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Soil Organic Matter: Ecology, Environmental Impact and Management : Ecology, Environmental Impact and Management [1 ed.]
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Copyright © 2012. Nova Science Publishers, Incorporated. All rights reserved. Soil Organic Matter: Ecology, Environmental Impact and Management : Ecology, Environmental Impact and Management, Nova Science

ENVIRONMENTAL SCIENCE, ENGINEERING AND TECHNOLOGY

SOIL ORGANIC MATTER

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ECOLOGY, ENVIRONMENTAL IMPACT AND MANAGEMENT

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ENVIRONMENTAL SCIENCE, ENGINEERING AND TECHNOLOGY

SOIL ORGANIC MATTER ECOLOGY, ENVIRONMENTAL IMPACT AND MANAGEMENT

PEDRO A. BJÖRKLUND Copyright © 2012. Nova Science Publishers, Incorporated. All rights reserved.

AND

FREDERICK V. MELLO EDITORS

Nova Science Publishers, Inc. New York Soil Organic Matter: Ecology, Environmental Impact and Management : Ecology, Environmental Impact and Management, Nova Science

Copyright © 2012 by Nova Science Publishers, Inc. All rights reserved. No part of this book may be reproduced, stored in a retrieval system or transmitted in any form or by any means: electronic, electrostatic, magnetic, tape, mechanical photocopying, recording or otherwise without the written permission of the Publisher. For permission to use material from this book please contact us: Telephone 631-231-7269; Fax 631-231-8175 Web Site: http://www.novapublishers.com NOTICE TO THE READER The Publisher has taken reasonable care in the preparation of this book, but makes no expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of information contained in this book. The Publisher shall not be liable for any special, consequential, or exemplary damages resulting, in whole or in part, from the readers‘ use of, or reliance upon, this material. Any parts of this book based on government reports are so indicated and copyright is claimed for those parts to the extent applicable to compilations of such works.

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Independent verification should be sought for any data, advice or recommendations contained in this book. In addition, no responsibility is assumed by the publisher for any injury and/or damage to persons or property arising from any methods, products, instructions, ideas or otherwise contained in this publication. This publication is designed to provide accurate and authoritative information with regard to the subject matter covered herein. It is sold with the clear understanding that the Publisher is not engaged in rendering legal or any other professional services. If legal or any other expert assistance is required, the services of a competent person should be sought. FROM A DECLARATION OF PARTICIPANTS JOINTLY ADOPTED BY A COMMITTEE OF THE AMERICAN BAR ASSOCIATION AND A COMMITTEE OF PUBLISHERS. Additional color graphics may be available in the e-book version of this book. LIBRARY OF CONGRESS CATALOGING-IN-PUBLICATION DATA Soil organic matter : ecology, environmental impact, and management / editors, Pedro A. Bjvrklund and Frederick V. Mello. p. cm. Includes bibliographical references and index. ISBN 978-1-62100-399-1 (eBook) 1. Humus. 2. Humus--Environmental aspects. 3. Soil ecology. 4. Soil management. I. Bjvrklund, Pedro A. II. Mello, Frederick V. S592.8.S673 2011 631.4'17--dc23 2011048491

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CONTENTS Preface Chapter 1

Chapter 2

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Chapter 3

Chapter 4

Chapter 5

Chapter 6

vii Soil Organic Carbon Stocks and Changes due to Modifications on Land Use and Management Practices in Brazil C. E. P. Cerri, T. F. Abbruzzini, C. B. Brandani, M. R. Durigan and D. Signor Management Practices to Preserve Soil Organic Matter in Semiarid Mediterranean Environment V. A. Laudicina, V. Barbera, L. Gristina and L. Badalucco Organic Carbon Stocks and Management Strategies of the Soils in Taiwan Based on the Soil Information System Shih-Hao Jien, Chen-Chi Tsai, Zeng-Yei Hseu, Horng-Yuh Guo, Chin-Tzer Duh and Zueng-Sang Chen Soil Organic Matter Characterization at Different Forest Stands in Slovenia N. Ogrinc, P. Simončič and N. Kovač Soil Organic Carbon Stocks in Relation to Different Land-use Types in a Mountainous Watershed Víctor Hugo Durán Zuazo, José Ramón Francia Martínez, Iván García Tejero and Armando Martínez Raya Effects of Soil Organic Matter on the Transport of Non- Aqueous Phase Liquid in Soils Junko Nishiwaki,, Yoshishige Kawabe, Yasuhide Sakamoto, Takeshi Komai and Ming Zhang

Index

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39

63

89

111

131

139

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PREFACE Soil organic matter (SOM) is a key constituent of soil as it is a "revolving nutrient find" and improves soil structure, maintains crop production and minimizes erosion. In semiarid environments, the major problem for sustainable farming systems is the continuous decline of SOM towards levels too low for agricultural purposes. In this book, the authors present topical research in the study of the ecology, environmental impact and management of soil organic matter. Topics include soil organic carbon stocks and changes due to modifications on land use and management practices in Brazil; the preservation of SOM in semiarid Mediterranean environments; effects of SOM on the transport of non-aqueous phase liquid in soils and soil organic carbon stocks in relation to different land-use types in a mountainous watershed. Chapter 1- The modern concepts of soil quality and agricultural sustainability must be viewed in a broad form that includes the needs for increasing agronomic productivity, improving resource conservation, and enhancing environmental quality. This view unquestionably highlights the role that soil organic matter (SOM) plays as an important component of the agroecosystem to promote agricultural sustainability. SOM comprises several fractions, such as the light fraction (or particulate organic matter), microbial biomass, water-stable organics, and humus (stabilized organic matter). It is considered one of the more useful indicators of soil quality, because it interacts with other numerous soil components, affecting water retention, aggregate formation, bulk density, pH, buffer capacity, cation exchange properties, mineralization, sorption of pesticides and other agrichemicals, color (facilitate warming), infiltration, aeration, and activity of soil organisms. It is the interaction of the various components of a soil that produces the net effects and not organic matter acting alone. According to recent concepts, sustainable land use must be assessed in terms of its impact on the soil organic carbon (SOC) pool. A non-negative trend in SOC poll would imply a sustainable land use/soil management system. All other factors remaining the same, a sustainable system would enhance SOC content. Because SOC can have tremendous effect on the capacity of a soil to function, it has been recommended as a basic component in every minimum data set for assessing soil quality. Therefore, the aim of this report is to assemble and synthesize the available information on soil carbon stocks and changes due to modifications on land use and management practices in Brazil. For instance, the focus will be on the following systems: i) conversion forest-to-pasture in the Brazilian Amazon; ii) burning versus unburning sugarcane harvesting system, and iii) conventional to no-tillage system in Brazil.

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Pedro A. Björklund and Frederick V. Mello

Chapter 2- Organic matter (SOM) is a key constituent of soil as it is a ― revolving nutrient fund‖ and improves soil structure, maintains crop production and minimizes erosion. In semiarid environments, the major problem for sustainable farming systems is the continuous decline of SOM towards levels too low for agricultural purposes. Furthermore, SOM is per se a dynamic entity. Its quantity and quality depend on numerous factors including climate, vegetation type, nutrient availability, disturbance, land use and management practices. In particular, soil organic carbon (SOC) stocks in Mediterranean semiarid agrosystems are constrained by 1) limited C inputs because of low precipitation and high evapotranspiration rates, 2) secular agriculture under intensive tillage systems combined with long bare fallows, and 3) the removal of crop residues for animal feed. Enhancing SOC content may be achieved by avoiding those techniques that speed up mineralization process or by increasing residue inputs, or both. A reduction in tillage intensity has been widely recognized as a successful strategy to reduce SOC losses. Conventional tillage (CT) systems is are supposed to accelerate SOM mineralisation and consequently increase CO2 flux from soil to the atmosphere. Ploughing favours residue mixing throughout soil, thus improving not only physical contact between soil microorganisms and crop residues but also soil microclimatic conditions for crop residue decomposition (e.g., higher soil moisture content, oxygenation and temperature). In contrast, no tillage systems (NT) reduce microbial activity and, therefore, SOM decomposition. The higher soil bulk density expected under NT, associated with reductions in soil porosity, may lead to a more limited O2 supply for heterotrophic decomposition. However, although many studies suggest that NT increases SOC within the soil profile compared to CT, other studies indicate no net change in SOC. The latter studies suggest that NT only stratifies the SOC, as a near-surface increase in SOC was offset by a concomitant decrease in the subsurface. Organic manuring and inorganic fertilization are the most common practices applied in agricultural management to improve soil quality and crop productivity, respectively. Organic amendments and inorganic fertilizers, above all when coupled together, may indirectly influence soil C inputs through the returned crop residues and rhizodepositions, while directly controlling C outputs via soil microbial activity. In particular green manuring, by introducing into the soil fresh organic matter with a low C/N ratio, enhances SOM content and quality, thus sustaining a high potential microbial activity and biomass. Under Mediterranean climate, both high compost inputs and reduced tillage may have beneficial effects on soil microflora activities and nutrient availability. Reversing CT to sustainable agriculture usually decreases soil bulk density, enhances SOM as favours the immobilisation of C and N and increases most soil microbial quality indicators. Despite all the benefits listed above, soil C sequestration, through conversion to a restorative land use and adoption of recommended management practices, is more intense in cooler and wetter than warmer and drier climates. In this chapter the authors review in detail 1) the effects of the most widespread agricultural management practices on SOM dynamics, either quantitatively and qualitatively, and 2) their potential role and reliability to preserve SOM in semiarid Mediterranean environment. Chapter 3- With the increasing concern over global climate change, it has become vital to quantify global and local soil organic carbon (SOC) stocks. In Taiwan, a total of 620 soil series for the rural soils and 69 soil series for the forest soils have been established, which may provide a clear scenario of a national scale SOC stock from the soil information system (SIS). The objective of this study was to investigate the SOC stocks and distribution in soils of Taiwan with different land uses by using SIS and digital soil mapping (DSM) from the soil

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Preface

ix

survey database. The total areas of the rural soils and the forest soils are around 16830 km2 and 16770 km2, respectively. Inceptisols, Entisols, Alfisols and Ultisols are the major soil types in the rural soils, while Inceptisols and Entisols are the dominant in the forest soils. The average SOC stocks within 0-30 cm, 0-50 cm, and 0-100 cm depths were about 5.97, 8.06, and 11.0 kg m-2 in the rural soils, and 10.2, 13.8 and 18.5 kg m-2 in the forest soils, excluding Histosols and Spodosols. The SOC stocks were concentrated within 0-30 cm which were 54% in average in the rural soils and 59% in the forest soils of the total stocks in the 100 cm depth. Furthermore, the carbon pools are 162 Tg (tera grams, 1012 grams) in the rural soils and 160 Tg in the forest soils. Additionally, land use gives clear impacts on the SOC stocks. The SOC stocks of forest soils were the highest (9.30-41.9 kg m-2), followed by paddy soils (14.8-20.0 kg m-2). However, the SOC stocks of grass soils (14.3 kg m-2) were slightly lower than those of the both soils above-mentioned, and the lowest SOC stocks were found in the upland cropping soils (9.12-12.5 kg m-2). A linear and positive correlation was found between the SOC stocks and soil ages in the rural soils, especially for SOC stocks at fluvial terraces with Entisols, Inceptisols, and Ultisols. The SOC stocks significantly increased with increasing the elevation but with decreasing the air temperature in the forest soils (p< 0.01). Regarding the management strategies for C sequestration, prolonging waterlogged duration of paddy soils and recycling crop residues are proposed as good ways to sequester SOC in the rural soils; moreover, thinning and reforestation timing after forest fire are needed to be noticed for C sequestration in the forest soils. The case study of reforestation at different time after forest fire suggested that reforestation treatment immediately after forest fire sequestrated more C in soils than the control treatment. Chapter 4- Soil organic matter (SOM) has been characterized at three forest stands with soil texture in carbonate karstic-dinaric areas of Kočevski Rog – Rajhenav (RA) and Snežna jama (SJ), and the silicate bedrock at Kladje (KL) in Pohorje, using elemental composition, stable isotope analysis, diffuse reflectance FT-IR spectroscopy (DRIFT) and crosspolarization magic angle spinning 13C nuclear magnetic resonance (CP-MAS 13C NMR). 13C and 15N of SOM suggested isotopic fractionation during decomposition at SJ and RA, while 15N and C/N ratios showed that microbial biomass constitutes an important part of SOM at KL. DRIFT spectra, which were similar at all three forest stands, suggested that organic horizons (Ol,f – litter/fermented and Oh - humified) were dominated by more labile organic compounds (protein and carbohydrates), whereas more persistent materials are present deeper in soil layers. Aryl C fraction was found to be the dominant C fraction in Oh horizon at RA and KL accounting for 37.2 to 35.3% of the total NMR signal intensity. The difference in SOM characteristics found at RA and KL were affected by different vegetation composition and litter quality. The vegetation composition together with climatic conditions and composition of microbial community were probably the main reason of more rapid degradation of SOM observed at KL. Chapter 5- Land-use change in mountainous areas is often a core problem with serious implications for sustainable resource use and environmental impact. Soils are potential sinks for atmospheric carbon and may significantly help mitigate the effects of climate change. The present study highlights information on C storage of different land-use types in a semiarid Mediterranean agroforestry system, and its potential for the restoration of degraded semiarid ecosystems. The authors focused on the implications of land-use type (LUT) for soil organic carbon (SOC) sinking and its impact on physico-chemical soil properties. The study area was

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a small agroforestry watershed (670 ha), located in Lanjaron on the southern flank of the Sierra Nevada Mountains in south-eastern Spain. Five LUTs were monitored: farmland (olive, almond, and cereals), forest (Aleppo pine and Scots pine), shrubland, grassland, and abandoned farmland. The forest with Aleppo and Scots stands, and shrubland had the highest SOC content and consequently the optimal physico-chemical soil properties in relation to the remaining LUTs. By contrast, the abandoned farmland had significantly lower SOC stocks than did farmland, grassland, or shrubland, although a progressive plant recolonization took place that offered greater potential capacity for C sequestering. In concrete, the weighted average SOC storage for Aleppo stands, Scots stands, shrubland, grassland, cereals, olive, almond, and abandoned farmland were 99.6, 83.3, 72.2, 63.2, 53.4, 50.8, 48.9, and 27.5 Mg ha-1, respectively. Thus, the watershed C dynamics indicate that due to intense land-use cover change, the watersheds studied are becoming a net source of C to the atmosphere. Chapter 6- Understanding the transport and fate of gasoline components in soils is of fundamental importance for protecting human health from possible risks. A series of column experiments were performed to investigate the effects of soil organic matter, on the transport of total petroleum hydrocarbons (TPH) and the paraffin (n-paraffin and isoparaffin), olefin, naphthene, and aromatic (PONA) components in 2 typical Japanese soils. The results of this study illustrated the following observations: 1) The remaining mass of regular gasoline in a soil is time-dependent. 2) The major degradation mechanism of regular gasoline in soils would be volatilization. 3) The sorption of regular gasoline by soil organic matter might be one of the major reasons that causes regular gasoline remaining in Kuroboku soil. 4) Aromatic and isoparrafine components are tended to remain in soils.

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Chapter 1

SOIL ORGANIC CARBON STOCKS AND CHANGES DUE TO MODIFICATIONS ON LAND USE AND MANAGEMENT PRACTICES IN BRAZIL

1

C. E. P. Cerri1,*, T. F. Abbruzzini1, C. B. Brandani1, M. R. Durigan1 and D. Signor2

Universidade de São Paulo, Escola Superior de Agricultura Luiz de Queiroz, Departamento de Ciência do Solo, Piracicaba, SP, Brazil 2 Empresa Brasileira de Pesquisa Agropecuária – Embrapa Cocais. Avenida Santos São Luís, MA, Brazil

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ABSTRACT The modern concepts of soil quality and agricultural sustainability must be viewed in a broad form that includes the needs for increasing agronomic productivity, improving resource conservation, and enhancing environmental quality. This view unquestionably highlights the role that soil organic matter (SOM) plays as an important component of the agroecosystem to promote agricultural sustainability. SOM comprises several fractions, such as the light fraction (or particulate organic matter), microbial biomass, water-stable organics, and humus (stabilized organic matter). It is considered one of the more useful indicators of soil quality, because it interacts with other numerous soil components, affecting water retention, aggregate formation, bulk density, pH, buffer capacity, cation exchange properties, mineralization, sorption of pesticides and other agrichemicals, color (facilitate warming), infiltration, aeration, and activity of soil organisms. It is the interaction of the various components of a soil that produces the net effects and not organic matter acting alone. According to recent concepts, sustainable land use must be assessed in terms of its impact on the soil organic carbon (SOC) pool. A non-negative trend in SOC poll would imply a sustainable land use/soil management system. All other factors remaining the same, a sustainable system would enhance SOC content. Because SOC can have tremendous effect on the capacity of a soil to function, it has been recommended as a basic component in every minimum data set for assessing soil quality. Therefore, the aim of this report is to assemble and synthesize the available information *

Email: [email protected]. Phone: +55-19-34172125; Fax: +55-19-34172110.

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C. E. P. Cerri, T. F. Abbruzzini, C. B. Brandani et al. on soil carbon stocks and changes due to modifications on land use and management practices in Brazil. For instance, the focus will be on the following systems: i) conversion forest-to-pasture in the Brazilian Amazon; ii) burning versus unburning sugarcane harvesting system, and iii) conventional to no-tillage system in Brazil.

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INTRODUCTION Brazil is the third agribusiness leader worldwide, following European Union and the United States (WTO, 2009). The priority of renewable energy sources and food supply has contributed to the wide expansion of agriculture and land use change in Brazil. Projections for 2019/2020 (MAPA, 2010) indicate an increase of 36.7% and 37.8% in crop and livestock production, respectively. However, food production and bioenergy must be assessed in a wider context due to legal and environmental concerns, which bring us to an ongoing discussion in relation to environmental quality and sustainability. The soil quality concept addresses the associations among soil management practices, land use change, observable soil characteristics, soil processes and the performance of soil ecosystem functions (Lewandowski et al., 1999). Thus, soil organic matter management is the most effective method to improve soil quality (USDA-NRCS, 2008) and ensure sufficient food supply to support life (Seybold et al., 1996). Changes in SOC stocks due to the conversion of natural vegetation to pastures (Fearnside and Barbosa, 1998; Cerri et al., 1999) and to croplands (Bayer et al., 2006; Carvalho et al., 2009) and the impact of management practices in different land use is a complex issue as different soil types can be managed from no-till to intensive land preparation (La Escala Jr. et al, 2006). Appropriate land use and adoption of recommended management practices can reverse soil degradation trends, improve soil quality and resilience, increase biomass production and decrease emission of GHGs. Therefore, there is a trend of new land-use strategies recently, such as no-tillage and no burning biomass or crops residues left on soil surface after harvesting. No-tillage minimizes SOM losses and is a promising strategy to maintain and even increase soil C stocks (Bayer et al., 2000; Sá et al., 2001), whereas no burning biomass is an important management tool in agricultural ecosystems on the tropics, especially in sugarcane areas. However, according to Galdos et al., (2009), there is little information about the effects of the addition of sugarcane trash on the soil C dynamics. The magnitude of depletion of SOC pool is greater for soils of the tropics than temperate regions (Lal, 2005). Climate change has the potential to alter terrestrial C storage since changes in temperature, precipitation and carbon dioxide (CO2) concentrations can affect net primary production, C inputs to soil, and soil C decomposition rates (Falloon et al., 2007). Brazilian fragile biomes such as the Amazon can act as an important sink or source for C depending on climate change, land use and soil management practices. According to Fearnside and Barbosa (1998), soil emissions from Amazonian deforestation represent a quantity of carbon approximately 20% as large as Brazil‘s annual emission from fossil fuels and the conversion forest-to-pasture in Brazilian Amazon is important to the global C balance and net greenhouse gas emissions. However, there is a lack of knowledge on the mechanisms involved in C sequestration and uncertainties on the estimate of C stock and chemical, physical and biological processes related to C soil modifications in this biome.

