of the Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.8 Structure of the Book . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1 1 4 6 9 9 9 9 10 11 11 12 12

2 Biophysical and Socio-economic Characteristics . . . . . . . . . . . . . . . . . . . 2.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Physical Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.1 Location and Extent . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.2 Topography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.3 Slope . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.4 Drainage Pattern . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.5 Geology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.6 Soils . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.7 Climate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.8 Natural Vegetation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Cultural Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.1 History . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.2 Demographic Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4 Infrastructure Facilities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4.1 Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4.2 Health . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

17 17 18 18 19 21 21 21 25 27 29 30 30 31 36 36 38

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2.4.3 Transport and Communication . . . . . . . . . . . . . . . . . . . . . . . . . 2.4.4 Banking Facilities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4.5 Trade Flows . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4.6 Hydropower Projects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5 Land-Use/Cover Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

38 39 39 40 40 42

3 Climate Variability and Farmers’ Perception . . . . . . . . . . . . . . . . . . . . . 3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Materials and Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.1 IMD Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.2 Questionnaire Survey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3.1 Assessment of Climate Variability . . . . . . . . . . . . . . . . . . . . . . 3.3.2 Farmers’ Perceptions and Adaptive Capacity . . . . . . . . . . . . . 3.3.3 Policy Initiatives to Raise Adaptive Capacity . . . . . . . . . . . . . 3.4 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

43 43 44 44 45 45 45 49 56 58 58

4 Spatio-temporal Change Delineation and Forecasting of Snow/Ice-Covered Areas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Materials and Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.1 Data Source . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.2 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3.1 Snow Cover Index (S3) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3.2 Normalized Difference Snow Thermal Index (NDSTI) . . . . 4.3.3 Perennial Snow Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3.4 Time Series Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3.5 Error Matrix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

61 61 62 62 63 66 66 69 69 72 73 74 76

5 Agriculture System and Agrobiodiversity . . . . . . . . . . . . . . . . . . . . . . . . . 79 5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 5.2 Agriculture Scenario of Sikkim . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 5.3 Agroecosystems of Sikkim . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 5.4 Analysis of Agrobiodiversity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 5.4.1 Crop Diversity in Sikkim . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 5.5 Analysis of Cropping Patterns . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 5.5.1 Food Crops . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 5.5.2 Non-food Crops . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92 5.6 Cropping Pattern in Sampled Households . . . . . . . . . . . . . . . . . . . . . . 106 5.6.1 Changes in Cropping Pattern . . . . . . . . . . . . . . . . . . . . . . . . . . 107 5.6.2 Farming Systems and Practices . . . . . . . . . . . . . . . . . . . . . . . . 108

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5.6.3 Functions of Farming Practices . . . . . . . . . . . . . . . . . . . . . . . . 5.6.4 Agricultural Inputs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.6.5 Reason Behind the Changing Pattern in the Yield . . . . . . . . . 5.7 Crop Diversification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.7.1 The Pattern of Crop Diversification . . . . . . . . . . . . . . . . . . . . . 5.8 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

108 109 110 110 111 114 115

6 Analysis of Food Availability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2.1 Gross Food Availability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2.2 Net Food Availability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2.3 Carrying Capacity of Land . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3.1 Pattern of Consumption . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.4 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

117 117 118 119 119 119 120 120 123 124

7 Analysis of Livelihood Security . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2.1 Logistic Regression Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2.2 Multinomial Logistic Regression . . . . . . . . . . . . . . . . . . . . . . . 7.3 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.3.1 Agricultural Diversities for Livelihood . . . . . . . . . . . . . . . . . . 7.3.2 Range of Livelihood Options . . . . . . . . . . . . . . . . . . . . . . . . . . 7.3.3 Factors Affecting the Livelihood Options . . . . . . . . . . . . . . . . 7.3.4 Econometric Analysis of Factors Affecting the Livelihood Options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.4 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

125 125 126 128 129 130 130 133 137

8 Conservation of Agriculture for Sustainable Livelihood . . . . . . . . . . . . 8.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.2 SWOT Analysis for Conservation Agriculture . . . . . . . . . . . . . . . . . . 8.3 Adoption of Conservation Agriculture . . . . . . . . . . . . . . . . . . . . . . . . . 8.3.1 Minimum Mechanical Soil Disturbance . . . . . . . . . . . . . . . . . 8.3.2 Permanent Soil Cover with Crop Residues and Live Mulches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.3.3 Diversified Crop Rotation and Intercropping . . . . . . . . . . . . . 8.3.4 Organic Farming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.3.5 Soil Conservation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.3.6 Integrated Pest Control and Management (IPCM) . . . . . . . . .

145 145 147 148 149

137 142 143

151 152 152 154 159

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8.4 Adoption of Conservation of Water . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.4.1 Low-Cost Micro-rainwater Harvesting Technology . . . . . . . 8.4.2 Rooftop Rainwater Harvesting . . . . . . . . . . . . . . . . . . . . . . . . . 8.4.3 Efficient Irrigation Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.5 Capacity Building Program . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

160 161 162 163 164 165

Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167 Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175

List of Figures

Fig. 1.1 Fig. 2.1 Fig. 2.2 Fig. 2.3 Fig. 2.4 Fig. 2.5 Fig. 2.6 Fig. 2.7 Fig. 2.8 Fig. 2.9 Fig. 3.1 Fig. 3.2

Fig. 3.3 Fig. 3.4 Fig. 4.1 Fig. 4.2 Fig. 4.3 Fig. 4.4

Four dimensions of food security (after Gunaratne et al. 2021) . . . Location map of Sikkim Himalaya . . . . . . . . . . . . . . . . . . . . . . . . . Elevation map of Sikkim Himalaya . . . . . . . . . . . . . . . . . . . . . . . . . Slope map of Sikkim Himalaya . . . . . . . . . . . . . . . . . . . . . . . . . . . . Aspect map of Sikkim Himalaya . . . . . . . . . . . . . . . . . . . . . . . . . . . Drainage network and order of two watersheds of Teesta basin in Sikkim Himalaya . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Geological map of Sikkim Himalaya . . . . . . . . . . . . . . . . . . . . . . . . Lineaments map of Sikkim Himalaya . . . . . . . . . . . . . . . . . . . . . . . Soil map of Sikkim Himalaya . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Land-use/cover map of Sikkim . . . . . . . . . . . . . . . . . . . . . . . . . . . . Agro-ecological zone map of Sikkim . . . . . . . . . . . . . . . . . . . . . . . Average annual maximum, average annual minimum, and average annual temperature recorded at Gangtok from 1985 to 2016 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mean monthly precipitation data of Gangtok from 1985 to 2017 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Average yearly precipitation data from 1985 to 2017 . . . . . . . . . . . Flow diagram showing the methodological approach . . . . . . . . . . . The change in the extracted snow area applying the S3 index in 2008 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The change in the extracted snow area applying the S3 index in 2018 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . a The identification of water bodies through NDSTI surrounding the snow-covered areas showing a grayscale image of NDSTI. b The identification of water bodies through NDSTI surrounding snowy areas in Sikkim surrounding the snow-covered areas reclassified image for the year 2018 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

5 19 20 22 23 24 25 26 27 41 46

48 49 49 64 67 68

70

xi

xii

Fig. 4.5

Fig. 4.6

Fig. 4.7 Fig. 8.1

List of Figures

a The grayscale extracted PSI image of the 2017. b The Perennial Snow Index (PSI) reclassified image of the year 2017 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The general trend line based on the acquired areal extent values of snow cover extracted from the S3 index from 1998 to 2018 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The observed and forecasting trend line of snow cover extent from the year 1998 to 2030 . . . . . . . . . . . . . . . . . . . . . . . . . . SWOT analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

71

73 73 148

List of Tables

Table 2.1 Table 2.2 Table 2.3 Table 2.4 Table 2.5 Table 2.6 Table 2.7 Table 2.8 Table 2.9 Table 2.10 Table 2.11 Table 2.12 Table 2.13 Table 3.1

Table 3.2 Table 3.3 Table 3.4 Table 3.5 Table 3.6 Table 4.1 Table 4.2 Table 4.3 Table 4.4 Table 5.1

Dominant soil groups prevalent over the physiographic units in Sikkim Himalaya . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Macro-ecological features of Sikkim Himalaya . . . . . . . . . . . . . Population density of Sikkim Himalaya, 2011 . . . . . . . . . . . . . . Sex ratio in Sikkim Himalaya, 2011 . . . . . . . . . . . . . . . . . . . . . . Literacy rates (%) of Sikkim Himalaya, 1981–2011 . . . . . . . . . Religious (%) aspect of Sikkim Himalaya . . . . . . . . . . . . . . . . . Percent contribution of different sectors to Sikkim’s GDP . . . . Sectoral real growth rate of gross state domestic product in Sikkim (%) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Occupational structure of Sikkim (%) . . . . . . . . . . . . . . . . . . . . . Educational facilities in Sikkim, 2015–16 . . . . . . . . . . . . . . . . . Road network in Sikkim . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The percent of land under forest cover in Sikkim, 2015–16 . . . The percent of other land-use/land covers area in Sikkim . . . . . Trends of annual temperatures (°C) and precipitation (mm) at Gangtok (1985–2016) using the Mann–Kendall trend test and Sen’s slope estimator . . . . . . . . . . . . . . . . . . . . . . . Socio-economic status of the respondents . . . . . . . . . . . . . . . . . Farmer’s perception of climate change . . . . . . . . . . . . . . . . . . . . Occurrence of climatic hazard . . . . . . . . . . . . . . . . . . . . . . . . . . . Proxy questions regarding climate change . . . . . . . . . . . . . . . . . Adaptive strategies reported by the farmers . . . . . . . . . . . . . . . . Details of satellite data acquired . . . . . . . . . . . . . . . . . . . . . . . . . The calculated S3 index values for the snow and ice-covered regions of the respected years . . . . . . . . . . . . . . Error matrix table showing 3 different sample class values for PSI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Accuracy assessment values of three different classes for the PSI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Agroecosystems of Sikkim Himalaya . . . . . . . . . . . . . . . . . . . . .

28 29 31 32 32 34 37 38 38 38 39 40 41

49 51 51 52 53 54 62 67 74 75 82 xiii

xiv

Table 5.2 Table 5.3 Table 5.4 Table 5.5 Table 5.6 Table 5.7 Table 5.8 Table 5.9 Table 5.10 Table 5.11 Table 5.12 Table 6.1 Table 6.2 Table 6.3 Table 6.4 Table 6.5 Table 6.6 Table 6.7 Table 7.1 Table 7.2 Table 7.3 Table 7.4 Table 7.5 Table 7.6

Table 7.7

Table 8.1

List of Tables

Food and horticultural crops cultivated in the Sikkim Himalaya . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The concentration of food crops in Sikkim (net sown area) . . . The concentration of non-food crops in Sikkim (net sown area) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Major crops grown in sampled villages . . . . . . . . . . . . . . . . . . . Change in cropping pattern . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Types of farming systems and practices . . . . . . . . . . . . . . . . . . . Functions of farming practices . . . . . . . . . . . . . . . . . . . . . . . . . . Agricultural inputs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Reason behind the changing pattern of yield . . . . . . . . . . . . . . . Comparative study of crop diversification index in different districts of Sikkim, 2015–16 . . . . . . . . . . . . . . . . . . Crop diversification index of food and cash crops in different districts of Sikkim, 2015–16 . . . . . . . . . . . . . . . . . . District-wise consumption units (2015–16) . . . . . . . . . . . . . . . . District-wise availability of giga calories of food crops, 2015–16 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . District-wise carrying capacity of land in calorific value, 2015–16 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . District-wise availability of food crops in monetary value (billion rupees), 2015–16 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . District-wise carrying capacity of land in monetary value, 2015–16 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . District-wise available consumption of giga calories 2015–16 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . District-wise availability of monetary value, 2015–16 . . . . . . . . Socio-economic information of surveyed households in different ecological zones of the study area, 2019 . . . . . . . . . Summary of the different variables considered in the study . . . Agricultural diversities of the households (n = 300) . . . . . . . . . Sources of livelihood/income for the people of Sikkim (n = 300) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Options of livelihood and numbers of respondents (n = 300) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Logit regression for livelihood choices between agricultural and non-agricultural activities as different strategies for farmers in Sikkim . . . . . . . . . . . . . . . . Multinomial logit regression for livelihood choices among agriculture, non-agriculture, and both as different strategies for farmers in Sikkim . . . . . . . . . . . . . . . . . . . . . . . . . . Important factors of agricultural development and their present status in different districts of Sikkim . . . . . . . . . . . . . . .

84 87 93 106 107 108 109 109 110 112 113 120 121 121 122 122 122 123 127 131 132 134 137

139

140 150

Chapter 1

Introduction

1.1 The Context Climate change threatens people with “food and water scarcity, increased flooding, extreme heat, more disease, and economic loss.” The World Health Organization (WHO) calls climate change the utmost threat to global health in the twenty-first century. Climate change is likely to deteriorate the condition in the major parts of the world which have already faced the serious problem of food insecurity. Higher rainfall variability has substantial consequences for food safety, the livelihoods of millions of people, and the migration of decisions of vulnerable households. Climate variability/change, directly and indirectly, influences several facets of food security, primarily in the livestock and farming sectors. The farming sector is the key source of income and engagement for about 70% of the world’s poor in the countryside. Though, the livestock sector also contributes substantially to climate change, accounting for 18% of greenhouse gases, while also being a prime source of soil and water pollution (https://datos.bancompundial.org). Though the connection between climate change and food security is complex, most studies gave emphasis only on food availability. Its practical impacts also were reported on agrobiodiversity, ecology, hydrology, and agriculture in numerous studies (Chakrabarty 2016; Salinger et al. 1997; Salinger 1994). An overall increase in global temperature during the twentieth century has been reported in various studies (IPCC 2013). Interannual climate changeability has also been noticed in several parts of the globe. In the twentieth century, the overall worldwide terrestrial precipitation has augmented by about 2% (Hulme et al. 1998), but this is not constant temporally or spatially. Changes in rainfall and temperature pattern can simply change the hydrological cycle and environmental processes (Feng et al. 2016). According to IPCC (2012) report the timing, intensity,

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 S. C. Rai, Food and Livelihood Securities in Changing Climate of the Himalaya, Human-Environment Interactions 9, https://doi.org/10.1007/978-3-031-22817-9_1

1

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1 Introduction

and frequency of extreme climatic conditions and weather variability are the results of changing climate. The occurrence and intensity of drought, flooding events, and heat stress are projected to increase, and these changes will create environmental, agricultural, and economical challenges for local communities all over the world. Apart from the environmental impacts of climate variability, its economic cost is also a foremost task. The average yearly damage caused by climate variability and extreme events has increased about 8 times between the 1960s and 1990s, globally the cost of extreme events between 1980 and 2004 was approximately 1.4 trillion US dollars (Mills 2005). Cost varies from region to region based on the climate, biophysical status, development level, vulnerability level, etc. However, the burden is more on developing and less economically developed countries as they are more susceptible to the paraphernalia of climate variation (IPCC 2014). Climate change and intense events also influence agricultural yield, quality, and quantity. Response of protein content in crops to vagaries in the mean annual changeability of temperature and rainfall has been observed (Porter and Semenov 2005; Hurkman et al. 2009). Climate change-induced climate variability will certainly increase extreme weather conditions and severely impact agricultural production. Agrobiodiversity is an outcome of both natural selection and human interventions over millennia. It has been developed with the interactions between the environments and genetic resources, and by management systems and practices used by farmers (GIZ 2015). Various research has shown the effects of climate variability on agrobiodiversity, quality, and quantity of agricultural production. The impact of climate variability has been observed in agriculture in India too, it is estimated that surface warming and change in precipitation may drop agricultural yield by 30% by 2050 (Kapur et al. 2009). Shift and crop reduction have already been observed in different parts of the country (Ramulu 1996; Boopen and Vinesh 2011). Climate variability is a foremost apprehension in the Himalayan region owing to its possible effects on the ecology, environment, and economy of the area. Glaciers in the Himalayan region cover about 17% of the global mountain area. The entire area of the Himalayan glaciers is 35,110 km2 . The overall ice preserve of these glaciers is 3735 km3 , which is equivalent to 3250 km3 of clean water. Himalaya is the source of the major nine rivers of Asia, i.e., Brahmaputra, Ganges, Mekong, Irrawaddy, Yangtze, Trim, and Yellow, and is the lifeline for 500 million peoples of the region, or around 10% of the total regional population (IPCC 2007). The glaciers in the Himalayan area are said to be melting faster than in any other portion of the planet. For example, the Gangotri glacier has retreated at a rate more than three times faster in recent years than it did in the previous 200 years. On the Tibetan Plateau, the glacier area has shrunk by 4.5% in the last 20 years and by 7% in the last 40 years (CNCCC 2007). In the Himalayan area, increased glacier retreat has resulted in a broader range of glacial dangers known as glacial lake outburst floods (GLOFs). Nearly 200 possibly dangerous glacial lakes in the region might create devastating floods that could wipe out all means of subsistence in one fell swoop (Bajracharya et al. 2007; Aggarwal et al. 2017).

1.1 The Context

3

The effect of climate variation has become very apparent in the Himalayan region. Sikkim Himalaya is not an exception where climate change is badly disturbing agriculture and related ecosystems. Environmental degradation in the Himalayan region because of overuse and misuse of various natural resources is well recognized. The mountains of the Himalayas which make vital contributions to the ecological sustainability of the region are threatened by increasing population, open grazing, deforestation and loss of biomass cover, and overall biodiversity. Farm-based activities are important livelihood options for people worldwide, largely depending on weather and climate. Agriculture is very sensitive to variations in precipitation and temperature, and the destiny of the local communities of the region is closely tied to climate. It is self-evident that climate change will have significant consequences for agriculture and thereby food security. Tiwari and Joshi (2012) reported that the farmers have already experienced decreasing water supply in many parts of the Himalayas. It is also experiential that the carbon on the earth’s surface and in the atmosphere due to its mobility contributes to climate change (Scherr and Sthapit 2009). Global warming is responsible for the increase of the world’s average annual temperature because of greenhouse gasses (GHGs), which further lead to climate change. A dynamic interaction exists between various biotic (microbes, flora, and fauna) and abiotic (soil, water, air) elements in farming operations, and any disturbance in the natural balance may impact crop productivity through damage to the environment (Rathore and Jasari 2012). Seasons and weather are becoming increasingly variable and extreme, making it difficult for the farmer to decide on and cultivate a specific crop. The whole agricultural system would be collapsed if climate change continues (Harbinson 2001; Lal 2001). These changes are not only a potential threat to food security but also largely determine the socio-economic status of a large population dependent on their agricultural livelihood. The accessibility of accurate climatic data and continuous monitoring has improved our understanding of the climate arrangement and the features affecting climate change. However, there is still a knowledge and data gap in our understanding of the effects of climate variability on agrobiodiversity. Mountain farming is unsustainable but some areas, such as Ningnan County in China, Ilam district in Nepal, and H.P. in India, have experienced a speedy change because of the adoption and implementation of environmentally caring and mountainspecific development strategies. The mountain-specific Research and Development, harnessing the comparative advantages of high-value cash crops, the promotion of agro-based industries, and off-farm employment are the focus of development strategies being followed in these parts (Sharma and Sharma 1996). The ancient cultivation of the large cardamom (Amomum subulatum) in Sikkim, on the other hand, is one example of connecting the native mountain niche. Large cardamom is a perennial high-value, low-volume, non-perishable cash crop growing beneath the forest cover on marginal and barren soils and is a hereditary plant of the Sikkim Himalaya. It is an exceptional example of the ecological and economic viability of a traditional farming system based on indigenously evolved agroforestry practices. In this case,

4

1 Introduction

the cash crop is domesticated and then developed commercially by the local farming community. The net result has been the availability of a broader range and a higher quality of livelihood options leading to a better quality of life (Partap 1995). But the question remains whether agriculture can maintain or preferably increase production by adapting to a changing climate. The most recurrent adaptive measure is to introduce new crops, change the dates of sowing and harvesting, save water by drip irrigation, and take advantage of organic fertilization by increasing nitrogen inputs to fields (Adams et al. 1998; Tol et al. 1998). Such adaptive measures will have a strong influence on the magnitude of estimated climate impacts (Tol et al. 1998). Good knowledge of the issues and progressions that affect farmers’ capability to cope with and adjust to seasonal change is grave to the development of acceptable, appropriate, and feasible assistance programs (Below et al. 2015). Therefore, a good understanding of climate variability, livelihood options, and factors and processes contributing to agricultural transformation can deliver useful policy insights for devising development interventions for improving the standards of living of mountain people and adaptive measures to cope with the changes. The main aim of the study is to develop a model for building an adaptive system to climate change that combines local tradition and indigenous knowledge with up-todate scientific research and government policies.

1.2 Definition of Problem The World Food Summit (1996) defined food security as: “Food security exists when all people, at all times, have physical, social and economic access to sufficient, safe and nutritious food which meets their dietary needs and food preferences for an active and healthy life.” Bestowing to this, there are four main elements to food security, i.e., food availability, access to food, food absorption, and stability, only the first is routinely addressed in simulation studies (Fig. 1.1). Hence, adequate food production alone is not enough condition for a country’s food security. Food security is one of the foremost apprehensions linked with climate change that affects food security in complex ways. The Sustainable Development Goals (SDGs) aim to end hunger, eradicate poverty, achieve food security, and improve nutrition. Food security continues to be high on the government of India’s list of development priorities because the country’s relatively high rates of economic growth have not to a reduction in hunger and undernutrition. About twelve Indian states fall under the “Alarming” category of the “Global Hunger Index” (Chakrabarty 2016). The long-term lessening in the prevalence of undernutrition worldwide has reduced since 2007, because of “pressures on food prices, economic volatilities, extreme climatic events, and changes in diet, among other factors” (Wheeler and von Braun 2013). Climate change is becoming one of Sikkim Himalayas’ most persistent environmental issues. Climate change is already influencing biodiversity, snow/ice cover, and the livelihood assets of impoverished and vulnerable groups, according to evidence.

1.2 Definition of Problem

5

Fig. 1.1 Four dimensions of food security (after Gunaratne et al. 2021)

The indigenous agricultural system in the Sikkim Himalaya includes a variety of agro-ecological zones that encompass a wide range of ecosystem diversity from 300 to 5000 m. It is one of the segments of the easterly Himalaya, an internationally important biodiversity hotspot, and houses a variety of agrobiodiversity. The agrobiodiversity in mountain systems faces inaccessibility, marginality, and fragility to withstand its resilience. The Eastern Himalayan areas are warming at a rate of 0.01–0.04 °C per year because of climate change (Sharma et al. 2009). Increasing uncertainty is influencing the dynamic Sikkim Himalayan agriculture. Between the vertical elevation gradients of the tropical to Trans-Himalayan region, only around 12% of the entire land area of Sikkim is cultivable, with agriculture providing subsistence to roughly 65% of the total people. Mountain farmers are dealing with a slew of dangerous scenarios because of global warming and climate change, apart from the previously existing drivers of change, influencing the lives and livelihoods of mountain people, such as social, political, economic, and environmental factors. Climate change is an additional component that disrupts and amplifies the effects of other change drivers. Farmers in the Sikkim Himalaya are already dealing with socio-economic problems like small and fragmented landholding, poverty, low employment opportunities in the state, low crop production of organic crops, and higher input cost of organic farming. Thus, on the socio-economic front, assessment of the impact of climate variability in the state is impartment. Hence, this study is an effort to understand the severity of the situation based on available climatic data and the perception of local communities regarding climate change and variability. However, there has been no such study that has comprehensively covered these aspects.

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1 Introduction

1.3 An Overview At this stage, we offer an outline of the pieces of proof for how climate change could disturb worldwide food and livelihood security, with emphasis on the Himalayan region. The consequences of land-use transformation from forest to agriculture, in the developing countries of the tropics, have motivated international concern for human poverty, loss of plant and animal species, erosion of landscape, siltation of watercourses, and flooding. In Asia and Australia, the loss of natural forest cover has already reached at least 21% (Jackson 1983; Rubinoff 1983) and has been a major contributor source of increasing CO2 concentration in the atmosphere in the region (Houghton 1990). Extensive utilization of natural resources and ignoring the fundamental ecological principles in the past have resulted in the present complex problems in the Himalayan region. Socio-cultural and biophysical constraints/opportunities need due consideration in identifying developmental strategies in the hills (Saxena et al. 1991) while considering the diversification of farming and livelihoods. Ways and means of motivating people toward these diversifications ought to be designed. In the recent past, the region has experienced extensive problems of environmental degradation because of deforestation, expansion of agricultural land, and demand for fuelwood (Jodha 1992) leading to degradation in both economic well as social values (Topal et al. 1999, 2000). There is ample indication that displays Earth has warmed since the middle of the nineteenth century (Wheeler and von Braun 2013). The global mean temperature has risen by 0.8 °C since the 1850s, with the warming trend seen in three independent temperature records taken over land and seas and in ocean surface water (Solomon et al. 2007). Climate change can result from natural causes, anthropogenic activities through the emission of greenhouse gases, and changes in land-use/cover. Thus, climate change is a major concern in the world today, and the Hindu-Kush Himalayan area is no different. At the local and regional levels, global warming has contributed to erratic rainfall patterns, the drying up of local springs and streams, a shift in crop sowing and harvesting periods, species migration to higher elevations, the spread of invasive species, and the incidence of diseases/pests in crop and fodder species. Droughts, cyclones, flash floods, and forest fires are anticipated to occur in the Indian area due to a rise in temperature (1.4 °C by 2020 and 3.8 °C by 2080s) and precipitation (93% by 2020 and 11% by 2080), according to the Intergovernmental Panel on Climate Change (IPCC 2001). According to some research, the seasonal temperature in north Indian floodplains has grown by 0.94 °C every 100 years during the postmonsoon season and by 1.1 °C per 100 years during the winter season (Arora et al. 2005). Adaptation has been critical throughout the last century, as global warming has the potential to negatively influence agriculture. It is understood that adaptation can reduce vulnerabilities. Increasing temperature and variation in rainfall have also been stated in Nepal (Shrestha et al. 1999). Such events would undoubtedly alter the nature and volume of ecosystem services, mostly affecting rural people and their crops. Climate variability is undeniably occurring, and it will have practical ramifications for micro-ecosystems, according to scientific research (IPCC 2007).

1.3 An Overview

7

Though, a very small impact is acknowledged on the vulnerability of mountain ecosystems due to climate variability, particularly in the Himalayan region. According to the International Centre for Integrated Mountain Development (ICIMOD), the Eastern Himalayas is warming at a rate of 0.01–0.04 °C each year (Sharma et al. 2009). The Indian Meteorological Department (IMD) statistics show that the climate of Sikkim changed somewhat between 1958 and 2005 (Anonymous 2008). Though there is a lack of detailed knowledge on the effects of climate change in the Sikkim Himalaya, long-term research projects have yet to be undertaken. Many climate studies in the past have focused on the mean of climate change. Climate change inevitably results in a change in climate variability, duration, spatial extent, and timing of extreme weather events (IPCC 2012). Effects of global warming on the economy and human society, specifically on forestry and agriculture, are of foremost concern (Vedwan and Rhoades 2001; Lobell et al. 2011; Islam et al. 2014). Intergovernmental Panel on Climate Change (IPCC) states vulnerability is “the degree to which a system is susceptible to, or unable to cope with, the adverse effects of climate change, including climate variability and extremes” (IPCC 2001). Increased occurrence and intensity of exciting weather events have been reported in various regions (Raleigh and Jordan 2010; Munich Re 2011; IPCC 2012). Several studies have reported the vulnerability of developing nations in response to climate change and climate variability (IPCC 2012; UNDESA 2013). Poverty and vulnerability are linked due to the limitations of recourses among the poor limits their ability to cope with climate change (Barua et al. 2014). Developing countries such as India where more than half of its inhabitants are still reliant on agriculture and its associated activities for livelihood are susceptible to the effects of climate variability. The relationship of the Indian crop with climate has been evaluated in several studies (Poudel and Shaw 2016; Ozturk et al. 2003, 2004). The trend of temperature and precipitation in India varies from one place to another (Bhutiyani et al. 2007) due to its vast geographical location and different climatic zones. Studies suggest that mountains are most vulnerable to change in climate, however restricted accessibility, remoteness, harsh weather conditions unavailability of field instrumental data are some of the major reasons for the unstudied impacts of climate change and its variability in mountain ecosystems globally. Climate studies conducted in the Himalayan region suggest warming trends at a diverse rate (Shrestha et al. 1999; Kattel and Yao 2013; Bhutiyani et al. 2007). However, the observed trend across the Himalayas is not the same, the north-western and central Himalayas show an encouraging trend in both minimum and maximum temperature whereas the Eastern Himalayas show a positive trend only in minimum temperature (Bhutiyani et al. 2007). Long-term precipitation data shows no trend in the Eastern Himalayas. Positive change in minimum temperature is linked to the upward shifting of the tree line in the alpine region. Mountain agriculture is dominated by subsistence and is thus insignificant in terms of feeding the growing population. Jodha (1996) defined that Himalayan farmers face major challenges in food production due to rough terrain, fragmented land plots, variable climates, short seasons, and slow plant growth. Access to markets and limited livelihood options that enable access to food is identified as further

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1 Introduction

constraining factors. Large-scale solutions to these problems will be solved if we focus on the viability of small-scale technologies such as irrigation and rainwater harvesting (Pandey et al. 2003), multifunctional agriculture (Bhatt 2012), or the introduction of specific Csn crops (Nautiyal et al. 2007). The population of the Eastern Himalayas is highly susceptible to cyclical moves in agricultural production. Existing sowing and harvesting cycles specify the likelihood of close to ten months of food insecurities and increased climate variability has worsened food security issues. This degree of food vulnerability may help explain the population’s poor nutritional outcome and lack of dietary diversity. Declining agricultural production has resulted in increased migration as households try to cover expenses (Blackmore et al. 2021). Hashem (2020) reported that there is a negative and significant impact of temperature on food production as increasing temperature leads to decreasing some crops’ production. A significant effect of climate variation on agrobiodiversity, agriculture, hydrology, and livelihood has been reported in Sikkim Himalaya (Seetharam 2008; Sharma and Shrestha 2016). Hussain (2004) evaluated the food security condition in the northeastern region of India. He observed that due to climate change, the entire northeastern region has a deficit in food production. Long-term trends in temperature and precipitations have been analyzed in various studies. Studies used annual and monthly temperatures (minimum, maximum, and average) and precipitation data from Gangtok and Tadong weather stations to analyze the trend of climate in the region. Monitoring changes in the snow cover in the region has also been attempted by various researchers (Kumar and Murugesh Prabhu 2012; Mool et al. 2001; Mool and Bajracharya 2003). However, the availability of primary and secondary data on snow cover is a big hurdle. Due to the harsh climatic condition of the high altitudinal areas only a few glaciers have been studied. Several glacier studies in the region suggest an average area loss of up to 20% in the region (Basnett et al. 2013; Racoviteanu et al. 2015). Reported warming results in the melting of glaciers in the region and consequently the expansion of glacial lakes. Several efforts have also been made to understand the perception of local communities on climate change and its impact. A comprehensive study on climatic changes and their cascading effects on biodiversity and the natural resource landscape in the Lachen valley was conducted by Ingty and Bawa (2012). Several other studies documented the traditional knowledge of farmers in Sikkim Himalaya to understand how local farmers have adopted the change in cropping pattern in response to climate variability (Sundriyal et al. 1994; Mishra et al. 2013). Despite the area being a biodiversity hotspot the appropriate data for in-depth analysis of rainfall, temperature, snow cover, and glacier changes are lacking. Most of the high-altitude areas in the region are inaccessible, hence data are mostly missing for high-altitude areas, only two major weather stations of the state are in the East Sikkim district, i.e., Gangtok at an elevation of 1812 m, and Tadong at 1322 m. Previous studies attempted to evaluate the impact of climate variability in the region; however, the detailed analysis of climate variability and data regarding the perception of farmers on climate

1.5 Methodological Approach

9

variability is still not enough. Perception plays a foremost role in the local population to make them alleviate the impacts of climate change on agrobiodiversity and livelihood security. Hence, more in-depth studies in the area are mandatory to combat and mitigate the effects of climate variability and to develop better adaptation strategies. Therefore, this study envisages analyses of climate variability and its effects on food and livelihood security in traditional farming of the Sikkim Himalaya.

1.4 Hypothesis and Objectives 1.4.1 Hypothesis (i) The projected climate change will have a substantial impact on agrobiodiversity and the yield stability of the agricultural production system. (ii) Agrobiodiversity will play a dominant role in the ability to react to the effects caused by climate change.

1.4.2 Objectives • To analyze the agrobiodiversity of the state. • To analyze the meteorological data over some time to see the climate changes in the state. • To understand the farmers’ perceptions and observations on climate change and its effect on the traditional farming system. • To identify tools and practices applicable in using agrobiodiversity for coping with climate change and making these extensively accessible.

1.5 Methodological Approach There are various methods for the documentation of primary information from the field. In past studies, authors have used methods to document the information directly collected from local communities such as personal interviews, participant observation, focused group discussions, village workshops, brainstorming, games, and participatory video/photo documentation. Along with this data can be also collected through field observation, case studies, SWOT analysis, flow chart mapping, taxonomies, and published data. In the present study, a questionnaire survey method has been adopted to collect data from the rural household of Sikkim Himalaya. Personal interviews of elderly people, members of gram panchayat, and people working in local govt. departments

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1 Introduction

were also done to verify the data collected through a questionnaire survey. Apart from this extensive field survey was also done in all the districts of Sikkim for field observation.

1.5.1 Data Collection 1.5.1.1

Primary Data

Primary data was collected through a questionnaire survey of 300 households in three different ecological zones of Sikkim Himalaya. Ecological zones were divided based on the agro-climate variation in the area. Verification of this data was done through personal interviews of local elderly people, members of gram panchayat, and people working in local govt. departments.

1.5.1.2

Secondary Data

Secondary data was collected in the form of published reports for literature review, census data to understand the demography of the state, temperature and precipitation data collected from the Indian meteorological department to monitor long-term changes, and satellite images acquired from the USGS earth explorer website for base map preparation of the study area. Cloud-free image of Landsat 8 has been used to prepare the location map of the study area. Apart from this DEM was also acquired to retrieve morphometric information about the study area, i.e., slope aspect and elevation. DEM was also used to divide the study area into three agro-ecological zones using elevation data, i.e., lower ecological zone < 1000 m, middle ecological zone 1001–2000 m, and high ecological zone 2001–3000 m.

1.5.1.3

Data Analysis

Household data was collected through questionnaire surveys and were stored in tabular form in Microsoft excel for the calculation and analysis of various statistical parameters. Secondary data sources such as data on temperature and precipitation were also first stored in excel for verification and preparation for statistical analysis. The statistical analysis of IMD data was done by R package software. Mann Kendall test and Sen’s slope were calculated for both rainfall and temperature data. The results of these tested parameters were then correlated with studies conducted in the past to check the similarities. Satellite images and DEM acquired from USGS were pre-processed in QGIS software and post-processing of the images was done in ArcGIS. Different maps of the study area such as location maps of the study area, elevation maps, slope maps, and aspect maps were created using satellite imageries. Final layout preparation of maps was also done in ArcGIS software.

1.7 Significance of the Study

11

1.6 The Study Area The study area Sikkim Himalaya is spread over the various climatic zones covering tropical climates in the south to subtropical and temperate up to the Trans Himalayan Tibetan plateau in the north. Despite being a small landlocked state the variation in elevation is very high even at small distances. The elevation range of the state is from 213 m in the south to the third-highest mountain in the world Khangchendzonga (8598 m) located in the northwest part of the state. There are more than 100 glaciers in the state and numerous glacial lakes. The state is part of 22 agrobiodiversity hotspots in India and 34 globally significant biodiversity hotspots. The region is very rich in environmental, ecological, agricultural, cultural, and biodiversity. There are around 5580 plant species found in the Sikkim Himalaya (SBAP 2012), of which around 550 species have food values and 50% of them are cultivated species. Physiographies, socio-economic and cultural aspects of the study area are discussed in detail in another chapter. A major source of more than 75% of the population in Sikkim Himalaya is agriculture which is around 17% of the gross state domestic product (Kumar 2012). The traditional farming systems of the Sikkim Himalaya involve livestock farming as an integral part of the farming system. More than 80% of the farmers in Sikkim Himalaya own livestock and use their products for personal consumption as well as a source of income. The land-use/cover of the state is undergoing rapid change for the past two decades. This change is driven by rising infrastructural development in the state, the pharmaceutical industry, hydropower projects, roads, and infrastructure playing the main role in change. Due to the rising population per capita landholdings have also decreased (0.1 ha per person according to the 2011 census), and poverty and unemployment are major challenges faced by the local population.

1.7 Significance of the Study People of this region are largely dependent on farm-based livelihoods, as nearly 70% of the workforce and over 85% of women are involved in diverse farming activities. The inhabitants of the Sikkim Himalayan region are facing several problems due to ever-increasing population, land-use/cover change, decreasing agricultural productivity, depletion of the natural resource base, and changing climatic conditions during the recent past. People are forced to go for alternative means of livelihood but due to a lack of proper guidance, scientific knowledge, and skills, they are not in a position to decide what to do. The findings of this research would provide opportunities to the community for exchanging experiences, and traditional knowledge and empower them for livelihood security by developing a climate-resilient farming system and facilitating marketing infrastructure for their products. Socio-economic issues like out-migration may also be addressed if livelihood options are available at door. By providing supplementary options to the marginalized farmers and weaker sections

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1 Introduction

of society, their dependency on natural resources, especially on forests, for livelihoods will also be decreased which will help environmental sustainability and ultimately contribute toward the National mission of sustainable environment, health, and poverty elevation. The results of this research are beneficial and add value to the field of climate change studies in mountain ecosystems. The outcomes of this work will be of great help to the state and local policymakers as the study contains both primary and secondary data to analyze and understand the severity of the problem faced by local communities.

1.8 Structure of the Book The present study is divided into eight chapters dealing with varied but interrelated aspects. This chapter describes the context, statement of the problem, review of literature, objectives, hypothesis, methods of data collection and significance of the study, etc. Chapter 2 deals with the biophysical and socio-economic characteristics of the area. Chapter 3 deals with climate variability and farmers’ perception. Chapter 4 is about spatio-temporal change delineation and forecasting of snow/ice-covered areas. Agricultural systems and agrobiodiversity have been described in Chap. 5. Chapter 6 is about the analysis of food availability. Chapter 7 describes an analysis of livelihood security. Conservation of agricultural and sustainable livelihood has been discussed in Chap. 8.

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Chapter 2

Biophysical and Socio-economic Characteristics

2.1 Background The Himalaya (Sanskrit Hima-snow, Alaya-house) establishes an exceptional geologic and geographical entity encompassing varied socio-cultural, and environmental setups. The conventional meaning of the Himalaya, sensu stricto, is that vast range of mountains that differentiates India, laterally its north-central and northeastern borderline, from China (Tibet), and encompasses between 26° 20' and 35° 40' N, and between 74° 50' and 95° 40' E. It is the youngest, highest, and most fragile mountain structure in the world. The region stretches from the Indus Trench below Naga Parbat (8125 m) in the west to the Yarlung Tsangpo-Brahmaputra gorge below Namche Barwa (7756 m) in the east, encompassing Afghanistan, Pakistan, India, Nepal, Bhutan, and China’s political-administrative territories (Ives and Messerli 1989). The Himalayas stretch out in the Indian Territory stretches over a length of around 2500 km and a width of 220–230 km covering partially or fully 12 states of the Indian Union with the Himalayan Kingdom of Nepal and Bhutan. It has been classified into five major geographical divisions viz., (i) The Eastern Himalaya (SikkimDarjeeling-Bhutan and Arunachal Pradesh), (ii) the Central Himalaya (eastern and central Nepal), (iii) the Western Himalaya (Kumaon-Garhwal, Himachal Pradesh, Western Nepal), (iv) North-West Himalaya (Kashmir-Afghanistan), and (v) the North-West Himalaya (Sino-Tibet). The Indian Himalaya covers a total geographical area of about 533,604 km2 and is inhabited by approximately 48,598,561 persons (48.5% female) and approximately 1.2 billion people reliant on its downstream river basins for food and energy production with multiple ethnic compositions which further has an impact on its ecosystem making it more fragile (GBPIHED 2015). Though it contains about 18% of India’s geographical area, the Himalaya are credited for around 50% of the country’s forest area and 40% of the species endemic to the Indian subcontinent (Myers 1990; Khoshoo 1992).

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 S. C. Rai, Food and Livelihood Securities in Changing Climate of the Himalaya, Human-Environment Interactions 9, https://doi.org/10.1007/978-3-031-22817-9_2

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It is a cradle of unique and important biodiversity elements known for their economic and ecological importance. The growing concerns for deteriorating environmental sustainability and formulation of appropriate land-use policies in planning research and developmental activities over the past five decades appear to have causeand-effect arguments and are tumbling very fast concerning socio-economic and environmental failure. These unknowing influences have been demonstrated in the form of uncontrolled population growth, landslides, deforestation, downstream flooding, poverty and malnutrition, poor management strategies, etc. Anthropogenic pressure on natural resources has triggered large-scale disasters throughout the Himalayan region. Unscientific spread of subsistence agriculture to support the growing undernourished population and a corresponding increase of grazing pressures that out-strip the carrying capacity of the forest continue to abridge the supportive ecosystem by various means. Management practices can do much to conserve or improve biological resources in the Himalayas. The dynamic accomplishment of an ecologically sound and environment-friendly, new green revolution is possible only when rural farming families learn to optimally manage their valuable geo-as well as bio-resources.