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Soil Organic Carbon Stocks and Changes due to Modifications ...

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Available information of land use change and climate change and its impact on the global C cycle has substantially advanced our understanding in order to evaluate the sustainability of agricultural systems in Brazil in terms of its impact on the soil organic carbon (SOC) pool and may also help to infer land-use strategies to improve agriculture sustainability and be very useful to evaluate soil quality in other tropical and subtropical biomes. Therefore, the aim of this report is to assemble and synthesize the available information on soil carbon stocks and changes due to modifications on land use and management practices in Brazil. For instance, the focus will be on the following systems: i) conversion forest-topasture in the Brazilian Amazon; ii) burning versus unburning sugarcane harvesting system; and iii) conventional to no-tillage system.

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CONVERSION FOREST-TO-PASTURE IN THE BRAZILIAN AMAZON The Brazilian Amazon covers about 40% of the world's remaining tropical forests and plays a vital role in the conservation of biological diversity, climate regulation and biogeochemical cycles (Malhi et al., 2008; Peres et al., 2010). The same area has approximately 20 million people and has been subject to annual conversion of about 1.8 million hectares of forests between 1988 and 2008 (INPE 2009), contributing to the higher absolute rates of deforestation of tropical forest in the last decade (Hansen et al. 2008). The process of deforestation has deepened in the last four decades, primarily concentrated in southern and eastern edges of the Amazon to form the so-called "Arc of Deforestation" (Houghton et al., 1991; Lambin et al., 2003; Rudel, 2005; Fearnside, 2007). According to IBGE (2010) in the period from August 1991 to August 2009, the cumulative gross deforestation in the Amazon, was approximately 750,000 km2. Inherent to this process of deforestation is occurring changes in land use. Among the consequences of the deployment of different systems of land use, those related to changes in soil carbon stocks, mainly to emissions of greenhouse gases deserve mention. Added to this current scenario of changes in land use is the threat of a regional climate change that can lead to large-scale drought, with devastating effects on forest conservation through the increased prevalence and intensity of fire in the region (Hammer et al., 2009; Aragão & Shimabukuru, 2010). Therefore, this extraordinary importance and complexity of the Amazon region demand scientific research of comparable magnitude and potential impact (Barlow et al., 2010). Soil organic C represents the largest reservoir of land containing approximately 1550 Pg C (Eswaran et al. 1993; Lal, 2004, Lal, 2008), which equates to more than twice the amount stored in vegetation or the atmosphere (Cerri et al., 2006; Anderson-Teixeira et al., 2009). The carbon soil stock is the result of a balance between inflows and outflows to the pool. In tropical soils, the rates of both inflow and outflow are substantially higher than in other parts of the world, making tropical soil carbon stocks respond rapidly to any changes in the flux rates (Fearnside & Barbosa, 1998). So the magnitude of the carbon stock in Amazon, and the way in which this stock can be expected to change over time, have important implications for the region‘s carbon balance and the net contribution of deforestation to global warming (Fearnside, 1996).

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Thus, land use and its change may serve as a source of emissions and at the same time as carbon sinks (Baker et al. 2007; Cerri et al. 2009). It is estimated that around a fifth of global carbon emissions are derived from activities related to land use (deforestation, burning, etc.). In addition to biomass, soils in the tropics also represent an important storage compartment and potential source of carbon release to the atmosphere. Post et al. (1982), related that tropical soils account for 11–13% of all carbon stored in the world‘s soils and the soils under the original vegetation in the Brazilian Amazon are estimated to contain 47 Gt C, of which a half of that is in the first 20 cm of the soil (Moraes et al., 1995).

Figure 1. Map of soil carbon stocks in Legal Amazon. Adapted from Bernoux et al. (2002).

Table 1. Estimates of organic carbon stocks in soil (SOC) in the Brazilian Amazon References Moraes et al. (1995) Batjes & Dijkshorn (1999) Bernoux et al. (2002) Batjes (2005)

DEPTH cm 0-20 0-30 0-30 0-30

SOC Stocks Pg 21,0 25,0 22,7 ± 2,3 23,9 a 24,2

Adapted from Cerri et al. (2007).

Bernoux et al. (2002) estimated carbon stocks in soils of Amazonia, using a database of 10,457 that gathered information from 3,969 horizons from soil profiles. Stocks representing varied between 1.5 and 1.8kg m-2 of C. However, more than three-quarters of the surface of Soil Organic Matter: Ecology, Environmental Impact and Management : Ecology, Environmental Impact and Management, Nova Science

Soil Organic Carbon Stocks and Changes due to Modifications ...

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the soil-vegetation associations have submitted inventories between 3.0 and 6.0 kg m2 of C. Since these values were obtained from profiles under native vegetation, it is considered that the total represents the initial state prior to colonization (Figure 1). In total, Brazilian soils stored 36,400 ± 3,400 million tons of carbon in the 0-30 cm layer, while Amazon stocked 22,700 tons of carbon, or about 62% of the total (Cerri et al., 2008). There are many researches that reported the stock of carbon in soils of the Amazon forest. Moraes et al. (1995) determined the stock of carbon in the Brazilian Amazon, based on 1162 soil profiles. The authors found about 47 Pg C stocked at 1 m depth. The surface layer (0-20 cm) had 45% of total C in the soil (Table 1). Batjes & Dijkshorn (1999) found about 54% of carbon stock in the layer of 0 to 30 cm depth. Bernoux et al. (2002) obtained a value of 22.7 Pg C and Batjes (2005) found a carbon stock of 24.2 Pg, both in the same depth (0-30 cm). Statistics on agricultural and deforested areas across the Legal Amazon from 2000 to 2006 analyzed by Barona et al. (2010) shows that deforestation is predominantly a result of pasture expansion (Figure 2). About 80% of the deforested area has been used in pastures planted and it is estimated that half of this area is degraded and in some cases, abandoned (Dias-Filho & Andrade, 2006).

Figure 2. Land-use transitions between 2000 and 2006 in the Legal Amazon (Barona et al., 2010).

The traditional system of training of the pastures in the region involves the forest clearing, removal of the wood being economically important, burning of plant biomass and subsequent seeding of the grass (Cerri et al., 2008; Galford et al., 2008). Besides being a low cost system, the ash from the burning of plant biomass improved soil fertility, which provides high yields of pastures during the first year of operation (Perón & Evangelista, 2004). Thus,

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one of the consequences of deforestation followed by burning, is the elimination of all of the microbial biomass, mainly in the topsoil (Cerri et al., 1985; Feilg et al., 2006; Cerri et al., 2008), which is responsible for many biochemical process that occurs in soil, particularly for some transformations of soil organic matter (SOM). Feranside & Barbosa (1998) related that the conversion of areas in the Amazon forest to pasture leads to changes in the quantity and quality of biomass in the physical and chemical characteristics of soil and the emission of greenhouse gases during the burning operations in the forest, or pasture (Fearnside, 2002). The maintenance of soil C in pasture depends on both the stability of organic matter derived from the former forest vegetation and rates of organic matter input from planted pasture grasses (Neill et al., 1997). With the introduction of pasture, C stocks in soil may decrease during the first year of implementation, and increase thereafter, reaching values close to or higher than those existing before the conversion (Feigl et al., 1995; Melo, 2003; Salimon et al., 2007). Nevertheless, some studies in Brazilian Amazon pastures have shown divergent responses for the soil organic carbon content. According to Houghton et al. (1991), most soil C models have assumed declines in soil C content following forest conversion for pasture. Thus, Moraes et al. (2002) found a little change or an increase of pasture soil C stocks in two chronosequences with forests and pastures, with 8 and 20 years in the Rondonia state. Through the use of isotopic techniques, such as the evaluation of δ 13C, it is possible to distinguish and quantify two sources of carbon in the pasture, ie the remaning carbon introduced by the forest and pasture. Through the results they found, a trend of increasing soil carbon derived from pasture is accompanied by a decline of soil carbon derived from the forest (Moraes et al., 2002). Maia et al. (2009) evaluated the effects of management on SOC stocks in grasslands of the Brazilian states of Rondônia and Mato Grosso and the potential for grassland management to sequester or emit C to the atmosphere, and found that degraded grassland management decreased stocks by about 0.27–0.28 Mg C ha−1 yr−1. According to them, nominal management on Oxisols decreased C at a rate of 0.03 Mg C ha−1 yr−1, while nominal management on others soil types and improved management on Oxisols increased stocks by 0.72 Mg C ha−1 yr−1 and 0.61 Mg C ha−1 yr−1, respectively. Therefore, when well-managed or improved, grasslands in Rondônia and Mato Grosso states have the potential to sequester C (Maia et al., 2009). Brown and Lugo (1990) estimated a loss of 44% of the soil C following conversion from native to tropical degraded pastures, Hughes et al. (2002) reported a 9% loss and García-Oliva et al. (2006) reported an 18% loss. Trumbore et al. (1995), found that grasslands increased the SOC from 10 to 16% relative to forest. Cerri et al. (2004) analyzed the effects of the conversion of tropical forest to pasture on total soil C using the Century ecosystem model and chronosequence data collected from the Nova Vida ranch, located in the western Brazilian Amazon. First, the model was realized to estimate equilibrium soil organic matter levels, plant productivity and residue carbon inputs under native forest conditions. Then, the model was set to simulate the deforestation following slash and burn. Soil organic matter dynamics were simulated for pastures established in 1989, 1987, 1983, 1979, 1972, 1951 and 1911. The Century model predicted that forest clearance and conversion to pasture would cause an initial fall in the stock of soil C, followed by a slow rise to levels exceeding those under native forest. The model predicted the longer-term changes in soil C under pasture close to

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those inferred from the pasture chronosequence. Mean differences between the simulated and observed values for the pasture chronosequence were about 17% for the total soil C (data not shown). Although variability in soil C observations for young pastures was high, they show a satisfactory agreement (75%) between the simulated and measured data (Cerri et al., 2004; Feilg et al., 2006; Cerri et al., 2008). Making a progression on the future status of land use in Amazonia, Cerri et al. (2008) report that some estimates indicate that by the year 2015, approximately 60% of newly deforested areas will be occupied by soy cultivation, and the remaining 40% occupied by pasture. But the scenario for the year 2030 would experience a difference, with approximately 70% of the area under soybean crop and 30% pasture. The latter, in turn, would still be divided according to their condition, 20% considered well managed pastures and 80% degraded (systems (Cerri et al., 2007). Araújo et al. (2011) evaluated the impacts of converting natural Amazonian forests in Brazil to pasture dominated by Brachiaria brizantha concerning to C dynamics and humic fractions in two soil chronosequences in the Acre State, Brazil. According to them, there were increases in stocks of soil C and δ13C soil with the time of grazing and the percentage of C derived from pasture was much higher in the surface layer in a site following 20 years of grazing, with proportions that reached 70% of the total C, and δ13C values for the humic acids ranged from -12.19 to -17.57 ‰, indicating a higher proportion of C derived from pasture. Carvalho et al. (2010) studied modifications in soil C stocks resulting from the main processes involved in the changes of land use in Amazonia and they compared areas under native vegetation, pastures, crop succession and integrated crop-livestock systems (ICL). Their study demonstrated that the conversion of native vegetation to pasture can cause the soil to function either as a source or a sink of atmospheric CO2, depending on the land management applied. According to them, carbon losses from pastures implemented in naturally low fertile soil ranged from 0.15 to 1.53 Mg ha_1 year_1, respectively, for nondegraded and degraded pasture. In contrast, their results show that the conversion to agriculture in areas under the ICL system, resulted in C losses of 1.31 in six years and of 0.69 Mg ha_1 in 21 years. Other studies observed a decrease in soil organic carbon content with conversion to managed pasture (Desjardins et al., 1994; Hughes et al., 2002). Fearnside & Barbosa (1998) concluded that the ― typical‖ pastures in the Brazilian Amazon are a net carbon source. In contrast, others studies have found an increase in the SOC content after several years of pasture management (Neill et al., 1997; Desjardins et al., 2004). Some of the varied results can be explained by correction factors such as soil compaction and clay content, and the effect of the short-term seasonal cycles. Factors like sampling depth, number of samples, soil type, dominant vegetation and the quantity and type of carbon previously present are of fundamental importance to calculating mean values for use in simulations of carbon emissions and uptakes. The need is evident for longitudinal studies monitoring soil carbon stocks and related parameters in long-term plots established in areas converted from forest to pasture (Fearnside & Barbosa, 1998). Galford et al. (2011) analyzed land use change using sensus-based historical land use reconstructions, remote-sensing-based contemporary land use change and simulation modeling of terrestrial biogeochemistry to estimate the net carbon balance over the period 1901–2006 for the state of Mato Grosso, Brazil, and they estimated that 21.092 km2 of this state was converted to pastures, with forest-to-pasture conversions have being the dominant

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land use. According to the authors, these conversions have led to a cumulative release of 4.8 Pg C to the atmosphere, with 80% from forest clearing. In other research, Galford et al. (2010) examined scenarios of deforestation and post clearing land use to estimate the future (2006–2050) impacts on carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) emissions from the agricultural frontier state of Mato Grosso. They estimated a net emission of greenhouse gases from Mato Grosso, ranging from 2.8 to 15.9 Pg CO2-equivalents (CO2-e) from 2006 to 2050 and they conclude that deforestation and the conversion forest-to-pasture is the largest source of greenhouse gas emissions over this period. To prevent a decline in soil carbon stocks and most importantly, to prevent the emission of greenhouse gases, at first it must control the deforestation in the Amazon. Then, seek to use agricultural practices and soil management, which are conservationists. That is, the role of sustainable agriculture is on the scene since the use of systems such as crop farming and maintenance of pastures in a good condition so they can reduce losses and control the flow of C to the atmosphere. Also, the Kyoto Protocol allows countries to receive emission credits resulting from land use activities that reduce actual emissions of carbon (reforestation, afforestation, forest management, etc.). For this and other reasons, there is increasing interest from government and investment groups combined with the potential benefits for biodiversity and carbon (eg. REDD) initiatives in forest conservation (Pistorius et al., 2010). However, in most cases, this discussion remains hypothetical and lacks a proper evidence base. In this sense, the Brazilian Government has recently launched the ABC Program, "Agriculture Low Carbon Emissions‖, which has as main objective to restore degraded pastures in order to increase soil carbon sequestration and reduce greenhouse gases emissions while promoting growth based on a sustainability.

BURNING VERSUS UNBURNING SUGARCANE HARVESTING SYSTEM Brazil is the main sugarcane producer in the world, with nearly twice the harvested area and with production almost 2.5 times bigger than the second place India (FAO, 2009). In 2010, the sugarcane harvested area in Brazil was bigger than 8 million hectares and production should be close to 625 million tons, an increase of 3.4% compared with last year. In this crop season, around 54% of sugarcane produced in Brazil will be devoted to ethanol production, generating approximately 27,669.55 million liters (CONAB, 2011). The first incentive of the Brazilian government to sugarcane ethanol use as biofuel occurred in 1931, when the adding of 5% of anhydrous ethanol to gasoline became mandatory. In 1933, to encourage ethanol consumption, the ― Sugar and Alcohol Institute‖ was created (Instituto do Açúcar e do Álcool - IAA). In 1975, after the oil shock, Brazilian government created the ― National Alcohol Program‖ (Proálcool), in order to reduce the country‘s dependence on oil imports. Between 1980 and 1985, Brazilian ethanol production increased 150% and the percentage of new vehicles powered by ethanol reached 96% of new vehicles commercialized (Coelho, 2001). Nowadays, gasoline sold in Brazil contains between 20 and 25% of ethanol.

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In addition to reducing the dependence on petroleum, another objective of ethanol use is to mitigate greenhouse gases (GHG) emissions (Ometto et al., 2009). Brazilian sugarcane ethanol presents a mean decrease of 85% in GHG emissions compared to fossil fuels, while American corn ethanol presents a reduction of only 25% (Borjesson, 2009). Galdos et al. (2010) presented data for Brazilian ethanol production showing that most of ethanol GHG emissions occur in the field, during the sugarcane production. de Figueiredo et al. (2010) quantified the carbon footprint of sugar production in two Brazilian mills and observed that 241 kg of CO2 equivalent are emitted to produce one ton of sugar, 44% of this from burning, 20% due to mineral fertilizers use and about 18% derived from fossil fuel combustion, confirming the information reported by Galdos et al. (2010). Brazilian ethanol has another advantage: lower production cost per liter in relation to fossil fuels extraction and refinement (Luo et al., 2009). Sugarcane is a semi-perennial specie and its cycle in Brazil lasts six years on average, a period in which five to six harvests are made. The first harvest is done 12 or 18 months after planting and the sugarcane harvested is called crop plant (in Portuguese; ― cana-planta‖). Other cuts from sugarcane regrowth, called ratoon-cycle (in Portuguese: ― cana-soca‖), are done annually for several consecutive years. Yields decrease annually after each ratoon-cycle until a level when renovation of sugarcane plantation is more viable than a new cut is achieved. In operations of renovation, sugarcane ratoons are destroyed and the soil that has not been managed since the last plantation is prepared to a new plantation. In some cases, the area could be cultivated with soybean, peanut or Crotalaria juncea as green manure before sugarcane replanting. These species fix atmospheric N and assure better soil fertility conditions (BNDES and CGEE, 2008). Brazilian sugarcane production is concentrated in two regions: South-Central and Northeast (Figure 3). The first one is the main producer and the harvest is done between April and December with mean yields achieving 80 Mg ha-1, while in the Northeast region, the harvest is done between August and April, with mean yields of 57 Mg ha-1. From the actual sugarcane area in Brazil, 54% is concentrated in São Paulo state, the main producer in the South-Central region and in Brazil (CONAB, 2011).

Harvesting Systems Traditionally, sugarcane harvest is done manually after leaves (trash) burning. However, this system is gradually being replaced by mechanical harvest which does not require burning (BNDES and CGEE, 2008). In Sao Paulo, a state law (Law number 11.241/2002) stipulates deadlines to burning harvest eliminating: until 2021 to mechanized areas (bigger than 150 hectares and slope smaller than or equal to 12%) and until 2031 to no mechanized areas (smaller than 150 hectares or slope bigger than 12%). Taking these in account, Sao Paulo producers organized themselves and are committed to anticipate these deadlines to 2014 and 2017, respectively (Unica, 2010). Burning sugarcane trash, although facilitating manual harvesting, has negative points such as the emission of pollutant gases to the atmosphere and nutrient losses (like nitrogen and sulfur) in addition to increase susceptibility to soil erosion, and higher water evaporation rates (Urquiaga et al., 1991). On the other hand, no-burning harvesting avoids gases emission and keeps the soil protected, increases organic matter levels, favors water infiltration and

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retention in soil profile, avoids soil disintegration and erosion, prevents direct exposure to sunlight, which reduces soil temperature and favors edaphic macro and microfauna development and reduce germination of weed seeds. Trash deposition in no-burning harvest areas is equivalent to 15% of the dry matter productivity, with a mean value of 13.9 Mg of dry matter per hectare per year (Campos, 2003). Among the related benefits of a no-burning harvest system, it could be cited: (i) higher longevity of sugarcane areas, with a decrease in costs for renewing areas as a consequence; recycling and gradual releasing of nutrients by straw decomposition; decrease in gases emissions and elimination of nutrients losses assigned to burning harvest (Canellas et al., 2003). There is also improvement in physical soil conditions, like moisture maintenance, which is especially important during little precipitation periods (de Resende et al., 2006), increase in soil aggregates stability (de Luca et al., 2008; Szakács, 2007), and improvement in soil structure, mainly in sandy soils with an original low level of soil C (de Luca et al., 2008). Trash decomposition is more intense in the first months after harvesting and the process became slower over time, following a logarithmic model (Campos, 2003). Four years after trash deposition on soil, considering annually no-burning harvest, approximately 11% of the total deposited straw still remain on the soil surface, and it could be observed in 3 distinct layers: one recently deposited layer; one intermediate layer, between one and two years after deposition; and a very old layer, with at least three years of deposition. Plant tissues in intermediate and old layers show cellulose and C/N ratio decrease and increase in lignin and other humic substances content in comparison to more recent deposition trash layers. In about three years, trash stock on the soil stabilizes around 4 Mg ha-1 of dry matter (Campos, 2003). Soil density could be higher in no-burning areas when compared to burning areas (Barbosa, 2010). In addition, soil density is higher between the lines of crop than on the line of planting and this probably occurs due to intensive agricultural machinery traffic used to mechanical harvest (Razafimbelo et al., 2006). This effect seems to be minimized in areas with higher organic matter input, for example, where organic fertilizers are used, allowing these soils to show physical characteristics similar to native areas (soil density and porosity) (Barbosa, 2010). Another soil physical property altered by sugarcane management system is the stability of aggregates. In no-burning areas, it was increased on average 15.3% per year on 0-30 cm depth as a result of the aggregation and formation of soil macroaggregates as a consequence of higher input of organic matter in no-burning areas (Szakács, 2007). Trash conservation on soil surface benefits both sugarcane and sugar production (de Resende et al., 2006). In Brazil‘s Northeast region, over 13 cuts no-burning sugarcane had 25% higher production than the observed in burned areas (de Resende et al., 2006). Regarding the sugarcane juice quality (important for sugar production), there were no detected changes due to trash surface deposition (Machado Pinheiro et al., 2010). In other words, the final product does not lose quality over the no-burning environmental benefits. However, sugarcane productivity in no-burned areas was approximately 4.7% (Campos, 2003) and 5.5% (Razafimbelo et al., 2006) less than in the burned areas, what is probably due to regrowth problems where trash is on the soil surface or due to nitrogen and other nutrients immobilization during trash decomposition (Campos, 2003).

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Figure 3. Distribution of sugarcane mills in Northeast and South-Central region, in Brazil. (Adapted from BNDES and CGEE, 2008).

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Parameters of soil fertility are also affected by sugarcane harvest systems. In the SouthCenter region, 14-year old no-burning areas showed an increase in soil pH, a decrease in available aluminum and maintenance in levels of calcium and magnesium up to 40 cm depth (Machado Pinheiro et al., 2010). In a 55 year old no-burned area, higher levels of calcium, magnesium, potassium, phosphorus, sodium and micronutrients were observed than in burned areas (Canellas et al., 2003). Furthermore, maintaining sugarcane trash on the soil surface increases cation exchange capacity of about 57% and 68% in 0-20 cm and 20-40 cm soil depth layers, respectively (Canellas et al., 2003).

Soil Carbon Accumulation Increasing organic matter levels in soils, although improving chemical and physical soil properties, as discussed above, have effects on soil C stocks and, consequently, impacts on mitigation of global warming. So, this is an important environmental consequence of noburning sugarcane systems. Many studies conducted in Brazil report conservationist sugarcane harvest systems benefit under soil C stocks. Areas harvested without burning management have more organic C than areas which use the fire: levels 20% higher in 0-5 cm and 15% higher in 0-10 cm layer depth. The main difference in organic carbon levels between the two systems occurs in a fraction of size 0-2 µm, where there is 35% more C under the conservationist management system (Razafimbelo et al., 2006). Razafimbelo et al. (2006) observed organic C stocks on soils in unburned areas around 16.4 and 30.8 Mg ha-1 in the layers 0-5 cm and 5-10 cm; in burned sites, these values were 13.7 and 26.9, respectively. Signor (2010) evaluated C stocks in an Oxisol under burned and unburned sugarcane areas. Considering 0-10 cm layer depth, C stocks varied between 28.4 to 33.4 Mg ha-1 in unburned areas and between 12.4 to 23.2 Mg ha-1 in burned areas. De Luca et al. (2008) evaluated C and N stocks on sugarcane areas with and without trash burning on soils with different clay contents in Sao Paulo state: Typic Hapludox (682 g kg-1 of clay), Typic Hapludult (141 g kg-1 of clay) e Typic Quartzipsamment (177 g kg-1 of clay).

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In these three soils, higher C stocks occurred under no-burning and the differences in relation to the burning system were more evident in the superficial layer. This was also observed by Machado Pinheiro et al. (2010) and by Signor (2010). Moreover, C stocks vary in different ways according to soil type and are bigger under noburning management. de Luca et al. (2008) observed, in the first 20 cm depth, C stocks varying between 47.9 and 54.2 Mg ha-1 in Typic Hapludox and between 20.9 and 28.5 Mg ha1 on the other two soils together. Feller and Beare (1997) synthesized results of many studies and showed a linear correlation between clay content and C quantity on soils, which is in agreement with data reported by de Luca et al. (2008).

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Figure 4. Carbon distribution on soil profile in sugarcane fields harvested with and without burning, one and six years after the last renovation of the plantation, in Sao Paulo State. Horizontal bars represent mean standard-error (n = 9).

Harvest systems also affect C distribution on soil profiles and it depends on soil type and time of management adoption. Compared to a burning harvest system, the conservationist harvest system during 55 years in a Inceptisol in the South-Central region of Brazil incremented 70% and 77% of the C levels in superficial and subsuperficial layers, respectively (Canellas et al., 2003). Also, in the South-Central region (in Espirito Santo state), after 14 years of continuous no-burning harvest (without renovation) in an Haplic Acrisol, soil C stock in 0-10 cm layer was approximately 36% higher in comparison to a no-burning area (Machado Pinheiro et al., 2010). In Pradópolis, Sao Paulo state, one of the first places to adopt a sugarcane no-burning harvesting system, 12 years of a conservationist harvest system in an Orthic Ferralsol promoted an increase of 74.5% on C stock (0-30 cm) and allowed C soil stock in 1 m depth to be similar to C stock in an adjacent native area (Czycza, 2009). In another study in the same region, 8 years after the last reformation, soil C concentration has been altered only on the first 10 cm depth and it was 30% higher in unburned than in the burned harvested area (Galdos et al., 2009). In a sugarcane field in the Northeast region, Chaves and Farias (2008) observed no differences between soil C stocked below 30 cm depth in areas with and without trash burning, confirming the occurrence of a gradient in C distribution on soil. Signor (2010) compared sugarcane fields, in Sao Paulo State, with one and six years after the last reformation, under burning and no-burning harvest management. In Figure 4, both the

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effects of time after the last sugarcane renovation and of the harvest management system are evident. However, due to the gradient in C distribution over soil profile, differences between harvest management decrease as the depth increases. Barbosa (2010) compared conventional (with and without trash burning) and organic sugarcane production, in Goias state (South-Center region). Organic management uses organic fertilizers and compounds, in addition to sugarcane processing residues such as vinasse and filter cake; in renovation operations, crop rotation and green manure are used to promote biological nitrogen fixation. Unlike most studies, in a three year sugarcane ratoon, until 30 cm depth, soil organic C stocks were higher in burned areas (values between 11.77 and 13.74 Mg ha-1) compared to no-burning (C stocks varying between 8.79 and 11.14 Mg ha-1). Soil under organic sugarcane management showed C stocks higher than soils under conventional management, with values between 15.09 and 22.23 Mg ha-1. Taking in account organic C stocked until 60 cm depth, the organic system promoted an increase of 40 tons per hectare when compared to conventional management, with a C stock value similar to that observed under native vegetation. Galdos et al. (2009) used the CENTURY model to evaluate temporal soil C dynamics in sugarcane areas in Brazil and South Africa and confirmed that in long term the conservationist sugarcane harvest management leads to higher C stocks than the burning system. Moreover, the C temporal dynamics on soil are influenced by some factors: initial C stocks, soil texture, mineral fertilizer and organic material input. Considering increments on soil C-promoted by no-burning sugarcane harvest system, the rate of annual increment of C in soils could be estimated. In areas under a conservationist harvest system for 14 years, this rate was 0.93 Mg C ha-1 year-1 (Machado Pinheiro et al., 2010). de Luca et al. (2008) observed rates of annual increment equivalents to 2.1 Mg C ha -1 in a Typic Hapludox (682 g kg-1 of clay) and 1.57 Mg C ha-1 in a Typic Quartzipsamment (177 g kg-1 of clay). Galdos et al. (2009) in a study done at Pradopolis, Sao Paulo state, showed that no-burning harvest system promotes an annual increment of 1.2 Mg ha-1 on soil C stocks, while Czycza (2009) obtained a rate increment of approximately 2 Mg C ha-1 year-1. Comparing three climatic conditions in the Brazil South-Center region, rates of C accumulation on soil until 30 cm depth was 1.70, 1.97 and 2.00 Mg ha-1 year-1 (Szakács, 2007). Signor (2010) observed a rate of C accumulation on soil equivalent to 0.7 Mg C ha-1 year-1 as a consequence of the adoption of a no-burning sugarcane harvest system in an Oxisol at Sao Paulo state. In the Brazilian Northeast, in 16 years of no-burning harvest (without reformation), there was increase on C stocks in the first 20 cm depth by a rate of only 156 kg C ha-1 year-1. Two points may be considered about C dynamics on soil under the sugarcane system. First, trash deposited on soil surface is not incorporated and it decomposes slowly, so that in the next harvest, a portion of the last deposited trash is still visible on the surface. Second, reformation operations and intensive soil tillage promote mineralization of soil organic matter and attenuate differences between burning and unburning harvest systems (de Resende et al., 2006). To better understand the carbon balance and the system potential to increase C stocks in no-burning sugarcane areas, it is important to take into account the tillage system during the reformation period (De Figueiredo and La Scala Jr., 2011). La Scala et al. (2006) conducted a study in Ribeirao Preto (Sao Paulo state) to evaluate the effects of conventional tillage (moldboard plowing followed by two applications of offset disk harrows), reduced tillage (chisel plowing) and non-tilled on CO2 emissions from sugarcane soils. The CO2

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emissions during one month after soil management were increased by 160% and 71% when soils were prepared with conventional and reduced tillage as compared to no-till, respectively. The results suggest that in a 1-month period after tillage, 30% of soil carbon input in sugarcane crop residues could be lost after plowing tropical soils, when compared to the notill plot emissions. Thereafter, sugarcane harvest management can promote changes on soil C dynamic, and in consequence, in the CO2 emissions. Soils of burning areas in South-Central region have CO2 emissions around 3.1 kg CO2 equivalent per hectare per year, while in no-burning areas, the emissions are 1.6 kg CO2 equivalent per hectare per year (De Figueiredo and La Scala Jr., 2011). Soil CO2 emission in the South-Central areas cultivated with sugarcane in burned areas were, on average, 35.5% higher than in un-burning areas (Panosso et al., 2009, 2011). Soil organic matter is more humificated under un-burned than in the burned areas, what means lower relative levels of labile carbon. C emitted as CO2 is mostly derived from labile carbon decay in burned areas, while in the areas harvested without burning, it came mainly from humified soil organic matter. Hence, the smaller CO2 soil emission in the conservationist harvest system could be a consequence of a higher humification index of organic matter under this management. Moreover, soil CO2 emission also changes less in space in unburned areas when compared to burned areas. The mechanized harvest and the greater amount of trash on soil surface in without a burning area could explain the smaller variability of most of the soil properties that affects CO2 emissions (Panosso et al., 2011). No-burning harvest system is also associated to higher humification indexes of soil organic matter (Panosso et al., 2011). There is an increase of up to four times in C on aromatic composts (as a result of alkali-soluble fractions condensation) and a decrease in C on carboxylic groups, although fulvic and humic acids accumulate on soil under sugarcane unburned system (Canellas et al., 2003, 2007). However, the effect of harvest management system under quantities of aromatic compounds on soil seems to occur slowly. The results reported by Canellas et al. (2003, 2007) occurred after 55 years of conservationist system adoption, while Czycza (2009), considering a period without burning of 12 years, did not observe differences in carboxylic and phenolic groups concentrations on humic acids due to sugarcane harvest management. Czycza (2009) also compared 12 and 19 year old areas and verified higher aromatic groups concentration on humic acids in the superficial layer (0-10 cm depth) of older areas, while in the subsuperficial layer (10-20 cm depth), there was no differences due to time of system adoption. Particulate organic matter is the main compartment of organic matter altered by sugarcane harvest management. It is formed by plant and hyphae residues where cellular structures are still recognizable. Proportion of C on particulate organic matter in areas with and without burning was 23.8% and 38.7%, respectively, in the first 10 cm depth. Eight years after the last sugarcane replanting, C content on particulate organic matter in the first 10 cm depth represented 40% of total C on soil in no-burning areas and only 15% on burned areas (Galdos et al., 2009). The maintenance of particulate organic matter on soil depends of physical protection in aggregates and its cycling in the soil is slow. So, a no-burning system increases soil organic matter in a form that will remain on the soil for a long time, which demonstrates its efficiency to mitigate global warming. Another organic matter component affected by this harvest system is microbial biomass, which represents between 60 and 80% of live organic matter on soil, being responsible for much of biological activity and by flux and fast nutrient cycling (Gama-Rodrigues and Gama-

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Rodrigues, 2008; Moreira and Siqueira, 2006). In the superficial layer, microbial C in the burned area represents 0.90% of total soil C, while in no-burning areas, this value is about 1.66%, showing the effect of the residue layer to increase the proportion of soil C on microorganisms. These results confirmed that microbial biomass is sensible to residue management alterations on surface in a short period of time (Galdos et al., 2009) and therefore could be used as an environmental quality indicator (Schloter et al., 2003). Barbosa (2010), comparing conventional and organic systems to cultivate sugarcane, did not found fire effect under microbial C, but observed the organic system favored accumulation of C on soil microbial biomass. Organic systems also promote increases of 115% and 157% on microbial C in comparison to no-burned and to burned sugarcane areas in 0-10 cm layer depths (Barbosa, 2010). The content of C on soil microbial biomass on superficial layer (0-10 cm depth) in areas without burning is approximately 2.5 times higher than in burned areas. On 10-20 cm depth layer, this difference decreases to 1.5 times, showing there is also a gradient on microbial C distribution on soil profile as seen for total C content (Galdos et al., 2009). Furthermore, in the layers 0-10 cm and 10-20 cm depth, burned sugarcane presented soil basal respiration higher than no-burned areas. In the dry season, soil metabolic quotient (qCO2, that represents the quantity of CO2 respired per unit of microbial biomass C) was higher in the burned area than in native vegetation area or in unburned area. These results suggest the harvest system with burning is associated to higher stress conditions of microbial communities (Barbosa, 2010). Campos (2003) considered both C stocked on soil and carbon dioxide, methane and nitrous oxide emissions to the atmosphere in an Oxisol cultivated with sugarcane at Ribeirao Preto (Sao Paulo state) and calculated the C balance (in CO2 equivalent). In a three years study period, the no-burning system had the ability to mitigate greenhouse gases emissions around 5 Mg C-CO2 ha-1 year-1. The total potential of C sequestration on soil due to sugarcane no-burning management in Brazil around 2.61 Tg C year-1 (1 Tg = 1 Mt) (de Luca et al., 2008). Focusing on GHG emissions and carbon sinks in agricultural and industrial phases, Galdos et al. (2010) synthetized data of many studies related to Brazilian ethanol production and concluded that the C sink promoted by no-burning management is around 1.5 Mg C ha-1 year-1. However, the net soil C sequestration to no-burning areas in Sao Paulo state is about 320 kg of C ha-1 year-1 (De Figueiredo and La Scala Jr., 2011). Based on this last value, the conversion of sugarcane burned to unburned system would avoid the emission of 1,484 kg of equivalent CO2 ha-1 year-1. Only in Sao Paulo state, it could be possible to avoid annually the emission of 2.71 Mt CO2 equivalent if all of the burned sugarcane would be converted to a no-burning system (De Figueiredo and La Scala Jr., 2011). Finally, sugarcane occupies more than 8 million hectares in Brazilian territory and it is the main raw material used to produce biofuel in Brazil. Taking into account harvest management without burning, the crop provides an environmental gain beyond that from fossil fuel substitution (reduction on GHG emission derived from combustion process). Many researches conducted in sugarcane producing regions in Brazil show that the adoption of a noburning harvest system promotes C accumulation in soil around 1.4 Mg C ha-1 year-1. Synthesizing results presented previously, in Brazil, soil C stocks until 30 cm depth in burned and no-burned sugarcane areas are, respectively, 17.0 and 26.5 Mg C ha-1. Beyond this potential to accumulate C on the soil and, consequently, mitigate global warming, the conservationist system promotes improvement in physical, chemical and biological

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characteristics of soil quality, providing conditions similar to those found in areas of native vegetation. However, conservationist soil tillage during the reformation of sugarcane plantation is also important so the C accumulated for many years is not lost due to higher rates of soil organic matter mineralization.

Figure 5. Origin of NT in Brazil and its expansion to other states after 1972. Adapted from Cerri et al. (2010).