2.2 Physical Characteristics 2.2.1 Location and Extent Sikkim or Sukhim means “New House” and is situated in the Eastern Himalaya and is covered with snow-clad high mountains, steep slopes, basins, foothills, and valley floors. Sikkim is one of the tiny states in India with multiplicity in the growing livelihood (Fig. 2.1). Sikkim is lying between 27° 3' 47'' to 28° 7' 34'' North and 88° 03' 40'' to 88° ' 57 19'' East in the Eastern Himalayan bio-geographic zone that shelters the greater number of endemics and threatened species in the Indian subcontinent is recognized as one of the biodiversity “Hot Spot” of global significance (Khoshoo 1992). Sikkim is nestled on the lap of the Eastern Himalaya lying on its southern slope with a total geographical area of 7096 km2 with elevations ranging from 250 to 8595 m above MSL, which constitutes about 0.22% of the total geographic area of India. Sikkim is bordered on the west by Nepal, on the east by Bhutan, and on the north by Tibet, while the state’s southern half has a border with West Bengal. In Sikkim, there are 440 villages, eight towns, and four districts. Each district comprises a district headquarters, namely Mangan in North Sikkim, Namchi in South Sikkim, Geyzing in West Sikkim, and Gangtok in East Sikkim. Gangtok is the capital of Sikkim and one of the major towns in the state. Gangtok is also the most known tourist place in North-East India. The state has four major ethnic groups’ viz., Lepcha(s), Nepalese, Bhutia(s), and Limbu(s).

2.2 Physical Characteristics

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Fig. 2.1 Location map of Sikkim Himalaya

2.2.2 Topography Sikkim extends from scorching deep valleys, a meager 250 m asl to high snow peaks like Khangchendzonga. Mt. Khangchendzonga is in western Sikkim at the border to Eastern Nepal in the Great Himalayan Belt. Almost 25% of Sikkim belongs to the Khangchendzonga National Park, which since July 17, 2016, has been inscribed as one of the UNESCO World Heritage Sites (UNESCO 2016). The mountain ranges in the center and north are steeper than those in the south (Fig. 2.2). Due to large elevation variations, steep slopes, and fragile geological characteristics, the state is subject to landslides and river erosion. The mountain system is oriented roughly east– west, while the major ridges run more or less north–south, with elevations ranging from 800 to 8595 m. The lower altitudes are subtropical comprising a variety of orchids, cardamom, fruits, and terrace farming. The northern part of the state is severely cut into escarpments without any population excluding the Lachen and Lachung valleys. The glaciers that descend to about 4000 m are fed by the snowcapped sharp ridges in the northern part of the state. The northern part of the Tibetan plateau is characterized by barren, reddish-brown hills and hillocks with large, flatbottomed valleys, which are typical of the Tibetan plateau.

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Fig. 2.2 Elevation map of Sikkim Himalaya

The elevation range map shows different elevation zones through SRTM data. Sikkim is a highly elevated state as it shows areas above 5000 m, which are mostly considered to be glaciated areas. The areas below 2000 m are suitable for agriculture and other economic activities and shelter numerous tribes and non-tribes people.

2.2 Physical Characteristics

21

2.2.3 Slope The slope map measures the degree of inclination or steepness of a surface. The slope has been measured in degree, where the change in color shows the rise in slope. The slope below 30° depicts the drainage channels, which are of lower height than the surrounding areas (Fig. 2.3). The slope for a specific site is considered as the maximum rate of change of elevation between that location and its surrounds. In physical geology, the aspect is the compass direction that a slope face. For example, a slope from the northern part of Sikkim toward the southern part due to decreasing altitude gives a southerly aspect, the aspect is the direction that makes the drainage system of Sikkim flow from North to South (Fig. 2.4).

2.2.4 Drainage Pattern The state has a good drainage network. The Teesta and the Great Rangit, with their various tributaries and sub-tributaries, drain the whole state. Lachung Chhu, Chakung Chhu, Dik Chhu, Rani Khola, and Rangpo Chhu are some of the Teesta River’s significant left-bank tributaries, while Zemu Chhu, Rangyong Chhu, and Rangit River are some of the right bank tributaries. Eastern flank tributaries are large in number with a shorter span of flow while the western flank tributaries have larger drainage areas with more amounts of course span of flow and discharging more amounts of glaciated areas with large snow-fields to the main river (Fig. 2.5). The most important tributaries include the Zemu Chhu, the Rangyong Chhu, the Lachung Chhu, Ranthong Chhu, and the Ramam Chhu. The combined course of the Ramam and the Great Rangit marks the southern boundary of the state. The entire state is divided into two catchments, i.e., the Teesta and the Rangit catchment. River Teesta, which originates as Chhombo Chhu from a glacier lake Khangchung Chho at a height of 5280 m in the state’s northeastern region, flows from north to south across Sikkim. It flows along with its major tributary Rangit, which meets Teesta at the border of West Bengal and Sikkim. These primary channels, Teesta and Rangit, which enter from north to south, create deep gorges and valleys, allowing the monsoon to reach the Himalayas’ northernmost portions and nourish it. The rivers are supplied by rain that gathers in the catchment areas during the monsoons, as well as melting snow in the highlands. The rivers are not navigable since they are narrow, serpentine, and full of rocks.

2.2.5 Geology Precambrian rock of much younger age prevails over a major portion of the state (Bhasin et al. 2002; Sharma et al. 2012). Hard massive gneiss rocks, capable of resisting denudation, cover the northern, eastern, and western parts. The middle

22

2 Biophysical and Socio-economic Characteristics

Fig. 2.3 Slope map of Sikkim Himalaya

and southern regions are mainly composed of relatively soft, thin, slaty, and halfschistose rocks that are easily removed. Sharp, rocky, snow-bound mountains with steep, difficult scarp sides can be found on the outcrops of gneisses with granitic intrusions (Fig. 2.6).

2.2 Physical Characteristics

23

Fig. 2.4 Aspect map of Sikkim Himalaya

The major part of the state is covered with Kanchenjunga and Darjeeling Gneiss (48% of land), shown in pink color in the map, which comes under the Central Crystalline Gneissic complex group of rocks. Approximately 18% of the state falls under the Gorubathan formation of rock comprising Quartzite, Phyllite, and Schists. The presence of schists and phyllites makes the slopes of the region prone to erosion

24

2 Biophysical and Socio-economic Characteristics

Fig. 2.5 Drainage network and order of two watersheds of Teesta basin in Sikkim Himalaya

of soil. Fossiliferous limestone with quartzite is found in the extreme northern part of the state. About 21% of the state is untouched due to inaccessible areas covered with snow and glaciers.

2.2 Physical Characteristics

25

Fig. 2.6 Geological map of Sikkim Himalaya

Sikkim is situated in a severe earthquake-prone area at the collision tectonics in the Himalayan arc and subduction tectonic below Myanmar’s arc between the continental Indian and Eurasian Plates (Fig. 2.7) and frequently gets affected by small and medium earthquakes. The lineaments and fractures play a significant role in landslide activities over mountainous regions. These lineaments and fractures originate through the geological formations of that area lying under several structural disturbances. These are the weaker zones of the land structures, which are also responsible for triggering earthquakes in the Himalayan state. Direct infiltration and rainfall through joints, fractures, worn zones of the rocks, and soil coverings are the main sources of spring recharge in the eastern half of the state.

2.2.6 Soils The soil of Sikkim state is classified into 3 taxonomic orders Entisols (43%), Inceptisols (33.4%), and Mollisols (23.6%), and 12 great subgroups based on the nature and properties of soil (Fig. 2.8) (NBSSLUP, Calcutta). The depth of soil differs significantly in different places due to the differences in topography and slope. The soil fertility also depends much on the geological formation of the rocks (Table 2.1).

26

2 Biophysical and Socio-economic Characteristics

Fig. 2.7 Lineaments map of Sikkim Himalaya

The soil formed by the gneissic group of rocks is brown clay, often shallow and poor, according to the Environmental State Report Sikkim (2007). The soil texture is naturally gritty, with high ferric concentrations, a pH range of neutral to acidic, and a lack of organic and mineral nutrients. They prefer to move as much as possible in both deciduous and evergreen woods.

2.2 Physical Characteristics

27

Fig. 2.8 Soil map of Sikkim Himalaya

2.2.7 Climate The climate of the Sikkim state differs from subtropical in the south and cold temperate and alpine in the northern and eastern parts. The southwest monsoon with seasonal setbacks plays an important role to control different seasons in Sikkim.

28

2 Biophysical and Socio-economic Characteristics

Table 2.1 Dominant soil groups prevalent over the physiographic units in Sikkim Himalaya S. No.

Physiographic units

Soil groups

1

Summit and ridge (< 30%)

Typic Hapludolls, Typic Udorthents

2

Side slope of hills

Typic Hapludolls

2.1

Very steeply sloping (> 50%)

Lithic Cryorthents, Entic Hapludolls

2.2

Escarpments (> 50%)

Entic Hapludolls, Typic Udorthents

2.3

Steeply sloping (30–50%)

Typic Argiudolls, Typic Hapludolls

2.4

Moderately steep sloping (15–30%)

Mollic Udarents, Typic Argiudolls, Fluventic Ustochrepts, Cumulic Hapludolls

3

Valleys (15–30%)

Cumulic Hapludolls

4

Rocky cliffs and precipitous snow

Lithic Udorthents

5

Glacier/perpetual snow

NA

Agrobiodiversity and tourism activities are mainly dependent on the following four seasons: Winter (December–February), Pre-monsoon (March–May), Rainy (June– September), and Post-monsoon (October–November). Local climate and weather are influenced by forest cover, water bodies, and the high mountainous orographic effect.

2.2.7.1

Rainfall

The climate is humid with rainfall occurring throughout the year and a maximum during the monsoon season from May to mid-October, owing to its nearness to the Bay of Bengal and the Great Himalayan orographic barrier. The southeastern areas, i.e., Mangan, Singhik, Dikchu, Gangtok, Rongli, etc., and the southwest mountainous region receive high rainfall whereas there is low rainfall around Namchi. The northwest district experiences less rainfall intensity with 4.9 mm as compared to South Sikkim. The average annual precipitation is about 2739 mm with a range of 84–3494 mm at Thangu and Gangtok, respectively (GSI 2012).

2.2.7.2

Temperature

Average minimum and maximum temperatures in the lower altitudes lie between 6°–8 °C and 21°–26 °C, respectively. The average annual temperature in the lower and moderate altitudes zones ranges between 4°–35 °C and 1°–25 °C, respectively (GSI 2012).

2.2 Physical Characteristics

29

2.2.8 Natural Vegetation Eastern Himalaya has been recognized as “Global 200 Eco-regions,” one of the 35 Global Priority Eco-regions hotspots, and one of the three Eco-regions in India by the World Wide Fund for Nature (WWF) around the globe to enable societal groups to secure sacrosanct regions. Approximately 81% of the total geographical area of Sikkim comes under the forest department. It the state-bound by more than 6000 plant species and more than 4000 species are flowering plants. About 12% of the land is available for cultivation and the main occupation of the hill people is farming. Some salient ecological features of the state are presented in Table 2.2. Table 2.2 Macro-ecological features of Sikkim Himalaya Parameters

Description

Rivers

Rangit (West Sikkim) and Teesta (North Sikkim) are the two major river systems that originate from glaciers

Ecological zones

Alpine (> 4000 m), sub-alpine (3000–4000 m), cold temperate (2200–3000 m), warm temperate (1400–2200 m), and subtropical (300–1400 m)

Terrain

Generally sloping land. These are marginal lands

Forests

Luxurious green broad-leaved mixed forests in subtropical and temperate zones whereas silver fir and rhododendron forests in the sub-alpine zone

Plants of special interest Rhododendrons, orchids, medicinal plants, and a large variety of wild edible plants Issues of concern

Explicit habitat degradation and loss have posed a threat to (i) wildlife such as the Red Panda, Thar(s), and Musk Deer, and (ii) plant diversity, such as medicinal plants (Aconitum sp., Nardostachys jatamansi, Picrorhiza kurrooa, Swertia chirata, Podophyllum hexandrum), wild edibles (Machilus edulis, Bassia butyracea, Elaeocarpus sikkimensis, Elaeagnus latifolia, etc.), wild orchids, and some species of rhododendron

Policy initiatives

Formation of protected areas, such as Singba Rhododendron Sanctuary, Kyongnosla Alpine Sanctuary, Fambonglho Wildlife Sanctuary, Maenam Wildlife Sanctuary, and Khangchendzonga Biosphere Reserve

30

2 Biophysical and Socio-economic Characteristics

2.3 Cultural Characteristics 2.3.1 History Sikkim has a deep-rooted history recorded from the seventh century with the presence of the first Lepcha Panu in the Thekong Adek region (Subba 2008). It has rich history of the Namgyal Dynasty since 1642, which formally started in the thirteenth century with the arrival of Guru Tashi, an evicted prince of the Mianyang Dynasty of Tibet (Census 2011). Sikkim Himalaya reflects Indian mythology and the religious customs of the locals for a long time. Sikkim was incorporated into India as the Republic of India’s 22nd state in 1975. The Lepcha custom is the foundation of Sikkim’s early history. The emergence of the Kingdom of Sikkim may be traced back to the seventeenth century (Risley 1968). The Buddhist faith has a lengthy tradition in Sikkim. The first Chogyal (King) of Sikkim was crowned in 1642 at Norbugang, Yuksom, during the Chogyal Dynasty’s reign. Buddhist communities have become firmly embedded in the Sikkimese people’s consciousness. However, Buddhism is practiced by around 25% of the local population, but Hinduism is the predominant religion (70%). Buddhism is visible in many aspects of life across the state, including ceremonies and festivals, embroideries elaborately woven with symbols from Buddhist myths and legends, Sikkimese architecture, and a huge number of temples and stupas dotting the landscape. It is vital to note that these exclusive values that have been established in Sikkim signify a combination of the common traditions of three communities: the Hinduism of the majority of Nepalese, the Buddhism of the Lepchas, and the Bhutias. The four Buddhist sects represented in Sikkim are Nyingmapa, Kagupa, Gelugpa, and Sakyapa. The Nyingmapa sect, founded by Maha Guru Padmasambhava, the Buddha incarnate, is the most notable. Sikkimese Buddhists, on the other hand, regard the entire state of Sikkim to be sacred. Padmasambhava, who is revered and worshipped by Sikkimese Buddhists, is said to have blessed Yuksam and the surrounding scenery of Demojong in Sikkim’s western region. This location has a big quantity of hidden gems concealed inside it (ters). Several of Lhatsun Namkha Jigme’s sacred treasures are in the Yuksam area. These terms are expected to be gradually introduced to enlightened lamas and at suitable moments. It is regarded vitally important for human welfare to preserve and protect these riches from damaging and disturbing influences. The area below Mt. Khangchendzonga in the landscape of Demojong is the core of the sacred land of Sikkim. Yuksam is a “Lakhang” (alter) and “Mandala” where gifts to protecting deities are offered. Any major disturbance in the countryside would enrage the presiding deities of the river Rathongchu’s 109 hidden lakes, resulting in major disasters. Lake Khecheopalri, for example, is supposed to have shifted away from the river during a period of historical turmoil. Its creation and shape are the subjects of numerous folklore and stories. According to the Sikkimese myth, the lake resembles Goddess Tara Jetsun Dolma’s foot.

2.3 Cultural Characteristics

31

The terrain and climate of Sikkim have defined the socio-economical activities of the people for a long time. However, unfaltering by natural hazards, conservation of the environment, and preservation of traditional values have been guarded by inhabitants for a long time, which leads to Sikkim as the cleanest and the most organic farming state in India.

2.3.2 Demographic Characteristics Sikkim state is the smallest populous state with a stated population of 610,577 in 2011 (0.5% of India’s population). The population increased by 13% in the last decade, whereas from 1991 to 2001, the population growth rate was 33.07%. The population is unevenly distributed across the state. Therefore, population density also differs immensely across the state. North Sikkim has a population density of only 10 people per km2 , whereas East Sikkim has a population density of 297 people per km2 . Rural regions account for 75% of the state’s population, with the rural percentage reaching 96% in the western district (Table 2.3). The SC/ST population consist of 4.63 and 33.8% of the total population of the state in 2011, respectively. The maximum concentration of the SC population (5.4%) is in the West district, whereas the ST population (65.70%) is higher in the North district of the state.

2.3.2.1

Sex Ratio

Sikkim’s population consists of 323,070 males and 287,507 females. Females found nearly 47% of the total population of Sikkim. The state recorded the highest sex ratio in the year 1921 of 970 females per 1000 males. Between 1931 and 1981, the sex ratio in Sikkim was falling, but it has begun to recover in the last three decades. In 2011, Sikkim had 889 females for 1000 males (Table 2.4). The largest sex ratio was found in the West district, followed by the South, East, and North districts, in that order. In 2011, the child sex ratio (0–6 years) was 944, which was higher than the overall sex ratio and the national average of 914. Table 2.3 Population density of Sikkim Himalaya, 2011

Districts

Population

Population density (km2 )

East

286,583

295

South

146,850

196

West

136,435

117

North Sikkim state

43,709

10

610,577

86

Source District Census Handbook (2011)

32

2 Biophysical and Socio-economic Characteristics

Table 2.4 Sex ratio in Sikkim Himalaya, 2011

Districts

Year (2011)

West

941

South

914

East

872

North

769

Sikkim

889

Source District Census Handbook (2011)

2.3.2.2

Literacy

In 1951, Sikkim’s total literacy rate was less than 7%, with just 11% of men and 1% of women being able to read and write. By 2011, the literacy rate had risen to 82%, with 87% of men and 76% of women being literate (Table 2.5). Sikkim’s female literacy rates are greater than the national average in both rural and urban regions. From 1981 (22%) to 2011, the female literacy rate increased by more than three times (76%). The female literacy rate in rural areas increased even more rapidly, from 18% in 1981 to 73% in 2011.

Box 1 The Bhutia(s) all over the state are the most progressive community. Their population is concentrated mainly in the northern district which is famous for growing large cardamoms. Due to the cultivation of cardamoms, they are highly educated and hence occupy the top echelons of the state bureaucracy and other technical posts. There are also some Bhutia(s) in the all-India civil service and they occupy high posts in other states and the central government departments. All this can be attributed mainly to large cardamom farming.

Table 2.5 Literacy rates (%) of Sikkim Himalaya, 1981–2011

Year

Literacy rates Male

Female

1981

44

22

1991

66

47

2001

76

60

2011

87

76

Source District Census Handbook

2.3 Cultural Characteristics

2.3.2.3

33

Ethnic Groups, Distribution, and Characteristics

The state of Sikkim is very luxuriant in cultural diversity. The state has a multi-ethnic structure viz., Nepalese, Bhutias, Lepcha, and Limbu. The Lepchas are the indigenous habitants of the state. After that Bhutias from Tibet arrive at the state. The recent immigrants are Nepalese and Tibetan refugees. They came here in the nineteenth century, because of the support given to Nepali settlers during the initial period of the British protectorate, the Nepali population has expanded many times since 1891 (Rai 1992). Bonpo Shamanists are said to be familiar with Lepchas, who are native to Sikkim. They originate in Mayel, a legendary valley in Khangchendzonga’s location, and have no practice of migration, according to Lepcha custom (Gowloog 1998). The Lepcha people, also known as Rong-pa or valley people, were widely dispersed throughout Sikkim. Adaptation to Bhutia culture was now the norm for Lepcha. Inter-marriage between the two tribes is prevalent, and Lepchas marrying Nepalese is not commonplace, especially among the Lepchas of Sikkim’s western region. Lepchas are traditionally hunters, gatherers of food, and animal husbandry specialists. Their economy is mostly based on agriculture and forestry. They have their clothing, eating habits, and festivals. The Lepcha ladies wear Gada, while the males wear Gyado. Bhutias are Tibetans who live in Sikkim. They dressed in Tibetan garb, and their language was Tibetan as well. Up in Bakku, the Bhutia ladies wear a long doublebreasted robe similar to the Japanese kimono. With the aid of a textile piece knotted around the waist, this gown is formfitting on the body. Women wear a flowy blouse (hanju) with long sleeves inside this garment. This outfit is known as Kho in the area. Married ladies wore a lined apron (pangden)-like material on the front of their waistcloths, which was typically stamped on both sides. Bakkhu is also dressed in long sleeves by the Bhutia males. Though, in recent years, the wearing of pants and hats has become more prevalent. Since Tibet’s closure, intermarriage has been a more prevalent occurrence. The scheduled tribe of the Bhutias are Buddhists. Sagadawa, Bum Chu rites, Pang Lhabsol, and Losser are some of the community’s major festivals. It is no surprise that the Rathong Chu River is a focal point for religious rituals. The holiest of all festivals, Bum Chu rituals, are celebrated yearly at the Tashiding monastery and are meticulously planned. Water is gathered from the place where Rathong Chu joins the Ringnya Chu, and the river is intended to become white and start singing. Thousands of worshippers from Sikkim and the surrounding area are enthralled by it. During “Pang Lhabsol,” a popular ceremony is performed to satisfy the Khangchendzonga’s different governing deities. In the nineteenth century, the Nepalese who make up the majority of the Sikkimese people moved from Nepal. They have developed a cultural identity because of the ethnic fusion that resulted in Sikkimese. They wore unique outfits and spoke Nepali and Hindi. Nepali ladies wear a Sari (gunyu) that is tied around their waist like a skirt and covers their torso with a blouse (cholo). A two-meter-long majetro, a kind of scarf, protects the head. Locals name this outfit Fariya cholo or Gunyu cholo. Dawra (shirt), Surwal (trousers), coat, and Nepali hat are worn by Nepali males. Desai is the Hindu Nepali’s most important and widely observed festival. Tiwar is the

34

2 Biophysical and Socio-economic Characteristics

Table 2.6 Religious (%) aspect of Sikkim Himalaya Districts

Hindu

Muslim

East

62.74

2.19

Christian 8.25

Sikh

Buddhist

Jain

Others

Not stated

0.30

25.55

0.08

0.61

0.29

South

57.60

1.29

14.61

0.10

23.87

0.03

2.16

0.33

West

55.18

0.71

9.53

0.03

26.67

0.01

7.68

0.19

North

34.05

1.86

6.09

1.87

53.25

0.08

2.11

0.60

Sikkim

57.76

1.62

9.91

0.31

27.39

0.05

2.67

0.30

other important celebration (the festival of light). The Goddess Laxmi is worshipped throughout this occasion. On this day’s evening, ladies of all ages go door to door singing Bhailo and receiving Bhaili offerings of money. On the third day, sisters bless brothers, and male folk sing Deoshirey door to door in the rural community.

2.3.2.4

Religion

The Sikkim people have exceptionally high religious and spiritual values and also believe in animism. Of the total state population, the major religious group is Hindus followed by Nepalese, which contributes 58%. Buddhism is followed by 27% and Christianity by 10% (Table 2.6). The remaining population follows Muslims, Sikhs, Jains, and other religions. The government of Sikkim also takes care of the religious aspect of the society and the conservation and preservation of monasteries and their rituals affairs are governed by the Ecclesiastical Affairs Department. The Lepcha community strongly believes in animism. This is the main reason that Sikkim’s lakes, forests, and natural heritage are sacred and preserved carefully.

2.3.2.5

Fairs and Festival

Festivals are an important aspect of Sikkimese life and every community in the state is known for its exuberant participation in social and religious functions. Sikkim is socially extremely vibrant and has intense bonding between various ethnic groups. Sikkimese festivals can be easily sorted into social and religious groups. Most of the festivals are deeply rooted in religious beliefs or have socio-cultural significance. Religious festivals can be categorized according to the dominance of the strong religious groups, for example, Buddhists, Hindus, and Tribal festivals: Buddhist Festivals: The Tibetan New Year’s Day or Losar, Bumchu, Lhabab Duechen, Saga Dawa, Drukpa Teshi. Hindu Festivals: Maghe Sankranti, Kusey Aunsi, Dasai, Bhimsen Puja, Bhai Tika. Tribal Festivals: Losseng, Pang-Labh Sol, Tendong Lho Rum Faat, ChasokThishok, Yokwa, Limbu’s New Year, Limbu’s Cultural Day, Sirijanga Birth Anniversary.

2.3 Cultural Characteristics

2.3.2.6

35

Food Habits

The principal food of the people of Sikkim is rice. The region is home to numerous tubers and seasonal vegetables which form an integral part of their daily diet. The Sikkimese are non-vegetarians, and beef and pork consumption are not uncommon except for a small group of the Hindu population. Alcohol use is rather widespread in all societies. The native brews Raksi and Chhang are made from rice and millet, respectively. Among the delectable fare, everyone enjoys Chhou-chhou, a Sikkimese version of Tibetan Chowmein. Gundruk, Kenema, and other regional dishes are also available. The Nepalis’ festive dishes include sel roti and phuralo. Sikkim maintains religious synchrony and cultural coexistence despite its extreme heterogeneity. Festivals are enjoyed with great enthusiasm and interest by everyone, regardless of ethnicity. The state is a one-of-a-kind example of cultural integration among all ethnic groups.

Box 2 The food habits of the people have drastically changed in recent years. However, the agricultural system remains to be dominated by maize and potatoes, maize is no longer the main food of the people. Virtually all households have swapped over to rice, yet the rice eaten by them is of poor quality. The people stopped eating maize long back. The factors which led to this change are: firstly, the decline in the productivity of maize, and secondly, an upsurge in both off-farm and on-farm engagement. Although more off-farm jobs became available in public works and government-sponsored programs, the on-farm employment openings acknowledged an improvement with the spread of the cultivation of large cardamoms. Thirdly, in recent years, the price of large cardamoms has increased quickly, and this has led to a rise in the incomes of the people. There is a saying in the area that if one has four kg of cardamoms, one can buy 40 kg of rice. Fourthly, the availability of rice, both throughout the public distribution system and in the open market, improved due to better infrastructural facilities such as roads. Fifthly, local people used to take maize in the form of a porridge meal and not as flour. The task of making maize flour is very tough and demanding.

2.3.2.7

Livelihood and Development Status

Sikkim’s The per capita income of Sikkimese people raised at an annual average rate of about 19% from 2004–05 to 2015–16, the maximum among Indian states and almost three times more than the national average of 6.7% per annum. By 2015–16, Sikkim was classified among the topmost five states in terms of per capita income. About 75% of Sikkim people live in rural areas. More than 60% of the population is dependent on agriculture and related industries, either directly or indirectly. The

36

2 Biophysical and Socio-economic Characteristics

rest is reliant on the manufacturing and service industries. Terrace farming is mostly used to cultivate maize, rice, and buckwheat, with channel irrigation serving as the primary supply of water. Due to the lack of modern technology, the typical output is significantly lower than the national average. Other challenges include the mountainous terrain and sparse infrastructure, as well as a lack of input supply and market support. As a result, Sikkim is food insecure and must rely on grain imports from other parts of the country to feed its people. Sikkim is the world’s leading producer of large cardamom, accounting for more than 88% of India’s total output and half of the global output. However, due to a wide-scale disease attack on cardamom plantations across the states, large cardamom yield has declined in recent years. Animal husbandry is an alternative significant source of income in rural areas, with milk procurement increasing every year since 2007. Different sectors’ contributions to Sikkim’s gross domestic product have been steadily increasing. Between 2004 and 2016, the dramatic increase in the industry’s share of GDP from 29 to 68% contributed to the reduction in agriculture’s share of GDP from 18 to 8.6% and the service sector’s share of GDP from 53 to 24%. Agriculture, forestry, and fishing employed about 64% of the workforce in Sikkim in 2015–16, compared to 48.9% nationally. The commissioning of electricity plants during the 12th Plan Period, 2012–2017, is attributed to Sikkim’s exceptional increase in Gross State Domestic Product. During this plan period, the agricultural industry, particularly floriculture and horticulture, has performed magnificently (Tables 2.7, 2.8 and 2.9).

2.3.2.8

Poverty

The share of people living in poverty in Sikkim has decreased from 31.1% in 2004–05 to 8.59% in 2015. The multidimensional poverty index (MPI) identifies overarching deficits at the household level across the three dimensions of the Human Development Index (HDI) and depicts the average number of poor people and deprivations experienced by poor families. With an MPI of 0.150, Sikkim was ranked eighth (SHDR 2014). Improvements in health and nutrition have made the most significant impact on the low MPI value.

2.4 Infrastructure Facilities 2.4.1 Education According to the 2011 census, Sikkim’s literacy rate was 82%. Sikkim Manipal University, which is a collaboration between the state government and the Manipal Education and Medical Group, provides technical, health care, and science education throughout the state. Table 2.10 has detailed information about Sikkim’s educational facilities.

29

53

100

29

52

100

Industry

Services

Total

Source CMIE (2012)

18

19

Agriculture

2005–06

2004–05

Parameters

100

53

30

17

2006–07

100

54

30

16

2007–08

Table 2.7 Percent contribution of different sectors to Sikkim’s GDP

100

51

35

14

2008–09

100

36

55

9

2009–10

100

37

55

8

2010–11

100

33

59

8

2011–12

100

23.7

67.7

8.6

2015–16

2.4 Infrastructure Facilities 37

38

2 Biophysical and Socio-economic Characteristics

Table 2.8 Sectoral real growth rate of gross state domestic product in Sikkim (%) Parameters

2004–05

2015–16

Agriculture

18.71

15.55

Industry

28.72

33.91

Services

52.57

15.23

Total

100

100

Table 2.9 Occupational structure of Sikkim (%) Occupational structure Rural

Urban

Total

Male Female Total Male Female Total Male Female Total Primary

62

86

73

1

3

1

50

77

62

Secondary

16

5

11

25

10

20

18

6

13

Tertiary

22

9

16

74

88

78

32

18

26

Source NSSO (2014)

Table 2.10 Educational facilities in Sikkim, 2015–16 S. No.

Type of educational institutions

1.

University

Number 5

2.

College

3.

Senior secondary school

182

4.

Secondary school

179

5.

Primary school

406

18

2.4.2 Health The state of Sikkim possesses good healthcare services. In almost every health metric, the state outperforms the national average. A network of two community health centers, 24 primary health centers, and 146 sub-centers has been recognized by the state as a well-functioning primary health care system. 273 physicians and nine AYUSH practitioners are among those who provide health treatment.

2.4.3 Transport and Communication Sikkim’s total road length is 2624 km. National Highway NH-10 connects Sikkim to West Bengal and the rest of the country. The roads are maintained by the state Public Works Department and the Border Roads Organization (BRO). Around 80

2.4 Infrastructure Facilities

39

Table 2.11 Road network in Sikkim S. No.

Type of roads

1.

National highways

2.

State highways

3.

District roads

4.

Border road

Length (km) 309 702 1081 335

buses and 94 trucks/tankers are operated by Sikkim Nationalized Transport around the state. The state has one airport near Pakyong (Table 2.11).

2.4.4 Banking Facilities Financial support is the key factor in strengthening the status of livelihood and raising opportunities. Sikkim’s banking framework grew in the post-merger period with a fair and broad network. Central institutions like the National Bank for Agriculture and Rural Development (NABARD) and the Small Industries Development Bank of India (SIDBI) have also been operating in the state. In 1999, Sikkim State Cooperative Bank helped to raise deposits and share capital to implement projects and schemes for farmers and non-farmers. Sikkim State Co-operative Bank settled 3292 independent and 354 co-operative firms and distributed loans of the sum amount of Rs. 260 million. About 67% of the state’s population is availing of banking facilities.

2.4.5 Trade Flows The state exports high-value cash crops, such as large cardamoms, ginger, and oranges. These goods, marketed through the Siliguri market, were destined for Delhi and other important markets in the country and abroad. On the other hand, the state imports commodities such as rice and fresh vegetables. The state is at a deficit in the production of food grains, particularly, rice and wheat. In addition, the state also procures items like salt, sugar, and palmolein oil from the Food Corporation of India. It, however, should be noted that a considerable amount of food import is necessary because of tourists, security forces, and other migrants, i.e., estimated to be more than 100,000 a year.

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2 Biophysical and Socio-economic Characteristics

2.4.6 Hydropower Projects Sikkim has a vast potential for hydroelectric power generation. Most of the constructed hydroelectric power plants are micro-hydroelectric plants. The Rathong hydroelectric project of 30 MW is under construction near Yuksum. Most of the constructed hydroelectric projects in Sikkim have not been realized and some of them are running with little efficiency. As of March 2011, the state of Sikkim had a total installed power production capacity of 201.4 MW. Central utilities account for 149.3 MW of the installed capacity, while state utilities account for 52.1 MW (CEA 2016). Thermal power supplied 79.1 MW, hydropower contributed 75.2 MW, and renewable energy sources contributed 47.1 MW to the total installed power generating capacity. Sikkim has the biggest hydroelectric capacity of 8000 MW, with a strong base of 3000 MW, indicating a large expansion potential.

2.5 Land-Use/Cover Analysis Nearly 49% of the area of the state comes under forest (Table 2.12). The land available for cultivation was 9.22%. Barren lands cover about 11% and glaciers 29% of the area, respectively (Table 2.13 and Fig. 2.9). Since 2000, the agricultural land has decreased significantly due to the conversion into non-agricultural for development activities. The agricultural sector is crucial for the state’s economy and rural livelihood. The agricultural systems have remained largely rainfed and traditional with minimal inputs. Large cardamom plantations accounted for about 0.08%. The very high dependence of the state on central grants to finance its development plans may indicate the unsustainability of the whole process of development. However, Sikkim has enjoyed a special category status; the funds from the central government of India are likely to continue for some time into the future. By that Table 2.12 The percent of land under forest cover in Sikkim, 2015–16 Types of forest

Area (km2 )

(%)

2718

37.61

Deciduous

137

1.90

Scrub forest

46

0.63

670

9.27

3571

49.41

Evergreen/semi-evergreen forest

Forest plantation Total

2.5 Land-Use/Cover Analysis

41

Table 2.13 The percent of other land-use/land covers area in Sikkim Parameters

Area (km2 )

(%)

Scrub land

10

0.14

Crop land

666

9.22

6

0.08

Agricultural plantation

827

11.44

Gullied/ravinous land

17

0.24

Built-up area

23

0.32

Barren rocky

Surface water bodies Glacier

19

0.26

2087

28.88

Fig. 2.9 Land-use/cover map of Sikkim

time, the state might be able to harness its abundant resources such as hydroelectricity. Large cardamoms, which at present account for around three to four percent of the total non-tax revenue, and other high-value cash crops also have the potential to contribute to the state exchange.

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2 Biophysical and Socio-economic Characteristics

References Bhasin R, Grimstod E, Larsen JO, Dhawan AK, Singh R, Verma SK, Venkatachalans K (2002) Landslide hazards and mitigation measures at Gangtok, Sikkim Himalaya. Eng Geol 64:351–368 CEA (2016) Progress of on-going hydro-electric projects (in fulfillment of CEA’s obligation under electricity act, 2003). Hydro-project Monitoring Division, New Delhi. Q Rev 85, Aug 2016 CMIE (2012) www.cmie.com Retrieved 21 May 2021 Environmental State Report Sikkim (2007) Prepared by ENVIS CENTRE SIKKIM “On Status of Env. & its Related Issues”, Forests, Env. & WL Mgt. Dept., Govt. of Sikkim GBPIHED (2015) Progress in developmental planning for the Indian Himalayan region. G.B. Pant Institute of Himalayan Environment and Development, Kosi-Katarmal, Almora Gowloog RR (1998) The Lepchas of Sikkim. In: Rai SC, Sundriyal RC, Sharma E (eds) Sikkim: perspectives for planning and development. Sikkim Science Society and Bishen Singh Mahendra Pal Sing, Dehradun, pp 69–74 GSI (2012) Geology and mineral resources of the states of India. Geological Survey of India, Miscellaneous Publication No. 3, part XIX. Government of India, Sikkim Ives JD, Messerli B (1989) The Himalayan dilemma: reconciling, development and conservation. Routledge, London Khoshoo TN (1992) Plant diversity in Himalaya: conservation, and utilization. G.B. Pant Institute of Himalayan Environment and Development, Kosi-Katarmal, Almora Myers N (1990) The biodiversity challenges: expanded hotspots analysis. Environmentalist 10:243– 256 NSSO (2014) Reports of the national sample survey, Government of India Rai SC (1992) Sikkim: cultural heterogeneity. Hima-Paryavaran 4:9–10 Risley HH (1968) Gazetteer of Sikkim. Calcutta Sharma ML, Maheshwari BK, Singh Y, Singhal A (2012) Damage pattern during Sikkim, India, earthquake of September 18, 2011. In: 15th world conference on earthquake engineering, Lisbon, Portugal, 24–28 Sept 2012, p 10 SHDR (2014) Expending opportunities, promoting sustainability. Sikkim human development report. Govt. of Sikkim. Routledge, Taylor & Francis, London, New York, New Delhi Subba JR (2008) History, culture and customs of Sikkim. Gyan Publishing House, New Delhi UNESCO (2016) Four sites inscribed on UNESCO world heritage list, 15 July 2016. https://whc. unesco.org

Chapter 3

Climate Variability and Farmers’ Perception

3.1 Introduction Change in yearly temperature and precipitation is recorded all over the world. Increasing temperatures and changes in rainfall patterns are the foremost indicators of climate change. Change in climate affects biodiversity, ecology, agricultural production, and water availability (Sharma and Rai 2012; Chettri et al. 2012; Chaudhary and Bawa 2011) and triggers extreme weather events, i.e., frequent flooding and drought, heatwaves, shorter winters, and landslides. According to the Intergovernmental Panel on Climate Change (IPCC) study from 2014, poor nations are more vulnerable to the consequences of climate change due to their incapacity to adapt. Since agriculture is directly impacted by climatic factors, rural people with limited resources that rely on agriculture for a living are especially vulnerable to the consequences of climate change. Studies designate that variations in rainfall and temperature will decrease agricultural production over the coming decades (Stige et al. 2006; Falco et al. 2011). An upsurge in the occurrence and intensity of extreme events impacts agricultural productivity and food security (Alcamo et al. 2007). Studies indicate that mountains are more prone to food insecurity than plain areas. According to the IPCC (2007) report, about 5–30% of the decline in crop yield can be seen in the Himalayan region by 2050 due to warming. Erratic precipitation patterns, dryness, increase in drafts frequency and intensity, shorter winters, and increasing temperature are intensifying the vulnerability of mountain agriculture. Change in rainfall and temperature directly influences the cropping rotation and agricultural yields which further impacts the livelihood of farmers. Various studies have shown significant changes in temperature and rainfall patterns in the Himalayan region (Mishra et al. 2013; Seetharam 2008; IPCC 2007; Du et al. 2004; Shrestha et al. 1999). In the upper Satluj basin of the Western Himalaya, Collins et al. (2013) reported a 30–40% decline in monsoon

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 S. C. Rai, Food and Livelihood Securities in Changing Climate of the Himalaya, Human-Environment Interactions 9, https://doi.org/10.1007/978-3-031-22817-9_3

43

44

3 Climate Variability and Farmers’ Perception

precipitation from the 1960s to the 2000s. The average annual temperature increase rate in Nepal since the 1970s is 0.06 °C per year (Sharma and Tsering 2009; Shrestha et al. 1999) the rate is highest in winter than in summer. The rate of rising is more prominent in the High and Middle Himalayas (Xu et al. 2009). Similarly, a temperature increase rate of 0.01–0.0158 °C per year has been reported in the Kanchenjunga landscape of Sikkim Himalaya (Chettri et al. 2012). Climate change is likely to have a significant impact on rural populations that rely on natural resources for their livelihood (ICIMOD 2011). Subsidence farming is practiced by the majority of the farmers in the Himalayan area, and agriculture is the primary source of income. Climate change affects people’s ability to adapt to them varies by site and situation (Smit and Wandel 2006). Climate changes are an important issue globally and understanding the rate of change and its impact on the local and regional level would help researchers and policymakers to predict its impact on the livelihoods of local communities. Studying people’s perceptions of climate is important to understand how they would respond to changes in climate (Vedwan et al. 2001). Sometimes people’s perception of climate change is different from observational shreds of evidence (Rebetez 2004) as the perception of an individual can be influenced by numerous factors such as occupation, gender, age, and access to the information (Chaudhary and Bawa 2011). Hence, it is important to study people’s observation of climate variation along with the actual rate of transformation based on meteorological data. Perception of climate variation highly determines the adaptive strategies for agriculture, environmental and Farmer’s observation of climate variation determines their adaptation approaches. As a result, while developing adaptation techniques, farmers’ knowledge and perceptions should be taken into account (Xu and Grumbine 2014; Xu et al. 2009). The present chapter aims to understand farmers’ perception of climate change and their adaptive policies along with the actual rate of climate change, based on 32 years of temperature and precipitation data. The study is conducted based on climate data collected from IMD and questionnaire survey data collected from 300 households in Sikkim from 2018 to 2021.

3.2 Materials and Methods 3.2.1 IMD Data The temperature and precipitation data of Sikkim were acquired from the Indian meteorological department. The data consist of daily temperature and precipitation for 32 years collected from Gangtok station. Missing data were computed using the method suggested by Bhutiyani et al. (2007) by averaging the data of ± 2 years of missing months. Analysis of the data was done in excel to extract the average

3.3 Results and Discussion

45

annual maximum, minimum, average annual temperature, and precipitation. Nonparametric tests of Mann Kendall and Sen’s slope were calculated to check the trend of annual temperature and precipitation using R software. Sen’s slope estimator was recommended by Sen in 1968, and it is the estimation of the regression coefficient constructed on Kendall’s Tau. Both tests are less affected by the outliers in data and they have been widely used in various studies. The significance of the tests was 95%, and the results are compared to other studies conducted in the name region.

3.2.2 Questionnaire Survey The questionnaire survey was performed in 20 villages of Sikkim covering three ecological zones, i.e., lower ecological zone, middle ecological zone, and higher ecological zone (Fig. 3.1). All the zones are divided based on altitude, vegetation type, and climatic conditions. The lower and middle zones are the most habitated and all the major agricultural practices are practiced in these ecological zones due to suitable climatic conditions. The higher zone has less population and the most prominent agricultural practice is traditional agroforestry. The main aim of this survey was to understand the farmer’s perception of climate change, their adaptive strategies, problems faced by farmers, and the role of govt. in helping farmers. The survey was conducted on 300 households and focused on the socio-economic indicators, farmer’s awareness of climate variation, the occurrence of climatic hazard, major crops grown, change in cropping pattern, types of farming systems and practices, functions of farming practices, agricultural inputs, the reason behind the changing pattern in the yield, adaptive strategies and plans or policies that have brought changes in the socio-economic conditions of the farmers. Farmers also suggested some steps for the improvement of socio-economic condition that is adaptive to climate change.

3.3 Results and Discussion 3.3.1 Assessment of Climate Variability Sikkim Himalaya contains more than 100 glaciers and the region is also recognized to be a part of biodiversity hotspots thus making it a climate-sensitive zone. Monitoring climate change and its impact on the region is not only significant to study the biophysical, atmospheric, and environmental changes but also to measuring the effect on the livelihood of local communities that are majorly dependent on

46

3 Climate Variability and Farmers’ Perception

Fig. 3.1 Agro-ecological zone map of Sikkim

agriculture and its allied activities. Few pieces of research have supported understanding climate change in the Sikkim Himalayan region. Seetharam (2008) shed light on patterns, effects, and initiatives of climate variation in the Sikkim Himalaya. Rahman et al. (2008) found an increasing trend of 1.95 °C in average annual minimum temperature from 1981 to 2010. Another study conducted by Sharma and Shrestha (2016) focused on the perception of local communities on climate change. They also

3.3 Results and Discussion

47

attempted to confirm the results with the trend of meteorological data. Kumar et al. (2020) tried to do a trend analysis of long-term climate data from 1961 to 2017 of Gangtok and Tandong weather stations and found a rising tendency in annual mean minimum temperature, while a decreasing trend in annual mean maximum temperature. However, there is still a significant need for data on farmers’ perceptions of climate change, as well as their readiness and adaptation strategies. As a result, we analyzed 32 years of temperature and precipitation data to try to understand the climatic change in the region.

3.3.1.1

Temperature Variability

The normal yearly minimum temperature recorded in the study ranges from 12 to 15.19 °C. While the average annual maximum temperature ranges from 18.50 to 24.25 °C, the mean annual temperature ranges from 15.44 to 19.61 °C (Fig. 3.2). The maximum annual temperature of 24.25 °C was recorded in 1998 on the other hand minimum temperature of 12 °C was recorded in 1987. In the present study trend of yearly maximum temperature and temperature yearly minimum temperature shows a decrease in temperature, whereas the average annual temperature shows no trend. Seetharam (2008) reported a − 0.003 °C/decade decrease in the mean maximum temperature and a 0.2 °C increase/decade in the mean minimum temperature.

3.3.1.2

Precipitation Variability

Maximum precipitation is received from May to September with maximum precipitation in June 573.4 mm. Minimum precipitation is received during the winter season from November to February with minimum precipitation in December 13.5 mm (Fig. 3.3). People in the region face severe water scarcity in the winter season. The average annual precipitation between 1986 and 2017 at Gangtok was found to be 3133.09 mm with the highest at 3769.5 mm in 1991 and the lowest at 2226.1 mm in 2016. The trend of annual average precipitation is given in Fig. 3.4. An increasing trend of precipitation can be seen in yearly annual precipitation. The years 1986, 1988, and 2016 received a minimum amount of precipitation of < 2600 mm while 1991, 2002, 2010, 2013, and 2015 received a maximum amount of precipitation of > 3600 mm. Rahman et al. (2012) found similar average annual precipitation between 1981 and 2010 at Tadong was 3097.78 mm.

3.3.1.3

MK Test and Sen’s Slope Analysis

Results derived from the MK test show a rising trend in annual precipitation while the average yearly maximum temperature shows a decreasing trend. P values of both are less than 0.05; hence, null hypotheses are accepted and there is a significant trend in the data. On the other hand, the annual average minimum and average annual

48

3 Climate Variability and Farmers’ Perception

Temprature in degree celcius

Average Maximum mean Temp 30.00 25.00 y = -0.1649x + 352.05 R² = 0.6362

20.00 15.00

10.00 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015 2017 Year

Temprature in degree celcius

Average Minimum Annual Temp 15.00

y = 0.005x + 3.5163 R² = 0.0029

10.00 5.00 0.00 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015 2017 Year

Temprature in degree celcius

Average Annual temperature 25.00 20.00

y = -0.0799x + 177.79 R² = 0.3671

15.00 10.00

5.00 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015 2017 Year

Fig. 3.2 Average annual maximum, average annual minimum, and average annual temperature recorded at Gangtok from 1985 to 2016

temperature show > 0.05 P-value hence, no trend in the data. Sen’s slope is an estimation of the regression coefficient based on Kendall’s Tau and it indicates the magnitude of change. Sen’s slope value for the annual average maximum temperature is 01.4253 while for the annual average minimum and an average annual temperature it is 0.0038 and − 0.0680, respectively. The greater increasing trend of minimum temperatures and lower or no trend of maximum temperature in the Sikkim Himalaya and other northeast regions of India is found in various studies (Sharma and Shrestha 2016; Kumar et al. 2020) (Table 3.1).

3.3 Results and Discussion

49 Mean Monthly Precipitation

precipitation in mm

700.0

573.4

600.0

549.2 495.0

500.0

424.4

400.0

384.9

303.4

300.0 200.0

159.9

117.2

100.0

50.0

18.7

46.9

13.5

0.0

Months

Fig. 3.3 Mean monthly precipitation data of Gangtok from 1985 to 2017

precipitation in mm

Annual Precipitation 4000 y = 11.844x - 20567 R² = 0.0745

3000 2000 1000 0 1985

1990

1995

2000

2005

2010

2015

Years

Fig. 3.4 Average yearly precipitation data from 1985 to 2017

Table 3.1 Trends of annual temperatures (°C) and precipitation (mm) at Gangtok (1985–2016) using the Mann–Kendall trend test and Sen’s slope estimator Variables

Z

Max T

− 4.0379 0.000054

Min T

0.3729 0.7092

0.0038

− 1.5081 0.1315

− 0.0680

Average T Annual precipitation

P-value

1.9622 0.04974

Sen’s slope

S

Var S

01.4253 − 250.000

1.525

Tau

Trend

3802.6666 − 0.5040 Negative

24.0000 3802.6666

0.0483 No trend

− 94.0000 3802.6666 − 0.1895 No trend 122.0000 3802.6666

0.2459 Positive

3.3.2 Farmers’ Perceptions and Adaptive Capacity 3.3.2.1

Socio-economic Status of Respondents

The socio-economic condition of the respondents was documented to study the household structure of the farmers and their source of income, the types of houses they live in, their religious background, their income, landholdings, etc. Data collected

50

3 Climate Variability and Farmers’ Perception

regarding the socio-economic conditions of the 300 households are presented in Table 3.2. Most of the respondents were Hindus, followed by Buddhists and Christians. The sampled survey shows that out of 300 households, 235 were Hindus, 41 were Buddhist, and 24 were Christians, which is 78.3%, 13.7%, and 8%, respectively. Most of the farmers in the area practice subsidence farming and the average area owned by farmers are 0.8 ha. Farmers in the area can be categorized into three different categories based on the size of their landholding, i.e., Marginal (< 0.5 ha), Medium (0.5–1 ha), and Large (> 1 ha). The family structure of the households in the lower ecological zone is 57% nuclear and 43% joint, while in the middle zone, it is 59% and 41% and in the higher ecological zone, 36% nuclear and 64% joint. Nearly, 40% of houses in all the ecological zones are made of pakka material and 40% are made of semi-pakka material and the rest were made of kachha material. The major source of income for the respondents was agriculture and livestock (63%) in the lower zone, about 66% in the middle zone, and about 92% in the higher ecological zone. The income of the farmers is majorly dependent on the size of landholdings, livestock, allied agricultural activities, and other sources of income. Income groups were divided into four categories, i.e., < 5000, 5000–10,000, 10,000–15,000, 15,000–20,000, and > 20,000. The average size of a household is 5 people.

3.3.2.2

Farmer’s Perception of Climate Variability

Major sources of knowledge about climate change among farmers are TV, newspapers, and other media sources. About 87% of respondents in the lower ecological zones are aware of the term ‘climate change’, while in middle and upper ecological zones, the awareness is 88% and 86%, respectively. Respondents in all ecological zones agreed to experience an increase in temperature. When asked about the temperature change, a farmer stated that “in sunrays, it feels like plain areas now.” A common perception among the farmers is that they are experiencing this change for the last 10–15 years. Along with the temperature rise, about 92% of the farmers in lower ecological zones agreed to experience decreased precipitation while in the middle 92.7% and higher zone 100% of farmers agreed that there is a decrease in precipitation. According to the respondents, snowfall in the upper ecological zones has also decreased (100%). Nearly 67% of farmers in the lower ecological zone, 80% in the middle, and 82% in the upper ecological zones also agreed to experience an increase in a hailstorm. About 55% of farmers in the lower, 55.3% in the middle, and 58% in the upper ecological zone stated experiencing an increase in thunderstorms (Table 3.3).

3.3.2.3

Climatic Hazard

Climatic hazards are a major indicator of climate variability. The occurrence of various climatic hazards according to the farmers in different ecological zones is presented in Table 3.4. Landslides, seasonal droughts, and strong winds are the major

3.3 Results and Discussion

51

Table 3.2 Socio-economic status of the respondents Socio-economic indicators Religion

Hindu

Type of houses

Major source of income

Monthly income of the family

Family structure

Middle (n = 150)

Higher (n = 50)

84

118

33

Buddhist

9

19

13

Christian

7

13

4

0.8 ha

Area owned (mean) Farmers

Lower (n = 100)

Marginal (< 0.5 ha)

27

66

27

Medium (0.5–1 ha)

43

60

16

Large (> 1 ha)

30

24

7

Pakka

44

72

21

Kaccha

18

12

9

Semi pakka

38

66

20

Agriculture and livestock

63

99

46

Agriculture and daily wage 15

21

1

Agriculture and other (job) 22

30

3

< 5000

17

52

22

5000–10,000

43

44

9

10,000–15,000

13

25

12

15,000–20,000

6

13

5

> 20,000

21

16

3

Nuclear

57

89

18

Joint

43

61

32

5

5

5

Average size of household (person/HH) Table 3.3 Farmer’s perception of climate change Lower (n = 100)

Middle (n = 150)

Higher (n = 50)

Aware of the term climate change

87% yes

88% yes

86% yes

Change in temperature

100% increased –

100% increased –

98% increased 2% decreased

Change in precipitation

8% increased 92% decreased

7.3% increased 92.7% decreased

100% decreased –

Change in snowfall

–

–

100% decreased

Change in hailstorms

67% increased 33% decreased

80% increased 20% decreased

82% increased 18% decreased

Change in thunderstorms

55% increased 45% decreased

55.3% increased 44.7% decreased

58% increased 42% decreased

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3 Climate Variability and Farmers’ Perception

Table 3.4 Occurrence of climatic hazard Climatic hazard

Lower (n = 100)

Middle (n = 150)

Higher (n = 50)

Drought

39%

42%

62%

Waterlogging

18%

–

–

Flooding

23%

–

–

Strong winds

–

–

63%

Heavy frost

–

–

59%

Landslides

87%

85.3%

84%

hazard faced by farmers in the area. Landslides are prevalent in all the ecological zones while strong winds and heavy frost are more prevalent in the upper ecological zones. Various factors can trigger a landslide including biophysical and anthropogenic factors. The biophysical factors include the slope of the land, tree cover, and erratic and heavy precipitation while the anthropogenic factors include deforestation, construction of roads, and mining. Waterlogging and seasonal flooding are rare as the area has high-altitude mountains and sloping land, however erratic and seasonal heavy precipitation combined with water released from hydropower dams create waterlogging and flood-like scenarios in the lower ecological zones. A farmer stated that “water enters the home during excessive rains when dam gates open, due to excessive release of water from the reservoir cracks are created at home and land in the lower areas near river gets eroded.”

3.3.2.4

Change and Conflict

Farmers were asked to answer multiple questions regarding the change in climate and the conflict-like situation that they are facing. All these questions had the choice of answers between Yes or No (Table 3.5). About 92% of the respondents agreed to experiencing the unprecedented occurrence of mosquitoes in the upland. The majority of the respondents stated that it has increased in recent years due to increasing temperature. Apart from the increasing temperature, a reduction in the availability of water from jhoras and springs is also a major problem reported by respondents. About 99% of the farmers agreed to experience a reduction in water availability. In Sikkim, farmers experience seasonal water shortage as a serious issue. Store Dhara in Tharpu, West Sikkim, Elaichibari water source near Sadam, and Tuk Khola near Sumbuk, South Sikkim, Nag Dhara in Bhanu Gram, Rongli, and Gari Dhara in Central Pendam, East Sikkim are among the water springs that are drying up or have already dried up, according to most respondents. Our observation is very much like that of Sharma and Shrestha (2016).

3.3 Results and Discussion

53

Table 3.5 Proxy questions regarding climate change Change and conflict 1. Have you experienced the unprecedented occurrence of mosquitoes in the upland?

Yes/no 92% yes 8% no

2. Have you experienced a reduction in the water availability on jhoras and 99% yes springs? 1% no 3. Do you or your family member migrate to other areas?

36% yes 64% no

4. Is livestock a driving force of food security other than crop cultivation?

26.7% yes 73.3% no

5. Have you felt a shortage of fodder in recent times?

41.3% yes 58.7% no

53.3% yes 6. Do you believe that the changing trend is harming you and your livelihood options like crop production, livestock, and the environment? 2.7% no 44% have no idea

Nearly 41.3% of the farmers agreed to experience a shortage of fodder in recent times. Only 26.7% of the farmers agreed that livestock is a driving force of food security other than crop cultivation. Approximately 36% of the families agreed that one or more family members had relocated in pursuit of work or education. Furthermore, people’s responses to decreased rainfall, rising temperatures, and the frequency of mosquitoes throughout the winter season were shown to have a high level of reliability when compared to a decade before. Sharma and Shrestha made similar observations as well (2016).

3.3.2.5

Adaptive Strategies

Farmers in the Sikkim Himalaya are well attentive to the changing climate and most of them have already started adopting various strategies to combat climate change. During the survey, farmers were asked multiple questions related to changes in farming patterns, awareness of govt. policies, their role, and benefits, any landscape planning measure taken by the individual or government to improve water balance, if any crop-specific/region-specific adaptive strategy should be adapted to combat climate change? Is the integrated Pest Management program through FSS popular in your area? “Do they have access to Agricultural Technology Management Agency (ATMA), Departmental extension functionaries to get advisory”? “And do they know Kissan call center”? Farmers were asked to answer yes or no to most of these questions and their responses are shown in Table 3.6. About 70.70% of farmers think that they need to bring change in the farming pattern to adapt to climate change, however, most of them have no clear idea of how they should proceed to adapt to the change. Few farmers suggested that more dry crops

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3 Climate Variability and Farmers’ Perception

Table 3.6 Adaptive strategies reported by the farmers Adaptive strategies

Yes/no

1.

Do you think you need to bring changes in the farming pattern to adapt to climate change

70.7% yes 29.3% no

2.

Any of the training given to you through e-media or on-farm demonstration regarding crop management and storage?

65.3% yes 34.7% no

3.

Any recycling technique adapted through organic farm waste?

38.7% yes 61.3% no

4.

Do govt. policies favor your crop and can you avail of those benefits?

33.3% yes 66.7% no

5.

Are you aware of any government plans and policies?

48% yes 52% no

6.

Is there any landscape planning measure taken by the individual or government 52% yes to advance the water balance (e.g., change of land-use, reforestation) of the 48% no village?

7.

Do you think that crop-specific/region-specific adaptive strategies should be adapted to combat climate change?

8.

Is the integrated Pest Management program through FSS popular in your area? 20% yes 80% no

9.

Do you have access to Agricultural Technology Management Agency (ATMA) 16% yes Departmental extension functionaries to get advisory? 84% no

10. Do you know the Kissan call center?

78.7% yes 21.3% no

22.7% yes 77.3% no

should be grown, farmers should switch to more cash crops to increase revenue and the government should make sure that their crops will be sold at a good price. Farmers also stated that the crops grown in plain areas are cheaper and farmers find it difficult to sell their crops at the right price in the Siliguri market. Farmers agreed that govt. provides pipeline supply, however, there is still a lot of water problem in the majority of the areas. Only 48% of the farmers are aware of the existing government policies and only 16% of farmers stated that they have access to Agricultural Technology Management Agency (ATMA) Departmental extension functionaries to get advisory, while the other 84% are unaware of ATMA. The majority (77.30%) of farmers are not even aware of the Kissan call center. Hence, they cannot communicate their problems to the government or get advice from experts. • Any plans or policies that have brought changes in the socio-economic conditions of the farmers to date? Yes, most of the farmers agree that govt. provides pieces of training, seeds, and manure free of cost. However, the delivery of seeds and manure is not consistent. Some farmers also complain that the quality of seeds is not good, and they don’t use them for cultivation. Some farmers have also received greenhouse/polyhouse tents for farming and received training. However, most of them want more support from the govt.

3.3 Results and Discussion

55

• Some suggestions for the improvement of socio-economic condition that is adaptive to climate change? Some steps to improve the socio-economic conditions suggested by the farmers • • • • • • • • •

The water problem should be resolved. Better quality seeds and manure should be provided by govt. on time and regularly. Water and pest management are needed. Technology is required for better cropping. Govt. should organize meetings ward-wise and share knowledge. Livestock management is needed. No facilities for market price. Marketing of the organic crop is needed. Govt. role should increase and proper implementation is needed.

Several studies all over the world have indicated the negative effect of climate variation on livelihood options owing to the decreased agricultural production (Vedwan and Rhoades 2001; Lobell et al. 2011; Islam et al. 2014). Global surface temperature is predicted to be increased by 1.5–4.5 °C with an average of 3 °C by the year 2030 (WHO 1990; IPCC 1990). The rate of change in temperature and precipitation in the Sikkim Himalayan area has been observed in numerous research (Rahman et al. 2008; Seetharam 2008; Sharma and Shrestha 2016). Even little temperature variations in the high-altitude region would have an impact on drinking water supplies and plant growth. Climate change will have a significant impact on the availability of water and temperature, resulting in a seasonal and altitudinal shift in agricultural production. Assessment of the effects of climate variation on the livelihood and food safety of rural communities residing in mountain ecosystems is important for planning and policymaking to strengthen the preparedness and adaptation to cope with climate change. In the present study, it was found that rural communities are aware of the changes. Results of the survey indicate a good enough understanding of local communities regarding various aspects of climate change, i.e., changes in temperature, precipitation, and erratic rainfall. Farmers have started adapting new cropping patterns and agricultural practices to fight climate change. However, the level of adaptation and awareness highly depends on their socio-economic conditions. Poverty, small landholdings, decrease in water availability, low production, increasing agriculture input cost, and declining agricultural productivity are among the major problems faced by farmers in the region. Farmers with small landholding and low levels of income are more susceptible to the effects of climate variation. The ability to cope with the changes is highly dependent on the economic condition of the farmers. Climate variation is not only a danger to their livelihood from agricultural products, but it also impacts local ecology, local flora, and fauna, and water availability which greatly influence various aspects of their lives. Apart from the threat of severe impacts of climate change, there are multiple issues faced by the villagers such as cracks created while blasting during the hydropower project (east district) due to this once a year they have to repair homes due to cracks

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occurring after the hydropower project started. Monkeys are also a content threat to their crops in areas nearby forests. Often the crops are destroyed by monkeys and increasing pests and insects. Not getting fair prices for the crops and no marketing facilities are also major problems faced by the local farmers. Different alternatives to traditional agriculture are also explored such as floriculture, dairy farming, and greenhouse-based cash crops to enhance the livelihood of the farmers. More than 50% of the farmers are not aware of existing government plans and policies, however, many of them agreed that the local agricultural department provides free training and hybrid seed from time to time. More than 80% of the respondents were not aware of other schemes such as the Integrated Pest Management program and Agricultural Technology Management Agency. Only 22% of respondents are aware of the Kissan call center. Many of the government initiatives don’t reach the marginal farmers. Due to a lack of resources, farmers are bound to use their traditional knowledge of farming to cope with the changes; hence, farming is done according to the availability of natural and economical resources. Farmers have rich knowledge of traditional agriculture which should be conserved and used with present-day scientific knowledge to mitigate the impacts of climate variation. It is needed that policymakers focus on marginal farmers and provide more direct support.

3.3.3 Policy Initiatives to Raise Adaptive Capacity The key goal of policymaking must be to maintain or preferably raise adaptive capacity without compromising agricultural productivity. Farmers’ flexibility is vital to reinforce their capacity to adapt to climate change. The policy aim should be to raise the upper thresholds of tolerance instead of pushing farmers closer to those thresholds. Despite all ecological zones and sample villages belonging to the indigenous agrobiodiversity, mode of production, the analysis has revealed the heterogeneous nature of Himalayan farming. Therefore, it would be a mistake to work out the same agricultural policy for the whole state. Instead, local variations must be taken into consideration. A local-specific approach should be the leading star for state policymaking. Migration from villages to near urban towns is a common characteristic in all cases. A considerable number of households have members working outside the village. Villagers move to towns and cities to improve their economic conditions, but young people also wish to enjoy urban life. Young people are encouraged to take higher education which is not offered in villages. Hence, it is not only negative aspects that push people out of the villages but also a lot of pull factors that attract young boys and girls to the cities. Migration produces the irony that some people migrate because mountain farms are too small to employ all household members, but the very absence of some young members leads to labor scarcity during peak agricultural seasons.

3.3 Results and Discussion

57

All farmers in the present study are “peasants” in the sense that they yield only parts for their utilization and partly for the sale. Improvements in roads and infrastructure will ease the market access of rural communities and reduce transport costs and time. Fe farmers are already partly integrated into national markets, but often only as net importers of cheap flowers and horticultural crops. Better infrastructure will be of great help if these communities wish to become producers of niche products, foods, forest products, etc. that can generate local business and income. Historically, people have chosen village sites that were favorable in topography and climate. But these locations may no longer prove to be optimal when the climate changes. Cultivation may have to be moved upward to higher elevations and settlements relocated to less hazard-prone places. In the situation of changing climate, the state should be flexible and willing to rearrange borders between agricultural land and land allotted for other purposes. Water is a vulnerable unit in most Himalayan farming systems. Even if the volume of precipitation is projected to remain more or less stable throughout this century, the pattern will most probably change into more erratic rain and less snow. To secure access to water during critical periods in agriculture and raise the upper threshold of tolerance for water, farmers should be enabled to introduce water retention technologies. Presently, concrete tanks, as well as plastic tanks, are installed by farmers jointly or individually. Agricultural departments should provide farmers with necessary inputs, such as pipes, cement or plastic tanks, know-how, and credit to acquire the items. Agricultural extension officers/workers advise farmers about growth requirements of crop varieties, the proper amount of fertilizers applications, proper treatment of hybrid livestock, new seeds, etc. Indigenous ecological knowledge of farmers has proved superior to formal education regarding traditional crops and technologies, but it is inadequate in coping with the stream of new species which are continuously introduced everywhere in the Himalayas. Kiwi, mushrooms, cross-bred barley, hybrid cows, chemical fertilizers, and other new arrivals require knowledge that is not part of the indigenous repertoire. The importance of adequate extension services is obvious irrespective of farmers’ priorities. The extension services have some problems, viz., there is a mismatch between the gender of farmers and the gender of extension officers. Women are not only increasingly important in farming operations but also farm management and decisionmaking. Due to this development in the mountain regions, extension services and agricultural counseling should target women and their specific needs and priorities. But extension officers are still overwhelmingly men. If we assume that female farmers communicate better with other women, more female agricultural extension officers should be employed. The other problem is that in several cases, villages have never been in touch with extension officers who are usually located in district headquarters. Remote villages suffer from inadequate road connections. During monsoon seasons roads are frequently blocked and traveling to district headquarters is timeconsuming as well as expensive for poor farmers. In this condition, a mobile phone can be a solution. If extension offices establish a telephone service where farmers can call and ask for advice. The policy proposal is to establish a phone counseling service at District Extension Offices where farmers can ask for advice at any time during the day.

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Innovations are encouraged by farmers’ exposure to new technologies. NGOs sometimes invite farmers on study excursions to other places to inspire modernization. Women dominate agricultural decision-making in all sampled villages, and it would stimulate innovation if women are involved in excursion tours on agricultural learning. Therefore, government, local NGOs, and other allied departments should target women for agricultural study trips. Because innovations contribute to increased flexibility and hence adaptive capacity under certain conditions would improve households’ and communities’ ability to face future uncertainties and changing production conditions.

3.4 Conclusion The present study was an attempt to understand the changing climate of Sikkim Himalaya and the perception of people on climate change. Meteorological data from 32 years was used to understand the trend of temperature and precipitation. Results from the analysis of meteorological data indicate an increase in the yearly average minimum temperature and a declining average yearly maximum temperature. There is no major change in precipitation trend; however, erratic and untimely rainfalls have been experienced by farmers. Most of the farmers in Sikkim are conscious of the impacts of climate variation on agriculture and their livelihood. Climate variation is a major threat to marginal farmers of the region, small landholding, poverty, and limited sources of income make them most vulnerable to change. The overall condition of the large and medium-sized farmers is good due to strong traditional farming systems that have well adapted to the local climate and terrain. Farmers are changing their farming techniques according to the need and availability of recourses still more options of livelihood need to be explored and support from the local govt. is needed to mitigate the impact of climate change. Besides, traditional knowledge of local people on climate variation could help climate scientists and policymakers. The findings of this study can be expanded as valuable material for making village-level action blueprints and approaches to manage ongoing climate variation.

References Alcamo J, Dronin N, Endejan M, Golubev G, Kirilenko A (2007) A new assessment of climate change impacts on food production shortfalls and water availability in Russia. Glob. The Alps using satellite data. Int J Remote Sens 15:1733–1742 Bhutiyani MR, Kale VS, Pawar NJ (2007) Long-term trends in maximum, minimum and mean annual air temperatures across the north-western Himalaya during the twentieth century. Clim Change 85:159–177 Chaudhary P, Bawa KS (2011) Local perceptions of climate change validated by scientific evidence in the Himalayas. Biol Lett. https://doi.org/10.1098/rsbl.2011.0269

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Chettri N, Shakya B, Sharma E (2012) Understanding the linkages: climate change and biodiversity in the Kangchenjunga landscape. In: Arrawatia ML, Tambe S (eds) Climate change in Sikkim: patterns, impacts and initiatives. Information and Public Relations Department, Government of Sikkim, Gangtok Collins DN, Davenport JL, Stoffel M (2013) Climatic variation and runoff from partially-glacierized Himalayan tributary basin of the Ganges. Sci Total Environ 468–469:s48–s59 Du MY, Kawashima S, Yonemura S, Zhang XZ, Chen SB (2004) Mutual influence between human activities and climate change in the Tibetan Plateau during recent years. Glob Planet Change 41:241–249 Falco DS, Yesuf M, Kohlin G, Ringler C (2011) Estimating the impact of climate change on agriculture in low-income countries: household level evidence from the Nile Basin, Ethiopia. Environ Resour Econ 52(4):457–478 ICIMOD (2011) Glacial lakes and glacial lake outburst floods in Nepal. ICIMOD, Kathmandu IPCC (1990) Scientific assessment of climate change. Report of working group I of the Intergovernmental Panel on Climate Change (IPCC)-draft, May 1990. Available at http://www.ipcc.ch/ publications_and_data/publications_and_data_reports.shtml#1 IPCC (2007) Summary for policymakers. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Avery KB, Tignor M, Miller HL (eds) Climate change 2007: the physical science basis. Contribution of working group I to the fourth assessment report of the Intergovernmental Panel on Climate Change. Intergovernmental Panel on Climate Change and Cambridge University Press, Cambridge Islam MM, Sallu S, Hubacek K, Paavola J (2014) Vulnerability of fishery-based livelihoods to the impacts of climate variability and change: insights from coastal Bangladesh. Reg Environ Change. https://doi.org/10.1007/s10113-013-0487-6 Kumar P, Sharma MC, Saini R, Singh GK (2020) Climatic variability at Gangtok and Tadong weather observatories in Sikkim, India, during 1961–2017. Sci Rep 10:15177. https://doi.org/10. 1038/s41598-020-71163-y Lobell DB, Bänziger M, Magorokosho C, Vivek B (2011) Nonlinear heat effects on African maize as evidenced by historical yield trials. Nat Clim Change. https://doi.org/10.1038/nclimate1043 Mishra B, Babel MS, Tripathi NK (2013) Analysis of climatic variability and snow cover in the Kaligandaki River Basin, Himalaya, Nepal. Theor Appl Climatol 116(3–4):681–694 Rahman H, Karuppaiyan R, Senapati PC, Ngachan SV, Kumar A (2008) Mid-hills of Sikkim and strategies for mitigating possible. Arrawatia ML, Tambe S (eds) Climate change in Sikkim: patterns, impacts and initiatives. Information and Public Relations Department, Government of Sikkim. Rahman H, Karuppaiyan R, Senapati PC, Ngachan SV, Kumar A (2012) An analysis of past three decade weather phenomenon in the Mid-hills of Sikkim and strategies for mitigating possible impact of climate change on agriculture. Arrawatia ML, Tambe S (eds) Climate change in Sikkim: patterns, impacts and initiatives. Information and Public Relations Department, Government of Sikkim. Rebetez M (2004) Summer 2003 maximum and minimum daily temperature over a 3,300 m altitudinal range in the Alps. Clim Res 27:45–50 Seetharam K (2008) Climate change synthetic scenario over Gangtok. In: Arrawatia ML, Tambe S (eds) Climate change in Sikkim: patterns, impacts and initiatives. Information and Public Relations Department, Government of Sikkim, pp 1–18 Sharma G, Rai LK (2012) Climate change and sustainability of agrodiversity in traditional farming of the Sikkim Himalaya. In: Arawatia ML, Tambe S (eds) Climate change in Sikkim: patterns, impacts and initiatives. Information and Public Relations Department, Government of Sikkim, Gangtok, India, pp 193–218 Sharma RK, Shrestha DG (2016) Climate perceptions of local communities validated through scientific signals in Sikkim Himalaya, India. Environ Monit Assess 188:578. https://doi.org/10. 1007/s10661-016-5582-y

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Sharma E, Tsering K (2009) Climate change in the Himalayas: the vulnerability of biodiversity. In: Sharma E, Khadka I, Shakya B (eds) Biodiversity and climate change in the Himalayas. International Centre for Integrated Mountain Development (ICIMOD), Kathmandu, Nepal, pp 10–12 Shrestha AB, Wake CP, Mayewski PA, Dibb JE (1999) Maximum temperature trends in the Himalaya and its vicinity: an analysis based on temperature records from Nepal for the period 1971–94. J Clim 12:2775–2786 Smit B, Wandel J (2006) Adaptation, adaptive capacity and vulnerability. Glob Environ Change 16:282–292 Stige LC, Stave J, Chan K, Ciannelli L, Pattorelli N, Glantz M, Herren H, Stenseth N (2006) The effect of climate variation on agro-pastoral production in Africa. PNAS 103:3049–3053 Vedwan N, Rhoades RE (2001) Climate change in the western Himalayas of India: a study of local perception and response. Clim Res. https://doi.org/10.3354/cr019109 WHO (1990) Potential health effects of climatic change. World Health Organization, Geneva. Accessed at http://www.ciesin.org/docs/001-007/001-007.html Xu J, Grumbine RE (2014) Integrating local hybrid knowledge and state support for climate change adaptation in the Asian Highlands. Clim Change 124:93–104 Xu J, Grumbine ER, Shrestha A, Eriksson M, Yang X et al (2009) The melting Himalayas: cascading effects of climate change on water, biodiversity, and livelihoods. Conserv Biol 23:520–530

Chapter 4

Spatio-temporal Change Delineation and Forecasting of Snow/Ice-Covered Areas

4.1 Introduction Sikkim is a tiny Himalayan state and is badly affected by climate change. The thawing and vanishing of the snow-covered areas in the state are of utmost concern. Climate change confirms fetches complications in the daily livelihood of the local people as well as in the farm practices because the water supply in the mountainous areas comes from the snow cover, in most of the world. The weeks during the winter season, when the seasonal snow appears have marked a huge change in the snow cover area than of the previous years. Thus, the vanishing of snow cover and an increase in debris and glacial lakes has made it prone to hydrological activity which hinders the local climatic balance. Mountainous regions are more affected by the sun’s scorching heat due to the dominance of clear skies and the heat consumed by the snow-covering area also depends upon the slope, aspect, and shadow of the adjacent terrain. Snow cover is also affected by the above-circulating air masses. Snow-covered areas in most of the mountainous regions of the world have started receding in the past 100 years due to global warming (Hansen and Lebedeff 1978). In remote mountainous areas, the change in the areal extent of the snow cover can be a guide to assessing the status of climate change (Bolch 2007). One of the main reasons for using satellite data in snow and glacier study is its inaccessibility. Thus, Remote Sensing and Geographic Information System techniques are on the front foot to delineate the glacier and snow coverage regions. Satellite data plays important role in earth sciences to continuously monitor natural and physical processes (Kuter et al. 2017). The monitoring and understanding of the snow studies at the regional level have been improved significantly through satellite image interpretations. The Landsat sensors are the most efficient tool for mapping and monitoring snow cover changes and the snow cover outlines can be derived from several band ratio techniques (Paul 2002). The main product of the Global Land Ice Measurement from Space (GLIMS) program is the GLIMS Glacier database which is a spatio-temporal database. This freely available data has been used in the study as a reference for observing and delineating thick/perennial snow © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 S. C. Rai, Food and Livelihood Securities in Changing Climate of the Himalaya, Human-Environment Interactions 9, https://doi.org/10.1007/978-3-031-22817-9_4

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4 Spatio-temporal Change Delineation and Forecasting …

cover outlines. In this study, Landsat TM and OLI (30 m) and TIRS (100 m) sensor bands have been used to delineate the snow-accumulated areas. Satellite images of both accumulation and ablation periods have been used to see the changes in the percent of snow cover area. The geospatial techniques have been applied in this study and it solely depends on the existing and available databases like GLIMS and the several band combination techniques applied on the Landsat imageries along with ASTER GDEM. The snow boundaries were demarcated in this study based on the observed reflectance values of the images. Images of various time series were used to detect the changes in the areal extent of the snow-covered regions of Sikkim. Thus, change detection analysis has been done to delineate the snow-covered areas based on comparing different spectral bands of the images.

4.2 Materials and Methods 4.2.1 Data Source Landsat 4–5 TM, Landsat 8 OLI, and TIRS data have been used for the analysis. The Images of late November–March (Accumulation period) and October–early November (Ablation period) were taken into consideration, which were mostly cloud-free and the demarcation of snow- and ice-covered regions were not difficult. The peak ablation period from April to August is occupied by pre-monsoon and monsoon rains; hence, the images remain under cloud cover. Table 4.1 shows the acquired imageries with their details. Satellite imageries were processed in ArcGIS and ERDAS software and diagrams were made in MS Excel and SPSS statistical software. Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Map (GDEM) data have been used to analyze the slope and aspect of the terrain and to visually interpret the shadow areas in the satellite imageries, which is a common problem in hilly terrain like Sikkim. The slope is also Table 4.1 Details of satellite data acquired Date

Sensor

Spatial resolution (m)

30/11/1998

Landsat 4–5 TM

30

16/11/2000

Landsat 4–5 TM

30

22/11/2008

Landsat 4–5 TM

30

22/09/2009

Landsat 4–5 TM

30

15/11/2017

Landsat 8 OLI and TIRS

30 and 100

07/03/2018

Landsat 8 OLI and TIRS

30 and 100

01/03/2000–30/11/2013

ASTER GDEM

30

4.2 Materials and Methods

63

considered to be an important topographic parameter while observing the change in the snow cover (Hazra and Krishna 2019). DEM provides the proper visualization of snow surface change. The reliability and accuracy of DEM become challenging to some extent, especially when the area dominates with high slope and deep shadowing and the collection of ground truth data becomes necessary at such stage (Pope et al. 2007), thus, the automated extraction technique S3 (Saito and Yamasaki 1999) has been used for delineation of shadows and clouds from the snow. A time series analysis has been performed for the years 1998, 2000, 2008, 2009, 2017, and 2018 and forecasted. Several band ratio techniques have been tried along with Normalized snow index (S3), and Normalized Difference Snow Thermal Index (NDSTI) (Haq and Jain 2012) to delineate the snow- and ice-covered areas of the Sikkim Himalayas. The multispectral bands cover the red and green bands of the visible spectrum observing snow and cloud density as well as the Infrared spectrum to differentiate the earth’s surface properties. A newly approached Snow Index has been achieved using the TIRS (11) band of Landsat 8 combined with a visible (Red) band to visualize the thick snow- or ice-covered regions from other loose and dry ice and snow-accumulated areas, which has been addressed as Perennial Snow Index. The objective of this chapter is to investigate the change detection of the area from 1998 to 2018 and forecasts a simple trend line with the help of the observed results. Thus, this study deals with the demarcation of the boundary of the snow- and ice-covered regions through several band rationing indices and the Perennial Snow Index as a new approach to delineating the thick/perennial snow cover. Snow cover recognition through Landsat Image gives fruitful results to a large extent (Hall et al. 1992; Bayr et al. 1994).

4.2.2 Methods 4.2.2.1

Snow Cover Index (S3)

The comprehensive methodology has been shown in Fig. 4.1. This is the only index that can be used without any ground-based surveyed data or any other reference data and was proposed by Saito and Yamasaki (1999). It differentiates the pure snow pixels from the snow-covered vegetation. It uses the reflectance values of the RED (0.63–0.68 µm), NIR (0.77–0.90 µm), and SWIR (0.77–0.90 µm) bands, which contain the properties to discriminate soil and vegetation from snow pixels and also can penetrate through thin clouds. S3 combines these visible and infrared bands’ reflectance values that enhance the snow-covered pixels’ reflectance value from the vegetation-mixed pixels and reduce error (Khosla et al. 2011). S3 values > 0.18 are recognized as pure snow pixels, whereas to identify the vegetation under snow cover, the values range from 0.15 to 0.18 (Shimamura et al. 2006). The underlying equation calculates the S3:

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4 Spatio-temporal Change Delineation and Forecasting …

S3 =

NIR × (RED − SWIR) (NIR + RED) × (NIR + SWIR)

(4.1)

Other band rationing techniques, such as NIR/SWIR and Green/SWIR, were applied to the acquired images to delineate and also evaluate the quality of extracted snow-covered pixels from the Landsat imageries. These band rationing techniques provide good results when compared to the S3 index but have some restrictions, where the extracted snow pixels get mixed with the pixels bearing shadows. Thus, the result of the S3 index was taken into consideration and further processed to calculate the areal extent of the snow- and ice-covered regions of the Sikkim Himalaya. In this study, the S3 index extracted the pure snow- and ice-covered pixels with reflectance values > 0.22 and values ranging from 0.22 to 0.14 as freshly accumulated snow found in the extracted pixels of accumulation period images while values from 0.19 to 0.9 were for vegetation under snow cover and values < 0.9 as

DATA ACQUISITION

LANDSAT 4-5 TM &LANDSAT 8 OLITIRS

S3

DSTI

DATA VALIDATION

ASTER GDEM

ed (4)/TIRS (11) erennial Snow Inde

DEM

GLIMS Database

Slope Snow cover delineation

Delineate old and thick snow and ice outlines

Demarcating threshold value ranges for snow and non-snow pixels

Calculating Error Matrix

Aspect

Overlay

Inferences of Temporal Changes

Calculating the areal extent of snow- and ice-covered areas in different years

Time Serise Analaysis

Fig. 4.1 Flow diagram showing the methodological approach

4.2 Materials and Methods

65

non-snow-covered pixels for all the year imageries. The raster image was further converted to vector form and the area of the snow- and the ice-covered region was calculated. Furthermore, a post-processing step of eliminating isolated areas as well as mixed snow areas smaller than 0.5 km2 were eliminated from the study area. The entire process was done depending on the extraction techniques, DEM, slope, and reclassification. Manual delineation of the snow cover boundaries was avoided.

4.2.2.2

Normalized Difference Snow Thermal Index (NDSTI)

This NDSTI index proposed by Haq and Jain (2012) is useful for the delineation of snow and ice from the surrounding areas and also surrounding water bodies. It considers the high reflectance of snow in the visible spectrum and the high absorptive characteristics of the thermal band. This index involves the Blue band of the visible spectrum and the Thermal TIRS band. The TIR wavelength of 10.40–12.50 µm (Landsat TM band 6) and Blue wavelength of 0.45–0.52 µm (Landsat TM band 1) have been resampled and used for computation of NDSTI. The following equation calculates NDST NDSTI = VIS (Blue) − TIR/VIS (Blue) + TIR

4.2.2.3

(4.2)

Perennial Snow Index (PSI)

This is a newly proposed Snow Index achieved in this study, which separates the long-term deposited or thick snow-covered areas from the surrounding freshly accumulated snow. This band combination was applied to only one year of Imagery available during the Ablation period. It is easier to demarcate thick snowy areas from the surrounding frisky snow at the time of ablation. However, due to the 100 m resolution of the Thermal band, though a limitation arises, this technique of delineating Perennial Snow cover can be fruitfully used to demarcate the long-term deposited snow-covers combining RED and TIRS bands of Landsat 8. For the year 2017, a thermal band of Landsat 8, i.e., TIRS (11) of the 100 m resolution was resampled to a 15 m resolution by merging with panchromatic band 8 of 15 m resolution. Similarly, the visible band Red (4) of 30 m resolution was resampled to 15 m by merging with the panchromatic band. The index calculated the difference in reflectance observed in the visible band (Red) and the Thermal infrared (TIR) band divided by the sum of the two reflectances to determine the thick snow-covered area from the other accumulated snow. The reflection of the snow pixels varies in several contexts, such as depth, presence of water molecules in the snow, i.e., wet or dry snow, grain size, presence of debris, etc. Snow mapping can be done using visible bands as it has higher reflectance in the visible spectrum, in comparison with other areas. However, if given choices, it is better to select a band closer to the infrared spectrum as the blue and green

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4 Spatio-temporal Change Delineation and Forecasting …

bands reach near saturation at higher sun angles losing details of the snow region with other earth surface features. In this study, the thermal band was used solely to identify the snow- and ice-covered boundaries from the rest of the hilly terrain in Sikkim, combined with the red band. PSI =

4.2.2.4

RED (BAND 4) − TIR (BAND 11) RED (BAND 4) + TIR (BAND 11)

(4.3)

Time Series Analysis and Forecast

Time series analysis was performed for the years 1998, 2008, 2008, 2009, 2017, and 2018 to show the trend line depicting the areal extent of the snow and icecovered areas for both accumulation and ablation periods and forecasting the future areal extent till the year 2030 in the SPSS software, with the help of Forecasting Traditional Model. In this study, apart from using the band rationing techniques, Perennial Snow Index, S3 index, and NDSTI index, for extraction of snow pixels, mixed pixels, and thick snow cover pixels, Global Iceland Measurement from Space (GLIMS) program data in the form of shapefile was availably demarcating the glacier outline and the study area which was used as a reference to corroborate with the thick snow-covered extracted pixels from the applied indices. It was taken into consideration to generate basic information and knowledge about the location and areal extent of the snow cover regions in the study area. The GLIMS database is accessible worldwide and provides glacier footprint layers.