CONVENTIONAL TO NO-TILLAGE SYSTEM The use of organic inputs was reported in the Middle East as far back as 2000 BC and later in continuous cropping systems in China, Japan, India, Mexico, Peru and the Greek and Roman Empires (Allison, 1973), where the yield differences were observed when different types of plant residues and animal manure were used, which became an interesting object of study (Canellas and Santos, 2005). Although some inorganic fertilizers were sporadically used (ashes, lime, and potassium nitrate), continuous cultivation primarily depended on organic nutrient inputs until the beginning of the 20th century (Sanchez et al., 1989). Since then, the benefits of SOM (soil organic matter) are known, although empirically/indirectly. In the 1970s, no-tillage (NT) had started to become common practice in southern Brazil to plant both a summer and winter crop, and hence fields were being ploughed twice a year. At that time, NT was introduced to control the severe widespread erosion in agricultural soils

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(Amado et al., 2006). This frequent ploughing stimulated loss of SOM and in many regions, soil erosion was becoming a serious problem. Therefore, the underlying land management principles that led to the development of NT systems in Brazil were the prevention of surface sealing caused by rainfall impact on soil surface, achievement and maintenance of an open soil structure, and reduction of the volume and velocity of surface runoff. However, the NT should not be viewed only as a procedure for sowing in soil and not revolved protected by plant residues of previous crops. Currently, the concept of NT takes the vision of an integrated system. Thus, the NT involves the combination of biological or cultural practices such as: (1) the use of chemicals and/ or mechanical practices in managing crops for green manuring, the formation of soil cover by maintaining of crop residues on the surface, (2) the combination of species with nutritional requirements, biomass production and root differentiation, that intends to serve as crop rotation, and (3) the adoption of integrated methods of weed control through the mulching, herbicides and non-soil disturbance, except in the furrows sowing (Sá,1998). Thus, some innovative farmers, with the help of pesticide companies and state and federal research organizations, started the introduction of NT. Until the early 1990s, adoption of this system was relatively slow, reaching approximately 1 Mha in 1992. However, farmers gradually began to appreciate that NT required less field operations, thus fuel consumption was considerably lower, and crops could be planted earlier than under CT. So then actually more than 70% of the soybean-based crop rotations in the southern region of Brazil are estimated to be under NT, and countrywide, most 14 Mha of grain and fiber production use this system (Embrapa, 2002). This alternative strategy quickly expanded to different states (Figure 5) and the cropped area under NT has since then increased exponentially (Cerri et al., 2010). Worldwide, approximately 63 million ha are currently being managed under NT farming, with the United States having the largest area (Lal, 2006), followed by Brazil and Argentina. Although Brazil occupies second place among the countries of the world in terms of area cultivated under NT, that figure represents only 25% of its total agricultural area, while in Argentina, this value is 37% and in Paraguay 52% (Derpsch, 2000). Considering the expansion of NT in Brazil, and the intake of residues on the soil, it is important to have a better understanding of the processes of decomposition of residues and its consequent contribution to the formation of SOM. The decomposition of plant residues is regulated primarily by soil microbial activity, and this, in turn, is determined by the type of management given to the soil, the quality (chemical composition) of the residue and of soil and climatic conditions (Berg & McClaugherty, 2008). Such factors are considered as key points in the decomposition and therefore, in the stabilization of C in soil (Smith & Collins, 2007). There is considerable evidence that the main effect is in the topsoil layers with little overall effect on carbon storage in deeper layers (Six et al., 2002). But, when associated with high-input cropping systems, no-tillage can even increase the SOM stocks (Amado et al., 2001; Bayer et al. 2000; Sisti et al., 2004). In general, the NT have showed increased SOC, mainly at the surface of the soil, as a result of less soil disturbance (Corazza et al., 1999; Bayer et al., 2000b; Sá et al., 2001; Schuman et al., 2002; Six et al., 2002; Amado et al., 2006), mainly, which have resulted also in the reductions of greenhouse gas (GHG) emissions to the atmosphere, especially CO2 (Lal, 1998; Paustian et al., 2000), compared to CT. In Brazil, various studies (Testa et al., 1992; Castro Filho et al., 1998; Riezebos and Loerts, 1998; Bayer and Bertol, 1999; Corazza et al., 1999; De Maria et al., 1999; Bayer et

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C. E. P. Cerri, T. F. Abbruzzini, C. B. Brandani et al.

al., 2000b, 2002; Amado et al., 2001; Machado and Silva, 2001; Freixo et al., 2002; Venzke Filho et al., 2002; Perrin, 2003; Scopel et al., 2003; Siqueira Neto, 2003; Zotarelli et al., 2003; Sisti et al., 2004) gave rates of SOC storage varying from 0 up to 1.7 Mg C ha-1 (Perrin, 2003) for the 0-40 cm soil, with the highest rates in the Cerrado region (Table 2). Increments in SOC have also been reported for layers below 30 cm depth in NT soils with high input cropping systems (Sisti et al., 2004; Diekow et al., 2005a, Rasse et al., 2005; Santos, et al., 2011). The relative contributions to soil C pools of roots vs. shoots is one aspect that has been mostly overlooked, although it appears to be a key factor that drives the fate of plant tissue C either as mineralized CO2 or as stabilized soil organic matter (SOM). Available studies on the subject consistently indicate that root C has a longer residence time in soil than shoot C (Rasse, et al., 2005), which seemed to play a more relevant role in building up soil C stocks, mainly in depth. In no-till system, Ferralsol Santos et al., (2011) observed that C roots evidenced more contribution than shoot of alfalfa residue additions. The highest increment in C stocks in alfalfa soil is therefore attributed to the largest root C addition (4.74 Mg C ha-1 year-1). Carbon contribution by alfalfa roots was attributed to the several mowing/re-growth cycles (6-7 in average per year) (Molin, 2008). Another evidence of root contribution is the higher C sequestration rate observed in the subsurface layer of 5–20 cm in the alfalfa-maize system, where more than two thirds of the overall C sequestration took place. The absolute contribution of roots to the total particulate organic matter occluded within soil aggregates ranges between 1.2 and 6.1 times that of shoots (Six et al. 2002, Rasse et al., 2005). From the few studies with complete datasets, Rasse et al., (2005) estimated that the mean residence time in soils of root-derived C is 2.4 times (ranging from of 1.5 to 3.7) that of shoot-derived C. Sisti et al., (2004) observed that where soil C stocks under NT were higher than under CT, much of the N gain was at depths below the plough layer, suggesting that most of the accumulated soil C is derived from root residues. Because this root C is placed and protected inside stable aggregates in the soil profile, it is better stabilized than the C added via shoot crop residue on the soil surface (Balesdent and Balabane, 1996). Besides, comparisons in situ and incubation experiments suggests that the higher chemical recalcitrance of root tissues as compared to that of shoots is responsible for only a small portion of the difference in mean residence time in soils of root-derived vs. shoot derived C. SOM protection mechanisms other than chemical recalcitrance are also enhanced by root activities: physic-chemical protection, especially in deeper horizons, micrometer-scale physical protection through myccorhiza and root-hair activities, and chemical interactions with metal ions (Rasse et al., 2005). A characteristic associated with high recalcitrance of the roots, but that also is a factor of great importance in the decomposition of any residue in the soil is its chemical composition (residue quality). The decomposition of residue is complex and involves chemical, physical and biological processes, resulting in changes in chemical composition of the substrate (Nierop, 1998) and in the succession of microorganisms capable of decomposing these residues (Berg, 2000; Berg & McClaugherty, 2008). Thus, residue quality is fundamental not only in determining the dynamics of decomposition, but also influence the amount of residue C and N in soil that is kept in the form of more stable SOM. In the soil, the more recalcitrant forms predominate in quantitative terms and constitute a compartment that plays an important role in C sequestration with prolonged residence time (Stevenson, 1994, Dijkstra et al., 2004; Silva & Mendonça, 2007, Berg & McClaugherty, 2008).

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Several studies have shown that the quality of organic residue, for ease of decomposition, can be evaluated satisfactorily by the N, P, lignin, water soluble organic compounds and phenols, as well as the C/N, C/P e lignin/N ratios (Melillo et al., 1982; Anderson & Flanagan, 1998; Buchanan & King, 1993; Tian et al., 1993, Schomberg et al., 1994; Janssen 1996; Mengel 1996; Mary et al., 1996). The cultivation of legume cover crops has also been reported to increase soil C stocks in no-till soils of Southern Brazil (Sisti et al., 2004; Diekow et al., 2005b; Vieira et al., 2009; Santos et al., 2011). In a long-term (13 years) study conducted in a subtropical Ferralsol of Brazil, Sisti et al. (2004) concluded that the main factor that appears to control C accumulation in no-till soil was the contribution of N2 fixation by winter legume cover crop (in that case, vetch (Vicia villosa Roth), emphasizing the importance of the inclusion of such species in rotation schemes. In this same study, it was observed that rotations where the N2-fixing legume vetch was planted as a winter green-manure crop (rotations 2 and 3), soil C stocks under NT were increased by approximately 10 Mg ha-1. Furthermore, the soil C stocks (to 100 cm depth) in the same rotations were 17 Mg ha-1 higher under NT than under CT. These results confirm many earlier studies that NT can promote the conservation of SOM in comparison to CT, but also indicate that where the net N balance of the whole crop rotation system is close to zero, no long-term accumulation of soil C is to be expected, even under NT (Sisti et al., 2004). Santos et al. (2011) compared some species under rotation observed that to W–S baseline system, the increments in TOC stocks (DC) in the 0–20 cm soil layer varied from 4.5% in vetch-maize- oat- soybean-wheat-soybean (V–M–O–S–W–S) to 16.7% in alfalfa-maize (AM) system. Considering the 17 years of experimental duration, the average annual C sequestration amount ranged in the following order: V–M–O–S–W–S (0.12 Mg C ha-1) < oatmaize-wheat-soybean (O–M–W–S) (0.16 Mg C ha-1) < vetch-maize-wheat-soybean (V–M– W–S) and (ryegrass-maize-ryegrass-soybean (R-M-R-S) (average of 0.30 Mg C ha-1) < A–M (0.44 Mg C ha-1) (Table 2). This clearly indicates the C accumulation capacity of the two forage-based systems of alfalfa and ryegrass and of the legume cover crop-based rotation with vetch. Amado et al. (2001) found that in the culture system maize-mucuna there was net sequestration of 15.5 t ha-1 of CO2 at a rate of 1, 9 t ha-1 yr-1of CO2. In addition, the authors say, the partial substitution of mineral fertilizers by nitrogen atmosphere for biologically fixed N may be important strategies for improving environmental quality, when you adopt the NT. On the other hand, if the N concentration of residue decomposition is low (for example, residues with C/N ratio greater than 30:1, such as oats, corn and sorghum), the amount of mineralized N will not be enough to attend the demand of the microorganisms, which immobilize mineral N (NH4+ and / or NO3-) in the soil solution (net immobilization) (Oliveira et al., 2002). Another situation is when the rotations include soybean as the only legume, as available evidence suggests that owing to the large export of N from this crop in the harvested grain, there is little or no overall N gain in the soil/plant system (Sisti et al., 2004).

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Table 2.1. Carbon storage rates (accumulation after conversion of a CT to NT system) in agricultural systems in the Cerrado region of Brazil

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Location Statea Succession or Reported Soil Dominant Plantb Classification

Layer

(%) Oxisol

(cm) 0-10

Dura- Rate tion (yr) (t C/ha) 22 0.31

Source

0-20 0-40 0-10

22 22 7

0.25 - 0.17 0.5-0.9

0-10

14

0.4c

0-20 0-40

21

0.2c 0d

Corazza et al., 2002

Typic 40-45 0-40 hapludox Tipic hapludox 40-45 0-40

22

0.9

Sá et al, 2001

10

- 0.5

Sá et al, 2001

Londrina

PR

Londrina Londrina

PR

S/W-S/L-M/O

Oxisol

PR

S/W/S or M/W/M or S/LM/O

Typic haplorthox

Londrina

PR

Typic haplorthox

Ponta Grossa Tibagi

PR

Ponta Grossa Tibagi

PR

S/W/S or M/W/M or S/LM/O (S or M)/(O or W) (S or M)/(O or W) S/T-S/A-M/T

Oxisol

0-20

15

0.66

Pavei, 2005

PR

M/W - S/O-S/O

Oxisol

40-45 0-10

22

10C

Tibagi Toledo

PR PR

M/W - S/O-S/O S/O

Oxisol Haplic Ferrasol Haplic Ferrasol Oxisol

42

0-20 0-10

10 3

1.6 - 0.68c

0-10

10

0.37c

Venzke Filho et al., 2002 Siqueira Neto, 2003 Riezebos and Loerts, 1998

0-10

11

0.59

0-20 0-40 0-30

11 11 13

- 0.07 0.29 0d

0-30 0-30

13 13

0.4 0.7

0-10

11

0.3

Freixo et al., 2002

0-20 0-30 0-10

11 11 11

0d 0d 0.4

Freixo et al., 2002

0-20 0-30 0-20

11 11 4

0.2 0d 1.3

Amado et al., 2001

PR

W/S

Clay

S/O Passo Fundo

RS

Passo Fundo

RS

Passo Fundo

RS

W/S

W/S W/S-V/M W/S-O/S-V/M W/S

W/S-W/M

Santa Maria

RS

M and Um/M

Typic hapludox

63

Typic hapludox

63

Typic hapludox

Ultisol

15

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Machado and Silva, 2001

Zotarelli et al., 2003 Castro Filho et al., 1998

Machado and Silva, 2001

Sisti et al., 2004

Soil Organic Carbon Stocks and Changes due to Modifications ... Location Statea Succession or Dominant Plantb Eldorad RS M/G o do Sul

Eldorad RS o do Sul Eldorad RS o do Sul Eldorad RS o do Sul Eldorad RS o do Sul

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Eldorad RS o do Sul

M/La O/M O+V/M+C O/M O+V/M+C

A/M

Reported Soil Classification Argissolo vermelho escuro

Clay

Typic Paleudult Typic Paleudult Typic Paleudult Argissolo vermelho escuro Sandy clay

0-17.5

Dura- Rate tion 5 1.4c

22

0-17.5 0-17.5 0-17.5

5 5 9

0.6c 0.2c 0.84

Bayer et al., 2002

22

0-30

9

0.51

Bayer et al., 2002b

22

0-30 0-17.5

9 12

0.71 1.26

Bayer et al., 2002a

22

0-17.5

17

0.07

Dieckow et al., 2005 b

0-20

18

0.23

Zanatta et al., 2007

0-30

18

0.23

0-20

8

1.0

Sandy loam 87 Paleudalf Sandy clay 220 loam Paleudult

0-20

10

0.12

0-20

16

0.12

Clay Hapludox 570

0-20

19

0.16

Lages

SC

O/M, V/M, 22 OV/MC 0 or 180 kg N ha- Loam granite1 yr-1 derived Acrisol M or S/W or O Cambissol

Santa Maria Eldorado do Sul Cruz Alta

RS

Bo-M

RS

Bo-M

RS

W-S

Cam-pos SC Novos Ponta PR Grossa

Bo-S-Bo/V-MRo-W-S R-S-V/M-Bo-B- High clay Bu/W-Ro Hapludox V-M-O-S-W-S Oxisol O-M-W-S V-M-W-S R-M-R-S A-M

Layer

21

Source Testa et al., 1992

Bayer and Bertol, 1999 Amado et al., 2006

0.25 760

0-20

7

0.43

400

0-20

17

0.12

Santos et al., 2011

0.16 0.30 0.30 0.44

Source: Cerri et al., Sci. Agric. 64, 83–99, 2007. a PR, Parana; RS, Rio Grande do Sul; SC, Santa Catarina. b Dominant succession: W, wheat (T. aestivum); S, soybean (G. max); So, sorghum (S. vulgaris); R, rice (O. sativa); Pg, P. glaucum; E, E. coracana; O, oat (A. sativa); V, vetch (V. sativa); M, maize (Z. mays); B, beans (P. vulgaris); Mu, mucuna (S. cinereum); C, cowpea (V. unguiculata); L, lupine bean (L. angustifollios); La, lablab. (D. lablab); G, guandu (C. cajan); Bo, black oat(Avena strigosa Schreber); Ro, radish oil(Raphanus sativus L); Bw, buck wheat (Fagopyrum esculentum Moench) c Calculated using an arbitrary soil bulk density of 1.2 g cm-3; Ud, unpublished data. d 0 means that the difference was not significant.

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Table 2.2. Carbon storage rates (accumulation after conversion of a CT to NT system) in agricultural systems in the Cerrado region of Brazil Location

Statea

Succession or Dominant Plant

Reported Soil Classifi-cation

Clay (%)

Layer (cm)

Duration (yr)

Rate (t C/ ha)

Source

Plana-ltina

DF

S/W

Oxisol

40-50

0-20

15

0.5

0-40

15

0.8

Corazza et al., 1999

50-65

0-40

5

1.7

Perrin, 2003

0-10

5

0.7

Ud Bayer et al., 2006a Bayer et al., 2006a Freitas et al., 2000 Jantalia et al., 2007 Marchão et al, 2009 Scopel et al., 2003

Sinop

MT

Oxisol

GO

R-S/So-R/So-S/MS/E Rice/Soya

Goiânia Luziânia

GO

S/M

Oxisol

35

0-20

8

0.3

Costa Rica

MS

S/M

Oxisol

65

0-20

5

0.6

Sen. Canedo Planltina

GO

M/B

Oxisol

50

0-20

4

0.3

DF

65

0-30

20

0.7

Planltina

DF

R/Fallow/Fallow or Oxisol S/M S/M/S/M or S/Pg Oxisol

60

0-20

13

0.3

Rio Verde

GO

M or S/Fallow

Oxisol

45-65

0-20

12

0.8

M or S

Oxisol

>30

0-40

16

0.4

R/Fallow/S/M

Oxisol

73

0-30

5

0.38

Oxisol

S/M or So or Mi Not specified Vilhena a

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b

RO

Resck et al., 2000 Carvalho et al., 2009

DF, Distrito Federal; MT, Mato Grosso; GO, Goiás. Dominat successions: W, wheat (Triticum aestivum); S, soybean (Glycine max); So sorghum (Sorghum vulgaris); R, rice (Oriza sativa); Pg, Penniseum glaucum; E, Eleusine coracana; O, oat (Avena sativa); V, vetch (Vicia sativa); M, maize (Zea mays); B, beans (Phaseolus vulgaris); Um, mucuna (Stilozobium cinereum); C, cowpea (Vigna unguiculata); L, lupine bean (Lupinis angustifollios); La, lablab (Dolicbos lablab); G, guandu (Cajanus cajan); Ud, unpublished data.

Besides the quality of residue, the edaphoclimatic factors exert great influence on the decomposition of residues, mainly due to variations in temperature, rainfall (Austin & Vivanco, 2006, Plante et al., 2009) and texture of the soil (Six et al. 2002; Denef et al., 2004). The subsequent cycles of wetting-drying and disturbance of soil structure by the use of agricultural implements are considered major contributors to the increase in the rate of decomposition, depending on the exposure of physically protected SOM in macro and microaggregates (Ballesdent et al., 2000; Six et al., 2000). The texture has a great importance in the compartment of SOM, since it is directly related to the formation of aggregates, besides the influence on nutrient dynamics and soil water (Berg & McClaugherty, 2008). Soil texture might alter the response of soil organic matter pools to tillage management by altering plant productivity, soil moisture retention, and community structure and activity of soil organisms, all of which could have impacts on C inputs and outputs. Overall, available data suggests that sequestration of soil organic C with NT compared with CT within the surface rooting zone might be higher in soils with finer textures (fractions clay and silt) (Franzluebbers, 2004). Variable charge minerals could

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improve this mechanism of SOM stabilization and as a consequence, contribute to C accumulation in NT soils (Parfitt et al., 1997; Hassink and Whitmore, 1997; Balesdent et al., 2000; Baldock and Skjemstad, 2000). In general, the less oxidative environment in NT soils increases the lability of SOM, as evidenced by spectroscopic techniques (Bayer et al., 2000a, 2001) and by the ratio between labile and non-labile pools of SOM (Diekow et al., 2005b). In this context, quantifying C accumulation in bulk NT soil subjected to crop rotations with varying rates of annual C additions, it is also important to quantify how C accumulates in the mineral-associated fraction (silt and clay size fractions). The amount of C accumulated in the mineral-associated fraction provides information about the potential of the soil to serve as a C sink. Several studies have reported that C mineral-associated particles, especially microaggregates within macroaggregates, store most of the C accumulated in NT soils, making it a diagnostic fraction to assess C accumulation in NT soils (Six et al., 2000; Denef et al., 2007). In contrast, the amount of C in particulate organic matter may serve as an indicator about the efficiency of macroaggregates to physically protect this C (Bayer et al., 2002; Diekow et al., 2005a; Santos et al., 2011). Bayer, et al., (2006) observed that compared to CT soil, the C stocks in NT sandy clay loam Oxisol increased by 2.4 Mg ha-1 (C sequestration rate of 0.30 Mg ha-1year-1) and in the clayey Oxisol by 3.0 Mg ha-1 (C sequestration rate of 0.60 Mg ha-1year-1). The same authors also emphasize that NT has not always resulted in Cerrado soils exhibiting increased C stocks when compared to CT soils (Freitas et al., 2000; Roscoe and Buurman, 2003) because factors such as soil texture and mineralogy and the amount of annual crop residue can affect the rate of C accumulation in NT Cerrado soils. Costa et al., (2004) also observed results influenced by the mineralogy of soil, in that the soil under NT had rate increases of 0.15 Mg ha-1 yr-1 of TOC and 0.006 Mg ha-1 yr-1 of the COP at 0-20 cm, in comparison to stocks of organic carbon CT. This low rate of increase in stocks of organic carbon is probably related to high physical stability of SOM and soil mineralogy, predominantly gibbsite. In a study involving four kinds of soil, it was observed that the NT soils showed a range of 0.12 to 0.43 Mg C ha-1 yr-1 of C accumulation relative to the CT soil (Table 3). In the sandy clay loam Paleudult, NT had 0.12 Mg ha-1 yr-1 C higher accumulation than CT under the double-cropping system (black oat–maize). In the clay Hapludox, NT had 0.16 Mg ha-1 yr1 of C accumulation compared to CT, with both under double cropping system (wheat– soybean). The similar rate of NT C accumulation in the clay Hapludox (0.16 Mg Mg ha-1 yr-1) in comparison to sandy clay loam Paleudult (0.12 Mg ha-1 yr-1) probably is related to higher C addition in the sandy clay loam Paleudult than in clay Hapludox, which partly compensates for the lower C stabilization in the Paleudult (Amado et al., 2006). The asymptotic relationship between residue C addition and C stocks in bulk soil and in mineral-associated fraction supports the idea of C saturation. In conclusion, plant residues cover crops contribute to C sequestration in no-till tropical soils, especially clay soils. Thus, the combination of soil and NT can reach an eventual soil C saturation. Developing and improving crop rotation schemes with high phytomass-C additions may lead to soil reaching saturation in regard to C sequestration. The concept of C saturation was introduced during the last decade (Six et al., 2002; Stewart et al., 2007) and proposes that soils have an upper limit for C accumulation, in which the steady-state C stock shows little or no increase with respect to further increases in C addition by changes in soil management practices. Traditionally, the models of soil C accumulation are based on a linear relationship between steady-state C stock and annual C addition, the so-called linear first-order model.

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C. E. P. Cerri, T. F. Abbruzzini, C. B. Brandani et al.

This model has been recently questioned and replaced by the C saturation asymptotic model (Stewart et al., 2007; Stewart et al., 2008). Considering this idea/concept about saturation of soils, Santos et al., (2011) observed that for the bulk soil, there was a relationship between min-C and root addition that could be described by an asymptotic curve, also suggesting a trend for C saturation (Figure 6a), with a storage capacity of about 47 Mg C ha-1 year-1 in the min-C fraction of the 0-20 cm layer (Figure 6b). A C-saturation trend was also observed in the clay mineral-associated pool in a previous study in Southern Brazil, but not in the silt or POM pools (Diekow et al., 2005a). The relation-only root C addition (below ground) to soil C stock, the relationship was much better (R2 = 0.72) (Fig. 6a) and improved even more (R2 = 0.98) when excluding the vetch-maize-oat-wheat-soybean rotation (V–M–W–S). This suggests, therefore, that roots seemed to play a more relevant role in building up soil C stocks in this no-till Ferralsol than shoot residue additions. However, more studies are required to come to consistent conclusions about whether soils can become C saturated, especially for tropical soils where little information is available and the management of soil under NT have been increased with agricultural expansion. Table 3. Effects of soil management and crop system on the annual rate of carbon accumulation in four different soil types from southern Brazil Soil

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Sandy loam Paleudalf

Clay content

Time Crop system adoption

TOC (0-20cm) CT NT

Carbon accumulation Tillage effect

g kg-1 87

yr 10

Mg ha-1 19.2

Mg ha-1 yr-1 -

-

20.8

-

-

25.1

-

33.8

35.6

ICS I TLCC (pigeon pea-maize) double-cropping (wheat-soybean)

-

39.4 41.3

0.12 (NT x CT under doublecropping) -

48.7

51.8

ICS II

53.6

58.3

ICS III

50.4

53.4

Sandy clay loam Paleudult

220

Clay Hapludox

570

High clay Hapludox

760

15

19

7

mono-cropping (fallow-maize) double-cropping (ryegrass-maize) TLCC + (velvet beans-maize) double-cropping (black oat-maize)

0.16 (NT x CT under doublecropping) 0.25 (NT x CT under ICS II) 0.43 (NT x CT under ICS III)

CT, conventional tillage; NT, no-tillage; TLCC, tropical legume cover crop; ICS, Intensive cropping system I = black oat + common vetch-maize + cowpea; ICS II = black oat-soybean-black oat + vetch-maize-radish oil-wheat-soybean; ICS III = tripicale-rye-soybean-common vetch maize-black oat-black bean-buck wheat-radish oil. (adapted from Amado et al., 2006).

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Figure 6. Relationship between annual C additions and C stocks in physical fractions (a) and total C addition from root (b) of the 0-20 cm layer of a Ferralsol subjected to the following no-till crop rotations systems: wheat-soybean (W-S); oat-maize-wheat-soybean (O-M-W-S); vetch-maize-wheatsoybean (V-M-W-S); vetch-maize- oat- wheat-soybean (V-M-O-W-S); ryegrass-maize-ryegrasssoybean (R-M-R-S); and alfalfa, with maize cropping each three years (A-M). Shoot plus root C addition related to mineral-associated fraction (min-C). Adapted from Santos et al. (2011).

In conclusion, more long-term tillage studies under different soil and climatic conditions are clearly needed to accurately understand the dynamics of soil organic matter under the wide diversity of environments in the world (Franzluebbers, 2004). In this context, the importance of physical protection to C accumulation in NT soils, imply in the better knowledge the relations among soil texture and mineralogy and the sequester C in the soil, effects that need to be better understood in tropical and subtropical soils. The conversion of CT to NT farming, however, is far from being the ultimate possible achievement in terms of soil C accumulation in tropics and subtropics. The challenge now is to develop and improve crop rotation schemes with high net primary productivity and phytomass-C additions that maximize the benefits of no-till as a strategy to promote CO2-C sequestration and soil quality (Vieira et al., 2009).

CONCLUSION Official Brazilian government data estimated that in 2010, the eight main crops occupied 54.6 million ha. This figure will increase by 14% (reaching 62.2 million ha) until 2017–2018. Four crops (rice, bean, wheat, and coffee) will decrease by 1.1 million ha, but the other four crops (soybean, maize, sugarcane, and cotton) will increase by 8.7 million ha. The demand for biodiesel will require an extra area of 2.6 million ha for oil crops (soybean, castor bean, palm, and sunflower). Re-forestation for industrial uses will also require an additional 3.4 million ha. The total land-use change to accommodate these requirements is estimated to reach 14.7 million ha. It is highly desirable that this production growth should not be linked to any further deforestation, but will instead come up with a better utilization of currently used pastures, which at present, occupy 172 million ha. The result would be a total of 157.3

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C. E. P. Cerri, T. F. Abbruzzini, C. B. Brandani et al.

million ha of pastures by 2017. However, beef production should also increase by 28% in the next 10 years. Based on the actual mean holding capacity of the pastures of 0.9 AU (animal unit) ha-1, 48 million ha of pasture would be necessary to meet this projection. To maintain the pasture extension of 157.3 million ha, Brazil should invest in science and technology to increase the present rate of 0.9 AU ha–1 to at least 1.4 AU ha-1. Our proposed goal of attaining a national mean of 1.4 AU ha–1 includes the followingcomponents: (1) increase pasture productivity; (2) rehabilitate degraded pastures; (3) introduce integrated crop-livestock system; and (4) partial cattle confinement and others. Land-use changes to meet the demand for food, fiber, and biofuels will occur in all Brazilian territories. National and regional public policies to incentivize these actions in existing pasturelands in the Amazon region would bring important social and economic benefits. Nevertheless, conversion of pastureland to agricultural land has to be done carefully, using best management practices as much as possible to avoid environmental impacts on water streams, soil biodiversity, air quality, etc. Part of the economic incentives could be provided by taxes derived from remuneration of avoided deforestation. Any further deforestation in the Brazilian Amazon should not be justified by the expansion of land use dedicated to produce grain, fiber, timber, and beef productions in order to meet national goals. Moreover, there is a need to develop a policy about population migration from rural places to cities, which imposes additional stress on natural resources and requires a substantial increase in food production. Finally, it must be stressed that NT, pasture, and re-forestation are the best options to achieve sustainable soil use.

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ACKNOWLEDGMENTS The authors would like to acknowledge FAPESP, CAPES, and CNPq for financial support and scholarships.

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In: Soil Organic Matter Editors: P. A. Björklund and F. V. Mello

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Chapter 2

MANAGEMENT PRACTICES TO PRESERVE SOIL ORGANIC MATTER IN SEMIARID MEDITERRANEAN ENVIRONMENT V. A. Laudicina, V. Barbera, L. Gristina and L. Badalucco* Dipartimento dei Sistemi Agro-Ambientali, Università degli Studi di Palermo, Viale delle Scienze, Edificio, Palermo, Italy

ABSTRACT

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Organic matter (SOM) is a key constituent of soil as it is a ―revolvi ng nutrient fund‖ and improves soil structure, maintains crop production and minimizes erosion. In semiarid environments, the major problem for sustainable farming systems is the continuous decline of SOM towards levels too low for agricultural purposes. Furthermore, SOM is per se a dynamic entity. Its quantity and quality depend on numerous factors including climate, vegetation type, nutrient availability, disturbance, land use and management practices. In particular, soil organic carbon (SOC) stocks in Mediterranean semiarid agrosystems are constrained by 1) limited C inputs because of low precipitation and high evapotranspiration rates, 2) secular agriculture under intensive tillage systems combined with long bare fallows, and 3) the removal of crop residues for animal feed. Enhancing SOC content may be achieved by avoiding those techniques that speed up mineralization process or by increasing residue inputs, or both. A reduction in tillage intensity has been widely recognized as a successful strategy to reduce SOC losses. Conventional tillage (CT) systems is are supposed to accelerate SOM mineralisation and consequently increase CO2 flux from soil to the atmosphere. Ploughing favours residue mixing throughout soil, thus improving not only physical contact between soil microorganisms and crop residues but also soil microclimatic conditions for crop residue decomposition (e.g., higher soil moisture content, oxygenation and temperature). In contrast, no tillage systems (NT) reduce microbial activity and, therefore, SOM decomposition. The higher soil bulk density expected under NT, associated with reductions in soil porosity, may lead to a more limited O2 supply for heterotrophic decomposition. However, although many studies suggest that NT increases SOC within *

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V. A. Laudicina, V. Barbera, L. Gristina et al. the soil profile compared to CT, other studies indicate no net change in SOC. The latter studies suggest that NT only stratifies the SOC, as a near-surface increase in SOC was offset by a concomitant decrease in the subsurface. Organic manuring and inorganic fertilization are the most common practices applied in agricultural management to improve soil quality and crop productivity, respectively. Organic amendments and inorganic fertilizers, above all when coupled together, may indirectly influence soil C inputs through the returned crop residues and rhizodepositions, while directly controlling C outputs via soil microbial activity. In particular green manuring, by introducing into the soil fresh organic matter with a low C/N ratio, enhances SOM content and quality, thus sustaining a high potential microbial activity and biomass. Under Mediterranean climate, both high compost inputs and reduced tillage may have beneficial effects on soil microflora activities and nutrient availability. Reversing CT to sustainable agriculture usually decreases soil bulk density, enhances SOM as favours the immobilisation of C and N and increases most soil microbial quality indicators. Despite all the benefits listed above, soil C sequestration, through conversion to a restorative land use and adoption of recommended management practices, is more intense in cooler and wetter than warmer and drier climates. In this chapter we review in detail 1) the effects of the most widespread agricultural management practices on SOM dynamics, either quantitatively and qualitatively, and 2) their potential role and reliability to preserve SOM in semiarid Mediterranean environment.

Keywords: Soil management, Organic carbon, Microbial activity, Microbial biomass, Semiarid Mediterranean environment

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ABBREVIATIONS SOM, soil organic matter; SOC, soil organic carbon; SMB, soil microbial biomass; MBC, soil microbial biomass carbon; MBN, soil microbial biomass nitrogen; MBP, soil microbial biomass phosphorus, CO2, carbon dioxide.

1. INTRODUCTION Soil organic matter (SOM) derives roughly from any bio-material produced originally by plants or animals that, once returned to soil,undergoes to microbial decomposition and transformation processes (Sollins et al., 1996). Therefore, at any given time, SOM consists of a wide range of continuously changing materials, from the intact original tissues of plants, animals and microbes to a mixture of their debris at very different states of decomposition, up to the naturally stabilised SOM, i.e. the humified native one. The build-up of SOM is generally a slow process, much slower than its decline. Basically, SOM accomplishes several services that have both environmental and agricultural consequences. Soils are the largest C reservoirs, harbouring approximately two-thirds of the C in terrestrial ecosystems (Schimel et al., 1994). Moreover, soil organic carbon (SOC) pools have the slowest turnover rates

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(Trumbore, 1997) and thus C sequestration in soils has the potential to mitigate CO2 emission to the atmosphere (Paustian et al., 1997). Relevant SOC stabilization also helps other important ecosystem functions, such as improved soil structure and fertility, increased water and nutrient holding capacity and a greater provision of energy for soil biota (Rasmussen et al., 1998; Lal, 2004; Robertson and Swinton, 2005). As a revolving nutrient fund, being derived mainly from plant residues, SOM contains by definition all of the essential nutrients for plant and also for microorganisms and it releases them when undergoing to decomposition processes. However, in order to maintain this natural nutrient cycling system, the rate of organic matter addition through crop residues, manure and other sources must be at least equal to the rate of its decomposition, taking into account the rate of uptake by organisms and losses by leaching and erosion.Where the rate of addition is less than the rate of decomposition, SOM declines. Conversely, SOM is expected to increase when the rate of addition is higher than the rate of decomposition. However, as regards the latter point, it remains to be clarified whether SOC stocks increase indefinitely with greater C input or if there is a limit to how much C can be stabilised in soils (Six et al., 2002). Most SOM models assume linear increase in SOC levels with increasing C input (Paustian et al., 1997). Indeed, many studies carried out in long-term agricultural experiments have showed that the amount of C sequestered is linearly related to C input (Huggins et al., 1998). However, it has also been observed in some soils that no extra C is sequestered with a further increase in C input (Campbell et al., 1991; Solberg et al., 1997; Gill et al., 2002). Both failure of increasing SOC content to enhancing levels of C input over many years and the apparent dependency between C content and stabilization efficiency suggest the existence of an upper limit of accumulation, i.e. a ‗saturation level‘ for soil C (Six et al. 2002). The amount of C in a given soil at a steady state could be defined as soil C capacity, i.e. the relative amount of C accumulated by a given soil under a specific management and environmental conditions. Soil C capacity could increase or decrease with changing management practices, until to a new steady state that can match with a new soil C capacity. Being a chemical attribute responding more slowly than other ones (for example soil microbial biomass C; Paul et al., 1999), the soil C content must be assessed for 20 years after any land use change known to cause a substantial change in soil C and/or in litter inputs to the soil C pool (Guo andg Gifford, 2002). After this time, rates of change in the mineral organic soil C pool become very slow, and for all practical purposes the pool may be considered close to steady state. Soil C saturation is defined as a ― soil‘s unique limit‖ to C stabilization as a function of C input and based on the cumulative behaviour of chemically-, physically-, biochemically-protected, and non-protected, C pools (Stewart et al., 2007), i.e. it is the highest absolute amount of C that a given soil can accumulate, and whatever slight changing will decrease this amount of soil C. Across 11 agro-ecosystems, Six et al. (2002) found that an asymptotic curve fits the SOC content and C input level data better than a linear relationship. They suggested that the smaller increase in SOC content with increased C input level was due to the decreased capacity of soil to store added C. Their conceptual model implies that the further a soil is from saturation, the greater is its capacity and efficiency to sequester added C, whereas a soil approaching saturation will accumulate a smaller amount of SOC at a slower rate and efficiency (Hassink and Whitmore 1997). In the semiarid Mediterranean lands, the major problem for sustainable farming systems

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is the continuous decline of SOM towards levels too low for agricultural purposes (Laudicina et al. 2011a). Soils of semiarid regions are characterized by low SOC contents, low water and nutrient retention, and thus low inherent soil fertility (Lal, 2004). In that environment, SOC is constrained by different factors. Even if the soil C content and accumulation capacity per hectare are low, they can make an important contribution to global C sequestration, at the same time preventing or decreasing the rate of desertification. In this chapter we review 1) the effects of the most widespread agricultural management practices on SOM dynamics, and 2) their potential role and reliability to preserve SOM in semiarid Mediterranean environment.