4.3 Results and Discussion 4.3.1 Snow Cover Index (S3) The S3 index applied to extract the snow-covered area shows a recession in the outline of snow- and ice-covered regions from the year 2000 to 2009 and 2017. These three years’ images were acquired during the ablation period mainly in October and early November, subject to the availability of cloud-free data. The results show an area of 1103.19 km2 , 958.81 km2 , and 392.04 km2 in the year 2000, 2009, and 2017, respectively, which comprise 15.55% (2000), 13.51% (2009), and 5.52% (2017) of the total geographical area of 7096 km2 of Sikkim. Similar extraction was performed for the years 1998, 2008, and 2018. These three years’ images were of the accumulation period, two images of late November (1998 and 2008), and one of February (2018), subject to the availability of cloud-free data. Results show a decline in the snow- and ice-covered regions. The year 1998 shows

4.3 Results and Discussion

67

Table 4.2 The calculated S3 index values for the snow and ice-covered regions of the respected years Date

Seasons/zones

Area (km2 )

Snow cover area (%)

30/11/1998

Accumulation

1251.34

17.63

16/11/2000

Ablation

1103.91

15.55

22/11/2008

Accumulation

1096.33

15.45

22/09/2009

Ablation

958.81

13.51

07/03/2018

Accumulation

528.94

7.45

15/11/2017

Ablation

392.04

5.52

an area of 1251.34 km2 , while 2008 demarcates an area of 1096.33 km2 and in the year 2018, the area is 528.94 km2 , which comprises 17.63%, 15.45%, and 7.45% for the years 1998, 2008, and 2018, respectively. The details of the values acquired are given in Table 4.2. The following S3 values were overlaid and visually validated with the GLIMS data. A part of the snow-covering area has been shown in Figs. 4.2 and 4.3 to notice the drastic change in area from the year 2008 to 2018. The area of these two snow-clad regions has reduced to almost 50% (approximately). The other band combinations like TM (NIR/SWIR) and TM (Green/SWIR) through their reflectance properties extract and demarcate the Snow boundaries. The band ratio of NIR and SWIR bands shows a greater prospect than when NIR is combined with the Green band. The Green band shows a brighter (lighter) tone for

Fig. 4.2 The change in the extracted snow area applying the S3 index in 2008

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4 Spatio-temporal Change Delineation and Forecasting …

Fig. 4.3 The change in the extracted snow area applying the S3 index in 2018

barren land; thus, the debris-covered snow areas and the surrounding barren areas were visualized in a whitish tone beside the snow. The outcome of this index value describes that the extent of Snow coverage increases in the accumulation period images, while the ablation period set of images has a 2% decrease in the total areal extent of snow cover when compared to the accumulation period set of images. The images were available at gaps of 8–10 years, which is sufficient enough to find the difference in the climatic change indicator. The successive year images have shown a decline in the trend of the areal extent of snow cover. Due to the accumulation of snow in the winter from late November to early March the coverage region increases. The snow accumulates moreover on gentle to moderate slopes than on steep slopes (Hazra and Krishna 2019) and was observed overlaying DEM data for all the images. The northern slopes of the Himalayas receive sunlight during the daytime, while the scorching heat of the afternoon is faced by the southern slopes due to the orientation of the Sikkim Himalayas from east to west (Hazra and Krishna 2019). Thus, the northeastern, eastern, and southern slopes of Sikkim Himalaya show a drastic change in the snow coverage values from 2000 to 2017. Whereas most of the southeastern parts of the state hills previously covered by snow have been turned into Quarry grounds and mine-filled water ponds, which are sometimes misinterpreted as glacial lakes surrounding debris areas in the satellite imageries. In this study, the acquired images of October and November did not have cloud covers over the snow-covered regions but faced shadows due to the undulating topography of the Sikkim Himalayas. The S3 technique applied to these images demarcated

4.3 Results and Discussion

69

the shadow regions showing negative values. In that case, those areas were checked with the referenced data used in this study. Thus, if the shadow regions had snow cover, then it was added to the vectorized data, and the snow area of that particular region was delineated. The extraction of debris-covered snow areas using only Landsat Images did not provide a fruitful result, as it got mixed with the surrounding debris-covered barren lands (Paul 2002). Thus, in this study, the visible and infrared bands have been combined with the thermal band of Landsat 8 separately to determine the thick snow boundary from the surrounding dry or recent accumulated snow.

4.3.2 Normalized Difference Snow Thermal Index (NDSTI) NDSTI index was applied to the accumulation period images, especially to the years 1998, 2008, and 2018 images. For the year 2018, the blue band was band 2 and the TIRS band was band 11. The NDSTI is defined as the difference in reflectance observed in a visible band (blue) and the Thermal infrared (TIR) band divided by the sum of the two reflectances (Haq and Jain 2012). Thus, it does not include the spectral emissivity data of the Thermal band. Hence, this technique is applied to accumulation period images to easily identify the snow- and ice-covered areas but does not include water bodies near the snow cover areas. The extraction gave positive results demarcating snow- and ice-covered areas with values < 0.04 and water bodies with negative values. Glacial lakes have been delineated surrounding the thick snow cover areas, shown in Fig. 4.4a, b. The resultant area was like that of calculated S3 index values. Thus, as it does not include water bodies in extracting snowy regions, water bodies or glacial lakes surrounding snow cover regions can be easily differentiated. This index can be very useful but due to the coarser resolution of the TIRS band, it does not look good (Haq and Jain 2012).

4.3.3 Perennial Snow Index The Perennial Snow Index or PSI is a newly proposed index in this study, which demarcates the thick or perennial snow cover pixels from the surrounding mixed snow-covered pixels, along with freshly fallen snow pixels. This technique involves the difference in reflectance observed in a visible band (red) and the Thermal infrared (TIR) band divided by the sum of the two reflectances. The two bands Red (0.64– 0.67 µm) along with Thermal Band TIRS (11.50–12.51 µm) have been resampled to 15 m resolution after merging both the bands with Panchromatic band 8 of Landsat and getting the same resolution for acquiring better results. In this study, the threshold range values are selected from 0.33 to 0.42 based on the spectral values of the

70

4 Spatio-temporal Change Delineation and Forecasting …

a

Fig. 4.4 a The identification of water bodies through NDSTI surrounding the snow-covered areas showing a grayscale image of NDSTI. b The identification of water bodies through NDSTI surrounding snowy areas in Sikkim surrounding the snow-covered areas reclassified image for the year 2018

extracted pixels, which show pure thick snow- and ice-packed areas around the surrounding other pixels. Figure 4.5a shows the grayscale image, where it’s seen that the brighter white colored thick/perennial snow- and the ice-covered region is visible vividly from its surrounding, for a better understanding Fig. 4.5b shows the reclassified raster image

4.3 Results and Discussion

71

where RED color shows the thick/perennial snow- and the ice-covered region and the surrounding whitish gray colored mixed-snow area is depicted in BLUE color. This index also has some restrictions, due to the usage of a 100 m resolution thermal band, but thermal bands are considered one of the best bands in delineating snowy boundaries from non-snowy boundaries. In a visible spectrum, snow and ice are highly transparent (Grenfell and Perovich 1981; Warren 1984), thus the reflectance of snow is not influenced by its grain size (Bohren 1983), rather it is sensitive to snow depth up to 0.5 m in the visible spectrum

a

High : 1 Low : -0.60384

b

Perrenial Snow Mixed Snow Snow/Debris

Fig. 4.5 a The grayscale extracted PSI image of the 2017. b The Perennial Snow Index (PSI) reclassified image of the year 2017

72

4 Spatio-temporal Change Delineation and Forecasting …

(Dozier 1987), especially interpreted through the ablation period imageries. Thus, in this study, the red band of the visible spectrum near to infrared band has been considered one of the bands for the PSI extraction technique to demarcate the thick snow cover outline. In the infrared spectrum grain size of the snow matters to a large extent than depth, this is the major reflectance clincher (Warren 1984). Ice is more reflective in the infrared spectrum than visible but often wet snow is less reflective than frozen snow (Koh 1986), this is because the optical properties of water in the near-infrared are similar to those of ice, except that water is more absorptive around 0.95 µm and between 1.3 and 1.4 µm while ice is more absorptive between 1.55 and 1.75 µm (Warren 1984). Thick and old snow may develop a compact crust increasing in moisture content, which will be less reflective in Near and Mid-infrared spectrums. Therefore, the red band and thermal band were opted to demarcate the thick or perennial snow outlines in this study. This extraction technique can be used for demarcating old and thick snowy boundaries using only remotely sensed data where there is a lack of field data and delineating from the surrounding thin snow and debris cover.

4.3.4 Time Series Analysis Time series analysis was performed with the values of all the year images used in the study. A time series helps in tracking the trend or movement of chosen data points at consistent time intervals and converts them to suitable information through forecasting future data. The biggest advantage of using time series analysis is that it can be used to understand the past as well as predict the future. Furthermore, time series analysis is based on past data plotted against time. The time series analysis was performed in SPSS software by preparing a line chart with the dependent variable as the areal extent values in km2 and the independent value as the years. The linear graph or the trend analysis performed in Fig. 4.6 is showing a decline in the trend from the observed values of the snow cover area for both accumulation and ablation periods separately. By the year 2028–2030, the observed predicted data in Fig. 4.7 indicates lower values than those recorded in 2018. This is the certainty of future snow melting, which might occur at an alarming rate if other climate elements impacting melting snow are not addressed. One of the key concerns of snow research is water scarcity in the next decades because 50–60% of the world’s population lives in mountainous areas and relies on snow water for existence. The melting of snow is a vital source of fresh water in the mountains, which is rapidly depleting. Thus, on a regional scale, monitoring snow-covered areas is also an essential economic factor.

4.3 Results and Discussion 1400

73

1251.34 1103.91

1200

1096.33 958.81

Area km ²

1000 800

528.94

600

392.04

400 200 0

1998

Accumulation Ablation

2000

2008

1103.91

1096.33

2009

2017

2018 528.94

1251.34

958.81

392.04

YEARS Accumulation

Ablation

Fig. 4.6 The general trend line based on the acquired areal extent values of snow cover extracted from the S3 index from 1998 to 2018

Fig. 4.7 The observed and forecasting trend line of snow cover extent from the year 1998 to 2030

4.3.5 Error Matrix The reference values were put in columns and the categorized values were put in rows to make an error matrix. The classified values are from the PSI image that was recovered, and the reference values are from the Landsat 8 image of 2017s Visible to Infrared Bands (ranging from 0.45 to 2.35 m). Various snow/ice-covered zones,

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4 Spatio-temporal Change Delineation and Forecasting …

Table 4.3 Error matrix table showing 3 different sample class values for PSI Classified

Reference Snow

Snow

Mixed-snow

Non-snow

Row total

49

6

3

58

Mixed-snow

9

22

6

37

Non-snow

7

4

19

30

65

32

28

125

Column total

such as accumulation, ablation, debris-covered, and water-on areas, have unique reflectance properties in the visible and infrared regions, which may be used to map the snow/ice and its various facies. Each class was given 20 training samples at random, and the results were interpreted based on the class values. Table 4.3 shows the spectral curves and visual interpretations for pure snow pixels, snow-mixed pixels, and non-snow pixels. Error matrix results for PSI have been shown in Table 4.4, which observes 75.38% producer’s accuracy in the sample class snow, while the accuracy of 84.48% is observed in user’s accuracy. The overall accuracy for the PSI is 72%. The overall accuracy is computed by dividing the total correct (i.e., the sum of the major diagonal) samples by the total number of samples in the error matrix (Congalton 2001). Similar matrices were prepared for S3 and NDSTI indices keeping reference data Visible to infrared bands for respective years. The overall accuracy for S3 was 78%, while NDSTI was 73% and the producer’s and user’s accuracy ranged from 69 up to 78%.

4.4 Conclusion When compared to satellite images from the previous two decades, snow is melting at a quicker rate. The snow cover change delineation method in Sikkim Himalaya has demarcated 17.63–7.45% during the accumulation period of snow and 15.55–5.52% during the ablation season from the years 2000 to 2017. As a result, it may be estimated that the area of snow and ice-covered regions in Sikkim Himalaya has changed by 10%. The two indices used to extract these photos both indicate a reduction in the snow cover outlines, and each index has its unique way of distinguishing pure snow pixels from mixed and non-snow pixels in the surrounding area. The findings show that the rate of melting of the snow cover is increasing, particularly in places with smaller areas than thicker coverage. Large glacial lakes have resulted from the retreat of such snow-covered areas. As a result, it is necessary to become familiar with the climate-controlling factors that will aid in the reduction of Snow melting. The Snow Cover Index (S3) is one of the most effective extraction techniques for processing Landsat TM and OLI imageries for both accumulation and ablation periods, and the resulting output has been used to evaluate change detection studies

Class value

19/28

Non-snow

0.75

0.68

0.69 67.86

68.75 19/30

22/37

49/58

49/65

22/32

Mixed-snow

Row total

Column total 75.38

User’s accuracy In %

Class value

Results

Producer’s accuracy

Snow

Class

Table 4.4 Accuracy assessment values of three different classes for the PSI

0.63

0.59

0.84

Results

63.33

59.46

84.48

(%) 90/125

Total sum in matrix

Sum of the major diagonal

Overall accuracy

0.72

Results

72

(%)

4.4 Conclusion 75

76

4 Spatio-temporal Change Delineation and Forecasting …

from 1998 to 2018. When compared to S3 values in defining snow and glacial waters, the Normalized Difference Snow Thermal Index (NDSTI), which was also used in the imageries of the various periods, produced good results for the ablation period (NDSTI does not mix snow and water pixels). The Perennial Snow Index (PSI) is a newly improved index for differentiating thick snow cover from nearby mixed snow or newly fallen thin snow cover. Due to the lower resolution of Landsat’s TIRS sensor bands, they cannot be used alone in snow studies; consequently, combining the TIRS band with the high snow reflectance visible red band generated a different result in this research. The approach proposed in this research of dividing the total of two reflectances by the difference in reflectance seen in the Red and TIRS bands yielded a 72% correct result. To prevent the water content in the ice crystals and thin snow sheet covers during the accumulation period, the approach was only used on a 2017-year image obtained during the ablation period in early November. This approach may now be used to effectively demarcate thick snow boundaries. GLIMS data was utilized as a visual reference to compare (as existing data) the generated output images and gain a basic understanding of the thick and old snowy areas. To determine the changing trend in the snow- and ice-covered region, time series analysis was used. The research revealed a decreasing trend line, as well as a forecasting line, showing lower values in 2028–2030 than in 2018, indicating a rapid reduction in the snow-covered region. Water is one of the most important resources. Freshwater scarcity will become a major concern, and mountainous areas will be more vulnerable to natural hazards such as floods, landslides, and other natural disasters. Climate change will put agriculture at threat. As a result, frequent updates of snow-covered regions must be done to measure changes in the snow and glaciers.

References Bayr KJ, Hall DK, Kovalik WM (1994) Observations on glaciers in the eastern Austrian Alps using satellite data. Int J Remote Sens 15:1733–1742 Bohren CF (1983) Radiative transfer of snow and bubbly ice. In: Optical engineering for cold environments. 1983 technical symposium east, proceedings of SPIE0414, Arlington Bolch T (2007) Climate change and glacier retreat in northern Tien Shan (Kazakhstan/Kyrgyzstan) using remote sensing data. Glob Planet Change 56:1–12 Congalton RG (2001) Accuracy assessment and validation of remotely sensed and other spatial information. Int J Wildland Fire 10:321–328 Dozier J (1987) Recent research in snow hydrology. Rev Geophys 25:153–161 Grenfell TC, Perovich DK (1981) Radiation absorption coefficients of polycrystalline ice from 400–1400 nm. J Geophys Res 86:7447–7450 Hall KD, Williams Jr RS, Bayr KJ (1992) Glacier recession in Iceland and Austria. EOS Trans Am Geophys Union 73(12):129–141. https://doi.org/10.1029/91EO00104 Hansen J, Lebedeff A (1978) Global trends of measured surface air temperature. J Geophys Res 92(11):13345–13372 Haq MA, Jain K (2012) Development of new thermal ratio index for snow/ice identification. Int J Soft Comput 1:2231–2307

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Hazra P, Krishna AK (2019) Spatio-temporal and surface elevation change assessment of glaciers of Sikkim Himalaya (India) across different size classes using geospatial techniques. Environ Earth Sci 78:387. https://doi.org/10.1007/s12665-019-8390-1 Khosla D, Sharma JK, Mishra V (2011) Snow cover monitoring using different algorithm on AWiFS sensor data. Int J Adv Sci Technol 7:42–47 Koh G (1986) Wavelength-dependent extinction by falling snow. Cold Reg Sci Technol 12:51–55 Kuter S, Gerhard-Wilhelm W, Zuhal A (2017) A progressive approach for processing satellite data by operational research. Oper Res 17:371–393 Paul F (2002) Changes in glacier area in Tyrol, Austria, between 1969 and 1992 derived from Landsat 5 Thematic Mapper and Austrian glacier inventory data. Int J Remote Sens 23:787–799 Pope A, Murray T, Luckman A (2007) DEM quality assessment for quantification of glacier surface change. Ann Glaciol 46:189–194 Saito A, Yamazaki T (1999) Characteristics of spectral reflectance for vegetation ground surfaces with snow-cover, vegetation indices and snow indices. J Jpn Soc Hydrol Water Resour 12:28–38 Shimamura Y, Izumi T, Matsuyama H (2006) Evaluation of a useful method to identify snowcovered areas under vegetation: comparisons among a newly proposed snow index, normalized difference snow index, and visible reflectance. Int J Remote Sens 27:4867–4884 Warren SG (1984) Optical constants of ice from the ultraviolet to the microwave. Appl Opt 23:1206– 1225

Chapter 5

Agriculture System and Agrobiodiversity

5.1 Introduction The widespread transformation of land in the Himalayan region is mainly through efforts to provide food, shelter, and products for human use. In Himalaya, more than 80% of the population has farming as a primary livelihood. The region is one of the global biodiversity hotspots, which serve as the source of ecosystems that directly serve more than 200 million persons in the region and indirectly serve 1.3 billion persons in downstream areas, with a total population of 3 billion people benefiting from food and energy produced in river basins (Schild 2008). Agrobiodiversity can be examined at three levels: (a) ecosystem diversity, (b) species diversity, and (c) genetic diversity. Within an area, “ecosystem diversity recognizes the diversity of living organisms’ systems in connection to their surroundings.” The diversity of species within an area is “referred to as species diversity.” The variation of genes within a species is “referred to as genetic diversity.” Biodiversity may be seen on three geographical levels (Whittaker 1960), viz., (i) alpha diversity, (ii) beta diversity, and (iii) gamma diversity. Alpha diversity is a measure of diversity within an environment. The number of species in a region is used to calculate it. The term “beta diversity” refers to the diversity of habitats. It represents how organisms react to changes in their environment. The number of species within an area is defined as gamma diversity, which is a measure of large-scale biodiversity. Agrobiodiversity is a type of biodiversity that contributes to the production of food and agriculture. “Agrobiodiversity” is described as “the range and variability of animals, plants, and microorganisms that are utilized directly or indirectly for food and agriculture, including crops, cattle, forestry, and fisheries” by the Food and Agricultural Organization (FAO 1999). It includes a diverse range of genetic resources (varieties and breeds), as well as food, fodder, fiber, fuel, and pharmaceutical species. Food, income, materials for clothes,

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 S. C. Rai, Food and Livelihood Securities in Changing Climate of the Himalaya, Human-Environment Interactions 9, https://doi.org/10.1007/978-3-031-22817-9_5

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5 Agriculture System and Agrobiodiversity

housing, and medicine are all provided by agricultural biodiversity. It also provides critical ecological services to humans, like nutrient cycling, pest and disease control, and pollination. The Sikkim Himalayan native agricultural system includes agro-ecological zone differences that encompass a range of ecosystem varieties from 300 to 5000 m above mean sea level. Settled agriculture predominates at mid-hills between 1000 and 2000 m elevation and is dependent on livestock. Due to extreme climate change, the state’s farmers are in serious trouble, in contrast to the previously prevalent causes of change impacting the lives and livelihoods of mountain peoples, such as political, social, and environmental factors. Unpredictability in the global climate is an additional concern that is directly hurting the multiplier effect of other transformational causes (ICIMOD 2010). The local people’s management of agricultural diversity serves a variety of purposes. A native farmer considers the land-use/cover pattern, aspects, soil fertility, water accessibility, and other factors while producing a variety of indigenous landraces on the farm for food security. Varieties related to the droughttolerant, disease-tolerant, residue of crops, agronomic yield, market potential, taste, and customs and rituals are all linked to the diversity of land-use/cover patterns. The agrobiodiversity of the region is made up of high-value local specialty crops, agroforestry systems, medicinal plants, integrated watershed management, spring and local water sources, and the Beyuls in the region’s cultural landscapes. The agroecosystems supply a variety of goods and services which are critical to the environment’s functioning. The ecosystem products and services in local habitats have provided opportunities for people to survive and are in great demand for lowlying people. They offer a natural landscape for recreation and freshwater for a variety of applications. Increasing demands for ecosystem goods and services place an extra strain on natural resources. Agricultural biodiversity, or the diversity of agroecosystems, crops, animals, and related husbandry techniques and knowledge, therefore plays a critical role. This chapter examines the overall pattern of agrobiodiversity and the agricultural scenario of the state.

5.2 Agriculture Scenario of Sikkim Agriculture, tourism, and related sectors continue to be important sources of income and constitute the foundation of the state economy. Remoteness, inaccessibility, fragility, and marginalization are all problems in the region. The cultivable area of the state’s total geographical area of 7096 km2 is around 1.09 lakh ha (about 16%) of the whole geographical area. With a total farmer population of 1.31 lakhs and 16,939 agricultural laborers, the net cultivated area is 79,000 ha (11.1%). Because just 11% of the land is irrigated, agriculture will be primarily rainfed in the future. However, the region receives a lot of rain (3250 mm/year), which falls for six months from May to October. However, due to the rugged terrain, the whole area cannot be used for

5.3 Agroecosystems of Sikkim

81

agriculture. Per capita holdings have decreased because of population increase and the fragmentation of farm land holdings. The average operational holding is 3.9 ha per person, compared to 0.69 ha nationally. Furthermore, because the forest controls around 81.28% of the state’s geographical area, the ratio of arable land to farming (cultivators and agricultural laborers) is just 0.74 ha per person. Agriculture is still practiced in the Himalayan area of Sikkim state. Farming is done on both terracing and non-terracing hill slopes. Chemical fertilizers and pesticides are no longer used, and farming is now organic by default. In 2003, Sikkim declared itself an organic state. Farming is generally centered on maize, paddy, and pulses, while the main cash crops are ginger, large cardamom, and mandarin orange. Livestock farming is the second source of income. Except for maize, mandarin oranges, and ginger, other crops have poor output and productivity compared to the national average. Indigenous farming methods continue to thrive in many locations, and agricultural techniques are passed down via families. Crops are grown in three seasons: Kharif, Rabi, and the remaining of the year. Pre-Kharif begins when the first showers appear in the spring. The time frame is February through mid-March. The only pre-Kharif crop is maize. During May and June, the Kharif season begins. During the Kharif season, farmers grow soybeans, paddy, urd, finger millet, different varieties of beans, ginger, and a few varieties of vegetables. Rabi season crops include wheat, mustard, sarson, rai saag, potato, pea, cabbage, cauliflower, radish, and carrot. The rabi sowing season runs from September to October. In the mid- and low hills, an agriculture-dominated mixed agricultural system covered around 81,320 ha of the overall geographical area of 709,600 ha. A large cardamom-based agroforestry system covers an additional 24,730 ha. About 23,270 ha, the area covered horticulture crops such as potato, vegetable, turmeric, and ginger are farmed. Nearly 7620 acres of horticulture crop-based (mandarin orange and apple) cultivation are successful. Around 200 ha of farmland are devoted to tea production. Alpine, sub-alpine scrub, and pasture land occupy 102,400 ha of the Reserve, Khasmal, and Goucharan forests.

5.3 Agroecosystems of Sikkim The Republic of India is home to a broad range of agroecosystems that are distinguishable by their lithology, soil, climate, vegetation, crop growth, and other characteristics. India has been divided into 21 agro-ecological zones based on topography, climate, soil characteristics, and growing season of the crop (Sahgal et al. 1992). One of the 21 agro-ecological zones is the Northeastern Hills, which includes Sikkim and has a warm, humid climate, red and lateritic soils, and a growing season of 210 days. Table 5.1 shows the agroecosystem of Sikkim Himalaya. Paddy, maize, finger millet, wheat, buckwheat, pulses, oilseeds, and cash crops such as ginger, orange, and large cardamom are the main crops grown in the state. In 2010, agriculture contributed approximately 16.30% of the state’s Gross Domestic Product, down from over 40% in 2001 (Sikkim Human Development Report 2001).

Above 5000

4000–5000

Alpine

Alpine

2700–4000

Subalpine

Very high hills

2000–2700

Temperate

High hills

1500–2000

Temperate

Mid-hills

Subtropical 500–1500

Snow-bound land without vegetation. Cultivable land is not available in this climatic type

Pastoral economy, yak herding

Remarks

Maize, barley, vegetables, potato, apple, plum, peach, peas, off-season vegetables, and large cardamom

Maize, paddy, finger millet, wheat, pulses like rice bean, rajma, beans, sarson, soybean, vegetables, potato, mandarin, plum, peach, pear, large cardamom, ginger

Vegetation is mainly herbs and medicinal plants

Apple, potato, and other horticultural crops

In the region cultivable land is not available, and precipitation is mainly through snowfall

Mainly used for pasturage

Snowfall is common during the winter months i.e., during December–January and heavy rainfall during June–July

Snowfall is common during winter (December–February) and heavy rainfall during June–July

This is the field and horticultural crops belt. Heavy rainfall during summer and dry and cold weather during winter is the feature

Paddy, finger millet maize, wheat, sarson, The climate is essentially subtropical urd, soybean, vegetables, potato guava, hence, suitable for subtropical crops ginger, mandarin, etc.

Crops

Yak herding, horticulture, pastoral Vegetables and seed potatoes are grown economy (wool, cheese, butter, hides, and in a few places potato are commercial commodities), livestock-yaks, sheep, horses, mules

Dry agriculture, livestock-cattle, yaks, sheep, horses, and mules are reared Lachung, Lachen, Damthang, Ravangla, Zabuk, Phadumchu, Hilley, Okhrey, Ribdi, and Bhareng are important cultivable areas of this climatic type

Wet and dry agriculture, rearing of goats, pigs, poultry, ducks, cattle, and sheep, growing of horticultural crops, collection of minor forest produce

Wet and dry agriculture, sedentary farming, horticulture, livestock rearing—goats, pigs, poultry, ducks, cattle, and sheep

300–500

Lower hills

Tropical

Altitude (m) Ecological adaption

Ecological zones Climate

Table 5.1 Agroecosystems of Sikkim Himalaya

82 5 Agriculture System and Agrobiodiversity

5.4 Analysis of Agrobiodiversity

83

Sikkim’s agro-climatic zone covers subtropical to warm temperate, cold temperate to alpine zones, all within short distances, resulting in a broad range of agroecosystems that support the state’s rich agricultural biodiversity (Table 5.1).

5.4 Analysis of Agrobiodiversity Agricultural diversity has afforded cultural, spiritual, religious, and aesthetic value to human societies while also designing the foundation for human food production systems. The agricultural diversity in the hilly areas faces inaccessibility, marginality, and fragility to bear its resilience. The indigenous arrangement of agrobiodiversity supervision practices represents adaptation devices established by local societies to adjust to the shifting climate variables over time. More than 190 wild edible food plants are found in the Sikkim Himalaya (Sundriyal and Sundriyal 2003). In addition to semi-domesticated wild edible plants like sweat gourd or Chuchey Karela (Cyclandra pedata), tree tomato or ramped (Cypomandra batacea), bee (Solanum incanum), ferns, and bamboo shoots, etc., are also found in the state. Sikkim cultivates approximately 69 species of food crops, vegetable, fruit, ornamental, and commercial crops (Table 5.2). About 5 varieties of cereal, 2 pseudo-cereals (buckwheat), 4 pulses, 5 oilseeds, 8 fruit crops, as many as 34 vegetables, 3 spices, and more than 8 species of ornamental flowers are reported in Sikkim Himalaya.

5.4.1 Crop Diversity in Sikkim Agricultural practices are carried out in Sikkim at elevations ranging from 300 to 2000 m. A vast range of micro-ecological niches are found, and agriculturalists can experience a variety of crop production techniques. Most food crops have a wide range of varieties, and local farmers own a substantial portion of the arable land. About 178 landraces are available among the 69 crop plants grown in Sikkim, according to an unsure estimate (Table 5.2). In Sikkim, paddy has a larger genetic diversity. In paddy, 43 landraces may be significant in the area. The occurrence of such a large number of cultivars in self-pollinated crops attests to the diversity of Sikkim’s ecosystem, as well as the producers’ selection and preservation efforts. Around 26 landraces of maize, including the Sikkim primitive maize, have been documented at the ICAR Sikkim Centre. Apart from this, there are 6 local cultivars of finger millet; 14 local cultivars of rajma, 7 rice beans, 9 each in chilies and chow-chow, 4 rai saag; and about 11 clones of large cardamom, 5 clones of ginger, and 4 clones of banana are being cultivated. Due to severe differences in height and climatic conditions, the hill’s amusing agrobiodiversity has evolved.

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5 Agriculture System and Agrobiodiversity

Table 5.2 Food and horticultural crops cultivated in the Sikkim Himalaya S. No.

Cultivated species

I

Food crops

Status

No. of local cultivars

Duration

1 2

Paddy (Oryza sativa)

Major crop

43

June–Sept

Wheat (Triticum aestivum)

Minor crop

Not known

Oct–Feb

3

Maize (Zea mays)

Major crop

26

Feb–June

4

Ragi (Eleusine coracana)

Major crop

6

June–Sept

5

Barley (Hordeum vulgare)

Minor crop

Not known

Oct–Feb

6

Buckwheat Minor crop (Fagopyrum esculentus and Fagopyrum tataricum)

1+1

June–Sept

II

Pulses

1

Urd (Vigna mungo)

Major crop

3

Aug–Oct

2

Rice bean (Vigna umbellata)

Minor crop

7

July–Oct

3

Rajma (Phaseolus vulgaris)

Minor crop

14

July–Oct

4

Mung (Vigna radiata)

Minor crop

1

Aug–Oct

III

Oilseeds

1

Rapeseed (Brassica campestris var. yellow sarso, brown sarson, toria) and Mustard (Brassica juncea)

Major crops

Not known

Oct–Feb

2

Soybean (Glycine max) Major crop

2

July–Oct

IV

Fruits

1

Mandarin (Citrus reticulate)

1

Fruiting in Nov–Jan

2

Peach (Prunus persica) Major crop

Not known

Fruiting in Feb–Apr

3

Plum (Prunus domestica)

Minor crop

Not known

Fruiting in Feb–Apr

4

Apple (Malus)

Minor crop

Not known

Fruiting in Feb–Apr

5

Strawberry (Fragaria ananassa)

Minor crop

Not known

Fruiting in June–Aug

Major crop

(continued)

5.4 Analysis of Agrobiodiversity

85

Table 5.2 (continued) S. No.

Cultivated species

Status

No. of local cultivars

Duration

6

Passion fruit (Passiflora edulis)

Minor crop

2

Fruiting in June–Aug

7

Guava (Psidium guajava)

Minor crop

Not known

Fruiting in Sept–Nov

8

Banana (Musa spp.)

Minor crop

4

V

Vegetables

1

Potato (Solanum tuberosum)

Major crop

Not known

Jan–Apr

2

Chilies (Capsicum annuum, Capsicum frutescence, Capsicum chinensis)

Major crop

9

May–Nov

3

Bhindi (Abelmoschus esculentus and Abelmoschus caillei)

Minor crop

4

May–Aug

4

Peas (Pisum sativum)

Major crop

2

Oct–Feb

5

Beans (Dolichos lablab)

Major crop

Not known

July–Oct

6

Butter bean (Phaseolus Minor crop lunatus)

3

July–Oct

7

Broad bean (Vicia faba)

Minor crop

Not known

Oct–Jan

8

Cowpea (Vigna unguiculata)

Minor crop

2

July–Oct

9

Tomato (Lycopersicon esculentum and Lycopersicon pimpinellifolium)

Minor crop

2 in pimpinellifolium

May–Aug

10

Cucumber (Cucumis spp.)

Major crop

2

May–Aug

11

Chow-chow (Sechium edule)

Major crop

9

Fruiting in Sept–Jan

12

Radish (Raphanus sativus)

Major crop

3

Oct–Dec

13

Pumpkin (Cucurbita moschata)

Major crop

3

May–Oct

14

Bottle gourd (Lagenaria cineraria)

Minor crop

2

May–Oct

15

Bitter gourd (Momordica charantia and Momordica subangulata var. renigera)

Minor crop

2

May–Oct

(continued)

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5 Agriculture System and Agrobiodiversity

Table 5.2 (continued) S. No.

Cultivated species

Status

No. of local cultivars

Duration

16

Cabbage (Brassica oleracea var. capitata)

Major crop

Not known

Oct–Jan

17

Cauliflower (Brassica oleracea var. botrytis)

Major crop

Not known

Oct–Jan

18

Broccoli (Brassica oleracea var. italica)

Minor crop

Not known

Oct–Jan

19

Tapioca (Manihot esculenta)

Minor crop

Not known

Feb–Dec

20

Sweet potato (Ipomoea Minor crop batatas)

2

May–Oct

21

Fenugreek (Trigonella foenum-graecum)

Minor crop

Not known

Oct–Jan

22

Rai saag (Brassica juncea var. rugosa)

Major crop

4

23

Taro (Colocasia esculenta)

Minor crop

Not known

Feb–Oct

24

Xanthosoma (Xanthosoma sagittifolium)

Minor crop

Not known

Feb–Oct

25

Coriander (Coriandrum sarivum)

Minor crop

Not known

Feb–Oct

26

Onion (Allium cepa)

Minor crop

Not known

Feb–Oct

27

Garlic (Allium sativum) Minor crop

28

Palak (Beta vulgaris var. bengalensis)

Feb–Oct

Minor crop

Not known

Sept–Feb

VI

Spices

1

Large cardamom (Amomum subulatum)

Major crop

11

Fruiting in June–Aug

2

Ginger (Zingeber officinale)

Major crop

5

Mar–Dec

3

Turmeric (Curcuma longa)

Major crop

2

Apr–Dec

VII

Flowers

1–3

Orchids, Gladiolus, Gerbera

Major crops

Not known

4–8

Rose, Anthurium, Marigold, Carnation, Glaxonia, Begonia, Tuberose lily, Chrysanthemum

Minor crops

Not known

Source After Rahman and Karuppaiyan (2011)

5.5 Analysis of Cropping Patterns

87

In addition to environmental factors and natural processes, the diversity that exists on-farm has been hampered by many socio-economic and cultural conditions that exist in agricultural cultures. Several ethnic groups with different socio-cultural favorites and necessities have paid attention to the diversity, and farmers have gathered a wealth of indigenous knowledge about these variations and the systems as a whole.

5.5 Analysis of Cropping Patterns 5.5.1 Food Crops Maize (Zea mays Linn.) Maize is the dominating crop in Sikkim Himalaya. There are four types of maize landraces in Sikkim: primitive, advanced, recent arrivals, and hybrid races. Several different races comprised the primitive group. These races may be found in the Eastern Himalaya and Sikkim, at altitudes of 600–2000 m. In the northern section of Sikkim, the most primordial race, Poorvi Botapa, may be found in its purest form. However, it is currently a critically endangered cultivar that has all but vanished from the agricultural landscape, but now it has become an endangered cultivar and gradually disappeared from farming. About 38,955 ha net sown area of the state is under maize crops. The South district reported the highest area (36%) and the lowest was recorded in the North district (7%) of the net sown area (Table 5.3). The area under the high-yielding variety of maize, such as NMH-51, and Swan-composite was 1725 ha. Table 5.3 The concentration of food crops in Sikkim (net sown area) Food crops

Districts

Sikkim total

North Area (ha)

South (%)

Area (ha)

East (%)

Area (ha)

West (%)

Area (ha)

(%)

Area (ha)

(%)

Paddy

920

9

1920

18

4813

45

3016

28

10,669

100

Wheat

50

15

110

34

143

44

20

6

323

100

Maize

2754

7

14,000

36

8991

23

13,210

34

38,955

100

Finger millet

609

21

700

25

833

29

711

25

2853

100

Barley

140

31

70

16

225

50

12

3

447

100

Buckwheat

211

6

1400

39

1227

34

732

21

3570

100

Source Department of Agriculture Cooperation and Farmers Welfare (2018)

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5 Agriculture System and Agrobiodiversity

Maize is the utmost vital principal food crop of the Sikkim state and surrounding hilly districts of West Bengal. It is locally known as ‘makai’ and in Hindi, it is called ‘Makka.’ The lower and mid-hills are best suited for maize. Its sowing begins from lower to higher altitudes. At lower elevations, sowing starts in February, i.e., before the transplantation of paddy, whereas, at higher elevations, sowing is done in April and May. At lower elevations (below 1000 m), it is possible to sow and grow maize as early as June, with rice, millets, and pulses, which are grown as the second crop whereas, at higher elevations, these crops are grown along with maize (Babu et al. 2016). Prominent local varieties of maize are Lachung Yellow (for Lachen and Lachung valley growing at 2500 m from mean sea level), Kukhrey (in hills at an altitude of 2600 m), Local White, Sathi, Poorvi Botapa, Tirap Nag-Sahypung, and Arun Tepi are the primitive landraces of Sikkim. The local white and yellow are widely accepted and are very tall and of long duration (150–180 days) and are also high-yielding varieties of maize. At present, in India, almost 13,059 varieties of germplasm (a complete set of the genetic material of maize used for desired purposes to improve plant varieties) maize are found, of which 554 are found in Sikkim alone and 271 are conserved. East district of Sikkim has the largest number of germplasms, i.e., 158 of which 91 are conserved while the South district has the lowest number of germplasms, i.e., 122 of which 57 are conserved. The least number of conserved germplasms of maize is in the West district which is 49, although 123 varieties of germplasm are found there. North district has the second-highest varieties of germplasm, i.e., 151 of which 74 are conserved. Conservation of germplasm is inherent in maintaining the aesthetic value of the natural ecosystem and the diversity of plant species (Pandey et al. 2015).