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2. MEDITERRANEAN CLIMATE According to Koppen classification system, in the Mediterranean Basin the climate is ― Mediterranean‖ (Csa, Csb) (Peel et al., 2007). During summer, regions of Mediterranean climate are dominated by subtropical high pressure cells, while during winter the polar jet stream and associated periodic storms reach into the lower latitudes of the Mediterranean zones, bringing rain, with snow at higher elevations. As a result, areas with this climate receive almost all of their yearly rainfall during their winter season (November to February), and may undergo anywhere from 4 to 6 months during the summer (April to September) without having any significant precipitation. The majority of the regions with Mediterranean climates has relatively mild winters and very warm summers. However, winter and summer temperatures can vary widely between different regions with a Mediterranean climate. Because most regions with a Mediterranean climate are near large bodies of water, temperatures are generally moderate with a comparatively small range of temperatures between winter and summer. Therefore, temperatures during winter only occasionally fall below the freezing point and snow generally is seldom seen, while in summer the temperatures range from mild to very hot, depending on distance from a large body of water, elevation and latitude. Even in the warmest locations with a Mediterranean-type climate, however, temperatures usually do not reach the highest readings found in adjacent desert regions because of cooling from water bodies, although strong winds from inland desert regions can sometimes boost summer temperatures, quickly increasing the risk of wildfires. The low and erratic rainfalls together with high evapotranspiration rates leads to a low crop biomass production and thus to a limited residue input into the soil (Alvaro-Fuentes et al., 2008a,b). The intensive tillage systems, combined with the use of long bare fallows (16– 18 months between crops) and the removal of crop residues for animal feed, are some factors playing a key role in reducing SOM inputs (Austin et al. 1998; Hernanz et al. 2009). For example, in South Italy, rural landscapes are often characterised by intensive agriculture, with use of large amounts of fertilizers and irrigation water (Laudicina et al. 2011a). Besides, in that environment, a common practice used by farmers to increase the water infiltration, especially in clayey soils, is deep ploughing before the rainy period (VidhanaArachchi 2009). This practice, coupled with the Mediterranean climate features (warm to hot, dry summers and mild, wet winters), has speeded up the degradation processes of SOM so that many lands have became less or not fertile. Hence, in a modern agriculture,

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maintaining or increase SOM is a key issue, in particular in the semiarid Mediterranean environment.

3. MANAGEMENT PRACTICES

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3.1. Tillage Tillage is one of the most used agricultural practice. However tillage, and in particular mouldboard ploughing, has caused great losses of SOC and N oxides as greenhouse gases to the atmosphere (Blanco-CanquiandLal, 2008; López-Garrido et al., 2011). Conservation tillage can contribute to a reduction in fossil fuel use and greenhouse gas emissions by reducing the number of tillage operations and avoiding the breakdown of soil macroaggregates. A reduction in the intensity of tillage has been widely recognized as a successful strategy to reduce SOC losses (Halvorson et al., 2002; West and Post, 2002). West and Post (2002), analysing the results from 67 long-term agricultural experiments, concluded that a shift from conventional to no tillage can sequester about 60 g C m-2 yr-1. Indeed, ploughing turns over soil, favours physical contact between soil microorganisms and crop residues, and creates more optimal soil microclimatic conditions for crop residue decomposition (Paustian et al., 1998; Bruce et al., 1999). In contrast, under no tillage system, the absence of soil disturbance produces a modification of surface soil conditions, reducing microbial activity and therefore SOM decomposition (Mielke et al., 1986). Several studies have measured greater soil bulk density values after the adoption of no tillage (Kay and Van den Bygaart, 2002). Increases in bulk density under no tillage are associated with reductions in soil porosity that may lead to a more limited O2 supply for heterotrophic decomposition (Álvaro-Fuentes et al., 2008a). However, although many studies suggest that no tillage compared to mouldboard ploughing increases SOC, some studies indicated that no net change had occurred. Indeed, no tillage was suggested only to stratify SOC along soil profile, since a near surface increase in SOC was offset by a concomitant decrease in the subsurface (Yang et al., 2008). West and Post (2002) found that conversion from conventional to no tillage can rise the C sequestration rate of 57±14 g C m-2 y-1, excluding wheat-fallow systems which may not result in a SOC accumulation. Other experiments carried out in Spain and South Italy, in which conventional tillage has been compared to minimum or no tillage in a wide range of crop rotation systems, have shown a significantly greater SOC concentration under no tillage in the soil surface (Álvaro-Fuentes, 2008b; Barbera et al., 2010). However, those authors reported that below the 10 cm depth, SOC concentration in no tillage treatment was similar or lower than that measured in the other tillage treatments. Luo et al. (2010) performed a metaanalysis of global data from 69 paired experiments and found that cultivation for more than 5 years resulted in SOC loss of more than 20 t ha−1 in the top 60 cm soil profile, with no significant differences between conventional and no tillage. Conversion from conventional to no tillage significantly altered the vertical distribution of C within the soil profile, resulting in increased SOC in the 0–10 cm layer and in a decline in the 10–40 cm. These findings confirm the concerns of Baker et al. (2007) that ― the widespread belief that conservation tillage favours C sequestration may simply be an artefact of sampling methodology‖ in many cases. Other authors hypothesized that small differences between conventional and no tillage could

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be also due to the high clay content of the soils (Ouédraogo et al., 2005, Barbera et al., 2010) that finally protects SOM from a quick degradation under a more intensive use. Tillage-induced changes in SOC distribution within soil profile is likely a result of two causes: redistribution of surface SOC and changed root growth. Firstly, the surface soil layer holds most of SOC and in conventional tillage ploughing moves it into deeper soil layers. Secondly, deep ploughing, sometimes down to 50 cm, changes soil physical conditions and promotes more crop root growth in those loose soil layers, thereby increasing C input through root senescence (Luo et al. 2010). In contrast, no tillage leads to increased soil cover, reduced soil disturbance and increased soil strength . It does not only discourage root growth into deeper soil layers (Lampurlanes and Cantero-Martinez, 2003; Qin et al., 2004; Martínez et al., 2008), but also reduces the downwards movement of surface SOC. In addition, residues on the ground surface under no tillage can cause a decrease in soil temperature especially during summer, leading consequently to a reduction of SOC decomposition (Duiker and Lal, 2000). No tillage can also increase moisture by reducing evaporation, leading to changes in crop root growth and other soil processes related to SOC decomposition in the top soil layer. Tillage promotes the oxidation of SOC basically for two reasons: 1) tillage fragments macro-aggregates and increases the surface area for soil microbes to attack and decompose the originally physically aggregate -protected SOC (Bearé et al ., 1994; Six et al., 1999); 2) incorporated crop residues lead to more favourable physical conditions (e.g., water and thermal condition) for their decomposition than on the soil surface (Aulakh et al., 1991; Coppens et al., 2007), thus providing nutrients and energy for microbial growth and further enhancing SOC decomposition, more inert C included (Fontaine et al., 2007). These two opposing effects of residue incorporation (i.e., C input increase vs. the stimulation of decomposition) may in part counteract each other. Hence, the net overall effect of tillage on SOC stocks may remain moderate and be regulated by crop systems that determine the quantity and quality of crop residues (as C input into the soil), and by soil conditions that determine the decomposition process of the incorporated crop residues (Luo et al. 2010). However, tillage induced changes in SOM status, that occur over relatively short periods (e.g. 1-5 years) are difficult to measure due to large background amounts of relatively stable soil organic matter that are already present (Gregorich et al., 1994). By contrast, because of their dynamic nature, labile fractions of SOM such as microbial biomass C (MBC), light fraction C and easily extractable or mineralisable C pools can respond rapidly to changes in C supply (Haynes, 2000). Such components have therefore been suggested as early indicators of the effects of soil management and cropping systems on SOM quality (Gregorich et al., 1994; Haynes and Beare, 1996) and are also considered to be key indicators of soil quality (Doran and Parkin, 1996; Laudicina et al., 2011b). Soil microbial biomass (SMB) is the very small portion of SOM constituted by living microorganisms smaller than 5-10 m3 (Jenkinson and Ladd 1981). MBC amounts to approximately 1-5% of SOC (Anderson and Domsch 1989; Sparling 1992) and 2-6% of the total organic nitrogen (Jenkinson 1988). Typically MBC ranges from 100 to > 1000 mg C kg1 soil (Paul et al. 1999). SMB has a turnover time less than one year (Paul 1984) and, therefore, responds to stress/disturbance factors more rapidly than the whole SOM, the content of which may need decades to appreciably change. Due to its dynamic nature, SMB content at any one time cannot indicate whether SOM (generally soil quality) is increasing, decreasing or at equilibrium.The effects of tillage on SMB have been extensively studied. Recently, Gonzalez-Chavez et al. (2010) reported the impact of 28-years of no-tillage on

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MBC, MBN and MBP in Texas. They found that MBC and MBN were nearly doubled, whereas MBP was 2.5 times higher compared to conventional tillage treatments. Balota et al. (2004) investigated the long-term effects of tillage and crop rotation on SMB in a subtropical environment and found that no-tillage increased MBC in soybean/wheat, maize/wheat and cotton/wheat rotations (from 11 to 98%) across all soil depths (0-5, 5-10 and 10-20 cm) when compared to conventional tillage. The increase of MBC and MBN was also recently found by Laudicina et al. (2011a) in a semiarid environment where the effect of conventional and minimum tillage was compared in plot amended with two doses of compost. Doran (1980) suggests that, in tropical or arid/semiarid environments, the larger SMB in no-tilled or minimally tilled soils when compared with soils that are conventionally tilled is due to the fact that surface litter can lower soil temperature and increase water content, soil aggregation and C content. Thus, no-tilled soils are not only high in available substrates but also wetter, cooler and less variable with respect to their temperature and moisture regimes. These conditions stimulate the growth of soil microorganisms, particularly in surface layers (Balota et al. 2004; Ferreira et al. 2000). Tillage practices may also affect soil carbon dioxide (CO2) emissions by different ways. The effect of tillage on soil CO2 emission is of particular concern as world soils play a major role in the global C cycle and have contributed to the changes in concentration of greenhouse gases in the atmosphere (Reicosky and Archer, 2007). Mouldboard ploughing stimulates soil microbial activity due to greater soil aeration compared to conservative tillage and to the breakdown of soil macroaggregates (Angers et al., 1993). Six et al. (1999) observed faster soil macro-aggregate turnover under mouldboard ploughing than no tillage and, thus, a greater release of labile organic matter previously protected from soil microbes within macroaggregates. Besides, mouldboard ploughing induces a redistribution of SOM within soil profile, modifies the soil microclimate conditions (e.g., soil temperature, aeration, and water content), and exposes aggregate-protected SOM to microbial attack, thus favouring SOM decomposition (Paustian et al., 1997; Peterson et al., 1998). For most soils, the potential of C sequestration upon conversion of plough tillage to no tillage with the use of crop residue mulching and other recommended practices ranges from 0.6 to 1.2 Pg C year-1 (Lal, 2004). Tillage could also increase short-term soil CO2 fluxes due to a rapid physical release of CO2 trapped in the soil air spaces (Bauer et al., 2006; Reicosky and Archer, 2007; ÁlvaroFuentes et al., 2008b). However, that rapid flux of CO2 depends on tillage system and on the amount of soil disturbance (Reicosky and Archer, 2007). Studies in South-Western Spain on CO2 fluxes reveal significant CO2 increases immediately after tillage, both in long -term and short-term conventional tillage experiments compared to conservative tillage treatments (López-Garrido et al., 2009). Besides, the difference between short-term conventional tillage treatment (4.38 g CO2 m-2 h-1) and short-term conservation tillage (0.27 g CO2 m-2 h-1) was greater (x16) than that between long-term conservation tillage (6.21 g CO2 m-2 h-1) and longterm conventional tillage (2.11 g CO2 m-2 h-1) (x3). However, the magnitude of the fluxes reported in the several studies carried out in the Mediterranean region are comparable each other. Álvaro-Fuentes et al. (2008b) reported mean seasonal CO2 fluxes ranging from 0.4 g m2 -1 h to 1.76 g m-2 h-1, with a peak of 4.7 g m-2 h-1 and lowest mean seasonal fluxes always observed under no tillage, although they did not find significant differences in soil CO2 fluxes among tillage treatments. Also, Álvaro-Fuentes et al. (2007), for semiarid areas of NE Spain, reported fluxes ranging from 0.17 g m-2 h-1 under reduced tillage to 6 g m-2 h-1 under conventional tillage, immediately after tillage; these data were 3 to 15 times greater than

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fluxes before tillage. Under no tillage, CO2 fluxes were low and steady during the whole study period.

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3.2. Crop Rotations and Residue Inputs The importance of rotations in agricultural systems has long been established and the procedure now forms a complex part of many conservation tillage practices. The inclusion of rotations has many benefits such as counteracting the build-up of crop specific pests and thereby lessening the need for costly pesticides and herbicides. Different crop species have a variety of rooting depths and this aids in distributing organic matter throughout soil profile. In particular, deep-rooting plants are especially useful for increasing C storage in depth, with SOM becoming less susceptible to degradation processes. The inclusion of nitrogen-fixing varieties in a rotation increases soil nitrogen without the need for energy intensive production of nitrogen fertilisers. Rotations, especially legume-based ones, are generally regarded as crucial for maintaining soil fertility and show a very good potential for sequestering C in soils of semiarid environments. For example, Gregorich et al. (2001) compared a conventional continuous maize cultivation with a legume-based rotation. The rotation had a greater effect on soil C storage than did fertilisation. The difference between maize monoculture and the rotation after 35 years was 20 t C ha-1. Additionally, the SOM present below the ploughed layer in the legume-based rotation appeared to be more biologically stabilised. These findings suggest that soils under legume-based rotations tend to increase and preserve residue carbon. A positive effect on SOC (increase of 2-4 t ha-1) was also found with legumes and alternate cattle grazing in a semiarid environment of Argentina (Miglierina et al. 2000). However, other studies have found that legume-based rotations are less efficient in storing soil C than cereals. For example, Curtin et al. (2000) have demonstrated the advantage of cereals over legumes in achieving maximum soil C sequestration rates. Indeed, in a semiarid area of Canada, they found that annual C added to soil ranged from 1.6 t C ha-1 in average for the black lentil and 2-3 times that amount for wheat crop. Similarly, in Argentina soybean, which produced 1.2 t ha-1 residues, resulted in a net loss of soil C while corn, with 3.0 t ha-1 residues significantly lessened the loss of soil C from the system (Studdert and Echeverria, 2000). Guo et al. (2009), comparing crop performance in soil CO2 emissions, found leguminous crop residues having more potential in enhancing CO2 emissions than wheat, although they improved soil quality and crop productivity. Those results confirmed that the quality of residue inputs, which generally is inversely related to the residue C/N ratio, can strongly affect CO2 emissions (Al-Kaisi and Yin, 2005) by changing the decomposition rate of residues (Kuo et al., 1997; Sainju et al., 2002). Plant residues provide renewable resources for incorporation into SOM. However, in agricultural systems, because plants are harvested, only about 20% of production will on average be accumulated into the soil organic fraction (Batjes and Sombroek, 1997). There is no wide agreement about the actual quantities of residue returned to the soil since it depends on the crop type, growing conditions and agricultural practices. Of the plant residue returned to the soil, Lal (1997) suggested that about 15% can be expected to be converted to passive SOC, whilst Schlesinger (1990) suggested that only 1% of plant production will contribute to soil C sequestration. In a semiarid environment of Canada, the conversion of residues to SOC

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was reported to be 9% in frequently fallowed systems, increasing up to 29% for continuously cropped systems (Campbell et al, 2000). All belowground production, unless a root crop is being harvested, is available for incorporation into SOM. Rhizodepositions are believed to be the major source of particulate organic matter, although tillage substantially reduces the net accumulation of C from roots (Hussain et al, 1999). In cool climates, belowground C inputs from roots alone can generally maintain soil C levels, but this is not the case in warmer or semiarid regions where residues are oxidized much more readily, provided sufficient moisture is available (Rasmussen et al, 1998). Consequently, when continuous cropping is practised in soil of semiarid environment, failure to return aboveground plant residues will invariably lead to a reduction in soil C (Woomer et al, 1997; Ringius, 2002). Besides the direct effect that residues input exerts on SOC content, it is to mention also an important indirect effect called ―m ulching effect‖. Indeed, residues accumulated on soil surface could affect physical soil properties. Mulches reduce water loss and soil temperature (Duiker and Lal, 2000), both important factors for the rate of soil processes in semiarid environments, especially if the soil temperature is above the optimum for plant growth. The modification of soil physical properties could modify the mineralisation (C depletion)/ humification (C accumulation) ratio. Crop rotation systems that include leguminous crops encourage a higher MBC/SOC ratio (microbial quotient) than monoculture systems (Anderson and Domsch 1989). This difference is attributed to the input of a higher organic residue variety under crop rotation systems (Anderson and Domsch 1989). Franchini et al. (2007) observed increases in MBC in soybean fields previously cultivated with legumes (lupins) in comparison with those previously cultivated with wheat, and found that crop rotations that included a higher ratios of legume to non-legume resulted in higher microbial quotient values. Positive effects of legumes on MBC have notnot observed in many studies, however. For this reason, it has been proposed that differences in microbiological parameters resulting from crop rotations are detectable in longterm trials only, even under no-tillage (Franchini et al. 2007). Moreover, results from crop rotations may be related to shifts in rhizodepositions of organic compounds (Matson et al. 1997; Badalucco and Nannipieri 2007) that either stimulate or suppress microbial activities. By increasing the above- and below-ground biomass production of the crops, i.e. rhizodeposits and root turnover included, the amount of residue returned to the soil can expand (Sainju et al., 2005), thus causing an increase in the whole CO2 flux from soil (Curtin et al., 2000; Al-Kaisi and Yin, 2005), which partly consists in the stimulated rhizosphere respiration (Amos et al., 2005).

3.3. Organic Manure Manure and other organic materials of different origin (farmyard etc.) are applied to the soil in order to increase the levels of plant nutrients and to improve the physical, chemical and biological soil properties that directly affect soil fertility. Organic manure directly influences SOC by increasing C input. A number of studies suggests application of organic manure, either alone or in combination with inorganic fertilizers, is more effective in increasing SOC than inorganic fertilizer alone (Wu et al., 2004; Blair et al., 2006; Rudrappa et al., 2006; Purakayastha et al., 2008; Gong et al., 2009).

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One of the key characteristics of manure application is that it promotes the formation and stabilization of soil macro-aggregates (Whalen and Chang, 2002) and particulate organic matter (Kapkiyai et al., 1999). Manure is more resistant to microbial decomposition than plant residues. Consequently, C input being equal, C storage is higher with manure application than with plant residues. Following five years of application, soil receiving manure had 1.18 t ha-1 more C present than soil receiving plant residues (Feng and Li, 2001). However, the application of even relatively high amounts of manure could increase SOC content until to soil saturation level. Consequently, not always a direct relationship between amount of applied manure and C sequestered could be guaranteed. Recently, Laudicina et al. (2011a) have investigated the combined effects of compost input and tillage intensity on soil chemical and biochemical properties in a semiarid Mediterranean conditions. They have found that compost was the main factor affecting SOC content (56% of total variance explained). Indeed, in plots amended at high input of compost (30 t ha-1), TOC was almost twice than the respective plots amended at low input. However, the authors concluded that also a low compost input (15 t ha-1) is suitable to improve soil fertility but under reduced tillage only. In a long-term study carried out in Kenya, Kapkiyai et al. (1999) have shown that SOM declined even when manure was applied and maize residues returned. Besides, high application rates of manure could cause several problems among which accumulation of K+, Na+ and NH4+ and production of water-repellent substances by decomposer fungi (Haynes and Naidu, 1998). In semiarid environments, moreover, an additional problem that restricts the amount of manure that can be applied is ― burning‖ of the crop when insufficient moisture is available at the time of application. Consequently, farmers often wait until the rains have come before making a manure application. Besides to affect SOC content and dynamics, organic manure had a great influence on MBC as well as CO2 and CH4 fluxes from soil. The majority of studies carried out to investigate the effect of organic manure on soil MBC report an increase in MBC and MBC/SOC ratio, concomitantly to an increase in soil respiration. This increase in CO2 flux is due to the addition of more rapidly decomposable organic amendments. For example, due to the high percentage of labile C compounds, liquid manures generally increase CO2 emissions immediately after application (Chantigny et al., 2001; Bol et al., 2003). When plant residues and other organic amendments are incorporated as fertilizer, mineral N should be applied as well, especially when their C/N is high, in order to obtain an adequate degradation rate by microbial biomass and to meet the crops N demand (Vanlauwe et al., 2002). These practices normally affect CO2 flux, as observed by Iqbal et al. (2009), when straw (high C/N) was applied with N fertilizer. Moreover, the addition of readily decomposable C by organic fertilizers may increase also the decomposition of native SOM through a priming effect devoted to reduce the N deficiency for microbial biomass (Kuzyakov, 2000).

3.4. Inorganic Fertilization In contrast to nutrients from organic fertilisers, which have to be subjected to microbial activity to be available for plant nutrition, the nutrients from inorganic fertilisers can be directly taken up by plants. This is why inorganic fertilisers directly affect crop yields, which is, of course, the main reason for applying them. Substantial SOC sequestration by inorganic fertilizers reported in previous studies was attributed to their positive effects on crop growth

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(Vermaand Sharma, 2007; Purakayastha et al., 2008; Gong et al., 2009). However, many studies have demonstrated that inorganic fertilization, either balanced or imbalanced, had no or negative effects not only on SOC accumulation but also on its fractions (Ogunwole, 2005; Russell et al., 2005; Manna et al., 2006; Rudrappa et al., 2006; Huang et al., 2010). Without doubt the N management impacts SOC dynamics (Lal, 2009). On the one hand, N fertilization has proven to increase the SOC through increasing biomass production and hence C inputs to the soil (Luo et al., 2010). On the other hand, N fertilization affects soil CO2 fluxes and hence C outputs from the soil (Sainju et al., 2008; Ding et al., 2007). As a result, N fertilization may affect the SOC balance. Khan et al., 2007 and Mulvaney et al., 2009 suggested that the loss of SOC from soils may occur in response to synthetic fertilizers. However, their findings were criticized by Powlson et al. (2010) and Reid (2008). The application of mineral N generally increases CO2 fluxes from soil (Iqbal et al. 2009), although other authors believe that at high N fertilization rate, fluxes of CO2 may decrease (Kowalenko et al,. 1978; Fogg, 1988; Wilson and Al-Kaisi, 2008), possibly because of the activity of many soil enzymes found to be decreased by N additions (DeForest et al. 2004). Long-term inorganic fertilizer applications (NPK), typical in intensive agriculture, can have either deleterious or beneficial effects on SMB and activity (Biederbeck et al. 1996; Simek et al. 1999; Böhme et al. 2005; Deng et al. 2006; Weigel et al. 1998; Kandeler et al. 1999a; Fließbach et al. 2000; Thirukkumaran and Parkinson 2000; Rampazzo and Mentler 2001; Ge et al. 2010). These contrasting results may be related to the rate and balance status of fertilizer additions, crop residue management, tillage regime, experimental duration and soil management before the experiment started (Raun et al., 1998; Su et al., 2006). Among different reports, comparable care is not always devoted to that information.

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3.5. Afforestation Carbon in soils ultimately comes from CO2 in the atmosphere, which is captured by plants through the process of photosynthesis. Globally, productivity is strongly correlated with water availability. Consequently, semiarid environments are disadvantaged by the fact that C fixation is lower than in many other ecosystems because of the limitation imposed by water shortage (Aguiar and Sala 1999). Afforestation of degraded or abandoned agricultural soils has been suggested as a way to increase soil C stocks (Lal et al, 1999; Pretty et al, 2002). Whilst aboveground biomass provides soils with organic matter by litterfall, belowground biomass is an important source of C, not only through root death but also from root exudates. Consequently, forest soils could contribute to a greater extent to total C storage than annual crops. From a merely C sequestration viewpoint, plants to be grown in semiarid environments should be selected on the basis of the best adaptation features.There is a wide range of plants suitable for semiarid environmentsand having not only a good potential to assimilate C, then available to be sequestered into the soil, but also being harvested for useful products (Lal et al, 1999). Following afforestation, changes inevitably occur in the quality, quantity, timing and spatial distribution of soil C inputs. With regard to C sequestration, controversial findings are reported about increases or decreasesin SOC content by afforestation. These discrepancies may be due to tree species, their density and/or degree of cover, as well as time since planting. Moreover, some topographic and pedological aspects should be taken into account,

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V. A. Laudicina, V. Barbera, L. Gristina et al.

such as slope, orientation and lithology as they affect both characteristics of the vegetation and soil properties (Kooijman et al., 2005). Fernández-Ondoño et al. (2010) reported significant differences at 0-10 cm soil depth with pine afforestation doubling the SOC values of adjacent open areas. Paul et al. (2002) reviewed global data on changes in soil C following afforestation available from 43 published or unpublished studies, encompassing 204 sites. They found soil C either increasing or decreasing, particularly in young ( Entisols (7.80 g kg-1) = Alfisols (7.80 g kg-1) > Oxisols (6.30 g kg-1). In present study, we compared the vertical distribution of SOC contnets in different Soil Orders (n = 40) (Figure 1), which the highest SOC contents were found in the depth of 50 cm from soil surface of Mollisols (10 to 29 g kg-1). The order of SOC contents in the depth of 50 cm was listed as follows: Mollisols > Entisols > Ultisols > Inceptisols. Our result differs from the

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results provided by Chen and Hseu (1997); the disagreement might be attributed to the variance of the soils and locations we sampled. However, the SOC contents ranged from 10 to 30 g kg-1 in common Soil Orders of rural soils were confirmed. The SOC contents of forest soils at three soil depth intervals are also listed in Table 3. Very high SOC content was found in Histosols (351 g kg-1), indicating a slow decomposed rate of organic matter in poorly drained conditions. Andisols, Inceptisols, and Spodosols have higher SOC contents (> 80 g kg-1) than other Soil Orders at a depth of 0-30 cm. Moreover, Entisols has the lowest SOC content (11.1 g kg-1) in forest soils. In general, SOC content decreased sharply from 0-30 cm interval to 30-50 cm and 50-100 cm sections. The SOC content of forest soils also showed the great variation in different Soil Orders or three soil depth intervals. Meanwhile, the mean SOC value of Soil Orders at a depth of 0-30 cm, excluding Histosols, was about 45.0 g kg-1. Table 3. The SOC stocks with different depths in Soil Orders of Taiwan (n = 212)

Soil Order

0-30 cm Mean CV* n¶

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kg m-2 %

0-50 cm Mean CV n

0-100 cm Mean CV n

Vertisols Mollisols Inceptisols Entisols Ultisols Alfisols

10.0 7.27 5.58 5.44 4.86 4.75

45 31 56 55 79 55

kg m-2 % kg m-2 Cultivated soils (n=140) 4 13.4 37 4 17.0 10 9.49 36 10 11.7 128 7.88 58 128 11.5 146 6.96 60 146 8.66 66 6.95 80 66 9.68 18 6.43 52 18 9.49

Oxisols Average

3.82 5.97

67 -

15 -

% 31 54 82 65 73 51

%

%

59 62 48 63 50 50

79 81 68 80 72 68

74 16 8.86 73 16 43 59 11.0 54 72 Forest soils (n=72) Histosols 36.9 38 3 63.8 37 3 -4 Spodosols 29.5 49 10 38.3 50 10 41.9 42 7 70 91 Andisols 14.0 47 24 19.5 46 24 27.7 43 24 51 70 Mollisols 11.1 65 3 15.9 35 3 19.3 42 3 58 82 Inceptisols 12.5 46 60 16.8 43 60 22.4 48 60 56 75 Ultisols 12.3 55 29 15.3 56 29 21.0 58 29 58 73 Vertisols 8.86 50 3 14.3 35 3 21.4 24 3 41 67 Entisols 7.12 59 27 8.32 77 17 8.47 77 17 84 98 Alfisols 4.67 69 6 6.53 61 6 9.30 42 6 50 70 Average 15.2 22.1 59 78 a A stand for the ratio of the soil organic carbon stock of 0-30 cm divided by in the 0-100 cm zone; B stand for the ratio of the soil organic carbon stock of 0-50 cm divided by in the 0-100 cm zone. *

5.26 8.06

4 10 128 146 66 18

Ratioa A B

: CV is the coefficient f variation (%).

¶: The number of soil pedons by depth interval. # : Data not available for the 30-50 cm or 50-100 cm depth interval.

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3.2. Estimation the SOC Stocks in Taiwan According to area and Bd of the soils presented in Table 1 and Table 2, the calculation of SOC stock was conducted for each Soil Order (Table 3) to obtain total SOC pools by multiplying area of each Soil Order in rural and forest soils in Taiwan (Table 4). From the estimation of SOC stocks in pedons of rural soils (Table 3), the highest SOC stock was found in Vertisols, and followed by Mollisols, Inceptisols, Entisols, Ultisols, Alfisols, and Oxisols regardless of soil depths we calculated. The differences between SOC content (g kg -1) and stock (kg m-2) in this study could be attributed to natural structures and non-soil components in soils. The SOC storage (kg m-2) is therefore considered as more realistically to reflect the amount of C stored in natural soils (Li and Zhao, 2001). Table 3 also presents that SOC stock ranged from 8.86 to 17.0 kg m-2 to the depth of 100 cm in the rural soils. Similar estimation of SOC stock consisted with the results of Li and Zhao (2001) which indicated that about 15 kg m-2 SOC was found in the cropped soils to 100 cm depth in China. Additionally, 40-65% of SOC was concentrated in the depth of 30 cm, and about 60-80% of SOC was found in the depth of 50 cm.

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Table 4. The estimated total SOC pools (Tg) in different depths of Taiwanese rural soils Soil Order

0-30 cm

Inceptisols Alfisols Entisols Ultisols Mollisols Oxisols Vertisols Total

47.9 17.4 6.21 7.89 1.39 0.19 0.01 81.0

Inceptisols Entisols Ultisols Alfisols Andisols Mollisols Spodosols Histosols Vertisols Miscellaneous lands Total

64.9 29.5 10.7 5.90 1.80 0.93 0.21 0.05 0.01 -# 114

0-50 cm 0-100 cm Cultivated soils (n=140) 67.7 98.8 23.6 34.8 7.95 9.89 11.3 15.7 1.81 2.23 0.26 0.44 0.01 0.02 113 162 Forest soils (n=72) 74.7 99.4 29.5 30.1 11.5 15.8 7.07 10.1 2.15 3.06 1.14 1.39 0.23 0.25 0.08 0.01 0.01 126 160

Table 4 presents estimated total SOC pools in the rural soils. The estimation indicated that 81 Tg (tera gram, 1012 grams), 113 Tg, and 162 Tg of SOC were stored within the depth of 30 cm, 50 cm and 100 cm, respectively, in the rural soils of Taiwan. About 50% of SOC Soil Organic Matter: Ecology, Environmental Impact and Management : Ecology, Environmental Impact and Management, Nova Science

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within 100 cm was stored in upper 30 cm, and 70% was stored in 50 cm depth from soil surface. Many studies estimated the amounts of organic C in the tropical soils. Kimble et al. (1990) estimated a value of 496 Pg (peta gram, 1015 grams) C in the upper 100 cm soil, which is comparable to the estimate of 506 Pg C by Eswaran et al. (1993), however, Batjes (1996) reported a relatively lower result of 384-403 Pg C. Li and Zhao (2001) also indicated that the amount of SOC in tropical and subtropical China is around 5.7-7.5% of the world’s tropical areas. In the present study, there is a total of about 0.16 Pg of stored SOC in upper 100 cm for the rural soils. The SOC stock was calculated by using intervals of both 30 cm and 50 cm soil depth for comparison with the results obtained from other countries or regions in the world. In most mineral soils, SOC stocks have been calculated to a depth of 100 cm except for Entisols with very shallow soil depth, or Spodosols and Inceptisols located on very steep landscape. The mean SOC stock of different Soil Orders of forest soils in Taiwan to a depth of 30 cm, 50 cm, and 100 cm was listed in Table 3. The mean SOC stock of Histosols is highest (63.8 kg m-2) in the upper 50 cm depth of forest soils, and Spodosols is highest (41.9 kg m-2) in the upper 100 cm depth. The higher mean values of SOC of Spodosols is attributed to the large number of complexes of soil organic matter in the soil surface (Chen and Hseu, 1997) or spodic horizon containing higher illuvial humus and iron materials, and thicker organic layer in the soil surface (Vejre et al., 2003). The mean SOC stock of forest soils in Taiwan, excluding Histosols and Spodosols, is 10.1 kg m-2 (0-30 cm depth), 13.8 kg m-2 (0-50 cm depth), and 18.5 kg m-2 (0-100 cm depth). Batjes and Dijkshoorn (1999) has reported that the mean soil carbon density in Amazon region, to a depth of 100 cm, range from 4.0 kg m-2 for Arenosols to 72.4 kg m-2 for Histosols, and the mean carbon density for the mineral soils, excluding Arenosols and Andosols (30.5 kg m-2), is 9.8 kg m-2. Tan et al. (2004) estimated the SOC stocks in Ohio and proposed the the mean soil carbon density (0-100 cm depth) for the mineral soils is about 10.2 kg m-2, ranging from 7.1 kg m-2 in Ultisols to 8.8 kg m-2 in Alfisols, 11.3 kg m-2 in Inceptisols, 12.7 kg m-2 in Entisols, and 16.9 kg m-2 in Mollisols, respectively. In Danish forest soils, Vejre et al. (2003) examined 140 forest soil pedons and calculated the average total soil organic C contents was 12.5 kg m-2, in which, Spodosols has greatest soil C stock (14.6 kg m-2), and Alfisols is the least content (8.8 kg m-2). The calculated results of this study are higher than those of literature reported, and are also associated with the differences on the sampling sizes and analytical methods of the original studies (Eswaran et al., 1995). Cumulatively, 41-84% (59% in average) of the total SOC to a depth of 100 cm is stored in the upper 30 cm and 67-98% (78% in average) in the upper 50 cm from the surface if the soil depth is only 50 cm (Table 3). For a global average (n=2,640), Batjes (1996) indicated that 39-70% of the total SOC in the upper 100 cm of mineral soils is in the first 30 cm depth, and 58-81% is in the first 50 cm depth. Batjes and Dijkshoorn (1999) also reported that about 52% of SOC stock in the Amazon region is held within 30 cm of the soil. Nearly the same trends appear for soil organic carbon distributed in different soil depths in the world. These results also indicate that a large amount of carbon dioxide can be potentially released from the soil surface to a depth of 30 cm owing to adverse human activity or environmental degradation (Detwiler, 1986; Batjes, 1996). The estimated total SOC stocks in forest soils of Taiwan to depths of 30 cm, 50 cm, and 100 cm are shown in Table 4. The SOC stocks in miscellaneous lands are not included in this estimation. More than 50% of total SOC stocks was found to be stored in Inceptisols. The

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summation of SOC stocks in Inceptisols, Alfisols, Ultisols, and Entisols were higher than 90% of total SOC stocks. The total SOC stocks in forest soils in 100 cm depth are estimated about 160 Tg.

Figure. 1. The distribution of rural soils (the areas with white color) and forest soils (the colorful areas) in Taiwan.

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Table 5. Changes of soil organic matter content in rural soils in some counties in Taiwan from 1950 to 1994 Location

a

Sinchen (Hualian) Jian (Hualian) Hihshang (Taitung) Beinan (Taitung) Dashe (Kaohsiung) Yongkang (Tainan) Changhua (Changhua) Hemei (Changhua)

Soil organic matter content (%) 1950

1967

1981

1994

2.30±0.38 (7) 2.35±0.33 (3) -a (0) 2.83±0.94 (18) 1.81±0.43 (4) 1.21±0.52 (6) 2.53±0.31 (6) 1.49±0.36 (7)

2.34±0.88 (142) 1.44±0.41 (273) 2.69±0.57 (160) 2.10±0.75 (160) 1.36±0.49 (161) 1.00±0.36 (303) 1.80±0.83 (426) 1.92±0.56 (329)

2.52±0.93 (21) 2.21±0.57 (21) 2.89±0.63 (19) 2.89±0.82 (19) 1.57±0.75 (8) 1.10±0.42 (5) 2.44±0.63 (20) 2.06±0.54 (42)

2.60±1.17 (213) 2.24±0.66 (494) 3.39±1.04 (493) 2.64±0.88 (502) 1.34±0.61 (220) 1.61±0.56 (308) 2.93±0.96 (469) 2.66±1.40 (522)

Not available. Values are shown as mean ± standard deviation (sample number). (Guo et al., 1995).

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3.3. The Effects of Environmental Factors on SOC Stocks in Taiwan Soils Time Paustian et al. (1998) indicated that SOC rose linearly with increasing additions of crop residues and root organic matter, and they also suggested that irrigated farming facilitated accumulation of SOC with time, which also agreed with Lal et al. (1998). For example, irrigated agriculture has been shown to increase SOC by 1.66 Mg ha-1 within the top 30 cm of soil after 15 year (Lueking and Schepers, 1985). In general, SOC declines at the beginning of irrigation and approaches a steady state within 25-50 years, and shows a clear increase of SOC in about 50 year after conversion of native soil to agricultural land (Swift, 2001; Janzen et al., 1998; Lal et al., 1998). This pattern suggests that time is an important factor for C sequestration in irrigated cropland. Based on previous investigated data (Guo et al., 1995), SOC contents in topsoils of rural soils in Taiwan increased with irrigated age from 1950 to 1994 (Table 5). The increase of SOC contents was attributed to the cultivation systems and fertilization. About 0.2% to 1.2% of SOC increased from 1950 to 1994 in Taiwan excluding Beinan and Dashe areas, where were long-term upland cultivated area. We considered that long-term rotation of paddy and upland field cultivation, extensive land use in rice-growing and long-term applying of chemical and organic fertilizers are major reasons in increasing SOC contents in rural soils of Taiwan in several decades. Wu et al. (2008) also indicated that SOC stocks increased by 0.5 to 1 time after five decades of irrigated farming in California, USA. Additionally, we also estimated the SOC sequestration rate in upper 100 cm of rural soils in Taiwan (Figure 2).