Maize diversity

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Maize is the principal crop in most crop rotations and mixed cropping. Maizewheat, maize-tori, maize-buckwheat, maize-paddy-potato, maize-millet, and maizepaddy-tori are the crop rotation usually practiced in the agricultural land of Sikkim. It was reported that maize with pulses is found to be advantageous for maintaining soil health (Ahloowalia et al. 1972). About 20% of maize is consumed when green. The mature grain is pounded like flakes and consumed like rice and also fully ground to make flour. Paddy (Oryza sativa L.) After maize, rice or paddy, in Hindi, locally known as ‘Dhan’ or ‘chamal,’ is the next important staple food crop of the Sikkim Himalaya known as ‘Demazong’— meaning ‘Valley of Rice.’ It is grown extensively from 300 to 1700 m above MSL. It is cultivated from May–June to October–November. The net sown area under paddy was recorded as highest (45%) in the East district and lowest (9%) in the North district of Sikkim (Table 5.3). Sikkim as a whole, the area under high-yielding varieties of paddy such as PD-12, 16, 18, CAUR-1, VL-65, and 82 was 1796.40 ha. Pre-Kharif rice is insignificant, but very few may be located only at lower elevations, such as Manpar, Teesta, and Rangit valleys where irrigation facility is available. In Sikkim, paddy cultivation is practiced on upland (also known as dry cultivation) as well as lowland (known as puddle cultivation), but highland paddy cultivation is not common, ‘Ghaiya dhan’ propagated on hillsides on the infrequent occasion is highland paddy (Babu et al. 2015). Dry field seeding and watered field seeding are the two main methods for paddy cultivation. The direct method is advantageous, as it protects labor by removing and transplanting processes as well as it does not suspend the progress of plants in the case of uprooted saplings. Although this method is advantageous, even though it is not practiced since paddy is cultivated in minor terraces, depends on spring water for irrigation. Throughout Kharif, it is not feasible at all. Consequently, in Sikkim the practice of transplanting paddy seedlings flourishes. Sikkim has a wide variety of agro-climatic conditions and therefore, a wide variety of paddy was cultivated. Almost all wet arable areas of Sikkim are devoted to paddy cultivation. Selection of different varieties of rice, generation after generation by different ethnic groups has led to numbering 43 varieties of paddy cultivation, which still dominate the age-old paddy cultivation practices with 55–60% stake in acreage (Rahman and Karuppaiyan 2011; Sharma et al. 2016). Based on a field survey and discussion with the farmer’s group, it was found that more than 50 local varieties of paddy were cultivated in the state. These indigenous landraces—Thakmaru, Phudungey, and Champasare—are more specific to high altitudes. Although they are also grown in Dzongu, Mangan, and upper Rumtek which lies between 1400 and 1700 m above MSL. Irrigated paddy diversities such

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5 Agriculture System and Agrobiodiversity

as Attey, Timmurey, Jhapaka, Krishna Bhog, Bacchhi, Nuniya, Mansure, BagheyTulasi, Kataka, Champasari, Sikrey, and Taprey were cultivated in agro-ecological zones between 300 and 1800 m. Taichung Native 1 and Kalimpong 1 are cultivated mostly in North Sikkim. All other landraces/cultivars are mostly grown in 1000–1500 m asl. From the above-mentioned indigenous rice varieties, some of the wet rice varieties such as Gauria, Krishna Bhog, and Mansure, and dryland paddy varieties GhyyaDhan, Takmaru, Bhuindhan, Marshi, etc., have mostly vanished from the system. Whereas other varieties such as Zornali, Thaprey, Thakmaru, Taichung, ShirkeyMarsee, Ramkalan, Nunia, Lama Dhan, Kalo Nunia, Kalo Dhan, Kalami, Japanese, Dut-Kate, Dharmali, Dhanase, Dahrey, Champey, Bhuinphul, Barmi Dhan, and Bacchi, are found hardly and their populations are facing serious genomic drift. There has been an unexpected decrease in paddy area primarily because of the diversion of paddy land to commercial crops like cardamom, apples, and potato. Wheat (Triticum aestivum) Wheat is also an important food crop sown in most of the villages irrespective of elevation. The cultivation of wheat is confined to an elevation of over 2000 m. However, these crops are also grown at low and mid-elevations as secondary crops to maize and paddy. Wheat is a rabi crop and is grown without irrigation. It is propagated in Sikkim at the end of September and continues up to the second week of December. The maximum net sown area under wheat was noted in the East district (44%) and the lowest in the West district (6%) (Table 5.3). Suitable agro-climatic conditions for the growth of wheat in Sikkim are not found. In 2015–16, the total wheat production in the state was 346 tons. The yield rate of wheat was about 1071.21 kg per ha as against the national average of 2750 kg per ha. Generally, unirrigated wheat is seeded from September to October. The crop takes about 160–180 days to be complete for reaping. Rainfed wheat crop is usually engaged later maize, in Sikkim. The sowing of wheat starts from the third week of September and continues up to the end of October. The reaping of wheat propagated through this period is done by the end of March. The initial weeks of October and November are the ideal time for spreading wheat in Sikkim state. Mixed cropping of wheat with Indian mustard is very popular in the state, especially in places where there is less rainfall. Tho, Mashi, Si, and Toksongsi are the local names of traditional wheat landraces practiced in Sikkim. The other varieties were also grown in the state. Finger Millet (Pennisetum glaucum) The major finger millet growing districts are East district, which covers about 29% of the net sown area in comparison to other districts of Sikkim state (Table 5.3). In the state of Sikkim, finger millet is commonly known as ‘Kodo’ or ‘ragi.’ It is grown up as an uprooted crop on well-drained and less productive soil. In Sikkim, the finger millet grain is largely utilized for malting and making a fermented beverage named ‘Tongba’ or ‘Chang.’ The millet powder is also used in making bread, or ‘dihinro.’ Its stalk

5.5 Analysis of Cropping Patterns

91

is used as fodder in winter. Bhadaurey, Chamligey, Kartikey, Mangshirey, Mudkey, Nangkatwa, Panchaunley, Pangdure, Tangsere are the nine varieties of finger millet found in Sikkim. In these indigenous varieties, Bhadaurey, Chamligey, and Tangsere are almost on the verge of extinction. Other varieties of finger millet grown in Sikkim are HPB 7-6, INDAF-5, PR 202, VL-101, and VL-204. Among these varieties, VL101 is found to be very high-yielding and has been suggested for Sikkim state. The suitable areas for the cultivation of millet are at altitudes around or below 1500 m elevations. Finger millet sown from May–June to September–October is known as Bhadaurey and is usually grown up at altitudes of 1400 m asl. When it is grown from July–August to December, below 1750 m above mean sea level, this is called ‘Mangsirey’ crop, and ‘Pangdure’ crop when grown on sloppy or virgin land from December–January to March–April. The broadcasting method of sowing is generally used for the Pangdure crop grown from December to January while the transplanted sowing method is used in the Bhadaurey crop and Manysirey crop. It matures earlier than wheat. Barley (Hordeum vulgare) The East district of Sikkim state covers the highest (50%) net sown area and the West district covers the lowest (3%) net sown area (Table 5.3). The area under highyielding varieties of barley such as Dolma-VLB, and other improved local varieties was less than 200 ha. Barley is propagated from the mid of October to the first mid of November. Barley remains grown up at low and mid-elevations as secondary crops to maize and paddy, confined at elevations of over 2500 m. Farming of barley is of immense significance because it is good for men as well as for cattle. It is too used as an elementary raw material in changing it into malt for preparation into liquor. In Sikkim state, nearly 80% of the total production of barley is for brewing and the rest is crooked into barley powder, or is termed ‘Champa’ in Sikkim state. Several highyielding varieties of barley are now available for diverse agro-climatic situations. The enhanced varieties of barley introduced in Sikkim state were VLB-1, BlB-5, Himani, and Dolma. These varieties are appropriate for growing in the mountains. Buckwheat (Fagopyrum tataricum) The South district of Sikkim reported the highest area (39%) under buckwheat cultivation followed by the East, West, and North districts (Table 5.3). Buckwheat is an important rabi crop. It is grown not only on hilly drylands from 300 to 2500 m nevertheless too as a main revolving crop of paddy and maize in Sikkim state. The sowing of buckwheat is generally done by the broadcast method. In the instance of buckwheat-paddy interchange, spreading is completed in February–May and picked in September–October, whereas in buckwheat-maize rotation, the seed is spread in August–September and reaped in October–November.

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5 Agriculture System and Agrobiodiversity

A variety of food and non-food items are sold in the local market

Dryland buckwheat depends on rainfall. Though, moisture management by agronomical practices, namely land terracing leveling, or less tillage technique may be accepted. Mithey-Phaper, Titey-Phaper, Kere-Phaper, Yapha, and Tambong-Kere are the traditional varieties of buckwheat in the Sikkim state.

5.5.2 Non-food Crops Legumes Legumes assume a place of importance in the cropping pattern of the state for soil fertility and protein intake of rural people. Legumes are grown both as a Rabi and Kharif crop. Legumes are also used as green manure. In the context of soil management, legumes constitute an important chain in crop rotation. Legumes include mainly pulses, beans, and peas. Arhar, bakuley simbi, borungey simbi, dudhey matar, etc., are the indigenous varieties of legumes grown in Sikkim. Pulses Legumes, pulses, etc., are good sources of proteins. Normally, pulses are grown as a relay crop after maize and are also intercropped with paddy. Pulses include food grains like gram, arhar, and lentils and are generally raised in dry areas of the state. The advantage of pulse cultivation is that they reinstate the fertility of the soil. Large varieties of indigenous and hybrid pulses are accessible for farming in Sikkim states such as Kalo dal, Paheli dal, T-9, Gwalior-2, Ujjain-4, and West Bengal-17. Paheli dal is usually grown and gets a higher price than ‘Kalo dal’ in the state. Pulses are grown in Sikkim and subsequently harvest maize crops in August–September with sole plowing for land preparation for spreading. In Sikkim, it is spread moreover by broadcast or in the lines of 20–25 cm separately. The South district covers around 53% of the net sown area under pulses (Table 5.4).

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93

Table 5.4 The concentration of non-food crops in Sikkim (net sown area) Non-food crops Districts

Sikkim total

North

South

East

West

Area

Area

Area

Area

(ha)

(%) (ha)

(%) (ha)

(%) (ha)

(%)

Pulses

267

5

3010

53

760

13

1633

29

5670

100

Oil seeds

612

9

2543

37

2610

38

1171

17

6936

100

Fruits

1023.7

6

3312.8 19

6661.6 38

6540.7 37

17,538.8 100

Vegetables

1562.5 10

5177.9 33

4558

29

4220.6 27

15,519

100

Potato

604

6

2503

24

2738

27

4401

43

10,246

100

Roots and tuber 654 crops

6

2763

25

2928

27

4596

42

10,941

100

21

7431

25

8760

30

7171

24

29,614

100

Spices

6252

(%) (ha)

Area

Source Department of Agriculture Cooperation and Farmers Welfare (2018)

Beans The major portion of the area under beans is located at the lower and mid-hills. Depending on altitudes, beans are grown as early monsoon, late monsoon, and monsoon crops. A wide variety of beans are grown in Sikkim which are normally consumed by the rural population. Their nutritive value is an important source of protein. Peas Peas are cultivated in between 300 and 2500 m of elevation. At lower and mid-hills, peas are cultivated as an early winter crop, whereas, at higher elevations, they are cultivated mainly as a monsoon crop.

Peas (local)

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5 Agriculture System and Agrobiodiversity

Normally, two cuttings of peas are obtained annually. Peas are grown both for marketing as green peas and for seed production. As a whole, the maximum area under pulses in terms of the net sown area is in the South district, followed by the West, East, and North districts, respectively. Oilseed The principal oilseed grown in Sikkim is mustard and soybeans. Earlier, mustard seeds were crushed in a small wooden oil expeller. At present, most of the mustard oil requirements of the state are met by import. Mustard (Brassica spp.) Mustard flourishes sound at an altitude of 4200 m. Mustard is cultivated as a Rabi crop and matures in a short time (110–120 days). Sowing of mustard is generally done at the end of October month and the early week of November in the fields vacated by maize and harvested in February. It is also intercropped with wheat and barley. Two varieties of mustard—Varuna and T-9—are cultivated in Sikkim.

Mustard or Sarso (local)

Indian mustard is generally used as edible oil, condiment, as well as in medicinal purposes, etc. Oil extraction is done by primitive methods only. To encourage farmers to mustard cultivation, a mini-oil expeller has been installed at the Merchak regional sub-center. Rapeseed oil is used in the manufacture of greases. Oil cake is consumed for nourishing livestock and also for manure. The area under high-yielding varieties of mustard such as B-9 and other improved local varieties was 428.50 ha. Soybeans (Glycine max) Soybean is a Kharif crop cultivated in June–October. It blooms when the temperature and humidity are fairly high. Soybean is grown in small plots of land by many farmers and it constitutes an important food crop. Nearly 50% of the soybeans are consumed green as the cooked pulse. This crop is grown well on low and mid-hills even on low moisture and on light soils. Soybeans are either grown as monocrop or intercropped

5.5 Analysis of Cropping Patterns

95

with maize and are also cultivated on bunds in paddy fields. Soybean is important both from the point of husbandry and nutrition and is considered as poor man’s meat. A variety of products are also made locally from soybeans like soybean biscuits, soybean milk, soybean sauce, etc. Local people consume soybeans in boiled and fermented forms called kinema. The high-yielding variety of soybeans, ‘gyalab,’ is obtained to be the maximum yield and thus expanded for farming in the state. The variety ‘Bragg,’ yet believed to be the maximum yield in India. It is observed to be inappropriate in paddy field bunds because of its height. Soybean is cultivated as mixed cropping with maize. Land preparation done during maize cultivation is enough for its farming. In single cropping, one intense plowing and one normal plowing, clod crushing, and leveling are adequate. When grown in paddy field bunds, straight seedlings by opening the soil enough. The area under high-yielding varieties of soybean such as PS-1024/1042/1029/, Black bold/VL-47, PK-1024/42, and other improved local varieties was 750 ha. Therefore, most of these oilseeds are grown in the East district of Sikkim, followed by the South and North districts (Table 5.4). West district has the least area under it. The area under oilseeds in the South and East district was more than the state average. Fruits Because of its varied agro-climatic conditions and topography ranging from tropical to temperate, different types of fruits (cash crops) like apples, oranges (Sikkim mandarin), walnut, almond, pear, plums, guava, peach, papaya, lime, lemons, grapefruit, pineapples, and banana are grown in different parts of Sikkim. Fruit crops are grown at an elevation ranging from 300 to 3000 m.

96

5 Agriculture System and Agrobiodiversity

Orange (Citrus reticulate) Sikkim mandarin orange is popularly known as ‘Suntala.’ It occupies the largest area under fruit crops. Besides occupying a large share of fruit crops, it is one of the utmost vital cash crops of the state. It is in high demand at the Government Fruit Preservation Factory for the preparation of jellies, squash, orange essence, etc., where about 2000 tons of oranges are processed in a year. The favorable areas for citrus fruits are lower and mid-hills up to 1500 m of elevation in the southern part of Sikkim. This crop is a perennial crop coming to fruit-bearing age after 5–6 years of plantation depending upon the age of transplanted seedlings. The economic life of orange plants is about 40 years. The orange crop is gradually deteriorating in some areas mainly because of bad management. They are mainly grown at Sang, Khamdong, Martam, Singtam, and Pakyong. They are located close to the Fruit Preservation Factory of Singtam. Quite recently, the area under orange cultivation has been extended in Lum-Gor-Sangtok, Gram Panchayat Unit (GPU) in North Sikkim which covers five blocks of Lum, Gor, Sangtok, Sagyong, and Tarang. This area has a wide topographical variation with hills and ridges extending up to 2134 m with the lower parts touching the bed of the Teesta River. The total gram panchayat unit has a geographical area of 405 ha which is at a distance of 25 km from district headquarters Mangan, where largely, large cardamom was practiced. But due to a disease outbreak, large cardamom productivity fell and at present, the whole GPU has been converted into an orange belt. Progressive farmers like Thinlay Lepcha, Pentuk Lepcha, and Phurba Lepcha of Lum village are supplying over 30,000 fruits each, annually to various outlets in and around the Siliguri market through SIMFED and other wholesalers. The annual export of nearly 2000 tons of oranges is made to Siliguri and other districts of West Bengal. In Siliguri, a large share of the crop is consumed by the Indian Army and the local population. Apple (Pyrus malus) Apple is another important fruit crop in the state. The cultivation of apples was confined to about 185 ha at an elevation of 1500–3000 m at Lachung, Yuksam, Ribdi, Dhareng, and Burikhop. Their cultivation is being extended due to its remunerative value to other non-traditional areas such as Hilley, Okheray, Sribadam, Uttarey, and in Dzongu area. Apple orchards can withstand the intense cold in winter and continue to live in a leafless or dormant form in the winter months. Severe temperatures are considered congenial for normal growth, and flowering. Apples start bearing fruit from the 5th to the 6th year of transplanting and continue to produce fruit for 30– 40 years. Traditional apple areas are at Lachen and Lachung situated at an altitude of 2500–3000 m. Lachung, however, produces the maximum quantity of apples in Sikkim. The plantation at Tuksam also gives an appreciable return.

5.5 Analysis of Cropping Patterns

97

There are many varieties of apples grown in Sikkim, but Sikkim apples look inferior to those of Himachal Pradesh and Kashmir. In Sikkim, apples are harvested in early autumn and late summer. Among the varieties, Summer Green comes to the market in early July, Arkin Russet in early summer, and the rest in October. With the onset of the orange season, apples lose their value. Guava (Psidium guajava Linn.) Guava is cultivated on a limited scale at low altitudes below 1000 m. The area under guava cultivation was only 140 ha while the total annual production is 120 tons. Among the many varieties, Allahabad Safeda and Lucknow-40 have proved fit for cultivation in Sikkim. One orchard of guava has been started at Majhitar at 570 m with 18 varieties for the propagation of seedlings. This fruit is likely to become commercially viable shortly. There is also a great demand for guava in the internal market, especially at the Fruit Preservation Factory. Pineapple (Ananas sativus) Of late, pineapple has become the significant cash crop of Sikkim state. The agroclimatic conditions in lower hills are extremely congenial for the growth of pineapple. The cultivation of pineapple is practiced on a commercial scale in the state. Ten thousand pineapple suckers mostly of Giant Kev and Queen varieties were imported and supplied to the growers. Pineapple suckers are being planted and intercropped with citrus orchards. Peaches (Prunus persica), Plums (Prunus), and Pears (Pyrus) These fruits are grown at upper-mid, higher, and very high hills. These fruits have been in cultivation in the state since time immemorial. Nearly 200 ha of land was under better varieties of fruits obtained from Himachal Pradesh and Uttar Pradesh. The cultivation of peaches and plums is confined primarily in the dry belts of South and West Sikkim. Similarly, a hard-shelled walnut occurs in abundance in the midhill forests of the state. Thin-shelled walnut has also been introduced in the state. Banana is grown extremely well in the lower hill region and it is a very important fruit of every village household. The cultivation of bananas has also been started by farmers on a commercial scale. It is acting as a filler crop in the lower belt and this trend is on increase. Other Fruits Papaya, grapefruit, almond, and apricot are also grown in the state but on a limited scale. It was estimated that nearly 90 ha of land were under these fruits. Efforts are being made by the State Agriculture Department to propagate better varieties of such fruits. In brief, the maximum area under fruit cultivation is in the East district (38%), followed by the West (37%), South (19%), and North districts (6%) (Table 5.4).

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5 Agriculture System and Agrobiodiversity

Vegetables The prevalent geographical conditions are congenial for the cultivation of various types of vegetables in Sikkim, extending from foothills to elevations of 2000 m above mean sea level. Several areas have been found suitable for producing quality vegetables. The production of vegetables even in non-traditional areas is becoming highly remunerative. Almost two decades ago, commercial growing of vegetables was exclusively restricted to Temi and Tarku. Now, many farmers have taken to large-scale cultivation of seasonal vegetables which pay rich dividends to them.

Rai Saag (Local)

Broccoli (Hybrid)

Cauliflower (white XL Hybrid)

5.5 Analysis of Cropping Patterns

99

Cabbage (local)

Pumpkin (local)

Vegetable Diversity (local)

Production of vegetables during the off-season is a profitable proposition in Sikkim where agro-climatic conditions vary widely. Cabbage and radish are extensively grown in Chungthang, Lachen, and Lachung areas. Tomato, chili, brinjal, lady’s finger, cauliflowers, and beans are grown in the South district, particularly around Namchi, Melli, and Nayabazar. Tomato (Lycopersicon esculentum) Tomato is quite a popular vegetable grown almost in the backyard of every rural household located between 1000 and 2000 m of elevation. There are mainly three varieties of tomato grown in Sikkim, i.e., blood red, crimson, and yellow. It is of great commercial value for the preparation of tomato sauce and as a substitute for real tomatoes. The Agriculture Department is encouraging its cultivation. Sadam Turuk, situated around 40 km from Namchi town (capital of South district), where 50–55 household lives there, is out of that 41 numbers of farmers who are engaged in developing their village into a model vegetable village. The Gangtok market is the biggest vegetable market in the state and acts as a great incentive for growers. A large number of farmers are growing vegetables at Pakyong, Bumtek, Makha, and Syari around Gangtok. Some improved varieties of vegetables have been introduced in the state in recent years. Marketing is of vital importance

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5 Agriculture System and Agrobiodiversity

and vegetables are brought fresh from the areas of production. The State Agricultural Department has formed an association in each area for the production and marketing of vegetables. The vegetable growers have specific days for bringing their produce to various collecting centers like Temi, Tarku, Karachi, Kelli, and Singtam. The association ensures the quality of vegetables before their transportation to the final market centers. In this process, the growers in general, get fair prices for their products and consumers get quality products at reasonable prices. In mid and higher reaches, off-season vegetable comprising cabbage, cauliflower, carrot, and radish is taken up. Traditional vegetables like peas, beans, and chayote have been received due to stress in all potential areas. The total area under cultivation of vegetables was 15,519 ha. Heegyathang, Ringhim, Lachen, Lachung, Kabi, Garigoan, Tumlong, Tingvong, and Phedang are the names of the cluster of North districts that constitute a 1562.5 ha area where the vegetable is grown. The area in East Sikkim under it was 4558 ha, which includes Dalapchen, Nimachen, Shyagyong, Rumtek, Senti, U/Sumin, Budang-Pachak, Namrang, Dhanbari, Kamerey, Thangsing, Bouchen, Sirwani, and Tshalumthang clusters. Lungchok, Saleybong, Panchgharey, Bul, Aneythang, Kongsa, Mungrang, Samatar-Chisopani, Sadam, Assangthang, Turuk, Chuba-Parbing, Jaubari, Simkharka, Gupti, and Pakjer are the cluster areas of South district of Sikkim where most of the vegetable cultivation was done and they together constitute 5177.9 ha area. In the West district, Naku-Chumbung, Yangsum, Dodok, Meyong Chinthang, L/Martam, Tareybhir, Sombarey, Ribdi, Okhrey, Nesha, and Baluthang are the main cluster where vegetables were grown in 4220.6 ha area (Horticulture Revolution 2017). In South Sikkim, the area under vegetable cultivation was 33% of the net sown area, which is the highest among all other districts (Table 5.4). North district has the least area under vegetable cultivation. Potato (Solanum tuberosum L.) The net sown area under potatoes recorded the highest (43%) in the West district in comparison to other districts of the state (Table 5.4). Potato is an important cash crop grown in two seasons as Kharif and Rabi crops at high altitudes of 2000 m and above. The potatoes cultivated at higher altitudes are usually disease-free and best quality used as seeds. Ribdi, Bhareng, Okharey, Sapri-Magi, Upper Burikhop (West district), Lacbung, Lachen, Thangu (North district), Rabangla (South district), and Padamchen in the East district are the main seed potato production areas. All these places are situated above 2000 m and have a suitable environment for the crop. Till mid-seventies, Ackersegen, Ultimus, Voron, and Pimperrel were popular but now high-yielding new varieties of Kufri Jyoti, Kufri Chandramukhi, Kufri Kundan, Kufri Kuthu, etc., are found to be more suitable for Sikkim. In higher regions, potato is grown as a monocrop, but it is rotated with potato-vegetable-potato, potato-wheatpeas/cabbage/radish, potato-wheat-barley, etc.

5.5 Analysis of Cropping Patterns

101

Potato (local)

Root and Tuber Crops These plants cultivate usually as yearly crops and yield roots, tubers, rhizomes, corms, and stems that are used mainly for food, moreover as such or in treated form. It is also used for animal feed. Sweet potato, taro, cassava, Sikkim cucumber, etc., are the other roots and tuber crops that are grown in Sikkim. Among tuber and root crops grown-up in Sikkim state, sweet potato is the utmost imperative. Presently, it is grown as a profitable crop. It is a yearly herbaceous shrub, reproduced using tubers. The tube is underground stems and from them, new shoots are formed. The maximum area under roots and tuber crops was recorded in the West district, followed by the East, South, and North districts, respectively (Table 5.4). Spices In Sikkim, the climatic condition is pretty suitable for the cultivation of spices, particularly ginger, cherry pepper, turmeric, coriander, and large cardamom. Large cardamom is the indigenous crop of Sikkim and is the leading state in its production. More than 70% of the need for this crop all over India is alone fulfilled by this state.

Coriander (local)

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5 Agriculture System and Agrobiodiversity

Ginger (Zingiber officinale) Ginger is a vital spice cash crop for the farmers of South and West districts where it flourishes well at about 1200 m even in dry fields. Ginger has good storage quality, as a result, it has little chance of damage. The villagers grow it in the backyards of their houses and of late, its cultivation has spread even in non-traditional areas. It is grown both in the lower and mid-hills. North district has little cultivation of ginger. Owing to its remunerative price and good export potential, the land under ginger cultivation is increasing. Gorubathaney, Bhainsey or Bhaise (large-size rhizome) or Bada Aduwa, Majhauley (medium-sized rhizome), Jorethangey, and Nangrey or Sano Aduwa are the traditional varieties of ginger cultivated in Sikkim. In these local cultivars, Bhaise is known for high yield and Nangrey is known as medical ginger because of its medicinal characteristics. These local varieties are fibrous. Recently two varieties of ginger with low fiber and good yield, have been introduced, viz., Rio de Janeiro and Nadia. The seeds of these improved varieties are being propagated at government farms at Marchak and Namchi. Potential areas of ginger cultivation are Jorethang, Khamdong, Fakyong, Sang, Martam, and Namchi.

Ginger (Local)

The famous ginger markets of Sikkim are Nayabazar, Reshi, Sikip, Singtam, and Dikchu. Besides, many small collection centers at village and GPU levels have also been established where the aggregation is done for marketing to Siliguri, Azadpur, and other parts of India and abroad such as Pakistan, Bangladesh, and the Middle East. The total area under ginger cultivation was 100.3 ha. The highest area under ginger farming is recorded in the South district, followed by the East and West districts and the Northern district of Sikkim.

5.5 Analysis of Cropping Patterns

103

Cherry Pepper Cherry pepper, locally known as ‘Dalley khorsani’ is a traditional chili, extremely popular for its pungency and unique flavors. The plant grows erect reaching about 2 ft. high. The fruit is bright red to orange when mature, and thick-walled with red flesh. Sikkim has around 300 ha of the area under cherry pepper. Cultivation of this crop has become a highly profitable venture for small and marginal farmers of the state. Nesha village located in the West district of Sikkim has become a major accomplishment for the cultivation of cherry pepper. The farmers of this area were previously cultivating mainly cereal with little quantity of vegetables, but merely 8 farmers took up the cultivation of Dalley in their field, and within a year, they produced 5000 kg of cherry pepper. The area under cherry pepper was 13 ha in Nesha, increasing the number of involved farmers to 23, after seeing the success story of the neighboring farmers. Turmeric (Curcuma longa) Turmeric is a perennial plant with tuberous rhizomes. It is widely used in almost every household for culinary purposes. This crop has been given special importance in Sikkim as an alternative to ginger by some farmers because of is turmeric far more tolerant crop to diseases and pests than ginger. Sikkim had around 1950 ha area under turmeric. An improved variety of turmeric ‘Lakadang’ from Meghalaya introduced in the state about a decade back, has become highly popular in the drier belt owing to its high curcumin (color and flavoring compound) content.

Turmeric production is an alternative adaptive crop in areas where other crops are damaged by wild animals

The government has set up two turmeric processing units, one at Birdang in West Sikkim and another at Rangpo in East Sikkim. A large chunk of the total production of turmeric in the state is absorbed by these plants. The maximum area under turmeric cultivation is in the West district followed by the South and East districts of Sikkim, respectively. North district had the least area under its cultivation.

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5 Agriculture System and Agrobiodiversity

Large Cardamom (Amomum subulatum) Large cardamom is the chief age-old cash crop of Sikkim state. While Amomum subulatum, is a cultivated species, wild families such as Amomum linguiforme, Amomum aromaticum, Amomum corynostachyum, and Amomum dealbatum are also found in the state. Collecting large cardamom capsules from natural forests has been a traditional activity of one of the aboriginal ethnic groups in the state, the Lepcha(s). Large cardamom is a perennial shrub with thick and fleshy rhizomes and is generally raised as a pure crop. Large cardamom is cultivated as a monocrop and agrobiodiversity issues do not arise in this system. However, this practice has supported highly diverse tree components as shade trees. The system supports as many as 23 tree species (Sharma and Sharma 1997). These trees have numerous usages for growers, e.g., fodder, fuel, timber, materials for field implements, and remains for livestock bedding. Its cultivation is confined to cool, moist, and shady areas in lower and midelevations ranging from 600 to 2000 m asl of elevation and preferably near water sources. The normal yield starts from the fourth year of planting. The crop gives maximum yield between the 6th and 9th years. The economic life of cardamom plantations is about 20 years but in Sikkim, some plantations are more than 40 years or more. The crop grows best on well-drained rich forest soils having enough humus, and leafy matter (Sharma et al. 2000, 2008, 2016). November is the best time for sowing and the harvesting of fruits starts from August to November. The sharp rise in price and demand for cardamom has led farmers to convert some paddy lands into cardamom fields. Considerable areas are brought under cardamom cultivation in the West and South districts. Its area in the West and South districts has increased. Almost all the land suitable for cardamom production on private holdings has already been saturated. The Forest Department is encouraging people to cultivate cardamom in forest lands. Sikkim has a greater area under large cardamom cultivation. It is also the major producer of large cardamom in the country.

Cardamom (local)

5.5 Analysis of Cropping Patterns

105

Cardamom is used in curries, cakes, pickles, and other culinary purposes. The oil is used somewhat in cooking and flavoring beverages. Sikkim produces an average of 2400 tons of cardamom annually. Ramsey, Golsey, Madhusey, Bharlangey, Chibe, Seremna, Ramla, Sawney, Ramnang, and Churumpho are the local cultivars of large cardamom in practice on agricultural farms in Sikkim. But prevalent varieties are Ramnag, Golshai, Sawaney, Varlangey, and Ramshai. Ramnag (Bhutia word for black color) has a dark color and its plantations are confined to Dzongu, Dikchu, Nampung, and Lingdok. This variety is sent to Calcutta, Bombay, Madras, and Delhi. Golshai (round-shaped yellow color) is mainly grown in the South and West districts. The variety is consumed in Punjab and Delhi. Sawaney (harvested in the month of Sawan, i.e., July–August) is grown in Assam Lingzey and Bhusuk area. Varlangey is almost disappeared from the agricultural farm of Sikkim due to unsuitable agro-ecological conditions and practices. Ramshai (Ram-color, and Shal-yellow) is grown in upper Mangan, Upper Nga, and Kanul in North Sikkim. In all the above-discussed indigenous cultivars, Sawney cultivars give premium quality cardamom with superior and bolder capsules containing 30–35 seeds and its performance is satisfactory between mid- and high altitude, i.e., between 700 and 1200 above mean sea level (Sharma et al. 2002; Partap et al. 2014). The important large cardamom-producing areas are Dzongu, Nga, Tolling, Dikchu, Phodong, Phensang, Kabi Rongpa, and Kanul in the North district; Ben, Sangmo, Barfung, Kewzing, Ralang, Brang, Rabang in the South district; NampungLingdok, Shotak, Penlang, Bhushuk, Assam Lingzay, Rongii in the East district; and Chakung, Sombaria, Binehenpong, Mana, Karji in the West district. In Sikkim, cardamom is grown in all four districts. North Sikkim accounts for the maximum area under large cardamom cultivation (5510 ha), followed by the East (5005 ha) and West districts (3548 ha) of Sikkim. In the South district, the area under cardamom cultivation was 3486 ha and the yield rate was 235 kg per ha (Department of Agriculture Cooperation and Farmers Welfare 2018). There is a rapid decline in the area and production of large cardamom due to a large-scale infestation of leaf blight which has been identified to be caused by a fungus (Colletotrichum gloeosporioides). This is a menace that appeared over and above the already existing two deadly Chirkey and Phurkey viral diseases which are dreaded maladies in large cardamom (Hunsdorfer 2015). Therefore, the area under spices cultivation in the North district was 59.84%, followed by the East (40.37%), South (33.82%), and West (31.09%) districts of Sikkim, respectively (Kumar 2020). The large cardamom is an excellent crop, highly suited to the mountain environment and ecology. Large cardamoms are grown on marginal and barren lands; they are a low-volume, high-value, non-perishable cash crop; have an assured market, and are not infrastructure-intensive. Efforts should, therefore, be directed toward mitigating diseases and saving crops from further damage. Other high-value cash crops which have a local niche need to be identified and brought into the mainstream to improve the sustainability of mountain agriculture.

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Box 1 Despite the important role of the large cardamom in the state economy in terms of accounting for around 17% of the total cropped area, providing a source of income for a significant proportion of the population, contributing around four to five percent of the total non-tax revenue to the state exchequer, and also earning foreign exchange for the nation, the crop suffers from the problem of marginalization. Further, it has received adequate attention neither from scientists nor from policymakers.

5.6 Cropping Pattern in Sampled Households Major crops grown in Sikkim are maize, paddy, and cardamom, followed by vegetables, fodder plants, ginger, and orange. Around 100% of the farmers during the survey agreed to experience a decrease in crop yield. Most of the marginal farmers in the area practice subsidence farming and grow crops for self-consumption, as a result, vegetable is grown by 100% of the farmers in all ecological zones (Table 5.5). Cash crops namely ginger and turmeric are grown up in all ecological zones. Maize and large cardamom are the major crops of all ecological zones while paddy is limited to only lower- and middle-ecological zones as it is difficult to grow paddy in the higher altitudes on sloping lands. Fodder plants are also grown by many of the farmers in all ecological zones which are used by their livestock. Table 5.5 Major crops grown in sampled villages Major crops

Lower (n = 100) (%)

Middle (n = 150) (%)

Maize

91

90.6

Paddy

70

64

Higher (n = 50) (%)

Decrease in yield

92

Yes

0

Yes

Large cardamom

83

86

88

Yes

Ginger

42

59.3

56

Yes

100

100

100

Yes

Vegetables Orange

13

48

82

Yes

Fodder plants

83

84.7

62

Yes

5.6 Cropping Pattern in Sampled Households

107

5.6.1 Changes in Cropping Pattern About 80% of the farmers responded that changing pattern is a threat to traditional farming. Major reasons for change as reported by farmers are the ban on fertilizers, increased water scarcity, dryness, increased temperature, erratic precipitation, land-use changes, labor shortage, increased pests and insects, low productivity, and increased pollution (Table 5.6). Major disadvantages faced by farmers are reduction in yield resulting in financial loss, and crops like maize and vegetables are growing in small sizes thus decreasing the net revenue of the farmers. A farmer stated that due to reduced production, farmers with small landholdings have sold their land to start a business as they are not able to maintain the land. Earlier, it was easier for them to practice farming; the use of fertilizers is banned and govt. does not help to improve farming technique; drainage problem is increasing and due to increased temperature, pests and insects have also increased. All these conditions are forcing marginal farmers to look for an alternative source of income. Some farmers also accept that they gained some advantages by switching to cardamom, floriculture, horticulture crops, and other cash crops. Table 5.6 Change in cropping pattern Major crops

Reasons

Advantages

Disadvantages

Maize

Banned fertilizers, – increased pests and insects, dryness, water shortage

The small size of maize, financial loss

Paddy

Less precipitation, land-use changes, labor shortage

Switching to cardamom and other cash crops

Stopped cultivating paddy, financial loss

Cardamom

Heat, increased pests and insects, water shortage, banned fertilizers, labor shortage

–

Financial loss

Orange

Heat, increased pests, and insects, water shortage

–

Financial loss

Ginger, turmeric

Pollution, heat, water shortage, low productivity

–

Financial loss

Fodder plants

Reduced cultivation, heat, increased pests and insects, water shortage

Switched to floriculture and horticulture crops

No fodder in winter, have to buy from the market or use forest products for livestock

Fafar, Kodo

Climate change, no labor, erratic precipitation

–

Financial loss

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5 Agriculture System and Agrobiodiversity

Table 5.7 Types of farming systems and practices Type of farming/farming practices Individual/family farming

Lower (n = 100) (%)

Middle (n = 150) (%)

Higher (n = 50) (%)

96

96.7

100

100

100

100

Another type (traditional crops)

24

46.7

82

Single cropping

78

69.3

42

Intercropping

38

51.3

56

Mixed cropping

82

88.7

86

29

22

42

100

100

100

Organic farming

Relay cropping Crop rotation

5.6.2 Farming Systems and Practices Various types of farming systems and practices are found in the Sikkim Himalaya such as traditional farming, family farming, and organic farming. Along with this, multiple cropping practices are observed such as mixed cropping, relay cropping, intercropping, and crop rotation during the field survey. The majority of these farming systems and practices are used in combination by farmers. Details of the data collected through a questionnaire survey regarding this are given in Table 5.7. Organic farming and crop rotation are practiced by 100% of the farmers in all ecological zones while relay cropping is the least used practice 29% in the lower, 33% in the middle, and 42% in the upper ecological zones. The majority of the farmers in all ecological zones practice individual/family farming, 96% in the lower, 96.7% in the middle, and 100% in the upper ecological zones. Single cropping is more prevalent in the lower ecological zone (78%) in comparison to the middle (69.3%) and higher ecological zones 42% (Table 5.7). This is due to the larger farm size available in the lower altitude which is suitable for single crops.

5.6.3 Functions of Farming Practices Due to the small and fragmented landholdings with the small size of farms, farming practices are manual (100%) with help of labor and traditional farming tools (Table 5.8). Functions such as sowing, weeding, and harvesting are done by farmers with the support of paid labors or the cooperation of other neighboring farmers in exchange for a similar favor. Labor shortage is one of the major problems addressed by farmers. According to the farmers, the young generation doesn’t want to work in the field and the majority of them have migrated in the search of jobs and education. Higher labor costs force them to work on the farms on their own or get help from family and neighbors. Other major problems are water shortage, erratic precipitation,

5.6 Cropping Pattern in Sampled Households

109

Table 5.8 Functions of farming practices Type of functions

Methods

Facilities

Problems

Sowing

100% manual

Labor

Labor shortage

Weeding

100% manual

Labor

Pest, insects

Irrigation

Rainfed

–

Water shortage, erratic rain

Harvesting

100% manual

Labor

Monkeys, labor costs high

Storage

100% self

Own place

NA

Marketing

100% self

Local market

Transportation cost, less price

pest insects, and in some areas monkeys. Storage and marketing of the crops are also done by farmers. All the farmers store their crops in their places and transport them to the local market. Farmers stated that transportation cost is high, and they get less price for their crops in local markets thus, decreasing the net revenue of the farmers. Farmers urged that govt. should take some steps for marketing and transportation.

5.6.4 Agricultural Inputs Every agricultural practice requires some inputs such as seeds, manure, water for irrigation, and support from the local government in the form of subsidies. The majority of the farming practices in the state are based on rainfed and due to the ban on fertilizers, farmers are only allowed to use organic manure. Farmers prepare organic manure from cow dung, waste of other livestock, and crop residuals. This organic manure is mostly produced and used on their farms or bought from local markets. To check the ground reality, we asked questions of the farmers regarding the kind of manure and seeds used, place of purchase, variety of seeds, and if there is any subsidy provided to them by the local govt. Around 100% of the respondents in the survey agreed to use organic manure on their farms (Table 5.9). Farmers stated that seeds are expensive in the market while seeds provided by govt. as a subsidy do not give sufficient production and the delivery of seeds and manure by govt. is not consistent. Hence, the majority of them use seeds produced from their farm. The commonplaces of the purchase of seeds are local markets. Farmers from East and South Sikkim also purchase seeds from the Siliguri market. Table 5.9 Agricultural inputs The kind of manure used

100% organic (cow dung)

The kind of seed used

Mostly from their farm

Place of purchase

Mostly local market

Subsidy

Govt. provides seeds but do not regularly

If any new varieties of seeds used

HYV maize, cabbage, paddy, tomato

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5 Agriculture System and Agrobiodiversity

5.6.5 Reason Behind the Changing Pattern in the Yield About 65.3% of farmers stated that climate change is the main reason behind changing patterns in their yield. Along with climate change, 45.3% of farmers agreed that anthropogenic activities are also responsible for the change in yield. 42.3% of the farmers agreed that overuse of land is also a major factor (Table 5.10). When the farmers were asked to specify other reasons, some stated that rising temperature, increased pollution, and dryness are also contributing factors. Apart from these, farmers also addressed some local issues that are causing a change in the overall yield, i.e., pollution from nearby factories and hydropower projects, increased heat, and water scarcity. Due to the smoke from the wine factory, oranges dried and died and the factory is just 9–12 km away (South district).

5.7 Crop Diversification Crop variation in India is typically noticed as a shift from less profitable conventionally cultivated crops to more lucrative ones (Hazra 2018). Crop shift (diversification) occurs because of government policies and programs that focus on certain crops over some time to meet national or state needs and lessen reliance on imports. Crop shift is also influenced by other natural variables, as well as human-generated ones such as price-related subsidies and market infrastructure development. Spices, which are often low-volume, high-value crops, have contributed to crop diversification, and they are especially important in the Sikkim Himalaya. Crop divergence is caused by high cost-effectiveness as well as resistance/stability in output. Crop modification and the planting of many crops are common in pakho bari fields to reduce the chance of crop failure due to drought or other natural disasters. In regions with specific soil issues, crop replacement and shift are also taking place. Crop divergence is therefore intended to provide a larger alternative in the production of crop variability in a given region, to expand production-related activities of several crops, and to reduce risk. More variation of farm innovativeness leads to greater cropping intensity of the farms, followed by high net farm income (Vyas 1996, 2006; Thakur 2010). Table 5.10 Reason behind the changing pattern of yield Parameters

Overall response

Climate change

65.3% yes

Anthropogenic activities

45.3% yes

Overuse of land

42.7% yes

Others (specify)

Hydropower project, wine factory pollution, factory pollution, dryness, heat, unfertile land

5.7 Crop Diversification

111

Crop divergence in Sikkim is pleasing in the form of enlarged areas under cash/commercial crops. In four decades since the formulation of Sikkim state barring mandarin orange and large cardamom, all other commercial crops have shown an increase in productivity (Kumar and Rai 2018; Chettri et al. 2015; Papola 2005). All other findings available on large cardamom validate it. Although in the last fifteen years, the area under mandarin orange cultivation increased its productivity declined by 23.13% in the last fifteen years (Kumar 2020). The area under cash crops increased by 64.36% over the last fifteen years (2001/01–2015/16). Among these, the area and production of ginger increased constantly, more than doubling over the same period. The yield of ginger and mandarin orange increased in these years but overall, the productivity of mandarin orange had decreased. Potato and off-seasonal vegetables have shown significant gain both in area and yield and are emerging as crops with increasing significance in the state’s farm economy (Kumar and Rai 2018). Among food crops, except fruits, seasonal vegetables, and tubers, the area under all food crops had decreased. The area under fruits, seasonal vegetables, and tubers had increased by 88.99% from 2000/01 to 2015/16. The production of fruits, seasonal vegetables, and tubers had increased by 122.42%. All other food crops have registered a negative rise in production in the last 15 years (Kumar 2020). Bhatt et al. (2005), also reported that the area and production of paddy showed a decreasing trend. The analysis reveals that the area under food crops was decreasing significantly and prominent among them was wheat (95.56%), followed by rice (Kumar and Rai 2018; Papola 2005). Patiram et al. (2001) reported similar findings. However, barring wheat, the productivity of all food crops had increased overall in these last fifteen years. But due to the hard work of the farmers, innovation diffusion of modern techniques, technology, and impetus to reduce welfare disparities for doing agriculture per hectare productivity had increased remarkably in almost all crops on the minimum available agricultural land in these years. The total area under food crops reached about 60%, which was 76.8% in 2000–01, i.e., a decrease of 28% in the last fifteen years (Kumar and Rai 2018). Such trends are indicating that the cropping pattern of Sikkim is subjugated by food crops and is gradually moving from subsistence to the cultivation of high-value crops in the last one and half decades.

5.7.1 The Pattern of Crop Diversification The index value for the overall crop diversification according to Gibbs (1974) was 0.83. It ranged from 0.78 index value in the North to 0.86 index value in the East district. The variations in the magnitude of crop diversification are shown in Table 5.11. According to Bhatia’s (1965) method, the index value of crop diversification in Sikkim Himalaya from 2015 to 2016 was 20.78. It varied from 14.93 in the East district to 28.76 in the North district. Therefore, the diversification of crops was

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5 Agriculture System and Agrobiodiversity

Table 5.11 Comparative study of crop diversification index in different districts of Sikkim, 2015– 16 Districts

Crop diversification index of all the crops grown in Sikkim Gibbs method

Bhatia’s method

Singh’s method

North

0.78

28.76

15.98

East

0.86

14.93

11.61

South

0.83

20.51

12.46

West

0.84

18.92

12.99

Sikkim

0.83

20.78

13.26

Source Kumar (2020)

more in the East district than in the North district (Table 5.11). Secondary data and crop combinations calculated by Doi’s method are also similar to the results obtained by Bhatia’s method of crop diversification index. In 2015–16, the overall index value for the study region after Singh’s (1974) method was recorded at 13.26. Though there was a district-wise variation in crop diversification index value. It was recorded as the lowest (11.61) in the East district and highest (15.98) in the North district (Table 5.11). It showed that the magnitude of crop diversification was not uniform but it highly varied in different districts of Sikkim, which was due to the result of partly the physical environment and partly the socio-economic environment. Therefore, in all three methods of calculation of the diversification index, it was found that in the East district, the crop diversification index was highest in comparison to other districts. Other studies’ (Sharma and Rai 2012) findings on crop diversification index are like the present study. Because of these different drivers of diversification, the diversification index of cash crops was different from that of the food crops (Table 5.12). The diversification index of cash crops in different districts of Sikkim by all these three methods reveals that the diversification index was comparatively more in the West and East districts and less in the North district. But, in the context of food crops, the diversification was more in the North and East districts and less in the West and South districts of Sikkim. So, it is evident that the diversification index of both food crops, as well as cash crops, was high in the East district and therefore, the overall diversification index was highest in the East district of Sikkim. With the advent of these changes, the yield level of the utmost of the crops particularly the cash crops has viewed a major swing making it probable to acquire a certain level of yield. Genetic loss and the decrease of multiplicity within species are worldwide risks to farming. The loss of agrobiodiversity in the mountains is owing to numerous reasons namely the ruin of natural forests, which sustained indigenous farm practices, the opening of recent and unvarying plant diversities in place of a mixed farming system with local varieties, demolition of habitat, etc. The introduction of new varieties of cow, goat, and poultry that are best adapted for commercial agriculture’s high input– output ratio is replacing the variety of local livestock breeds. For a variety of factors,

5.7 Crop Diversification

113

Table 5.12 Crop diversification index of food and cash crops in different districts of Sikkim, 2015–16 Districts

Gibbs method Food crop

Cash crop

Bhatia’s method

Singh’s method

Food crop

Food crop

Cash crop

Cash crop

North

0.70

0.57

22.00

29.18

22.00

20

East

0.70

0.76

27.91

20

22.50

20

South

0.57

0.76

37.51

20

19.20

20

West

0.55

0.79

39.57

20

23.20

20

Sikkim

0.63

0.72

31.75

22.30

21.73

20

Source Kumar (2020)

the green revolution technology has not spread in Sikkim. This implies that much of indigenous agriculture has survived, preserving a large variety of crops and animals, as well as the knowledge and traditions linked with them. Single cropping replaces indigenous intercropping and mixed cropping systems, and a wide range of species is substituted by a few crop species. Furthermore, in locations where rigorous farming is practiced, a few varieties with a little genetic foundation interchange genetic variation within a crop species. Indigenous crop varieties have been dislodged and eventually wiped out as a result of these and other practices. Although such a situation has not occurred in Sikkim, it is anticipated to arise shortly due to rising population pressure and progressive operations in the agricultural and non-farm sectors. As a result, appropriate mitigating techniques and procedures are mandatory for the protection and use of these agricultural genetic resources. Mountains have been identified as biodiversity hotspots, yet they are vulnerable. Isolation and relative inaccessibility have aided in the conservation and protection of species in the highlands. Over short distances, frequent changes in elevation, slope, and sun direction have a huge impact on temperature, wind, moisture availability, and soil composition. A typical Sikkimese household includes some upland around the house, a few terraced plots (Dhan khet) at lower reach, a few fruit trees like Sikkim mandarin and pear, few fodder or fuel trees like Alnus, a vegetable like wild brinjal, local chilies, tree tomato, beans, cucurbits, and flower crops like orchids, Zinnia, Primula, one or two cows, pigs, goat, and a few fowls. More than two types of seeds can be found in a paddy, ragi, maize, or rice bean field. From the standpoint of seed certification, this is not a recommended technique, although it promotes the emergence of novel traits while increasing a species’ genetic variety and resilience. Many farmers in Sikkim, whether deliberately or unknowingly, engage in this technique. Sikkim is said to grow approximately 70 crop species and 200 cultivars of cereals, millets, pseudo-cereals, pulses, oilseeds, tubers, bulbs, and spices. In Sikkim, oldstyle farmhouse gardens are not only a key source of family requirements, but they also serve as a biodiversity hotspot for agri-horticultural and forest species. As agricultural techniques become more homogenized, the area under traditional crops such as buckwheat, and naked barley (Hordeum Himalayans), adzuki bean, and horse gram is shrinking and many of the landraces like Murli makai of maize, Ramzira,

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Thaprey, Ramkalan, Birinpool, Dharmali, Dhorokey Jholungey, Ramkalan, Kalchhati, Kataka, Khaiya Dhan, Mansare, and Sirkey-Marsee of rice, Harey sibi, Potherey sib, Jotharey, Jureli, Kali sibi, Harey Doode, Doode Haddey, Lam Rangey, Bharlangey, Kalo Mantulal, and Thakmanacy of rajmash, and Ghew Kera, Japadi, and Kadali of banana are obsolete (out of cultivation). According to the Government of Sikkim’s statistics, 45–55% of old rice types have been replaced by better-quality varieties. Livestock genetic resources are also under threat, owing to intentional crossbreeding with exotics to boost milk or other animal product production. Pure Sikkim goat and cow breeds are difficult to come by. Exotic breeds’ sperm are typically stored in semen banks. Finally, over 178 cultivars were diversified within the limited area of the agroecosystem, which is home to 69 crop species. However, over time, a significant amount of the genomic material cultivated by farmers has been destroyed or is no longer available in the field. However, some of them have been gathered and stored in the Sikkim Centre’s gene banks.

5.8 Conclusion The farming practices in the area are established and deeply interlaced with the ecological zones and climatic conditions. No single crop or a variety of crops can suit all elevations. Rainfed agriculture is a predominant feature, having only 15.08% area under irrigation. The main crops grown in the state are maize, wheat, rice, millets, barley, buckwheat, pulses, oilseeds, vegetables, fruits, large cardamom, and mandarin orange. Of these crops, mandarin orange and large cardamom are the traditional crops. The cultivation is done in sloping topography with or without proper bench terracing which calls for careful approaches and a scientific system of farming. About 50% of other lands are either improperly terraced or un-terraced. The mixed farming system is indigenous to Sikkim. The agriculture department in collaboration with the Indian Council of Agricultural Research has taken many steps to popularize the integrated farming system approach for sustainable agriculture. Traditional varieties and higher specific crop concentration areas need to be replaced with highyielding varieties to achieve expected growth. The century-old practices need to be revived and therefore, crop diversification with higher cropping intensity is necessary to feed the growing population and to reduce the pressure on the land resource. Agriculture needs to be practiced in such a way that it should not decrease the option of future biological production while satisfying the basic assumptions of agricultural production. Consequently, farming should be practiced as environmentally friendly, and it is only possible through agricultural diversification.

References

115

References Ahloowalia BS, Dhawan NL (1972) A synopsis in maize from Sikkim. Indian J Genet Plant Breed 32(2):229–233 Babu S, Singh R, Avasthe RK, Yadav GS, Chettri TK, Phempunadi CD (2015) Effect of organic nitrogen sources on growth, yield, quality, water productivity and economics of rice (Oryza sativa L.) under different planting methods in mid-hills of Sikkim Himalayas. Res Crops 16(3):389–400 Babu S, Singh R, Avasthe RK, Yadav GS, Rajkhowa DJ (2016) Intensification of maize (Zea mays) based cropping sequence in the rainfed ecosystem of Sikkim Himalayas for improving system productivity, profitability, employment generation and energy-use efficiency under organic management condition. Indian J Agric Sci 86(6):778–784 Bhatt BP, Bujarbaruah KM, Pattanayak A, Mandal BK, Vinod K, Venkatesh MS, Rajkhowa C, Kumareshan A, Santosh B, Datta M (2005) Rice-based integrated farming system in north-east. In: Bhatt DP, Bujarbaruah KM (eds) Agroforestry in north east India: opportunities and challenges. ICAR, Research Complex for NEH Region, Umiam, Meghalaya, pp 557–569 Bhatia SS (1965) Crop concentration and diversification in India. Economic Geography 41(1:39-56) Chettri S, Krishna AP, Singh KK (2015) Community forest management in Sikkim Himalaya towards sustainable development. Int J Environ Sustain Dev 14(1):89–104 Department of Agricultural Cooperation and Farmers Welfare (DACFW) (2018) Retrieved from http:/agricoop.nic.in/ FAO (1999) Agricultural biodiversity. In: Multi functional character of agriculture and land conference, Maastricht, Netherlands, Sept 1999. Background paper 1 of Food and Agricultural Organization, Rome. Available ftp://ftp.fao.org/docrep/fao/007/y5609e/y5609e00.pdf Gibs M (1974) Diversification index, quantitative techniques in geography: an introduction. H. Clarendon press, Oxford University Press, London Hazra CR (2018) Department of agriculture and cooperation. Ministry of Agriculture, India. Retrieved from http://www.fao.org/3/x6906e/x6906e06.html Horticulture Revolution (2017) Horticulture and cash crops development department. Government of Sikkim, Gangtok Hunsdorfer BC (2015) Purposeful emergence and knowledge networking in large cardamom (Ammum subulatum). Agro-ecosystem of Sikkim and beyond. Norwegian University of life Science, Department of Plant and Environmental Science ICIMOD (2010) Glacial lakes and associated floods in the Hindu-kush Himalayas. Working paper 2/10. Kathmanu Kumar P, Rai SC (2018) Agricultural diversities and its sustainability in Sikkim Himalaya: an analysis. Political Economy Journal of India 27(1-2):91–102 Kumar P (2020) Agricultural diversification and livelihood security in mountains farming systems of Sikkim Himalaya. Unpublished Ph.D. thesis, Department of Geography, University of Delhi, Delhi, India Pandey A, Semwal DP, Ahlawat SP, Sharma SK (2015) Maize (Zea mays): collection status, diversity mapping, and gap analysis. National Bureau of Plant Genetic Resources, New Delhi, India, p 34 Papola TS (2005) Development and livelihood in Sikkim: towards a comparative advantage based strategy. Discussion paper series-14. Human Development Resource Centre, UNDP, India Partap U, Sharma G, Gurung MB, Sharma E (2014) Large cardamom farming in changing climatic and socioeconomic conditions in Sikkim Himalaya. Working paper 2014/2. ICIMOD, Kathmandu, Nepal Patiram, Subba JR, Avasthe RK (2001) Indigenous nutrient management for crop production in Sikkim Hills. In: Acharya CL, Ghosh PK, Rao SA (eds) Indigenous nutrient management practices—wisdom alive in India. Indian Institute of Soil Science, Nabibagh, Bhopal, India, pp 274–284 Rahman H, Karuppaiyan R (2011) Agrobiodiversity of Sikkim. In: Arrawatia ML, Tambe M (eds) Biodiversity of Sikkim—exploring and conserving a global hotspot. Published by the Information and Public Relations Department, Government of Sikkim, pp 403–428

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Sahgal JL, Mandal DK, Mandal C, Vedivelu S (1992) Agro-ecological regions of India. Technical bulletin, national bureau of soil survey and land use planning. Indian Council of Agricultural Research, New Delhi and Oxford & IBH Pub. Co., New Delhi Schild A (2008) ICIMOD position on climate change and mountain systems. Mt Res Dev 28(3):328– 331 Sharma G, Rai LK (2012) Climate change and sustainability of agrodiversity in traditional farming of the Sikkim Himalaya. In: Arawatia ML, Tambe S (eds) Climate change in Sikkim: patterns, impacts, initiatives. Information and Public Relations Department, Government of Sikkim, Gangtok, India, pp 193–218 Sharma HR, Sharma E (1997) Mountain agricultural transformation processes and sustainability, in the Sikkim Himalayas, India. MFS series no. 97/2. International Centre for Mountain Development, Kathmandu, Nepal Sharma E, Sharma R, Singh KK, Sharma G (2000) A boon for mountain populations, large cardamom farming in the Sikkim Himalaya. Mt Res Dev 20(2):108–111 Sharma G, Sharma R, Sharma E, Singh KK (2002) Performance of an age series of Alnus-cardamom plantations in the Sikkim Himalaya, nutrient dynamics. Ann Bot 89:273–282 Sharma E, Sharma R, Sharma G, Rai SC, Sharma P, Chettri N (2008) Values and services of nitrogen-fixing alder based cardamom agroforestry systems in the Eastern Himalaya. In: Snelder DJ, Lasco RD (eds) Smallholder tree growing for rural development and environmental services: lessons from Asia. Springer Science Publications, Business Media, Springer, Netherlands Sharma G, Partap U, Sharma E, Rasul G, Awasthe RK (2016) Agrobiodiversity in the Sikkim Himalaya: socio-cultural significance, status, practices, and challenges. ICIMOD working paper 2016/5. Kathmandu Singh J (1974) Agricultural atlas of India: a geographical analysis. Vishal Publication, Kurukshetra Sikkim Development Report (2001) Government of Sikkim. Social Science Press, New Delhi Sundriyal M, Sundriyal RC (2003) Under utilized edible plants of the Sikkim Himalaya: need for domestication. Current Science 85(6):731–793 Thakur RN (2010) Nature and pattern of agricultural diversification in Bihar and Eastern India. In: Roy PK, Sharma SP (eds) Globalization and agricultural diversification of India. Regal Publications, New Delhi Vyas VS (1996) Diversification in agriculture: concept, rationale and approaches. Indian J Agric Econ 51(4):46–59 Vyas VS(2006) Diversification in agriculture: concept, rationale and approaches. Majumdar NA, Kapila U (eds) Indian agriculture in the new millennium. Academic Foundation, New Delhi Whittaker RH (1960) Vegetation of the Siskiyou mountains, Oregon and California. Ecol Monogr 30:279–338

Chapter 6

Analysis of Food Availability

6.1 Introduction Food availability states to “the availability of sufficient quantities of food of appropriate quality is supplied through domestic production or imports (including food aid).” Food availability is a concept that involves production and distribution concerns. Food availability refers to “the physical availability of food at the home, community, state, and international levels (Clay 2002).” Self-production or community production is the primary mechanism for the bulk of the world’s hungry to ensure the physical obtainability of food for themselves and their families. As a result, obtainability denotes the dispersal of food and food items across the population to humanitarian organizations, retail stores, etc. (FAO 1996). A foremost element of food obtainability is the occurrence of well-functioning market structures capable of delivering food to the area in a consistent, acceptable amount, and quality. Whereas food accessibility mentions an individual’s ability to obtain adequate food to encounter his dietetic demands (Jain 2016). It may also relate to a family’s capacity to get enough food to suit their requirements. It all comes down to food supply and trade, not fair in terms of amount but also in terms of value and variety. Supportable productive agricultural systems, well-managed resources, and productivity-enhancing strategies are all required to increase availability. Both financial and physical availability of food is referred to as “access.” Smallholders need better market access to make more money from cash crops, animal products, and other activities (Reutlinger 1977; Sarris and Taylor 1976). It is a measure of a family’s ability to access available foodstuff at any one time by combining homebased production and stockpiles, acquisitions, exchanges, and gifts. The two subconcepts of food accessibility and availability, which formed the foundation for the formation of the notion of food safety, are noteworthy characteristics of human safety in and of themselves. Food security is difficult to imagine unless and until the food is available and accessible. Per capita income, land availability, crop yields, land fertility, food charges, inflation, subsidy, investment, minimum support prices, agricultural policy, food waste, © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 S. C. Rai, Food and Livelihood Securities in Changing Climate of the Himalaya, Human-Environment Interactions 9, https://doi.org/10.1007/978-3-031-22817-9_6

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climatic variation, high energy costs, export limitations, interest rate, and so on all have an impact on food security. Studies on such parameters reveal that every rise or decrease in these elements has a proportional effect on food supply and accessibility as well as food security (Reeves et al. 2017; Saravia et al. 2012). Subsequently, food security is based on livelihood, any changes in food accessibility (resulting from changes in economic titles) and food availability (resulting from changes in production or trade) must be considered when assessing food security and hence livelihood. According to the United Nations, our earth will be home to roughly 10 billion people by 2050. The requirement for food and other farming goods is anticipated to rise by 50% between 2015 and 2050 because of this population growth. Providing food security for all will be extremely crucial, especially in a country like India, where 21.91% of people live in poverty and approximately half of all children are undernourished. Promoting creative and long-term livelihood opportunities is critical to living comfortably (Mathew 2010; Prasad and Pratap 2014; Jain 2016), especially in states like Sikkim where the present condition is rather odd and unlike. In Sikkim, the quantity of tourists arriving occasionally exceeds the total population of Sikkim, putting even more strain on the resource on which agriculture depends. So, what can be done to feed an ever-increasing population while accessible farmland per capita is restricted and shrinking? This is a crucial problem that must be investigated. Therefore, an effort has been made in this chapter to examine the gross and net food accessibility in the region.

6.2 Methods This chapter is constructed on various sources of data. The data was compiled from a variety of printed and unpublished documents from government and nongovernment organizations. For numerous years, agriculture statistics were obtained from the Department of Economics, Statistics, Monitoring, and Evaluation (DESME 2016), the Government of Sikkim’s Bulletin of Agriculture Statistics. For the years 2015–16, agricultural data was used. By multiplying the typical calorie need (2430) by 365 (2430 × 365 = 886,950), the normal annual calorie requirement has been calculated. After subtracting 12.5% (110,868.75) for processing waste and seed, the final amount is 997,818.75, or one Standard Nutrition Unit (Mohammad and Rai 2014). Discretely, one person = 0.773 consumption units, and 1000 people equals 773 consumption units (Chakravarty 1970). As a result, 0.773 is the consumption coefficient. To calculate the total consumption units, the total population of each district has been multiplied by the Consumption to: Total Consumption Unit = Total Population × Coefficient to Consumption

6.2 Methods

119

6.2.1 Gross Food Availability The consumption of food crops, which are the people’s basic diet, was used to calculate the land’s carrying capacity. Sikkim’s gross cropped area is dominated by food crops, which account for 72% of the state’s total cultivated area. Only food crops were considered in the future when determining the caloric production per hectare. We used a common conversion scale (Gopalan 2000) to convert 10 food crops into their calorific value, which we then combined to produce the gross availability of food in calories for each district t. Gross Availability of Food = Production The gross availability of food in monetary value was calculated with the help of market price for all the food crops during the study period.

6.2.2 Net Food Availability Meanwhile, due to leakage between the production and consumption of food grains, such as damages in storage and transportation, obliteration by insects and pests, kitchen waste, seed use, and so on, all of the food grains produced are not available in the same quantity for eating, but precise figures for all of these losses are not available. Following that, other researchers conducted research and stated several loss estimates (Kendall 1939; Raza 1992). According to Chakravarty (1970), a total deduction of around 16.8% of total gross output should be made to get net food accessible for consumption. As a result, the production coefficient is 0.832 (100 − 16.8 = 83.2), 83.2 × 100 = 0.832: Net Availability of Food = Gross Food Available × Coefficient to Production Using market prices for all food crops during the research period, the gross availability of food in monetary cost was estimated. When the given result is multiplied by the production coefficient, the net availability of food in monetary value is obtained.

6.2.3 Carrying Capacity of Land Various methods are available to determine the land’s carrying capacity (Stamp 1958; Shafi 1972; Gopalan 2000; Chakravarty 1970; Bernard and Derrik 2007). Net food availability in calories divided by net sown area equals net food obtainability in calorific value per unit of land, i.e., hectare. It has been further divided by the usual need of calories per head per year, yielding the land’s carrying capacity, i.e., how

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many people can be supported by one hectare of land in the district. Calories available for consumption are divided by total consumption unit to provide calorie availability per head per year, which is then multiplied by 365 days to yield calories available per head per day. Using the analytic approach of population valuation, the triennium average district-wise population for the years 2014, 2015, and 2016 was projected (Khan 1998). Agriculture in India is incredibly diverse, with crops ranging from paddy to opium being cultivated in various sections of the nation. The nature and look of the crop’s growing sections prevent them from being combined or added to. Weight, food grain equivalent, standard nutrition unit, calories, and monetary worth have all been advocated in the future (Singh 1972; Kendall 1939; Raza 1992). Because the other approaches have certain limitations, the monetary value was chosen in this chapter, even though it has numerous issues in terms of price assortment owing to seasonal and yearly volatility (Mohammad 1992). Access to food inside the home and elsewhere is ensured by the net availability of agricultural products in monetary value.

6.3 Results and Discussion 6.3.1 Pattern of Consumption The state’s demographic structure is broad and complicated, encompassing people of various ages, genders, occupations, and so forth. Though for the data related to agriculture at the district level were only available up to 2015–16. The triennium normal population of the anticipated total population for the years 2014, 2015, and 2016 of each district had been transformed into consumption units by multiplying it with the coefficient of consumption unit, 0.773. Table 6.1 shows the outcomes obtained. The average Projected Population in Sikkim for the year 2014–2016 was 643,112 (Table 6.1) with the highest population in the East district followed by South, West, and North. Consumption units and their percentage also follow similar orders in districts as population. The highest district-wise accessibility of giga calories of food crops is for maize, followed by paddy, soybean, buckwheat, urd, finger millet, and other pulses being the major food crops (Table 6.2). Table 6.1 District-wise consumption units (2015–16) Consumption

Districts North

Sikkim total South

East

West

Average projected population up to 2016 44,861 153,862 301,988 142,401 643,112 Consumption units (giga calories)

34.67

118.93

233.43

110.07

497.12

% of consumption units

6.98

23.92

46.96

22.14

100

6.3 Results and Discussion

121

Table 6.2 District-wise availability of giga calories of food crops, 2015–16 Crops

Districts North

Sikkim South

East

West

Paddy

4.660

12.933

30.278

20.244

Wheat

0.153

0.402

0.552

0.071

1.179

Maize

14.979

86.115

53.488

79.036

233.620

68.117

Finger millet

1.933

2.350

2.889

2.462

9.635

Barley

0.514

0.218

0.816

0.036

1.585

Buckwheat

0.701

4.658

4.186

2.325

11.870 10.030

Urd

0

5.912

1.084

3.033

Other pulses

0.854

4.549

1.539

2.203

9.146

Mustard

0.627

3.277

3.448

1.539

8.892

Soybean

1.123

Total

25.546

5.572

4.838

2.246

13.789

125.990

103.122

113.199

367.858

The total area under food crops in the year 2015–16 in Sikkim was 69,423 ha. The maximum area was in the South district, followed by the West, East, and the minimum in the North district (Table 6.3). Gross food obtainable in giga calories and Net food availability in giga calories were maximum in the South and minimum in the North. Per hectare, net food availability was similar in South, East, and West districts (0.004) and No. of SNU were maximum in the West followed by South, East, and North. Overall the highest value crop of Sikkim is maize with 6.831 billion rupees in the year 2015–16. Paddy holds second place after maize with 1.220 billion rupees. In districts, highest availability of maize is in the South and the lowest is in the North while the highest availability of paddy is in the East and the lowest is in the North. District-wise food crop availability in fiscal terms is presented in detail in Table 6.4. Table 6.5 shows the carrying capacity of land per district in fiscal terms. South district has the most area under food crop, Gross Fiscal term, and Net Fiscal term, followed by West, East, and North, while West district has the most Net Availability of Fiscal Value per hectare, followed by South, East, and North. Table 6.3 District-wise carrying capacity of land in calorific value, 2015–16 Districts

Sikkim

North

South

East

West

Area under food crops (ha)

5563

23,753

19,602

20,505

69,423

Gross food available (giga calories)

25.546

125.990

103.122

113.199

367.858

Net food available (giga calories)

21.254

104.824

85.797

94.181

306.058

Per ha net food available (giga calories)

0.003

0.004

0.004

0.004

0.00375

No. of SNU

3.82

4.41

4.38

4.59

4.30

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6 Analysis of Food Availability

Table 6.4 District-wise availability of food crops in monetary value (billion rupees), 2015–16 Crops

Districts

Sikkim

North

South

East

West

Paddy

0.083

0.231

0.542

0.362

1.220

Wheat

0.00095

0.00248

0.00340

0.00044

0.007

Maize

0.438

2.518

1.564

2.311

6.831

Finger millet

0.023

0.029

0.035

0.030

0.119

Barley

0.007

0.002

0.011

0.00050

0.021

Buckwheat

0.010

0.068

0.061

0.034

0.173

Urd

0

0.189

0.034

0.097

0.321

Other pulses

0.022

0.118

0.039

0.057

0.237

Mustard

0.024

0.126

0.133

0.059

0.343

Soybean

0.023

0.116

0.100

0.046

0.287

Total

0.633

3.402

2.526

2.999

9.563

Table 6.5 District-wise carrying capacity of land in monetary value, 2015–16 Monetary value

Districts

Sikkim

North

South

East

West

Area under food crops (ha)

5563

23,753

19,602

20,505

69.423

Gross monetary value (billion rupees)

0.633

3.402

2.526

2.999

9.563

Net monetary value (billion rupees)

0.527

2.831

2.102

2.495

7.956

Per hectare net availability of monetary 0.000095 0.000119 0.000107 0.000122 0.00011 value (billion rupees) No. of SNU

3.69

4.64

4.17

4.74

4.31

District-wise available consumption (Table 6.6) shows that the maximum consumption unit per year is in the South district, followed by the West, North, and East, similarly, the maximum consumption unit per day is also highest in the South district, followed by West, North, and East. Table 6.7 represents district-wise availability of fiscal value, and availability of funds per head per year also followed a similar pattern in districts as District-wise available consumption was highest in the South followed by West, North, and East. Table 6.6 District-wise available consumption of giga calories 2015–16 Concentration of calories

Districts

Sikkim total

North

South

East

West

Consumption unit/year

612.920

881.353

367.542

855.609

679.356

Consumption unit/day

1.679

2.414

1.006

2.344

1.861

6.4 Conclusion

123

Table 6.7 District-wise availability of monetary value, 2015–16 Monetary value Fund per head per annum Fund per head per day

Districts

Sikkim total

North

South

East

West

15,198.45

23,804.27

9005.81

22,674.76

17,670.822

41.64

65.22

24.67

62.12

48.412

It is clear from the tables that altogether four districts of Sikkim are in a foodinsecure situation. A primary explanation for the high incidence of food insecurity was topography, techno-economic, and socio-cultural elements. Subba’s (1984), Lama’s (2001), and Chakrabarti’s (2010) findings are also like our findings.

6.4 Conclusion The East district of Sikkim had a higher consumption unit than the North district. The South district had the largest food crops, followed by the West, East, and North districts, resulting in similar gross and net food availability in calories. The West district, however, had the highest net food availability per acre. The availability of consumption units and per hectare net food availability did not follow the same trend in all districts except the North. As a result, the consumption unit was maximum in the East district, while food availability per acre was significantly lower than required. In addition, the daily need for average calories per person was insufficient in all of Sikkim’s districts. The carrying capacity of land in Sikkim’s South and West districts was reasonably sound in terms of both calorific value and monetary worth, but the situation in the North and East districts was appalling and required immediate attention and concern for development. In terms of the monetary worth of agricultural produce per day per person, the money available in different districts of Sikkim was similarly very small. As a result, increasing profits on the one hand and increasing revenue on the other hand, while maintaining environmental protection is vital for making the state’s food self-sufficient. The key parts that must be robust for the state to realize its goal of food grain self-sufficiency are various farming techniques, crop rotation, and crop diversity. Increased investment in the farming sector, rather than relying on subsidies, can improve and sustain the state of carrying capacity of land by increasing these factors of food security, adopting locally appropriate best land-use patterns and practices, improving cropping patterns, and increasing investment in the farming sector.

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References Bernard FE, Derrick JT (2007) Population pressure and human carrying capacity in selected locations of Machakas and Ketni districts. Thakur B (ed) Prospective in resource management in developing countries. Concept Publishing Company, New Delhi Clay E (2002) Food security: concepts and measurement. Paper for FAO expert consultation on trade and food security: conceptualizing the linkages. Rome Chakrabarti AK (1970) Food grains sufficiency patterns in India. Geographical Review 60(2):208– 228 Chakrabarti A (2010) A critical review of agrarian reforms in Sikkim. Economic and Political Weekly 45 (5):23–26 DESME (2016) Sikkim statistical handbook. Government of Sikkim, Department of Economics, Statistics, Monitoring and Evaluation, Gangtok, Sikkim FAO (1996) The state of food and agriculture. Agriculture series 29. Food and Agriculture Organization, Rome Gopalan C (2000) Nutritive value of Indian foods. Indian Council of Agricultural Research, Hyderabad Jain S (2016) Food securing in India: problems and prospects. OIDA Int J Sustain Dev 9(1):11–20 Kendall MG (1939) The geographical distribution of crop productivity in England. Journal of Rural Statistical Society 38 Khan N (1998) Quantitative methods in geographical research. Concept Publishing Company, New Delhi Lama MP (2001) Sikkim human development report 20021. Social Science Press, Delhi Mathew J (2010) Food security: yesterday, today and tomorrow. In: Vattoly J (ed) Food security in India. Catalyst, Kerala Mohammad N (1992) New dimensions in agricultural geography, vols I–VIII. Concept Publishing Co. Pvt. Ltd., New Delhi Mohammad N, Rai SC (2014) Agricultural diversification and food security in mountain ecosystem. Concept Publishing Co. Pvt. Ltd., New Delhi Prasad P, Pratap A (2014) Food security in India: key issues and strategies. Bihar Econ J 3(1) Raza M (1992) Regional dimensions of agricultural development. Mohammad N (ed) Perspectives in agricultural geography. Concept publishing Company, New Delhi Reeves A, Loopstra R, Stuckler D (2017) The growing disconnects between food prices and wages in Europe: cross-national analysis of food deprivation and welfare regimes in twenty one EU countries, 2004–2012. Public Health and Nutrition 20: 1414–1422 Reutlinger S (1977) Food insecurity: magnitudes and remedies, Washington. Revealed by TRMM precipitation radar. J Meteorol Soc 133:149–165 Saravia SM, Gomez y Paloma S, Mary S (2012) Economics of food security. Bio-Based Appl Econ 1:65–80 Sarris A, Taylor L (1976) Central stock, food aid and food security. Food, Nutrition and Agriculture 4 (2): 15–27 Shafi M (1972) Measurement of agricultural productivity of the Great Indian Plains. The Geographer 19 (1): 7–9 Singh J (1972) A new technique of measuring agricultural efficiency in Haryana, India. The Geographer 19 (1): 14–33 Subba JR (1984) Agriculture in the hills of Sikkim. Sikkim Science Society, Gangtok Stamp LD (1958) The measurement of land resources. Geographical Review 48 (1): 1–15

Chapter 7

Analysis of Livelihood Security

7.1 Introduction The term ‘livelihood’ denotes the “means of safeguarding the basic requirements (food, water, shelter, and clothing) of life.” Since livelihood is common in economic activities, like “self-employment, wage-employment, and other types of engagement, etc., it is defined as the use of one’s endowments, both human and material, to produce acceptable resources, either in cash or kind, for meeting one’s own and family’s needs” (Chambers 1995). As a result, it is usually done continually, and as a result, it has become a way of life. A livelihood thus includes individuals, their talents, and their means of subsistence, such as food, income, and possessions. As a result, food safety is a critical constituent of livelihood safety (Minhas 1991; Dev 2008; Chambers 1995). Wages, labor, social pensions, payments from household members working in an urban region, unpaid domestic and farm labor, and other lawful and illicit activities are all factors that affect livelihood security. All these possibilities help people to live a pleasant life in society from time to time (Bandyopadhyay 1992; Dwivedi 2012). Farming is a fundamental and integral aspect of rural life. Villagers must contend with annoyances such as unemployment, poverty, malnutrition, illiteracy, and so on because they lack adequate livelihoods. People in rural areas will be able to satisfy their physical demands if they continue to be trained to apply their abilities (World Bank 1986; Su et al. 2018). Development, innovation, and resilience of livelihood sources must be promoted to enable rural people to obtain more economic ethics, enhance their level of life, and improve their production system. A livelihood can be sustainable if it is self-sustaining, capable of maintaining long-term natural resource production, strong in the face of external shocks and stressors, and does not threaten the livelihood opportunities of others (Kollmair and Gamper 2002; Petersen and Pedersen 2010). People who want to get a correct and genuine knowledge of people’s strengths, also known as ‘assets,’ ‘capitals,’ or ‘resources,’ are the focus of Livelihood’s approach. The importance of livelihood capital on poverty reduction in rural regions of northern Pakistan was underlined by Israr and Khan (2010). Their research found that the © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 S. C. Rai, Food and Livelihood Securities in Changing Climate of the Himalaya, Human-Environment Interactions 9, https://doi.org/10.1007/978-3-031-22817-9_7

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7 Analysis of Livelihood Security

degree of and access to various livelihood capitals affected the choice of livelihood alternatives and, as a result, the level of family welfare. As a result, it’s vital and fascinating to look at how people try to turn their abilities into great career results. The primary premise of this procedure is that people require a variety of assets to attain excellent living outcomes (Singh and Mathur 2006). When it comes to the technique of livelihood, it’s important to remember that such an approach must be feasible, flexible, and adaptive to unique local contexts and shared goods. The basic concepts of livelihood techniques include people-centered, holistic, dynamics, the construction of strengths, macro–micro linkages, and sustainability (Kollmair and Gamper 2002; Wichern et al. 2017). Based on the global agreement on which livelihoods are built, there are primarily four types of recognized properties or assets: social capital, human capital, natural capital, and physical capital. Though, a six-capital, also known as info capital, has been developed to cope with people’s access to data information needed to make decisions in pursuit of their livelihood goals (Odero 2008; Scoones 2009; Chambers 1994; Kumar 2020). In this chapter, we look at people’s alternatives for various livelihood security measures as well as the elements that influence mountain farming systems. The livelihood analysis is primarily intended to have a detailed dialogue with farmers to gain a well understanding of existing farming natures, such as agrarian diversities, market linkages, sources of livelihood/incomes, ways and means of increasing agricultural production, and limitations in agricultural production. As a result, an attempt was made to analyze the farming family’s socio-economic situation and their opinions of livelihood security.

7.2 Methodology To assess livelihood security, household data was gathered. The original data was collected using a multistage stratified random sampling procedure. To gather the information for the area, the entire state was separated into three ecological zones (upper, medium, and lower). After extensive consultation with various stakeholders, 12 villages were chosen, including Lachung, Padamchen, Chungthang, HeeGyathang (high-altitude villages above 1500 m asl), Yuksum, Rakdong Lingchom, Machong (middle-altitude villages between 1000 and 1500 m asl), and Turuk, NehBrun, Kamrang, and Dhalam/Daramden (low-altitude villages below 1000 m asl), covering 300 households (Table 7.1). The structured surveys included multiple questions on several pertinent topics. To add value, a complete conversation consisting of various questions on a subject linked to livelihood and institutional assistance was also discussed with the focused group during the reconnaissance survey to learn about the farmers’ perceptions of their livelihood.

7.2 Methodology

127

Table 7.1 Socio-economic information of surveyed households in different ecological zones of the study area, 2019 S. No. Parameters

Ecological zone High (> 1500 m) Middle (1000–1500 m) Low (< 1000 m)

1.

2.

3.

Number of households surveyed

81

74

63

19

26

37

Age of household head Between 20 and 30 yrs.

13

10

11

Between 31 and 45 yrs.

30

29

37

Between 46 and 59 yrs.

42

43

40

Between 60 and 70 yrs.

15

18

12

Age structure of household members Children (< 14 yrs.)

100

108

96

Young (14–30 yrs.)

114

111

104

Middle (31–45 yrs.)

172

172

174

Upper middle (46–60 yrs.)

128

103

111

55

50

68

Educational status of respondent 3

4

7

Less educated (below 10th)

55

56

49

Moderately educated (10th–12th)

40

37

41

2

3

3

36

35

34

Highly educated (graduation and above) Family size of household 1–4

6.

7.

100

Male (M)

Uneducated

5.

100

Female (F)

Old (> 60 yrs.) 4.

100

5–8

49

52

53

>8

15

13

13

Operational land holding size (ha) Marginal (≤ 1)

57

56

54

Small (> 1 to ≤ 2)

23

25

25

Medium (> 2)

20

19

21

Level of innovativeness Low (< 3)

16

13

18

Moderately (3–6)

69

71

70

Highly (> 6)

15

16

12 (continued)

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7 Analysis of Livelihood Security

Table 7.1 (continued) S. No. Parameters

Ecological zone High (> 1500 m) Middle (1000–1500 m) Low (< 1000 m)

8.

Sources of livelihood Farming

56

60

65

Non-farming

11

4

16

Farming + non-farming

33

36

19

7.2.1 Logistic Regression Model The logit regression model and the multinomial logit regression model were applied to know which factors influence the choice of various livelihood safety plans (Kumar 2020). The logistic regression model is the most effective statistical strategy for examining the factors that influence livelihood choices. It’s a method of determining an outcome by analyzing one or more independent variables. A dichotomous variable is used to assess the outcome. The purpose of this strategy is to create the best-fitting model to characterize the link between the dichotomous features of interest, that is, the dependent variable equals the response or outcome variable and a collection of independent (predictor or explanatory) variables. It has a dichotomous or binary dependent variable, which means it only has data 1 (success, true, etc.) or 0 (failure, false). Logistic regression predicts a logit transformation of the likelihood of the presence of the feature of interest by generating the coefficient, standard error, and significance levels of a formula. Logit ( p) = b0 + b1 X 1 + b2 X 2 + b3 X 3 + b4 X 4 . . . bk X k where p is the probability of the presence of the characteristic of interest. The logit transformation is defined as the logged odd: probability of the presence of characteristic p = 1− p probability of absence of characteristics )  p i.e. Log (Likelihood) and logit (P) = ln 1− P

Odd =

Rather than picking parameters to minimize the sum of square error (as in conventional regression), logistic regression estimation uses parameters to optimize the likelihood of witnessing the sample values. In this situation, the log of odds ratio reflects the probability of a person choosing agriculture over non-agriculture as a source of income. Here, p (probability) denotes the likelihood of a person working in agriculture, and 1 − p is the likelihood of working in non-agriculture.

7.2 Methodology

129

7.2.2 Multinomial Logistic Regression One form of logistic regression is multinomial logistic regression. Multinomial logistic regression is used when the dependent variable has many classes. The goal of multinomial logistic regression is to choose one of the response categories as the benchmark/baseline/reference cell, compute log-odds for all other categories relative to the baseline, and then make the log-odds a linear function of the predictors. So, following Greene (2003), let us explore the variables influencing the choice of household livelihood strategies among the three mutually incompatible livelihood strategy options. For the ath respondent choosing option b, the strategy may be expressed as: Sab = Z ab β + εab

(7.1)

If the respondent makes choice b in particular, then we assume that S ab is the maximum among the b strategies. So, the statistical model is derived by the probability that choice b is made, which is: Prob (Sab > Sak ) for all other values of K /= b

(7.2)

where, Sab is the utility to the ath respondent from livelihood plan b. S ak is the function of the ath response of the people from livelihood approach k. Therefore, ath household’s decision can be modeled as maximizing the expected option by choosing the bth livelihood strategy B discrete livelihood strategies, i.e., maxb = E(Sab ) = f b (xa ) + εab ; b = 0 . . . B

(7.3)

In general, for an outcome variable with B categories, let the bth livelihood strategy that the ath household chooses to maximize its options/utility could take the value 1 if the ath household choice bth livelihood strategy and 0 if this is not the case. The probability that a household with some characteristics x chooses means of support plan B, then Pab is modeled as: Pab with the requirement that

) ( exp X a βb = ∑J )B = 0 ( i=0 exp X a βb

∑J j=0

(7.4)

Pab = for any a

where, Pab Probability representing the ath respondent’s chance of falling into the category j X Interpreters of answer likelihoods

130

βb

7 Analysis of Livelihood Security

Covariate effects are specific to the bth response category with the first category as the reference.

Appropriate normalization that removes indeterminacy in the model is to assume that β1 = 0 (this arises because probabilities sum to 1, so only B parameter vectors are needed to determine the B + 1 probability), so that exp (X a βb ) = 1 implying that the generalized Eq. (7.3) above is equivalent to: ) ( exp X a βb ) for b = 0, 2 . . . B ( ∑J 1 + i=0 exp X a βb ) ( exp X a βb Pr (Ya = b/ X a ) = Pa1 = ) ( ∑J 1 + i=0 exp X a βb

Pr (Y a = b/ X a ) = Pab =

(7.5)

(7.6)

where, Y A polytomous outcome variable with categories coded from 0 … B Pa1 Probability derived from the constraint that B probabilities sum to 1. Like the logistic regression model, it implies that B log-odds ratios can be computed as: ⎡

Pab ln Pab

⎤ = X 1 (βb − β B) = X 1 β B, if B = 0

(7.7)

Analyzing the multinomial logit model will provide livelihood options for persons who are only involved in agriculture or non-agriculture, or for those who are reliant on both agricultural and non-agricultural sources of income. To accomplish the goal, logistic regression and multinomial logistic regression were used to evaluate the impact of various independent factors on the choice of sources of livelihood strategies. The information from published materials, focus group discussions, and primary surveys all guided the selection of such independent variables (Table 7.2).

7.3 Results and Discussion 7.3.1 Agricultural Diversities for Livelihood Farmers are involved in a wide variety of agricultural activities, including cash crop, dairy farming, poultry, floriculture, vegetable, food crop cultivation, and fish farming, among others (Table 7.3). Virtually every household respondent engaged in more than one source of income. Crop farming is quite common, with over 90% of households engaging in it. Food crop production was most prevalent (95%) in the mid-altitude

7.3 Results and Discussion

131

Table 7.2 Summary of the different variables considered in the study Name of independent Dummy variables variables 1st (benchmark variables)

2nd

3rd

1.

Size of land holdings Marginal (≤ 1 ha)

Small (> 1 but ≤ 2 ha)

Medium (> 2 ha)

2.

Education level of household head

Illiterate

Less educated (below 10th class)

Moderately educated (10th and above)

3.

Age of household head

Young (below < 30 yrs.)

Middle (30–59 yrs.)

Old (60–70 yrs.)

4.

Age structure of household members

1 child (< 14 yrs.) and young (14–30 yrs.)

Middle (31–45 yrs.)

Upper middle (46–60 yrs.) and old (> 60 yrs.)

5.

Family size of household head

Small (1–4 members)

Medium (4–8 members)

Large (> 8 members)

6.

Level of innovativeness of household head

Low (< 3)

Moderately (3–6)

Highly (> 6)

7.

Distance from the market/headquarters (km)

≤ 17

18–34

> 34

8.

Dependency ratio

Low (< 0.25)

Medium (0.25 to < High (> 0.45) 0.45)

S. No.

zone, followed by low-altitude (88%) and high-altitude (85%), respectively. Cash crop farming was the second most common agrarian activity, with more than 70% of households participating. Because of the high population density, the households’ survey found that most respondents (84%) lived in lower altitudes, followed by medium (66%) and higher altitudes (60%) accordingly. The second most popular farming activity was vegetable growing, which is necessary for practically everyone in some form or another and was undertaken by more than half of all families at all altitudes. Vegetable cultivation was more predominant in the lower and higher altitudes, according to the study, while the number of respondents in the medium altitude replied with greater incompletion (Table 7.3). With a few exceptions, all three activities were carried out across the state. In the state, dairy farming is also quite popular. Lower altitudes dominate dairy farming (37%) compared to medium and higher elevations. Farmers also engaged in poultry farming, although it was not a prevalent activity. Floriculture was another important activity carried out by 56 households, which is a new blooming activity due to the favorable climate conditions and increasing popularity due to its attractive monetary worth. As per the field survey, it was found more prevalent at the lower- and higher-altitude areas. Another major source of income for the people of Sikkim is fish farming. Nearly 24 households practiced it. According to the household survey, it was gaining grip at both the higher and lower

20

10

37

Daramdin

Sub-total

105 (35.00%)

7

12

Neh-Brum

Kamrang

8

36

Sub-total

Turuk

8

Machong

175 (58.33%)

72

13

18

21

20

46

9

14

8

10

11

Rakdong

Lingchom

15

57

14

12

11

7

8

32

Hee-Gyathang

Sub-total

Yuksam

6

Chungthang

Source Kumar et al. (2021)

Total

Low

Medium

9

9

Lachung

High

Number of respondents

Vegetable farming

Agricultural diversities

Dairy farming

Phadamchen

Village’s name

Altitude

Table 7.3 Agricultural diversities of the households (n = 300)

56 (18.67%)

39

5

15

0

19

4

0

0

4

0

13

0

5

0

8

Floriculture

85 (28.33%)

47

7

13

15

12

14

4

4

3

3

24

7

6

6

5

Poultry farming

24 (8%)

2

0

0

2

0

7

0

0

0

7

15

0

0

7

8

Fish farming

269 (89.67%)

88

24

25

19

20

95

23

22

25

25

86

24

25

24

13

Food crop farming

210 (70%)

84

17

18

25

24

66

12

16

18

20

60

16

8

13

23

Cash crop farming

31 (10.33%)

12

3

3

3

3

10

3

3

2

2

9

3

2

2

2

Others

132 7 Analysis of Livelihood Security

7.3 Results and Discussion

133

altitudes. Non-farming activities were carried out by about 31 families (Table 7.3). The preceding analysis depicts an overall picture of agricultural diversification, but there are many inter- and intra-village variances as well.

7.3.2 Range of Livelihood Options Table 7.4 shows the number of livelihood alternatives used by the sample families from Sikkim’s various ecological zones. According to the data, there are no substantial variations in the number of livelihood alternatives used by households in the three ecological zones. Despite low returns, almost 90% of farmers still rely on the cultivation of food crops for their livelihood. In the lower and medium altitudes, the number of such responses was higher (Table 7.4). Even though the amount of area used for food crops is declining, it still accounts for a significant share of agricultural land. The various environmental conditions of the settlements at higher elevations allowed the production of just a few key food crops including wheat, millet, rice, and maize. Maize, rice, paddy, wheat, mustard, and millet were the most common agricultural food crops grown in middle-altitude settlements. Maize, rice, lentils, barley, and other staple foods were farmed in lower-altitude settlements. Nearby, 72.33% of Sikkim’s total agricultural families rely on the production of cash crops to make a sustainable living. The number of such responders was greater at the higher altitudes, according to the initial survey (Table 7.4). Cash crop farming transformed the paradigm of agriculture, with many farmers making lakhs of rupees each year. Villages at higher elevations play an important role in the production and cultivation of commercial crops including ginger, vegetables, huge cardamom, and orange. Similarly, ginger, large cardamom, vegetables, and potatoes are the principal income crops in middle-altitude settlements. Large cardamom, drumstick, ginger, orange, and vegetables including potatoes are the main cash crops grown in the lower-altitude communities. Potato, large cardamom, ginger, vegetables, and oranges were the first-order crops produced in middle altitude. Floriculture provided a livelihood for about 44.33% of Sikkim’s rural households. The number of such respondents was particularly high in the middle and upper altitudes. In the Sikkim Himalaya, wide altitudinal fluctuations give ample opportunity for floriculture. Farmers were making a net income of Rs. 50,000–70,000/- from a small unit of 500 plants, according to the targeted group discussion. As a result, floriculture revolutionized the farming paradigm in Sikkim, with many farmers earning an average of Rs. 100,000/- per year. Villages in the East area, such as Karthik and Basilakha, have begun a new diversification to improve their economic situation. Dairy farming, poultry, piggery, goat development, rabbit and yak development, and so on are all examples of animal husbandry. As per the household survey, over 46% of Sikkim’s farmers rely on livestock for their livelihood. In the intermediate and low-altitude communities, the number of such responses was high (Table 7.4). Dairy production generates revenue while also providing manure for organic farms. Sikkim’s milking animals are cows, goats, and buffaloes. East district villages,

19

78

90

Sub-total

24

93

Daramdin

Sub-total

269 (89.67%)

23

22

Neh-Brum

Kamrang

24

23

Machong

Turuk

21

23

Rakdong

Lingchom

217 (72.33%)

72

17

20

18

17

67

17

16

19

23

86

Hee-Gyathang

Sub-total

20

15

22

Chungthang

21

18

23

19

22

Lachung

Phadamchen

Yuksam

Cash crops

Number of respondents

Food crops

138 (46%)

45

12

10

11

12

49

11

13

14

11

44

8

10

13

13

Livestock

Village’s name Source of livelihood/income

Source Kumar et al. (2021)

Total

Low

Medium

High

Altitude

134 (44.67%)

46

13

12

11

10

48

11

11

12

14

40

9

10

13

8

Agricultural labour

Table 7.4 Sources of livelihood/income for the people of Sikkim (n = 300)

134 (44.67%)

46

13

9

13

11

53

12

14

16

11

35

9

7

14

5

MGNREGA

122 (40.67%)

40

10

11

10

9

43

13

11

11

8

39

7

9

11

12

Forest

182 (60.67%)

48

12

13

12

11

59

17

10

19

13

75

17

18

20

20

Driving

133 (44.33%)

33

10

9

7

7

53

11

12

18

12

47

8

11

14

14

Floriculture

228 (76%)

68

18

18

17

15

84

23

19

25

17

76

18

18

21

19

Tourism

109 (36.33%)

41

10

11

11

9

40

11

8

15

6

28

8

7

10

3

Aquaculture

134 7 Analysis of Livelihood Security

7.3 Results and Discussion

135

followed by West district villages, were in a better situation in terms of dairy farming. Following a discussion with the focused group, it was discovered that it had assisted over 3180 farmers. Approximately 60% of milk was sold on the open market. In 2015–16, these farmers received 125 lakhs in incentives, as well as 12,920 kg of maize and oats seeds. Pork meat is consumed by a large portion of Sikkim’s people. Most of the villagers raise pigs and other animals as a result of their eating habits and to meet the need for pork meat and manure. The farmers stated that the Sikkim piggery department, ICAR, provides high-quality piglets to farmers, notably those from scheduled castes, scheduled tribes, other disadvantaged sectors, and marginal farmers, as part of the state’s livelihood self-sufficiency program. 5000 poultry producers frequently deliver their products to several marketplaces in Sikkim, as per government officials’ discussion. In 2015–16, total poultry bird and broiler outputs were 218.5 MT and 3300 MT, respectively. Under the credit, cum subsidy plan, educated jobless youth were given a 15% subsidy on the project cost for commercial poultry operations, so creating a significant initiative for the youth of Sikkim’s livelihood security. Many people in Sikkim keep goats as a source of income since they give quick cash to poor farmers in times of need. The government of Sikkim is supporting these farmers with subsidies and other forms of aid. Goats and sheep combined accounted for 38% of Sikkim’s total livestock population. During the field survey, farmers revealed that females were selling wool items to visitors at premium rates, which supplemented their income. Similarly, the yak is a Sikkim poverty-relieving animal. Each portion of its body has a market worth, from top to toe. Its milk and flesh were fermented and prepared into a variety of items. In Sikkim, the Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA 2005) has served as a model for improving livelihood security in rural households. Out of a total of 92,000 rural families, about 82,044 have received job cards (Group discussion). An average of 66 person-days per year has been worked by about 71% of households. Furthermore, roughly 27% of all households in rural Sikkim belonged to the poorest groups, which were covered and directly benefited by this initiative. Women’s involvement increased to 48% in 2015–16, up from 26% when the initiative first began. The West district has the most households engaged in this plan, followed by the South, East, and North districts. According to the primary survey, all the abovementioned works under this plan have supplied livelihood to 44.67% of Sikkim’s rural households, improving the people’s well-being (Table 7.4). According to a field survey, the forest provides a source of livelihood for 40.67% of rural households. As per the focus group discussion, numerous gram panchayat wards were identified as ‘poor hotspots,’ with many of them relying on forest resources for their livelihood, including fuelwood, fodder, medicinal plants, industrial wood, bamboo, and herbs. In 2015–16, the forest industry contributed 0.46% of the gross domestic product (GDP) at current prices. In these studied villages, various training such as interpretative guide training, bird watching guide training, rafting, and so on were performed, supplementing the farmer’s income.

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7 Analysis of Livelihood Security

In 2015–16, the forest department’s commercial branch, the utilization circle, generated more than 29.49 lakh from such sales and invested it in a variety of forest development projects, including afforestation, nursery development, and so on. As a result, the forestry sector may be defined as a diverse set of operations that includes ecosystem services, wildlife management, biodiversity protection, and non-timber forest product management. Forest management in the state is now changing from production-oriented to protection-oriented, and eventually to conservation-oriented. During the field study, it was discovered that just a few farmers are active in fish farming. Because of the shift in eating patterns and the increased usage of protein supplements, it is becoming more popular. In the intermediate and lower-altitude zones, 36% of farmers rely on aquaculture for their livelihood, according to the main survey. Inland fishes have been documented in the state in 48 different species. Sikkim’s fisheries development program included trout fishing, crap fishing, riverine fishing, Mahaseer fishing, ornamental fishing, and reservoir fishing. At current rates, the fishing sector contributed 0.04% to the total state domestic product in 2015–16. Approximately 76% of rural families were reliant on tourism for their livelihood. The number of such people was larger in the communities that were chosen, which were located at higher and middle altitudes (Table 7.4). Because of Sikkim’s natural beauty and diversity, tourism is regarded as the highest potential activity. It has been one of the state’s fastest-growing industries. It directly helps people’s lives by giving them direct employment. The tourism sub-sector has been developing at a quicker rate and now accounts for a considerable portion of the state’s revenue. More than 75,000 people were believed to be directly employed in hotels, travel agencies, and taxi businesses, but the tourist industry’s indirect employment was significantly bigger. Village tourism, which combines components of eco and cultural tourism, was shown to have the most direct influence on village communities’ livelihoods. While the houses that provide accommodation and boarding make money from these services, others earn money by working as porters, guides, and performers in cultural shows. Ravangla, in Sikkim’s South district, has demonstrated a form of resort tourism in a rural context of village tourism, which included the notion of “homestay.” However, since it was tied to the local economy and environment, it stood a strong chance of supporting local livelihood. In 2016–2017, the total revenue produced by visitors in the state was estimated to be Rs. 7068.86 million. In Sikkim, people are also engaged in driving professions to earn money. Driving professions offer by around 60.67% of rural families as per the household survey. Villages at upper and medium elevations had a larger proportion of such responses (Table 7.4). As a result, except for a few families in Sikkim’s villages, private light motor vehicles (taxis) were parked in many of the households. Farmers stated that, in comparison to all other types of vehicles, taxi registrations were growing every year. As a result, taxi driving made a major indirect contribution to the state’s economy. Agricultural labor was a source of income for 44.67% of farmers. The number of respondents that fit into this category was higher in the intermediate and lower altitudes. Sikkim had a total of 25,986 agricultural laborers, with 1106 of them working in the city and the remainder in the countryside. The East district had the most such laborers, followed by the West and South areas. There were only 2262

7.3 Results and Discussion Table 7.5 Options of livelihood and numbers of respondents (n = 300)

137 S. No.

Sources of livelihood

No. of respondents 181

1

Agriculture source

2

Non-agriculture source

31

3

Agriculture + non-agriculture

88

Source Field Survey, 2018–19

agricultural laborers in the North district. It accounted for 8.44% of all employees, including both main and marginal workers, and 4.26% of the entire population. In comparison to the involved spadework, an agricultural laborer earns the least. As a result, those agricultural laborers who were able to find other non-farm jobs redirect their attention to them. According to the field study, they are paid between Rs. 300 and 350/- per day, which adds gasoline to the fire of non-farm activities and occupations. Given the lack of prospects for growing the state’s net sown area, the state’s agricultural production and productivity of cultivated crops must be increased through intensive cultivation, which necessitates an increase in agricultural labor. As a result, the diversion of agricultural laborers and cultivators to other non-farming activities or employment is a major challenge that requires an immediate response.

7.3.3 Factors Affecting the Livelihood Options As witnessed during the field study, various households converted diverse livelihood possibilities in their day-to-day lives. The sample families engage in eleven distinct types of livelihood activities. These data were then divided into three categories: agriculture-based livelihoods, non-agricultural livelihoods, and both (Table 7.5).

7.3.4 Econometric Analysis of Factors Affecting the Livelihood Options The dependency ratio is a comparison of the total population between the ages of 15 and 64 years with the number of dependents aged 0–14 years and above 65 years. “It gives evidence on the number of people in the non-working age group vs. those in the working-age group.” It shows that when the reliance ratio rises, the ability of various families to satisfy their subsistence demands decreases and that a larger dependency ratio forces household to diversify their sources of income. Agriculture is less profitable for households with larger dependence ratios, especially in the mountainous terrain, as a source of income (Jansen et al. 2004). It means that when the degree of dependency ratio rises, the capacity of the various selected families to support their family’s requirements declines, but the possibility of diversifying livelihoods into

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7 Analysis of Livelihood Security

non-agricultural industries rises. The likelihood of a household slipping into both agricultural and non-agricultural livelihood methods grows as the dependence ratio rises. As a result, in areas where the dependence ratio is greater, there is an urgent need to address population growth as well as the availability of job opportunities for the working population. Warren (2002) and Rao et al. (2004) found such results to be substantial. However, because mountain farming is a family agricultural system in Sikkim, the results of the logistic regression and multinomial logistic regression were not found to be significant. Table 7.6 shows that, when compared to the benchmark variable, marginal farmers, the log of odds ratios for households with operational land holdings greater than one hectare was in favor of being more involved in maximizing their earnings through agriculture-related activities for their livelihood. Farmers in this situation were expected to rely on agricultural rather than non-agricultural sources of income. Similarly, the multinomial logistic regression result revealed that those with bigger landholdings had a lower likelihood of engaging in non-agricultural occupations as a source of income (Table 7.7). Berhanu’s (2007) and Tatek’s (2012) findings are likewise similar to ours. At the 5% level, the value of p (0.023) was significant. Even after performing multinomial logistic regression, the conclusion remained robust, since the value of p (0.021) was significant at a 5% level (Table 7.7). Furthermore, while the land is a natural asset for all families, farmers with large operational landholdings would favor agriculture-related enterprises because they may employ more efficient techniques and profit from economies of scale. As a result, they become less reliant on non-agricultural activity. The growing importance of agricultural/non-agricultural activities as a source of income, as well as the complexities involved (such as selling agricultural produce, its value-added products, labor, part-time wage employment, and petty trading), shows how different households respond to the shrinking farmto-household ratio. As a result, it’s reasonable to conclude that agricultural and nonagricultural sources of livelihood compete for limited family resources. This means that households who rely on agricultural revenue for their livelihood stability will continue to rely on it alone; otherwise, they will transition to a non-agricultural approach or a combination of both. Higher education is one of the most important predictors of choosing nonagricultural forms of income, because non-agricultural sources of income need trained or semi-skilled human resources, especially in high-paying paid positions. As a result, education improves the ability of farmers to diversify their sources of income. Even better-paying local employment requires formal education, often the completion of high school or beyond. The p-value of 0.035 derived from this model also supports the overall argument presented above, which was significant at a 5% level. Table 7.6 shows that in comparison to illiterate Sikkim household heads, those with less education were more involved in agricultural forms of subsistence. Moderately educated persons are less likely to work in agriculture since they perceive non-agricultural jobs such as driving, tourism, and so on to be more lucrative (Table 7.7). In other words, farmers with less education were less likely to engage in non-agricultural activities. Household heads with an average of a higher degree of education frequently live better lives by diversifying their sources of income. These

7.3 Results and Discussion

139

Table 7.6 Logit regression for livelihood choices between agricultural and non-agricultural activities as different strategies for farmers in Sikkim Sources of livelihood

Coefficient

Std. err.

z

P > |z|

[95% conf. interval]

Non-agriculture is the benchmark variable Dependency ratio

0.6955304 1.373471

0.51 0.613

− 1.996423 − 0.659831

3.387484

Land holdings Small

0.4609837 0.5718547

0.81 0.42

Medium

2.954351

2.27 0.023**

1.303088

0.4003463

1.581798 5.508356

Education Less educated

3.009432

1.423464

2.11 0.035**

More educated

1.532278

1.132336

1.35 0.176

0.2194931

5.799371

− 0.6870601

3.751616

Age 30 < age ≤ 59 years − 2.614445

0.8935537 − 2.93 0.003*** − 4.365778

60 ≤ age ≤ 70 years − 3.812224

1.474142

− 2.59 0.01**

− 6.70149

− 0.8631117 − 0.9229578

Family size Medium

0.1870274 0.5363064

0.35 0.727

− 0.8641139

1.238169

Large

0.4495996 1.124361

0.4

0.689

− 1.754108

2.653307

Middle (3–6)

− 0.3375899 0.8793025 − 0.38 0.701

− 2.060991

1.385811

High (< 6)

− 0.9975499 1.713843

− 4.356621

2.361521

Innovativeness − 0.58 0.561

Distance Near to market

0.9540996 0.6524732

1.46 0.144

− 0.3247243

2.232924

Distant from market

1.016415

0.8707832

1.17 0.243

− 0.6902883

2.723119

Constant

2.52951

1.301395

1.94 0.052*

− 0.021178

5.080197

***, **, * Significant at 1%, 5%, and 10% probability level, respectively Source Logit regression result (Kumar et al. 2021)

alternatives were more likely to be non-agricultural sources of income. This outcome was also consistent with Tatek (2012) and Galab et al. (2002). The age composition has a vital impact on the adoption of new ideas connected to the diversification of diverse sources of livelihood strategy possibilities. In comparison to young farmers, the p-value of the household head’s age between 30 and 59 years was 0.003 and 0.01, respectively, indicating that farmers in their middle age (30–59 years) and between 60 and 70 years had a higher probability of relying solely on agriculture as a source of livelihood (below 30 years). As a result, those under the age of 30 have a lower likelihood of relying only on agriculture as a source of income than those in the middle and older age groups. As a result, they were more inclined toward the non-agricultural source of livelihood strategy option, which was significant at 1% and 5%, respectively (Table 7.6). Even after using multinomial logistic regression, the outcome was solid. People in their later years (30–70 years) were more likely to choose agriculture as a source of income (Table 7.7). The likely

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7 Analysis of Livelihood Security

Table 7.7 Multinomial logit regression for livelihood choices among agriculture, non-agriculture, and both as different strategies for farmers in Sikkim Sources of livelihood

Coefficient

Std. err.

z

P > |z|

[95% conf. interval]

Agriculture is the benchmark variable Non-agriculture Dependency ratio

− 0.5219882 1.404573

0.51 0.71

− 3.2749

2.230923

Landholdings Small

− 0.454855

0.5891246 − 0.77 0.44

Medium

− 2.967745

1.289222

− 2.3

0.021**

− 1.609518

0.699808

− 5.494574

− 0.4409161

Education Less-educated

− 2.688489

1.481819

− 1.81 0.07**

− 5.592801

0.2158238

Moderately educated

− 1.731811

1.196502

− 1.45 0.148

− 4.076912

0.6132896

Age 30 < age ≤ 59 years

2.590712

0.9361813

2.77 0.006***

0.7558299

4.425593

60 ≤ age ≤ 70 years

3.637946

1.537319

2.37 0.018**

0.6248568

6.651036

Family size Medium

− 0.1446186 0.5568187 − 0.26 0.795

− 1.235963

0.946726

Large

− 0.2099066 1.12269

− 2.410339

1.990526

− 0.19 0.852

Innovativeness Middle (3–6)

0.3153724 0.9036165

0.35 0.727

− 1.455683

2.086428

High (< 6)

0.8920626 1.74638

0.51 0.609

− 2.530779

4.314904

Distance Near to market

− 1.014777

Distant from market − 1.281818 Constant

− 1.938419

0.6617063 − 1.53 0.125

− 2.311698

0.2821432

0.8900006 − 1.44 0.15

− 3.026187

0.4625509

− 4.56738

0.6905412

1.341331

− 1.45 0.148

Agri + non-agri. Dependency ratio

0.5453424 0.8317836

0.66 0.512

− 1.084923

2.175608

0.0316165 0.4112975

0.08 0.939

− 0.7745117

0.8377447

0.921

− 1.407044

1.27164

0.72 0.471

− 1.047736

2.268285

− 0.6096789 0.7360513 − 0.83 0.407

− 2.052313

0.8329551

Land holdings Small Medium

− 0.0677019 0.6833503 − 0.1

Education Less educated Moderately educated

0.6102742 0.8459393

Age 30 < age ≤ 59 years

0.0028507 0.6493183

60 ≤ age ≤ 70 years − 0.6489245 1.140219

0

0.996

− 0.57 0.569

− 1.26979

1.275491

− 2.883713

1.585863 (continued)

7.3 Results and Discussion

141

Table 7.7 (continued) Sources of livelihood

Coefficient

Std. err.

z

P > |z|

[95% conf. interval]

Family size Medium

0.114933

0.4176802

0.28 0.783

− 0.7037052

0.9335711

Large

0.949476

0.9767029

0.97 0.331

− 0.9648266

2.863778

Innovativeness Middle (3–6)

− 0.0622254 0.6059867 − 0.1

0.918

− 1.249938

1.125487

High (< 6)

− 0.3467485 0.9522538 − 0.36 0.716

− 2.213132

1.519635

− 0.194552

− 0.912457

0.523353

− 1.815574

− 0.0449495

− 1.355943

0.92783

Distance Near to market

0.3662848 − 0.53 0.595

Distant from market − 0.9302616 0.4516981 − 2.06 0.039** Constant

− 0.2140565 0.5826058 − 0.37 0.713

***, **, * Significant at 1%, 5%, and 10% probability level, respectively Source Multinomial logit regression result (Kumar et al. 2021)

reason is that assuming all other conditions remain constant, older farmers are more interested in floriculture/cash crop cultivation and earn an average of Rs. 1 lakh per year. In addition, the necessary expertise for non-agricultural occupations is missing. As a result, middle-aged and elderly family heads find it difficult to adapt their ageold crop-farming techniques, which require more spadework and lower output. As a result, these households either gradually transition to non-agricultural sources of livelihood strategy options or forsake agriculture operations. Berhanu (2007) and Tatek (2012) found comparable results to the current investigation. The diversity of multiple sources of income is positively connected with the size of the family. It’s because a greater family size and home labor correspond to a higher need for food in the household, implying that adding a family member increases the chances of the family participating in both agricultural and non-agricultural activities to fulfill their fundamental requirements. This means that even one more member in the home might push the family over the financial barrier, increasing the chances of diversifying the family’s sources of income. In other words, having an additional family member reduces the likelihood of working only on the farm. Bezemer and Lerman (2002) observed a similar finding as well. The availability of various families of indigenous seeds, high-yielding types of seeds, manure, shading, agricultural instruments, agricultural financing, insecticides, and pesticides is explained by their level of innovativeness. According to Tatek (2012), Adunga (2005), and Berhanu (2007), access to various levels of innovativeness has a substantial and favorable impact on families’ decisions to select either agriculture or non-agriculture as a livelihood strategy. Farmers may engage in petty commerce and other non-agricultural activities because of increased productivity and the use of varied innovativeness. This implies that the wealthy can afford to buy manure, superior seed kinds, and essential tools, whereas the poor cannot. Therefore, people who utilize manure/improved seed varieties/necessary instruments may

142

7 Analysis of Livelihood Security

be able to produce more per unit area than those who do not. As a result, they will have access to higher-quality, larger-quantity food and will be able to diversify their revenue sources for both subsistence and accumulation. Distance from the market or headquarters significantly impacts the livelihood options employed by various households, especially in hilly areas. Because of their proximity to the market/headquarters, they have better access to the market to sell their agricultural goods or look for new jobs. As the distance from the market grows, it becomes a deterrent to many households, particularly those residing at a higher elevation. When the strategy for livelihood choice was agriculture, non-agriculture, or both, the independent variable distance from the market was significant at a 5% level. The value of p was 0.039, indicating that as the distance between the market area and the corresponding district headquarter grows, the likelihood of choosing a source of livelihood strategy based on agriculture or non-agriculture drops, while the inclination toward agriculture increases. The most likely reason is that people in Sikkim, who live at a higher altitude, choose to perform agriculture for a living rather than looking for and choosing non-agricultural forms of income. By doing so, they avoid the greater unpredictability that comes with choosing non-agricultural forms of income. Similar findings were previously reported by Tatek (2012) and Berhanu (2007). In sum, the micro-evidence clearly shows that households with enough land to grow cardamoms, a high-value cash crop, adopt fewer livelihood options than smallholders. In other words, some evidence supports the hypothesis that the diversification of livelihood options tends to be distress-driven. However, it should be noted that the number of options practiced by a household is, inter alia, contingent upon their quality. A household might adopt fewer options that yield enough income, for example, large cardamom and mandarin orange.

7.4 Conclusion Sikkim state’s livelihood is based on a variety of agricultural activities. The major sources of livelihood for the local communities include cash crops, food crops, farming labor, tourism, motor driving, floriculture, and so on. Despite the massive profit from the cash crop, many people still relied on food crops to survive. In the Sikkim Himalaya, possible livelihood opportunities included beekeeping, mushroom farming, and sericulture. The dependency ratio, family size, educational status, age, landholding size, level of innovativeness, and distance from the market are all factors that influenced the farm family’s livelihood strategy options. The ‘main sectors’ in Sikkim’s state should be recognized and developed within a framework of sustainable use of the state’s rich natural resource base. The establishment of effective market connections and infrastructure is critical for the expansion of income and job opportunities in all industries. The judicious use of agricultural land, as well as mechanisms for boosting farmer price realization, should be given top priority. Floriculture has been identified as a thrust area in which a strong marketing strategy is critical to

References

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success. To enhance rural livelihoods, there is a considerable opportunity and potential to develop tourism both geographically and purposefully. Without efficient private sector engagement, the progression of economic growth and development will not be sustainable in the long run. Establishing food processing units in the state would increase market options, aid to preserve value, and generate jobs. Building efficient public–private partnerships should be a priority for the state administration. The policies should be formulated in such a way that they safeguard the economic interests of both producers and non-producers to provide long-term livelihood security.

References Adugna L (2005) The dynamics of livelihood diversification in Ethiopia revisited: evidence from panel data. Department of Economics, University of Massachusetts, Boston Bandyopadhyay J (1992) Sustainability and survival in the mountain. Ambio 21(4):297–302 Berhanu E (2007) Livelihood strategies of smallholder farmers and income poverty in draught prone areas: the case of Gena-Bosa woreda, SNNPRS. M.Sc. thesis, School of Graduate Studies of Haramaya University Bezemer DJ, Lerman Z (2002) Rural livelihoods in Armenia: the centre for agricultural economic research. The Department of Agricultural Economics and Management discussion paper no. 4.03 Chambers R (1994) The origins and practice of participatory rural appraisal. World Dev 22(7):953– 969 Chambers R (1995) Poverty and livelihoods: whose reality counts? ID discussion paper, 347. IDS, Brighton Dev SM (2008) Inclusive growth in India: agriculture, poverty and human development. Oxford University Press, New Delhi Dwivedi N (2012) Suggestions for female farmer’s areas of gainful employment: a study of rural area of Sikkim in north-eastern India. Res J Humanit Soc Sci 3(3):304–315 Galab S, Fenn B, Jones N, Raju DSR, Wilson I, Reddy MG (2002) Livelihood diversification in rural Andhra Pradesh: household asset portfolios and implications for poverty reduction. Working paper no. 34 Greene HW (2003) Econometric analysis, 4th edn. New York University, Macmillan Publishing Company Israr M, Khan H (2010) Availability and access to capitals of rural household in Northern Pakistan. Sarhad J Agric 26(3):443–450 Jansen H, Damon PA, John P, Wielemaker W, Schipper R (2004) Policies for sustainable development in the hillside areas of Honduras: a quantitative livelihood approach. International Food Policy Research Institute (IFPRI), Central America Office, Washington, DC Kollmair M, Gamper S (2002) The sustainable livelihood approach. Input paper for the integrated training course of NCCR north-south. Development Study Group, University of Zurich Kumar P (2020) Agricultural diversification and livelihood security in mountains farming systems of Sikkim Himalaya. Unpublished Ph.D. thesis, Department of Geography, University of Delhi, Delhi, India Kumar P, Rai SC, Verma R (2021) Evaluating the status of gross and net food availability in special reference to carrying capacity of land of Sikkim. Curr Res Environ Sustain 3:100099. https://doi. org/10.1016/j.crsust.2021.100099 MGNREGA (2005) Mahatma Gandhi National Rural Employment Guarantee Act 2005. Ministry of Rural Development, Government of India Minhas BS (1991) On estimating the inadequacy of energy intakes: revealed food consumption behaviour versus nutritional norms. J Dev Stud 28(1):1–38

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Odero PK (2008) Information capital: 6th asset of sustainable livelihood framework. Discov Innov 18(2):83–91 Petersen EK, Pedersen ML (2010) The sustainable livelihoods approach from a psychological perspective: approaches to development. University of Aarhus, Aarhus Rao PP, Birthal PS, Dharmendra K, Wickramaratne SHG, Shrestha HR (2004) Increasing livestock productivity in mixed crop-livestock systems in South Asia. Report of a project. National Centre for Agricultural Economics and Policy Research, New Delhi, India; International Crops Research Institute for the Semi-Arid Tropics, Patancheru, Andhra Pradesh, India Scoones I (2009) Livelihoods perspectives and rural development. J Peasant Stud 36(1):171–196 Singh NP, Mathur VC (2006) Sustainable agriculture and rural livelihoods: a synthesis. Agric Econ Res Rev 19:1–22 Su F, Saikia U, Hay I (2018) Relationships between livelihood risks and livelihood capitals: a case study in Shiyang River Basin, China. Sustainability 1–20 Tatek G (2012) Dynamics of livelihood strategies in the context of food security: the case of Bereh District, Oromia Especial Zone, Ethiopia. M.Sc. thesis, School of Graduate Studies, Haramaya Warren P (2002) Livelihoods diversification and enterprise development: an initial exploration of concepts and issues. Food and Agriculture Organization, Rome Wichern J, Wijk MV, Descheemaeker K, Frelat R, Van Astan PJA, Giller K (2017) Food availability and livelihood strategies among rural households across Uganda. Food Secur 9:1385–1403 World Bank (1986) Poverty and hunger: issues and options for food security in developing countries. A world bank policy study. Washington, DC

Chapter 8

Conservation of Agriculture for Sustainable Livelihood

8.1 Introduction Conservation agriculture is a crop-cultivation strategy that aims for a high and viable product, good quality, and financial rewards while also being environmentally friendly. Conserving soil and water are at the core of this process. The present century is demonstrating a time of enormous transformation for Indian agriculture. Agrarian commodity prices are low, economic support structures are shaky, and the threat of ever-lower trade blockades will add to the financial feasibility and keenness of Indian farming systems. Farmers are responsible for not just producing food grains, but also for caring for the surrounding community. Development of agriculture is a technique to increase food crops that sets out to attain maximum productivity for higher monetary return whereas preserving the basic natural resources viz., soil and water. The importance is on enriching natural biological processes both above and below ground. The most significant operations are reducing digging, protecting soil cover during the year, and employing operative crop alternations, which support to reduction of pesticide and fertilizer contributions and losses. Environmental projects prioritize soil, water, and biodiversity conservation. Soils are, without a doubt, the most essential factor in agricultural output. Soil development is expected to range between half and one ton per hectare per year at a “normal” pace. This means that just one centimeter of new topsoil might take a century or more to generate. As a result, the soil must be regarded as a primarily nonrenewable resource. “Agriculture soil is a valuable and restricted resource.” Irretrievable deprivation of this resource entails not only destroying current farmers’ principal resources but also reducing agricultural opportunities for future generations. As a result, soil conservation guidelines must pay special attention to the proper use and supervision of agrarian soils to accurately assess the fertility and agronomic value of agricultural land. Similarly, pure freshwater is necessary for survival, and both the quality and amount of

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 S. C. Rai, Food and Livelihood Securities in Changing Climate of the Himalaya, Human-Environment Interactions 9, https://doi.org/10.1007/978-3-031-22817-9_8

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8 Conservation of Agriculture for Sustainable Livelihood

availability are declining. Around the world, farming consumes nearly 70% of our existing water resources (Anonymous 2006). The Indian Parliament’s most recent agricultural changes, dubbed “New Agriculture Policy-2020,” focus on increasing farming’s environmental performance in exchange for subsidies, while leaving food production to market forces. Farmers must adhere to certain environmental ethical standards. Conservation agriculture is an approach to empower people in general and agrarian society in particular, to gain for themselves and for their children, more of what they want and need. Therefore, it involves the people among those who depend more on agriculture and seeks a livelihood and more control over the benefits of agricultural development (Swaminathan 2010; Taher 1975). Hence, conservation agriculture can be considered as a tool, for increasing the standard of living of low-income farmers, who mainly reside in villages, and making the process of their self-sustaining even more resilient. In India, there are mainly three goals of agricultural development, viz., firstly, to achieve high growth by enhancing agricultural productivity; secondly, completeness by concentrating on sheathing areas, small farmers, and women; and third is the agriculture sustainability (Chand 2004; Vaidyanathan 2010; Vyas 1996). Climate unpredictability has long-term paraphernalia on recharge rates and mechanisms. As climate fluctuates, the amount and position of normal groundwater recharge led to variations in storage, water table, and discharge (Resende et al. 2019). These variations in time and space show a vital task in monitoring the exchange of moisture and energy across the Earth’s land surface and attaching progressions grave to hydro-ecology and nutrient cycling. Climate change impacts water systems in both direct and indirect ways via recharge and through changes in groundwater use. Most of the groundwater flowing in sedimentary aquifers was recharged by precipitation and focused recharge via leakage from surface water sources (wetlands, streams, ponds, etc.) and is highly dependent on prevailing climate, land-use/cover, and underlying geology (Foster and MacDonald 2014). Both land-use and climate are mainly accountable for evapotranspiration and precipitation, it is determined by the soil and geology that water can be diffused and stored on the underground surface in the form of aquifers. Anthropogenic actions are attractive to the Earth’s greenhouse consequences and these happenings will likely increase warming. Global warming is expected to upsurge precipitation variability and fluctuations in seasonal patterns (David and Kaufmann 2014). Even small variations in rainfall patterns may lead to changes in recharge in semi-arid and arid regions (Neukum and Azzam 2012). In today’s times, the relationship between rainfall and water is intricate by water usage, which includes, the extension of rainfed and irrigated areas in the drier region in the absence of surface water (Russo and Lal 2017). Modern agriculture does not reply to deviations in rainfall in the same manner as traditional agricultural practices. In fact, these changes may employ a sturdier influence on terrestrial hydrology than climate change.

8.2 SWOT Analysis for Conservation Agriculture

147

Sikkim state can be one of the promising states in the Himalayan region concerning agriculture and allied services if properly managed. Poverty is not solely of the land but also, of the system of management and lack of capital for the development of the region (Grover 1974; Lepcha et al. 2008). According to the agro-climatic conditions and soil structure, other alternative enterprises like dairy, poultry, fisheries, floriculture, etc., should be developed with the development of transport and marketing facilities. In such a region, endowed with abundant natural resources, we may have to adopt development for agriculture. Agricultural development in such a food deficit state cannot have any success if it is undertaken in small doses of investment (Narain et al. 1991; Ahluwalia 1976). It must emerge from within and conform to the prodigy of the people. The initial thrust must be sufficient to enable the region as a whole to move from its present state of agricultural development to that of the initiation of the landmark development. Thus, it may take advantage of the collective effects of steady growth and set an example for other Himalayan states. Hence, keeping these points in the assessment, it is necessary to undertake an analytical study of the various measures to improve agricultural development and land-use arises in the different districts of Sikkim to ensure a sustainable livelihood.

8.2 SWOT Analysis for Conservation Agriculture To suggest measures to improve the conservation of agriculture and land-use to ensure sustainable livelihood, it is obligatory to know the strength, weaknesses, opportunities, and threats prevailing in Sikkim state concerning agriculture. Therefore, SWOT analysis from the agricultural scenario is necessary to evaluate and classify both the in-situ and ex-situ factors that are positive or adverse to attaining the goals. This investigation will benefit in evolving a premeditated strategy to make this sector competitive. Henceforth, this statement will be focused on inspecting the strengths, weaknesses, opportunities, and threats of the agriculture sector. There is a need to discuss a critically different aspect of this alternative management approach to finding out its feasibility under Sikkimese conditions. Therefore, the suggestive measures for conservation agriculture are based on the discussion with the focused group, household survey, secondary data, observations, literature review, and SWOT analysis (Fig. 8.1). In this context, for undertaking agricultural development in terms of production, productivity, area of food crops and cash crops, entire commodity chain, market and credit facilities linkages, government as well as private entrepreneurs, etc., need to be best equipped. By doing this, advantages can be taken, for ascertaining the sustainable livelihood security from the naturally endowed strength and opportunity prevailing in Sikkim Himalaya and to ameliorate and wipe out the weaknesses and threats it has, in the overall development of Sikkim.

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8 Conservation of Agriculture for Sustainable Livelihood

Fig. 8.1 SWOT analysis

8.3 Adoption of Conservation Agriculture The term “conservation agriculture” is commonly used, yet it is frequently misunderstood or misinterpreted. Normally, it is primarily discussed in the context of food crops; nevertheless, the application of Conservation Agriculture has been identified for “annual crops (both food crops and vegetables), as well as perennial crops (fruit trees and grassland in animal farming systems).” Most of the rural people are involved in the cultivation of food crops as their main source of income is from agriculture. Conservation Agriculture provides an insight into the dynamic forces of agricultural growth, and into the changing sources of progress. The economies range from those in which output is growing to those in which agricultural output is increasing. Conservation of Agriculture is generally based on three entangled philosophies which are prerequisites to be adapted to certain cropping systems: (i) lowest soil disturbance, (ii) continuous soil cover, and (iii) rotations of the crop. Thus, it is frequently observed as an integrated approach to improving the environment and well-being of the people in general and the farming community in specific.

8.3 Adoption of Conservation Agriculture

149

Conservation of Agriculture in Sikkim Himalaya can be achieved through agricultural diversification, assured irrigation, maintenance, and improvement of soil and water resources through an integrated system aimed at environmental and economic sustainability. In brief, effective natural resource management can be an important basis for conservation agriculture. The agro-climatic zones of Sikkim superimposed on landform act as a modifier to climate and length of the growing period. The natural endowment of Sikkim can bridge the gaps between actual and potential yields through its enormous potential for the development of agriculture, horticulture, animal husbandry, and fisheries by using available and accessible technologies. The basis of policy formulation should be ‘glocal,’ i.e., local to global, which means “think, globally and act locally, and support nationally and globally.” Therefore, the varied farming system is an opening to improve the people’s livelihoods and soil health of hilly regions under changing climatic situations. The vision for agricultural development in Sikkim should comprise providing multiple livelihood opportunities, sustainable farming systems approach, converting ‘backwardness’ to comparative advantage, and strengthening capital formation in the agriculture sector. The important indicators of agricultural development and their status in different districts of Sikkim are presented in Table 8.1. With the factors of agricultural development, net sown area/grossed cropped area, irrigated area, land-use efficiency index, crop diversification index, cropping intensity, the number of agricultural credit and agricultural market societies, numbers, and size of landholding are the most important indicators of agricultural development. Because any change in the value of these indicators will immediately and commensurately affect the agricultural development of Sikkim (Lepcha et al. 2008). A close perusal of Table 8.1 indicates that barring a few exceptions, the value of these indicators of agricultural development of West Sikkim is comparatively better in comparison to other districts of Sikkim. Similarly, the other factors of agricultural development, such as agricultural density, physiological density, literacy rate, number of cultivators, and agricultural laborers are comparatively less important indicators of agricultural development. But all indicators of agricultural development are very necessary for agricultural development in Sikkim. Therefore, farm practices are essential to be reoriented to afford climate resilience.

8.3.1 Minimum Mechanical Soil Disturbance The importance of plowing variety has been well explored and addressed in agricultural conservation ethics. To the degree that the phrases conservation tillage, ideally no-tillage or minimum, and non-inversion tillage are frequently used in place of typical moldboard plowing, non-inversion tillage is strongly preferred (where the soil is reversed). Nevertheless, the nature and severity of soil disturbance should be suitable for the soil type, crop, and weather circumstances. The alteration of tillage will be uppermost in the minds of adopting agricultural producers, particularly when they embrace any new practices. This method can be used for all perennial and annual vegetables and crops. The term direct seeding is also known as no-tillage,

0.78 6.23 8.71 16 3570 13.87 77.39 929 749

Irrigated area (%)

Agricultural density (no. of farmers and cultivated area)

Physiological density (population size and cultivated area)

Cropping intensity

Irrigation intensity

Land-use efficiency index

Crop diversification index

No. of cultivators (%)

No. of agricultural laborers (%)

No. of agricultural credit societies

No. of agricultural market societies

No. of holdings

Grossed cropped area (%)

Literacy rate (%)

No. of large size holdings (> 2 ha)

No. of small size holdings (≤ 1 ha)

No. of medium size holdings (> 1 to ≤ 2 ha)

2.

3.

4.

5.

6.

7.

8.

9.

10.

11.

12.

13.

14.

15.

16.

17.

18.

Source Kumar (2020)

13.54

Net sown area (%)

1.

1892

17

3.2

144.08

126.64

3.64

0.80

7.11

North

Factors of agricultural development

S. No.

5712.05

11,165.25

7686.70

84.67

27.42

24,566

50

50

44.18

26.83

0.86

2.4

133.79

120.56

12.36

1.87

36.81

28.12

East

Table 8.1 Important factors of agricultural development and their present status in different districts of Sikkim

5310.03

10,375.78

7143.20

82.07

27.98

22,829

47

47

16.12

32.19

0.83

2.4

124.81

121.49

6.15

1.78

19.11

28.47

South

5794.25

12,748.32

5420.43

78.69

30.72

23,963

72

73

30.99

34.75

0.84

2

130.8

127.03

5.32

1.9

36.97

29.89

West

150 8 Conservation of Agriculture for Sustainable Livelihood

8.3 Adoption of Conservation Agriculture

151

zero tillage, direct drilling, etc. Land preparation for direct seeding involves zero or no equipment. All the activities are done manually such as weeding, clearing previous crop residues, and herbicides spray. Crop residues are used as per the need to give the soil maximum coverage. Planting involves the precise placing of large seeds, whereas the constant flow of seeding is in the case of small cereals like barley, mustard, and wheat. The equipment used for seeding, infiltrates the soil cover, using a seeding slot and putting the seed into that slot and then the seed slot is completely covered by mulch again. Once the process is complete, no movable soil remains evident on the surface. It has been observed that farmers in several villages have been practicing deep plowing techniques, which are very much harmful to the fertility of the soil. Thus, minimum tillage has been suggested given the problem in the area, which has multifaceted benefits for the conservation of both water and soil viz., (a) it shields the soil against wind and water erosion, (b) advances infiltration and conserves soil moisture, (c) increases soil organic matter, and (d) cost savings for fuel, time, and labor in the long term. Conservation tillage cannot be implemented in loneliness because it is a rudimentary managing tool (Lal 1989).

8.3.2 Permanent Soil Cover with Crop Residues and Live Mulches In the absence of a crop, having a vegetative cover on the soil plays an important role in protecting and improving the soil’s qualities. In yearly crops, this protection can be accomplished by cutting and dispersing the harvested crop’s leftovers, or by planting a cover crop that will be merged or dehydrated before the following crop is drilled. Control of soil protection is one of the essential values of agriculture conservation. Crop remains are left on the soil surface, but cover crops are also desirable if the gap between the two crops is long. Protection crops are usually grown during fallow times, between harvest and planting of marketable crops to apply the remaining soil moisture. It improves not only the fertility of the soil but also promotes biodiversity for the entire agroecosystem. Commercial crops are grown for selling purposes while protection crops are for their effect on soil fertility or used as livestock fodder. These coverings protect soil from rainfall and wind, which cause erosion, while also improving its qualities by adding organic matter to restore its structure and fertility. The presence of a mulch layer prevents the evaporation of soil moisture and leads to better water penetration into the soil profile. In hilly regions where erosion rates are very high, cover crops are applied in many ways, i.e., (a) to give an extra source of organic matter to rally soil structure, (b) by rallying and recycling nutrients (especially P and K) in the soil profile to make them more eagerly available for the following crops, (c) improving the soil structure and break compacted layers and hardpans, (d) permitting rotation in a monoculture and can also be used to control pests and weeds, and (e) utilizing easily leached nutrients (especially N).

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8.3.3 Diversified Crop Rotation and Intercropping Pests, weeds, and diseases will have a worsened effect on a specific crop variety, giving prospects for alternate management devices or reducing the necessity for outside inputs. Plants with legume roots have bacteria that extract nitrogen from the sun and convert it into forms that plants can utilize, eliminating the need for fertilizers. The culture of the rice–wheat cropping sequence for more than three decades in the state has contributed to a tremendous decline in the water table of the groundwater. Thus, crop diversification is the need of the hour, to recover soil strength, water conservation, and maintain the dynamic balance of the agroecosystem. Crop rotation means that diverse crops are interchanged in the same field preferably cereals followed by legumes. The crop alternation provides a diverse diet to the bacteria available in the soil microorganisms and allows them to reach out to different soil layers in the search for nutrients. The crop rotation functions as a biological pump and helps in retaining the nutrients that have been percolated into deeper layers and are no longer available for the present crop. The roots of diverse crops defecate diverse organic matters that appeal to varied types of bacteria and fungi that play a vital role in retrieving depleted nutrients over the period. Crop alternation also has a significant phytosanitary role as it breaks the monotony of crop-specific pests and diseases from one crop to the next through crop residues. During Rabi, the wheat can be replaced by oilseed, and in the Kharif season, the rice can be replaced with low water-consuming crops such as maize, cotton, fodder, and agroforestry. Paddy must be watered 40 times each season. Only five to six times is plenty for maize. If non-basmati paddy producers switch to maize, they may save around 4 million liters of water per hectare. The following are the benefits of crop rotation, i.e., (a) increasing soil fertility, (b) controlling pests and disease, (c) improved circulation of water and nutrients through the soil profile, (d) investigation of water and nutrients for varied strata of the soil profile using various root channels for different plant species making the best use of the available nutrients and water, (e) improved soil structure through leguminous plants, and (f) augmented humus development. There is an utmost need to set up public investment in expanding and distributing crop varieties that are more lenient of temperature and precipitation variations and are more water- and nutrient-efficient. Agriculture policy should focus on improving crop production and evolving safety nets to cope with the risks of climate change.

8.3.4 Organic Farming The green revolution was introduced in the 1960s to feed millions of people through increased production. This revolution intricate hybrid seeds which give maximum results if used in combination with chemical fertilizers, pesticides, and a hefty dose of irrigation. The native crops were unable to stand up to the chemical application, so farmers had to purchase high-yielding varieties of seeds. This has resulted

8.3 Adoption of Conservation Agriculture

153

in the displacement of indigenous species and led to monocropping. Although the green revolution was initiated with the best intentions to ensure food security, it has resulted in water table depletion and the soil has been depleted of nutrients essential for growth.

Manure in farm

The demand for organic food emerged after the negative impact of the green revolution when the ill effects of agrochemicals on human health and the local environment were realized in the developed and developing world. Therefore, organic farming drew attention to its potential to produce healthy food together with environmental conservation. In recent times, organic farming is being viewed also as a means of conserving biodiversity and mitigating climate change impact. Therefore, the solution lies in the introduction of organic farming. Agriculture is a major landuse in terms of spatial extent and is the backbone of locals’ livelihoods in the Sikkim Himalaya. It highlights the use of managing practices in favor of the use of off-farm inputs, taking into account local and regional situations, viz., barley, sorghum, and millet, which are suitable for rainfed conditions. Thus, organic agriculture is an integrated farming system that strives for the sustainability of groundwater resources, enhancement of soil fertility, and promotes biological diversity. Linking organic farming with other development programs and promoting organic agroforestry in degraded lands would be more beneficial to the farmers. The demand for organic food is increasing day by day because of environmental and human health problems. Agriculture is a minor land-use in terms of spatial extent in the mountainous region. Majority of the farmers of Sikkim practice organic farming. There is a need for linking organic farming with other development programs. Promoting organic agroforestry in degraded lands increase agricultural productivity. There is also a need to develop direct links with consumers by operating “organic restaurants.”

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8 Conservation of Agriculture for Sustainable Livelihood

The government policies and programs should be for mandatory consumption of organic food in events fully funded by the government. There is a need for the establishment of participatory research stations for further improvement in the existing organic farming system.

8.3.4.1

Bio-composting

Conservation of weeds and other farm resources into nutrient-rich compost is detailed below: Methods • Raw material resources (such as poultry wastes, soil, paper, dairy and vegetable wastes, eggshells, eupatorium weed, other plants, and old compost) available easily at villages/farms were used. • This is mixed with fresh cow dung and put into compartments (1 m2 ) made up of hollow blocks or bamboo. • Perforated HDP pipes or bamboo are inserted into the mixture heap. This acts as an exhaust for gas coming up from the mixture. • The compartments are protected from rain by polythene sheets or any other traditional thatching material. • A compost heap is churned weekly. • The compost is ready for use between 19 and 31 days depending on composition. Observation The compost was tried and found to be useful to a host of field crops. Almost all the vegetables responded well to it. The compost with a low N/P ratio is found more suitable for mountain farming systems.

8.3.5 Soil Conservation In Sikkim, 20% of the cultivable land is being cultivated without any soil conservation measures. Indiscriminate exploitation of land resources accelerated the soil erosion process more intensely. Improper management of land is leading to land degradation. All these sorts of things are prevalent in Sikkim. So, this untreated land needs to be brought under suitable soil conservation measures by considering the land capability classes and soil depth.

8.3 Adoption of Conservation Agriculture

155

Methods • Contour bunds can be created either in a mechanical way or by a vegetative barrier across the slope to retard the runoff during rain which in turn retard the soil erosion processes. They are created by excavating a channel parabolic in shape, 0.3 m top to 0.2 m deep on the contour. The soil so obtained is kept at the lower edge of the created parabolic channel. Depending on the degree of slope, land-use, and soil depth, the vertical intervals of these bunds vary from 0.5 to 5.0 m. • Bench terraces can be built throughout the slope in space amid two contours, leveled by the cut-and-fill method. Wherever the soil depth is more than 1 m, a vertical limit of such bench terraces should not exceed more than 1 m. In Sikkim to convert slopes into bench terraces, the inception of construction should start from the bottom of hilly terrain. • A half-moon terrace can also be constructed around the level circular beds having a diameter ranging from 1 to 1.5 m by cutting on the hill slope. The edge of such terraces can be used for the plantation of Thysanolaena maxima (broom grass) species to contain soil erosion. As it has a strong, deep, and dense fibrous root system, it binds the soil and therefore, enhances shear strength which helps in armoring the slope against surface erosion from both runoff and rain splash. It is a harder species suitable to rehabilitate graded land. Other species such as Dicranopteris linearis (bhui amla), Erythema spp., and Viburnum spp. (one of the fastest-growing species mending soil profile) can also be used in controlling soil erosion.

Benefits • Such soil conservation technique retards and checks the process of soil erosion. The bunds and terraces so constructed slow down the speed of runoff water from which the water reaches the inner soil molecules also and therefore, the moisture content of the soil prolongs.

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8 Conservation of Agriculture for Sustainable Livelihood

• Increases the carrying capacity of land and thus farming became more sustainable and productive. • Thysanolaena maxima (broom grass) inflorescence is used as a broom. It also provides fodder throughout the year. 8.3.5.1

Sloping Agriculture Land Technology (SALT)

This technique is soil-conserving. In these techniques, contour and hedgerows play an important role. An instrument, the A-frame, is used to locate the contour line of the field. Three sturdy wooden or bamboo sticks, at least a meter in length, and strings are required to construct the simple device. The A-frame is shifted forward by inserting the rear leg where the front leg had previously stopped. Adjust the front leg until it is level with the back leg. A pole is placed every 2–3 m along the contour line to mark it. This procedure is repeated until the whole length of the contour line, which is on the other side of the peak or hill, has been covered. The field is plowed and harrowed until it is suitable for planting once the contour lines have been reached. On each ready contour line, two troughs are made one-half meter apart. Between each such pair of furrows, a space of 6 m is maintained (the Alley) for growing cash crops, etc. To ensure a nice, dense stand of seedlings, the seed is spread in each furrow. Nitrogen-fixing trees are ideal plants for rebuilding forest cover over slopes and fields that have been devoid of trees because of their capacity to grow on impoverished soils and in locations with extended dry seasons. Flemingia macrophylla, Desmodium rensonii, Gliricidia sepium, Calliandra catotyrsus, and Thysolina maxima (broom grass) are the finest examples of nitrogen-fixing plants for hedgerows on the SALT farm. The contour hedgerow system once adopted leads to various direct benefits from crops. Indirect benefits are soil conservation and rehabilitation of degraded slopes and retention of soil water moisture.

Thysolina maxima (Broom grass)

8.3 Adoption of Conservation Agriculture

8.3.5.2

157

Polyhouse and Polybeds

Polythene-covered houses are a scaled-down version of the conventional greenhouse. Cutting down on the cost of polyhouses makes them accessible to a large section of users who grow vegetables, ornamentals, foliage plants, and other plants in them. The plants fare better in the polyhouse environment than outside especially in temperate and high altitudes, so off-season vegetables may be grown inside it. Germination of seeds and their subsequent growth are quite appreciably better in a polyhouse. Heat retention was appreciable in all the designs. Different cash crop seedlings including cardamom have done well in the polyhouse environment. Even bamboo responded well and shoots were produced which were later successfully transplanted elsewhere. Looking at the growing population, climate variation, declining landholdings, increasing pressure on natural resources, and high demand for quality products, such techniques can be useful in the Himalayan region. Methods It is built with the help of a certain number of specially designed bamboo and plastic sheets suitable for the requirement of the crops, topography, and hilly terrain. These constructed playhouses act as tabular greenhouses as they are equipped with UVstabilized materials. Above 150 GSM polythene sheets were used in most of the constructions. Polybeds are simple structures, used as and when required, especially at night, and useful in frost-prone locations.

Polybed technology

Vegetables grown in polyhouse

Benefits • It modifies the natural environment to achieve optimum plant growth. • This technique can help in protecting the cultivated plants by overcoming the adverse climatic conditions of high rainfall and low temperature which are more prevalent in hilly terrain.

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8 Conservation of Agriculture for Sustainable Livelihood

• This technique is also cost-effective and requires less effort in construction and maintenance.

8.3.5.3

Strengthen Agroforestry Practices

Agroforestry practices are ecologically and economically viable natural resources management practices. It is an important land-use management system in the area for sustainable farming practices in sloppy lands, recycling organic dry matter for soil fertility improvement, resource use, and enhancement of the agroecosystem functions and services. In this land-use system, the farmers can frequently convert wastelands/degraded lands or abandoned lands into agroforestry. The adoption of such a land-use system requires neither costlier external inputs nor complex technology. The Intergovernmental Panel for Climate Change (2007) has cited agroforestry as one of the possibilities to reduce emissions and enhance sinks of greenhouse gases. In the international community which is now known to act on both mitigation and adaptation, agroforestry can provide great potential to influence these synergistically. Such practices can provide opportunities for the thriving of a variety of crops grown in Sikkim by enhancing resilience to climate change in the rainfed farming system of Sikkim Himalaya.

Large cardamom-based agroforestry system

8.3 Adoption of Conservation Agriculture

Bar (fodder)

Nibaro (fodder)

159

Rai khanew (fodder)

Osho grass (fodder)

8.3.6 Integrated Pest Control and Management (IPCM) The pest attacks and new diseases have enhanced due to climate change, causing additional damage to plants and crops. Increased incidents of pest and insect attacks in recent times have had an active role in mitigating agricultural challenges and adapting to climate change. Integrated Pest and Nutrient Management is an environmentfriendly method that purposes to keep the pest population below fiscal threshold levels by using all accessible alternate pest control approaches and techniques. It highlights the growth of a healthy crop with the minimum probable disturbance of the agroecosystem and inspires natural pest control mechanisms. Methods • The Integrated Pest Management method is an ecologically based strategy with the approaches applying a combination of techniques such as biological control (pheromone traps, earthworm, botanical pesticides, and fungicides), habitat

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8 Conservation of Agriculture for Sustainable Livelihood

management, amendment of farm practices, use of unaffected varieties, and organic manure is employed. • Integrated Nutrient Management uses resource components that are already available to the farmers or can be made easily available. These resource components are herbal extracts, farmyard manure, composts, vermicomposts, weed biomass, green manures, liquid manures, bio-fertilizers, crop rotation, biodynamic preparation, household wastes, botanical extraction, by-products from integrated farming systems, etc. Benefits • Integrated Pest Management methods help to control fruit flies and control crop diseases particularly vegetables of the Cucurbitaceae family. • Integrated Nutrient Management methods help in improving productivity and soil fertility through the judicious use of components of resources of Integrated Nutrient Management of inputs.

8.4 Adoption of Conservation of Water Proper management of water resources is essential for agricultural development. Water management options viz., new storages and water harvesting are vital in the Himalayan region. Water is assessed to be the main input for increasing crop production worldwide. Concerning water resources and their potential, the northeastern region is gifted with plenty of water resources. The yearly normal precipitation of the region is about 2000 mm, reporting 10% of the country’s total water. Ironically, an area known for high rainfall suffers from water shortage during the lean period (November–April). In the lack of large and medium storage amenities, the alternate way is to discover operative water conservation measures. Farming in the region is typically rainfed and monocropped. The economic growth of this area is extremely reliant on the careful use of its natural resources, mainly soil and water. Crop production through effective water management and appropriate agronomic practices improves the rural economy, and quality of life and generates more career prospects through the development of the agro-based industry. Water Conservation is the practice of using a water-efficient manner to ensure the accessibility of water for future generations. It does not simply mean “saving water” but also having enough fresh water at any given time and place to fulfill our requirements. It is an integral part of our culture since time immemorial. The following methods can be used for water conservation.

8.4 Adoption of Conservation of Water

161

8.4.1 Low-Cost Micro-rainwater Harvesting Technology Water management is important for crop cultivation. The accessibility of reasonable water for irrigation is a significant issue in attaining higher productivity. The obvious effect of climate change in the Himalayan region resulting in non-uniform distribution of rainfall has caused alarming glacial melt, erratic rainfall, skewed distribution, and drying up of perennial water sources.

Water harvesting tank (WHT)

All these phenomena have led to a shift in priorities for sustainable agriculture through the judicious use of water management. Water harvesting is the central theme of water management strategies. Rainwater harvesting has an amazing probability for domestic usage as well as for farming purposes. The introduction of an affordable rainwater harvesting construction called Jalkund of different sizes can serve as a critical intervention for efficient water management and use. Mass-scale construction of community water tanks, firm ponds, and water reservoirs on individual farms, can help to mitigate water scarcity. Construction The ground is unearthed to a dimension of 6 m × 4 m × 1.5 m with the width decreasing along with depth so that the sides slope toward the bottom of the tank. Polythene sheet is carefully set over the depression and the free ends at the four

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8 Conservation of Agriculture for Sustainable Livelihood

sides are covered by mud plaster. In case the rains are not sufficient or rainy days are fewer, the tank may be filled by connecting with natural springs, streams, etc. The tank is protected with thatch roofing (5–8 cm thick) and prepared with nearby accessible bamboo and grass. Neem oil is also promoted to reduce evaporation during the summer season. Benefits • A water harvesting tank of the size mentioned above when properly maintained can be useful to about six households and is especially suited for growing vegetables. A well-maintained WHT may remain functional for more than 5 years after which poly sheet change may be required. WHT is recommended for rainfed mountain farming systems. • The water stored in these sunken pounds and community water tanks through rainwater harvesting can be judiciously used to tide over the long dry spell of winter and sometime in summer. • Sustainability in hilly terrain can be created at a low cost, with less effort, and maintenance. These techniques can serve the water requirement during the dry spell and they can prove to be a boon in Sikkim, especially for the horticulture crops. • The knowledge may open opportunities for agriculturalists who can provide a polyhouse technology for the cultivation of vegetables, not only for fetching high market value during off-seasons but also for offering job opportunities to unemployed rural youth. • A water conservation information center should be established in each village to publicize the know-how among farm families. This cost-effectively and easily adoptable technology needs to be propagated among huge segments of village communities.

8.4.2 Rooftop Rainwater Harvesting Harvesting of rooftop rainwater is the most applied and feasible method of rainwater harvesting in rural and urban areas. It is a very simple, cost-effective method that needs the minimum expertise. Rainwater is collected from the rooftop and elated with channels into a storage reservoir, where it delivers water at the point of drinking or can be used for recharging a well or the aquifer. Collected rainwater can be used for domestic purposes and added to other water sources during the lean period. The following factors have to be kept in mind while implanting a rooftop rainwater harvesting technique viz., size of the catchment for storage, local rainfall data and patterns, alternative water sources, and the cost required for installation. A rooftop area of 20 m2 can save up to 9000 L of water annually. The basic calculation for Rooftop rainwater harvesting techniques is:

8.4 Adoption of Conservation of Water

163

Rooftop flat area = 4 m ∗ 5 m = 20 m2

(8.1)

Total annual rainfall in mm = 500 mm

(8.2)

Efficiency factor/runoff coefficient = 0.9

(8.3)

Annual Water supply in liters = 20 ∗ 500 ∗ 0.9 = 9000 L

(8.4)

8.4.3 Efficient Irrigation Method Irrigation is the process of spreading water to crops artificially in the absence of precipitation to fulfill their water requirements. It offers moisture for the growth, germination, and other related functions of the crops. A large amount of water gets wasted if not used carefully. The key lies in optimum irrigation because overirrigation can lead to waterlogging, increase salt concentration, hinder germination, and ultimately spoil crop production. Farmers are in a habit of over-irrigation without judging whether the crop requires it or not. When water is infrequent, irrigation should be limited to the most critical periods such as propagation and fruit set. But this is very essential to adopt an efficient irrigation system for the best cultivation and to save water from depletion. The appropriateness of the diverse irrigation means, i.e., sprinkler, surface, or drip irrigation, depends mainly on many issues like natural conditions, type of crops, required labor and cost inputs, and type of technology. (i) Sprinkler Irrigation: A sprinkler is a device used to irrigate crops which is like natural rainfall. It is an exclusive irrigation arrangement, intended to guarantee extreme water-saving, affordability, and comfort of installation. Water is disseminated via a system of pipes generally by pumping and provides coverage from small to large areas. The water is sprayed into the air using spray heads (Nozzle) and irrigated the entire soil surface. This method is preferred over superficial irrigation on steeper or inclined lands. Sandy soils in semi-arid environments have a high infiltration rate and low water storage capacity, therefore they required recurrent but small irrigation submissions. Under such circumstances, the sprinkler is more suitable than surface irrigation. (ii) Drip Irrigation: Despite the benefits of drip irrigation, it is still largely adopted for high-value horticultural crops. It is an arrangement in which water has directly reached the root of the plants. The very notion of this irrigation scheme is to irrigate only the root zone in its place of the entire field surface. Water is applied under gravity, dripping one drop at a time through the small emitters. This system is good for smaller areas or for watering individual plants. It is the utmost effective type of irrigation scheme, with 80–90% efficiency levels. It is possible because of: smearing water droplet by droplet so that soil infuses it

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8 Conservation of Agriculture for Sustainable Livelihood

before it evaporates, and the water is functional in the crop root zone (localized) where it is required utmost. This technique is mostly used for vegetables and horticultural trees because of the high investment involved per hectare. Thus, this technique makes abundant healthier use of water than a sprinkler system, as it is beleaguered to the roots rather than spray up into the air and helps in water mitigation. Drip irrigation is appropriate to reduce the wastage of water. This technique is best suited for individual plants such as fruit trees and vegetables. This method is not appropriate for close-growing crops like wheat and rice, where sprinkler irrigation gains recognition. Thus, it is very much essential to improve water-use efficiency by strengthening bunds, leveling land, cleaning field channels, and adopting the proper architecture of irrigation plots depending on slope, soil physical conditions, and drainage. At the same time, acquainting enhanced irrigation schemes, educating farmers in different irrigation exercises, less water-intensive crops, and optimistic encouragements which reduce investment and danger contractions for growers should be implemented, which will merely reduce return flows to the underlying aquifers and hence will help in water conservation.

8.5 Capacity Building Program The farming community needs no letter of credence as they provide bread and butter to the entire world and therefore their all-around development, particularly their skill development, is very necessary. Therefore, there is an urgent need to bridge the gap between their needs. Doing action research and focused research on problems that farmers are challenging in their daily life can help to increase farmers’ knowledge about crop techniques and improve their modus operandi on the farm. The reallife experience should be incorporated into their way of farming through training programs at local levels, farmers’ visits to other places for the exchange of knowledge, Kisan Melas, Kisan clubs, exhibitions, competitions, and advisory bulletins. • Increases capacity buildings of the farming community and brings achievements to themselves, their families, and the entire people of the state and in turn helps in knowledge dissemination in and out of the state. • Provides sustainability to the farming practices as well as to the farming communities and resources by an increase in production, minimum input and maximum output, and judicious use of resources. • Empowers the farming community, and opens new ventures of agricultural development and employment opportunities.

References

165

References Ahluwalia MS (1976) Inequality, poverty and development. J Dev Econ 3:1–13 Anonymous (2006) Conservation agriculture in Europe. SOWAP, Jealott’s Hill, Bracknell, UK Chand R (2004) India’s national agricultural policy: a critique. Working paper no. 85. Institute of Economic Growth, New Delhi David IS, Kaufmann RK (2014) Anthropogenic and natural causes of climate change. Clim Change 122:257–269 Foster S, MacDonald A (2014) The water security dialogue: why it needs to be better informed about groundwater. Hydrogeol J 22:1489–1492 Grover BSK (1974) Sikkim and India: storm and consolidation. Jain Brothers, New Delhi IPCC (2007) Summary for policy makers: scientific-technical analysis of impacts, adaptation and mitigation of climate change. In: IPCC working group II Kumar P (2020) Agricultural diversification and livelihood security in mountains farming systems of Sikkim Himalaya. Unpublished Ph.D. thesis, Department of Geography, University of Delhi, Delhi, India Lal R (1989) Conservation tillage for sustainable agriculture: tropics versus temperate environments. Adv Agron 42:186–197 Lepcha B, Avasthe RK, Singh R, Phukan P (2008) Enhancing livelihood of tribal farmers of Sikkim through integrated organic farming system: a case study. ICAR, Research Complex for NEH Region, Tadong, Sikkim Narain P, Rai SC, Shanti S (1991) Statistical evaluation of development on socio-economic front. J Indian Soc Agric Statist 43:329–345 Neukum C, Azzam R (2012) Impact of climate change on groundwater recharge in a small catchment in the Black Forest, Germany. Hydrogeol J 20(3):547–560 Resende TC, Longuevergne L, Gurdak JJ, Leblanc M, Favreau G, Ansems N, Van der Gun J, Gaye CB, Aureli A (2019) Assessment of the impacts of climate variability on total water storage across Africa: implications for groundwater resources management. Hydrogeol J 27(2):493–512 Russo TA, Lal U (2017) Depletion and response of deep groundwater to climate induced pumping variability. Nat Geosci 10(2):105–108 Swaminathan MS (2010) From green to evergreen revolution, Indian agriculture: performance and challenges. Academic Foundation, New Delhi Taher M (1975) Regional basis of agricultural planning in the Brahmaputra valley. North-East Geogr 7(1–2):1–8 Vaidynathan A (2010) Agricultural growth in India: role of technology, incentives and institutions. Oxford University Press, Delhi Vyas VS (1996) Diversification in agriculture: concept, rationale and approaches. Indian J Agric Econ 51(4):46–59

Summary

The Himalayan region is facing a serious problem due to climate change and the Sikkim Himalaya is not an exemption. Climate change/variability badly disturbs the farming activities and related ecosystems in the region. Environmental degradation in the Himalayan region because of overuse and misuse of various natural resources is well documented. The mountains of the Himalayas which make vital contributions to the ecological sustainability of the region are threatened by increasing population, land-use/cover change, open grazing, deforestation and loss of biomass cover, and overall biodiversity. Climate variability/change is now becoming one of the leading environmental problems in the Sikkim Himalaya. Here is a sign that climate change is now disturbing biodiversity and diminishing the livelihood assets of poor and marginalized farmers. The Sikkim Himalaya indigenous farming system incorporates distinctions of agro-ecological zones that cover a long range of ecosystem diversity ranging from 300 to 5000 m. The region is part of the Eastern Himalaya—a worldwide significant biodiversity hotspot and houses a variety of agrobiodiversity. The agrobiodiversity in the Himalayan region faces inaccessibility, marginality, and fragility to sustain its resilience. The self-motivated agriculture system in the region is being impacted due to cumulative ambiguity. Farming in Sikkim is rapidly moving toward high-value cash crops, such as floriculture, off-season vegetables, ginger, large cardamom, pulses, and fruits. This is evident from a significant decline in the percentage of area under food crops. The agriculture in Sikkim is dominated by three major farming systems, whereas in the north, it is dominated by large cardamom, in the east, west, and south maize and potatoes dominate the farming system at higher altitudes, and paddy, ginger, mandarin oranges, and wheat at lower altitudes. The two farming systems, viz., the large cardamom-dominated and the maize-potato-dominated, account for more than 70% of the total cultivated area of the state. The farmers of the region are facing several serious problems due to global warming and climate change. Apart from the already prevailing drivers of change such as socio-economic, political, and environmental disturbing the lives and livelihoods of the local people. The worldwide

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 S. C. Rai, Food and Livelihood Securities in Changing Climate of the Himalaya, Human-Environment Interactions 9, https://doi.org/10.1007/978-3-031-22817-9

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168

Summary

climate change/variability is an added factor that is directly disturbing and increasing the impact of other drivers of change. Though, there has been no such study that has comprehensively covered these aspects. The key objectives of the current study were undertaken: (i) to analyze the agrobiodiversity of the state, (ii) to analyze the meteorological data over some time to see the climate changes in the state, (iii) to understand the farmers’ perceptions and observations on climate change and its effect on the traditional farming system, and (iv) to identify tools and practices relevant in using agrobiodiversity for coping with climate change and making these widely available. Salient Findings (i)

(ii)

(iii)

(iv)

(v)

Sikkim is situated between 27° 00' 46'' and 28° 07' 48'' N and 88° 00' 58'' to 88° 55' 25'' E. It extends 112 km from north to south and 64 km from west to east and has a total area of 7096 km2 . Sikkim comprises 0.22% of the total geographical area of India and 0.5% of India’s total population in 2011. The population is unequally distributed across the state. North Sikkim is a reported population density of only 10 persons per km2 , while the other hand East district has a population density of 297 persons per km2 . The elevation ranges from 300 m asl, where the Teesta River leaves Sikkim to West Bengal, to 8598 m asl. The state is vulnerable to landslides and river erosion due to fragile geological conditions. The Teesta and Rangit rivers are the main river systems and have many tributaries. The main dominating soils are Inceptisols (42.84%), and Entisols (42.52%) in Sikkim. Mollisols (14.64%) are the main order soil that covers the rest of the study area. Soil with a slope of 50% and above is disproportionately exhausted, coarse-loamy to fine-loamy soil with surface stoniness and modest erosion capacity. Soil with a slope between 30 and 50% is also excessively drained but dominated by fine silt to fine loamy and moderate stoniness and erosion. Below a slope of 30%, the soil type is coarse-loamy to fine-loamy with slight stoniness and erosion. Trend analysis of precipitation shows high seasonal and annual variability. The mean Indian summer monsoon rainfall or the monsoon season contributed 83% of the annual rainfall, followed by July, August, and May. The annual average rainfall has shown a decreasing trend over a 32-year time (1985–2017). For the complete data series (1985–2017), six months showed a negative value of which four months were significant. Trend analysis of annual maximum and minimum temperature for the period 1985–2017 shows a decreasing trend. Among the seasons, temperature trend lines show a gradually decreasing trend. The diurnal range of temperature also shows a negative trend. Respondents specified that the five extreme climate change effects among the communities of different ecological zones were, an increase in minimum temperature, a decrease in rainfall, an increase in mosquitoes in the upland, declining crop productivity, and drying up of water resources. Reduction in water availability has a great impact on each ecological zone. All respondents responded that area is facing a serious problem due to the drying up of

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water sources. About 96% of respondents responded that due to an increase in temperature mosquitoes is found in the high-altitude areas of Sikkim Himalaya. Approving the results of the household survey, the springs are dried up over the past 10 years or more. Other reports also suggest that 15– 30% of springs have dried up in the last decade in 2 other mid-hill watersheds in Nepal. Local farmers have adopted several measures to fight climate change effects. The most important adaptive procedures are: (i) they have made changes to their water supplies and have employed new farming practices and knowhow, and (ii) they have also started planting fodder trees on their farmlands. This is a good step for ecosystem-based climate change adaptation to augment public resiliencies. Snow cover index (S3) techniques were applied to abstract the snow-covered area of the state. It demonstrates a declining trend in the outline of snow and ice-covered areas between 2000 to 2009 and 2017, respectively. The satellite images were attained during the October and early November (ablation period) subject to the availability of cloud-free data. The results display that around 15.55% (2000), 13.51% (2009), and 5.52% (2017) of the total area of the Sikkim state were receded. A similar notion was adopted for snow/Ice-cover accumulation. The three years of satellite data, i.e., 1998, 2008, and 2018 were extracted subject to the availability of cloud-free data. These three years’ images were of the accumulation period, two images of late November (1998 and 2008), and one of February (2018). Outcomes display a declining trend in the snow and ice-covered regions. The result shows that an area of 17.63% (1998), 15.45% (2008), and 7.45% (2018), respectively, were covered with snow/ice. The resulting S3 values were authenticated with the GLIMS data. The snowcovering area has observed a drastic change from 2008 to 2018. The area of these two snow-clad regions has reduced to almost 50%. The result describes that the extent of snow coverage increases in the accumulation period, while the ablation period has a 2% decrease in the total areal extent of snow cover. The images were available at gaps of 8–10 years, which is enough to find the difference in the climatic change indicator. Due to the accumulation of snow in the winter from late November to early March, the coverage region increases. The snow accumulates moreover gentle to moderate slopes than steep slopes and was observed overlaying DEM data for all the images. The northern slopes of the Himalayas receive sunlight during the daytime, while the scorching heat of the afternoon is faced by the southern slopes due to the orientation of the Sikkim Himalaya from east to west. Thus, the northeastern, eastern, and southern slopes of Sikkim Himalaya show a drastic change in the snow coverage values from 2000 to 2017. Whereas most of the southeastern parts of the state hills previously covered by snow have been turned into Quarry grounds and mine-filled water ponds, which are sometimes misinterpreted as glacial lakes surrounding debris areas in the satellite imageries.

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It is observed through the time series forecasting that, by the year 2038– 2040 the snow-covered area shows negative values, thus, snow melting can transpire at an alarming rate if climatic factors do not be controlled. One of the foremost worries of studying snow is the shortage of water in the next decades because 50–60% population of the world living in mountainous areas depends on the snow water for their existence. The melting of snow is a foremost worry diminishing freshwater in the mountains. Hence, regular monitoring of snow-covered areas is also a necessary economical aspect on a regional scale. The agricultural systems in the state are purely traditional with an agrarian economy over centuries due to remoteness, inaccessibility, fragility, and marginality. Of the total geographical area of 7096 km2 , almost the arable land is 1.09 lakh ha or about 16% of the total geographical area. The net cultivable area is 79,000 ha (11.1%) with a total cultivator of 1.31 lakhs and 16,939 agricultural laborers. The irrigated area is only 11% henceforth agriculture is, by and large, rainfed. The State receives plenty of rainfall (3250 mm/annum), well distributed over 6 months from May to October. The average size of operational land holding is 3.9 ha/person against the national average of 0.69 ha. Agrobiodiversity is the variety and variability of animals, plants, and microbes that are used directly or indirectly for food and agriculture, including crops, livestock, forestry, and fisheries. Sikkim, a constituent state of the northeastern region of India, has a diversified ecosystem as evidenced by 5 diverse climatic zones, six diverse forest types, three soil orders, 26 soil subgroups, 21 glaciers, 28 mountains and peaks, 227 lakes and wetlands, more than 104 rivers and streams within a small geographical area. It is estimated that about 178 landraces are available among the 69 crop plants grown in Sikkim state. About 43 landraces could be distinguished for rice. Paddy has more genetic diversity in Sikkim as compared to other food crops. Around 26 landraces of maize were recorded in addition to 14 local cultivars of Rajmah, 6 landraces of finger millet, 7 rice beans, 9 each in chilies and chow-chow, and 4 in rai sag. Apart from this around 11 clones of large cardamom, 5 clones of ginger, and 4 clones of banana were also reported. The rich agrobiodiversity in the area has progressed due to extreme altitudinal variations and environmental conditions. In addition to this, the diversity that exists on-farm has also been greatly influenced by the diverse social, cultural, and economic conditions of the farming communities. Several ethnic groups with varying socio-cultural preferences and needs have contributed to the diversity and farmers have amassed a wealth of knowledge on these diversities and the systems as a whole. The main crops grown in the region are maize, paddy, and large cardamom followed by vegetables, ginger, and orange. Maize is the most dominant crop in the state. Nearly 38,955 ha net sown area of the state is under maize crops. South district reported highest (36%) are under maize. Paddy is the next important staple food crop of Sikkim. The net sown area under paddy

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was recorded highest in the East district. Wheat is also one of the major food crops grown in the state. The maximum area under wheat is also recorded highest in the East district in comparison with other districts. The major finger millet-grown district is East which covers 29% of the net sown area. Under non-food crops, pulses dominate in the south district. Oilseeds and fruits also dominate in the East district. About 43% of the net sown area comes under potato cultivation in the West district. Ginger is an important spice cash crop for the farmers of the South and West districts. Large cardamom is the chief traditional cash crop of Sikkim. The important large cardamom-producing area is the North district (5510 ha), followed by the East district (5005 ha), West district (3548 ha), and South district (3486 ha), respectively. (xv) The household survey revealed that the majority (more than 90%) of farmers grow maize in their agricultural fields. About more than 80% of respondents responded that they grow large cardamom in their field to fetch higher income. More than 60% of farmers of low- and mid-altitude zone responded that they cultivate paddy in their fields. Farmers of all ecological zones responded that they cultivate vegetables in their fields. (xvi) The diversity index of the state showed that the diversification of crops was maximum in the East and minimum in the North district. The diversity index of cash crops in different districts of Sikkim showed that the diversity index is comparatively high in the West and East district and low in the North district. But, in the context of food crops, it was more in the North and East districts and less in the West and South districts of Sikkim. But the overall diversity index for both food crops, and cash crops, was recorded as highest in the East district of Sikkim. (xvii) The consumption pattern of food crops showed that the East and South districts have the highest consumption pattern. The maximum food available in calories was in the South and West districts, in the year 2015–16. The carrying capacity of land in calorific value was highest in the West and South districts of Sikkim. It is because of the fertile agricultural land and intensive agricultural practices. Gross food and net food availability in giga calories were maximum in the South and minimum in the North district. Per hectare, net food availability was highest in the South district, followed by the East, and West districts (0.004). The number of SNU was recorded as highest in the West district in comparison with other districts. North district had the lowest carrying capacity both in calorific and monetary terms among all districts in Sikkim because of unfavorable physiographic conditions especially relief, climate, and soil conditions. (xviii) The average availability of funds per consumption unit per annum as well as per day in the North and East district of Sikkim was far below the state average, and hence, they were comparatively more food-insecure regions than the South and West districts of Sikkim. The analysis showed that all the districts of Sikkim were food-insecure regions. It is clear from the tables that

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all four districts of Sikkim are in a food-insecure situation. A primary explanation for the high incidence of food insecurity was accessibility, marginality, physiographic, techno-economic, and proper market facilities, etc. The primary survey showed that food crop farming, cash crop farming, vegetable farming, dairy farming, poultry farming, floriculture, fish farming, and other non-agricultural activities, such as agricultural labor, driving, tourism, and MGNREGA were the main sources of livelihood options available in Sikkim. The logit regression of agricultural source/non-agriculture and multinomial logit regression of agriculture/non-agriculture and both livelihood strategy choices showed that the choices of livelihood strategy adopted by the farmers were mainly dependent upon age, and size of the operational landholdings, education, and distance from the market/headquarter. The p values of these variables were found significant. Although other variables such as the size of the family, dependency ratio, and use of a level of innovativeness in the agricultural farm were also taken for logit regression and multinomial logit regression their p-value in the present study is not found to be significant, they are important variable and hold importance in determining the livelihood strategy choices. Adaptation of conservation agricultural practices viz., conservation tillage (minimum tillage or no-tillage) and cover crops, soil and water conservation, and soil fertility management through organic farming, etc., have major benefits in reducing erosion and compaction. Other measures, such as lowcost water harvesting tanks, strengthening agroforestry practices, and integrated pest control methods, including appropriate crop rotations, can reduce the quantity and frequency of chemical pesticide application and avoid the problem of pest resistance, polyhouse, and polybed cultivation, etc. Conservation agriculture must also rise to the challenges of the future, responding to changing climate and producing crops for new markets. Therefore, it can be concluded, that the agricultural diversities and livelihood security in Sikkim will be sustainable only if applied correctly and can bring substantial benefits to farmers, the environment, and society across the range of farm types and climatic regions found in the Himalaya. The large cardamom, from all viewpoints, is an outstanding crop suitable to the mountain ecology and environment. For most farmers in Sikkim, the sustainability of this crop as a livelihood option is extremely important. Apart from economic considerations, the crop also needs to be protected as a valuable genetic resource. Several problems, such as diseases, traditional technology, and marketing, hamper the crop. Its sustainability is being increasingly endangered by the spread of viral diseases. Therefore, measures are needed, first to evolve disease-resistant varieties and second to educate farmers about the available technical know-how to combat the diseases, this can be achieved by strengthening the extension facilities. The evidence supports the necessity for substantial investment in adaptation and mitigation action toward a “Climate-smart-food system” which is more resilient to climate change influences on food security.

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(xxii) In conclusion, efforts should be made to allow the control of climate change under the COPE protocol. Irrespective of scale and geographic location, a key objective should be identified and implemented best available management practices to improve agricultural productivity, thereby ensuring food security and sustainability. Strengthening agroforestry practices would be one best examples to combat climate change in the Himalayan region.

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© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 S. C. Rai, Food and Livelihood Securities in Changing Climate of the Himalaya, Human-Environment Interactions 9, https://doi.org/10.1007/978-3-031-22817-9

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