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Although the sample number is small (n = 24); however, the time scale is long and ranges from 3,000 to 480,000 yrs. The results showed that SOC sequestration rate dramatically dropped from 12.4 g m-2 per year to 1.14 g m-2 per year within 1000 yrs, and then toward to be a stable rate about < 0.50 g m-2 per year after 1000 years. The SOC sequestration rate could be well fitted into the equation of Y = -12.92 / (1-9.861X) (r = 0.81, p < 0.01). Schulp et al. (2008) indicated that C sequestration rate could be increased by 9-16% in 2030 relative to 2000 when they estimated the future C sequestration in Europe. Based on our estimated equation, SOC sequestration rate of rural soils in Taiwan is about -0.03% in future 30 years, which differed from the results of Schulp et al. (2008), and the difference could be attributed to scale of time in calculating C stocks. Soil pedons at marine terraces in eastern Taiwan

SOC accumulation (g/m2 ) per year

14

Y = -12.92 / (1 - 9.861 X) r = 0.81, p < 0.01

12 10 8 6 4 2 0 0

5

10

15

20

25

30

35

40

45

50

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Soil age (*104 year)

Figure 2. SOC accumulation rate with soil age on the river and marine terraces of Taiwan. The points in grey zone are SOC accumulation rate at marine terraces; others in white zone are SOC accumulation rate at river terraces.

Table 6. Environmental characteristics of soils and soil classifications at sample sites Sample site1)

1)

GDS JHS SMS FS PL TPS WF CL1 CL2 CL3 JS

Elevation (m) 700 195 1150 300 490 1950 1200 1710 1110 1100 230

Slope (°) 25 10 25 20 25 25 15 5~25 5 10 15

Aspect (°) 250 270 20 60 0 0 280 40 350 10 220

SMR2)

STR2)

udic udic udic perudic perudic perudic udic perudic perudic perudic perudic

thermic thermic thermic thermic thermic mesic thermic mesic thermic thermic thermic

Parent material3) SS-shale SS-shale SS-shale Shale SS-shale Slate Slate Slate Slate Slate Slate

Soil Order Inceptisols Ultisols Inceptisols Inceptisols Ultisols Ultisols Inceptisols Ultisols Inceptisols Inceptisols Inceptisols

GDS = Gandaoshan; JHS = Jiouhuashan; SMS = Sihmasian; FS = Fushan; PL = Pinglin; TPS = Taipingshan; WF = Wufong; CL = Chilan; JS = Jiaosi. 2) SMR, soil moisture regime; STR, soil temperature regime (Soil Survey Staff, 2006). 3) SS, sandstone. (Tsai et al., 2009).

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Table 7. Locations and climatic characteristics of selected plantation tree species Tree species Broadleaf trees Acacia confusa Aleurites fordii Zelkova formosana Coniferous trees Cryptomeria japonica Cryptomeria japonica Cryptomeria japonica Taiwania cryptomerioides Chamaecyparis obtusa var. formosana Cunninghamia konishii Chamaecyparis formosensis Calocedrus formosana 1)

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2)

Stand age (yr)

Sampling site1)

MAT(°C)2)

MAP (mm yr-1)2)

50 20 27

GDS JHS SMS

20.2 21.8 17.1

2300 1850 2700

20 40 51 10 37

FS PL TPS WF CL1

20.7 19.5 13.5 18.6 14.0

3200 3250 2700 2500 2800

16 16 30

CL2 CL3 JS

16.3 16.3 19.8

3250 3250 2800

Sample sites are defined in the footnotes of Table 6. MAT, Mean annual temperature; MAP, Mean annual precipitation (Central Weather Bureau, Taiwan).

Climate Climate characteristics are an important factor to affect SOC stocks in Taiwan where clear change of altitudes ranged from sea level to 4000 m was found. According to Tsai et al. (2009), nine plantation tree species distributed in nine plantation forest sites, including three broadleaf vegetation species and six coniferous vegetation species were selected to study the carbon pool in northern Taiwan. The elevation of 9 study sites ranged from 200 to 2000 m above sea level (Table 6), and the climatic condition also changed with increasing elevation from subtropical to temperate zone. The lowest mean annual temperature (MAT) was found at TPS site (13.5℃), and the highest was at JHS site (21.8℃) (Table 7). The mean annual precipitation (MAP) ranged from 1850 mm (JHS site) to 3250 mm (PL and CL sites). In each plantation forest, three soil profiles were dug at least to 1 m from the soil surface or to the bed rock if the soil profile was less than 1 m. Total 33 soil profiles were sampled. Five layers of each soil profile were collected, including 0-15 cm, 15-30 cm, 30-50 cm, 50-75 cm, and 75100 cm depth. Tsai et al. (2009) indicated that the SOC pool have significant differences among nine plant species (p < 0.05), but there are no significant differences among different plantation time of same species (Table 8). The lowest SOC pool was found in Aleurites fordii Hemsl. plantation forest (only 4.0 kg m-2 at 0-100 cm depth from soil surface) and the highest was in Chamaecyparis obtusa Siebold & Zucc. var. plantation forest (21.1 kg m-2). In general, the mean SOC pool within the depth of 30 cm, 50 cm, and 100 cm in broadleaf plantation forest is about 6.5, 8.2, and 9.6 kg m-2, respectively. In coniferous plantation forest, it is about 7.4, 9.7, and 12 kg m-2, respectively. After the analysis of SOC data, about 50% of C pool was stored in upper 30 cm of soil pedon and about 70% of C pool was stored in upper 50 cm of soil pedon of different plant species. Tsai et al. (2009) also indicated that other environmental factors, including air temperature and precipitation, have significant effects on

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the accumulation of SOC stocks, except the tree species of plantation in northern Taiwan. Linear regression model was calculated between mean SOC stocks (Y, kg m-2) of plantations and elevation (X, m), and the results showed significantly positive correlation (Figure 3). Besides, mean SOC stocks (Y, kg m-2) of 0 - 30 cm depth also showed significantly but negative correlation with annual mean air temperature, but no correlation with annual precipitation (Figure 4). As indicated by Garten et al. (1999), the changes of air temperature along an elevation gradient affect the dynamic changes of soil organic matters. Soil organic carbon was accumulated at higher elevation because of the lower air temperature reducing the microbial activity for decomposing soil organic matters.

Land Uses With increasing population in the world, additional land is expected to be converted to irrigated farming or reclaim for agriculture (Bruinsma, 2003). However, extremely few field survey data are available, and quantifying of impact of cropped lands on dynamic transformation of SOC is also limited (Lal et al., 1999; Follett, 2001). Different land uses have been indicated to lead to change of SOC storages (Purakayastha et al., 2008; Jelinski and Kucharik, 2009). The SOC sequestration could be positively or negatively influenced by land use change from native soils to cropland soils, which depended on the management policy of those converted cropland soils, e.g. tillage systems, frequently alternative cultivation, and fertilizer application. Table 9 lists the SOC stocks of soils with different land uses in Taiwan. Based on our previous survey data (Chen and Hseu, 1997; Chen et al., 2001-2003; 2005; 2006), the SOC stock in 30 cm depth in forest soils was the highest (12.4 kg m-2), following by rice-growing soils (7.99 kg m-2), fallow soils (7.21 kg m-2) and upland cultivated soils (5.11 kg m-2). The trend of SOC stock sequence with different land uses in the depths of 50 cm and 100 cm of the studied soil pedons were also the same with that in 30 cm depth, which also agreed with that of Post and Kwon (2000) which indicated that conversion of forests into croplands will decrease the SOC storages and the opposite situation usually lead to increase of SOC storages. For rural soils, greater accumulation of SOC in rice-growing soils could be probably ascribed to long-term flooding in those soils in spite of the soils in fallow. Additionally, to consider dynamic changes of SOC stocks in different land uses, the estimation of SOC storage in different land uses from 1969 to 2002 was conducted in Tainan city, where is an area with high potential productivity of agriculture in southern Taiwan. The permanent ricegrowing practice led to increase of SOC storage in the depth of 30 cm from 4.92 ± 0.74 kg m2 to 6.74 ± 0.91 kg m-2 for past 33 years, however, the increase of SOC storage was insignificant in the depth of 50 cm but decrease in the depth of 100 cm (Table 11). Change of land use from rice-growing to fallow and upland cultivation (sugarcane planting) decreased SOC storage from 6.36 ± 1.64 kg m-2 to 4.87 ± 2.44 kg m-2 and 5.92 ± 0.80 kg m-2 to 5.75 ± 0.01 kg m-2, respectively, in the depth of 30 cm, as well as in the depth of 50 cm and 100 cm. Nevertheless, no obvious change of SOC storage in persistent upland cultivation; but SOC stock will obviously increase with ceasing to plant sugarcane based on our result.

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Table 8. The organic carbon storage (kg m-2) of plantation tree species for three soil depth intervals in this study Tree species

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Broadleaf vegetation Acacia confusa Merr. (Aca)

*

Aleurites fordii Hemsl. (Ale) Zelkova formosana Hay. (Zel) Coniferous vegetation Cryptomeria japonica (L.F.) D. Don I (Cry I) Cryptomeria japonica (L.F.) D. Don II (Cry II) Cryptomeria japonica (L.F.) D. Don III (Cry III) Taiwania cryptomerioides Hayata (Tai) Chamaecyparis obtusa Siebold & Zucc. var. formosana (Hayata) Rehder (ChO) Cunninghamia konishii Hayata (Cun) Chamaecyparis formosensis Matsum. (ChF) Calocedrus macrolepis Kurz var. formosana (Florin) Cheng and L.K. Fu (Cal)

Stand age n (yr)

0-30cm Mean CV%

0-50cm Mean CV%

0-100cm Mean CV%

50

3

24

15 abc

33

3 3

12 abc 4.0 e 8.6 bcd

23

20 27

9.8 ab* 2.2 d 7.4 bc

67 9

4.0 e 9.7 cde

67 42

20

3

21

6.9 de

8

8.1 cde

2

40

3

5.7 bcd 5.5 cd

21

7.0 de

23

8.4 cde

33

51

3

7.0 bc

3

8.4 cd

16

12 bcd

36

10

3

30

14 ab

19

17 ab

17

37

3

9.2 abc 12 a

33

16 a

35

21 a

40

16

3

37

12 bcd

35

3

30

12 abc 6.6 de

35

16

16

6.6 de

16

30

3

9.0 abc 5.9 bcd 5.1 cd

23

6.6 de

29

7.8 cde

23

61 19

Means followed by same letter within each column are not significantly different based on the Duncan’s multiple test (p30. C/N ratios were greater in organic horizons than in the underlying mineral soil layers, while the variation of C/N in deeper soil horizons was less. At KL site the C/N ratio increase with increasing depths. 13

15

 Csoil [‰]

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Depth [cm]

-30

-27

 Nsoil [‰]

-24

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SOC [wt.%]

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40

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surface

carbonate bedrock

40

40

40

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RA

SJ

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Figure 1. Depth profiles of the isotopic composition of soil organic carbon (13Csoil) and nitrogen (15Nsoil), soil organic carbon content (SOC) and C/N ratios at all three sampling locations: RA – Rajhenav, SJ – Snežna jama and KL – Kladje. Lines represent soil surface at RA, SJ and KL and thickness of the soil at RA and SJ.

Diffuse Reflectance FT-IR Spectroscopy The DRIFT spectra of untreated/bulk soil samples at all three sampling locations are presented in Figures 2-4. In general, the spectral features for all organic horizons showed the same peak pattern indicating the presence of typical main bands summarized in Table 3. In the spectra of mineral horizons the signals of quartz and clays were observed. Spectra of RA (M5-M40), KL (M5-M80) and SJ (M10-M40) horizons showed new bands at 3698 and

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3620 cm−1. They are characteristic of the kaolin group (Qtaitat & Al-Trawneh, 2005), indicating the presence of kaolinite (Sidheswaran et al., 1990) or montmorillonite structure (Patel et al., 2007). Spectra of mineral horizons showed significant presence of quartz (1870, 800, 780, 695, 533-538 cm–1) and of other silicate structures by signals appearing in the silicate (Si-O) stretching region (1150 to 950 cm-1). In the spectra of the SJ sample (M40 horizon) the peaks at 2626 cm-1 and 730 cm-1 the presence of dolomite (Figure 2). It is also indicated by other dolomite FTIR absorptions at 3020, 2528, 1821, 1445-1451, 885, 882, and 729-730 cm-1 (Jones & Jackson, 1993; Ji et al., 2009). Vibrations in 3020-2850 cm-1 result from dolomite and the alkyl CH stretch of organics, indicated also by elemental and mineral analyses of this horizon sample. The content of carbonates present at this depth was estimated to be 8.6% (Urbančič et al., 2009). In the other spectra of selected samples no dolomite or other carbonate peaks were observed, since the content of carbonates was < 1% at both locations SJ and RA.

Figure 2. FTIR spectra of the bulk soil samples at SJ: Ol,f (litter/fermented layer 4-0 cm), M5 (0-5 cm), M10 (5-10 cm), M20 (10-20 cm), M30 (20-30 cm), M40 (30-40 cm).

The DRIFT spectra of demineralized residues showed a successful acid digestion confirmed by disappearing or highly reducing the mineral signals described in bulk samples spectra. The demineralization was accompanied by a loss of mass of the sample before and after HCl/HF treatment which was estimated to be about 10-20% for organic layers and up to 30% (46%; RA, M 40) for mineral layers. These results are comparable with the data obtained by Rumpel et al. (2006). In general, the major organic bands are similar to that appearing in the spectra of untreated samples presented in Table 3.

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Soil Organic Matter Characterization at Different Forest Stands in Slovenia Table 3. Band assignments for DRIFT spectra of bulk samples Wavenumbers (cm-1) 3000-3600 2925-2929 and 28532857 1729 (shoulder) 1660-1620 1510-1520

1460-1450 1420-1410 1365 1230

Possible assignaments and comments O-H and N-H stretching of various functional groups such as phenol, alcohol and/or carboxylic and amine groups aliphatic C–H stretching of CH2 and CH3 groups stretching of COOH and other carbonyl groups such as ketones or aldehides C=O stretching of amide groups (amide I band), aromatic and olefinic C=C vibrations, water deformational mode aromatic skeletal vibration of the lignocellulosic materials (Ait Baddi et al., 2004; Boeriu et al., 2004; Calderón et al, 2006), N–H deformation and C=N stretching of amide groups (amide II band) aliphatic C–H and OH groups of phenolic (alcoholic) compounds

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stretching of COO- and CH3 groups C–O stretching, OH deformation of COOH, or/and C–O stretching of aryl ethers 1160 asymmetric stretching of C–O–C of a glycosidic link, C–O of alcohol and ether groups 1100 -1000 C–O stretching of polysaccharide or polysaccharide-like components and Si–O of silicates (Haberhauer et al., 1998; Moenke, 1974) Assignments after Pretsch et al. (1989) and others cited above.

Figure 3. FTIR spectra of the bulk soil samples at RA: Ol,f (5-2 cm) and Of (2-0 cm), M5 (0-5 cm), M10 (5-10 cm), M20 (10-20 cm), M30 (20-30 cm) and M40 (30-40 cm). Soil Organic Matter: Ecology, Environmental Impact and Management : Ecology, Environmental Impact and Management, Nova Science

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Figure 4. FTIR spectra of the bulk soil samples at KL: Ol (surface layer 12-8 cm), Of (surface layer 8-7 cm), Oh (surface layer 7-0 cm), M5 (0-5 cm), M10 (5-10 cm), M20 (10-20 cm), M40 (20-40 cm), M60 (40-60 cm), M80 (60-80 cm).

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CP-MAS 13C NMR Spectroscopy Qualitative differences were found between depth profiles and between sampling locations. The major signals were found at 30, 56, 72, 105, 130, 150 and 175 ppm at both sampling locations RA and KL, at the organic horizons Ol,f and Oh, respectively. The intensity of these peaks is lower deeper in the soil, and the signal at 72 ppm is already absent at the Oh horizon sampling location at RA (Figure 5B). In the soil sample M5 from KL (spectra not shown), the only considerably signals are those around 30 and 175 ppm, and those for the aromatic pattern for RA. It should be due to the low SOC content in the mineral samples comparing to the organic layers. NMR spectra of mineral samples deeper in the soil (M10) have so low resolution that it is not possible to see the characteristics of the OM. Terminal methyl groups (at approximately 17 ppm) were found only in horizon Ol,f at RA (Figure 5B). The signals 56, 130 and 150 ppm were assigned to methoxyl C, C-substituted aromatic C and phenolic C, respectively, in lignin. The signals at 72 and 105 ppm, together with the shoulders around 65 and 80-90 ppm, can most probably be assigned to polysaccharides. The signal at 175 ppm could derive from carbonyl groups of aliphatic acids, benzene-carboxylic acids, esters and amide groups in various compounds, especially from proteins (Wershaw et al., 1996; Mahieu et al., 1999). Tannins and lignins are the main contributors in the aromatic and phenolic regions. The peak at 216 ppm could be attributed to aldehydes and ketones.

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A)

B) Figure 5. A) FTIR and B) CP-MAS 13C NMR spectra of HCl/HF-treated soil samples at different depth profiles; Ol,f (5-2 cm), Oh (2-0 cm), M5 (0-5 cm) at RA.

The quantitative results of NMR spectra were focused mainly on a organic horizons (Ol,f and Oh), since spectra of mineral horizons has low resolution and thus large S/N ratio. The structure of SOM at both sites RA and KL was dominated by aryl C (30.4 - 41.2% of total intensity) and O-alkyl C (30.9 - 32.5%) following by alkyl C (20 - 31.2%), while carbonyl C

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were of minor importance (6.7 - 15.0%). The alkyl C/O-alkyl C ratio was estimated to be 0.57 and 0.64 at RA Ol,f and Oh, respectively (Figure 5B) and 0.67 at KL (Oh) (Figure 6). These data do not correspond to the review of Mahieu et al. (1999) showing that CP-MAS 13C NMR spectroscopy from bulk soil are remarkably similar dominated by O-alkyl C (45%), followed by alkyl (25%) and aromatic C (20%).

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A)

B)

ppm

Figure 6. Comparision of CP-MAS 13C NMR spectra of HCl/HF-treated soil samples at Oh horizon in A) KL and B) RA.

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DISCUSSION

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Chemical Analysis The increase of 15Nsoil from the surface to the lower horizons was steeper at KL than at SJ or RA. The increase in 15Nsoil with depth within the range of 5 to 10‰ observed in our study is consistent with the results of other studies of well-drained, undisturbed forest soils (Nadelhoffer and Fry, 1988; Högberg, 1997; Boström et al., 2007). Explanations for the 13Csoil patterns at RA and SJ include: a) fractionation upon microbial decomposition, b) preferential decomposition of isotopically distinct fractions of the organic source material, and c) soil carbon mixing dynamics and changes in the sources over time. In addition, the Suess effect could account for some of the 13C enrichment in soil SOC (Balesdent and Mariotti, 1996). Alternatively, the microbial biomass itself may be the origin of the isotopically enriched organic material, since the enrichment in 13C, and especially in 15N, relative to the fresh plant litter, has been observed in microbial biomass in different types of soil (Dijkstra et al., 2006; Williams et al., 2006; Boström et al., 2007). This could explain the changes in isotopic data and C/N ratios within the depth profile at location KL. On the other hand, microbial biomass in carbonate-rich soils showed only non-significant enrichments (Dijkstra et al., 2006). Thus, at least at locations RA and SJ, the depth profiles of 13C in the soil could be the consequence of the isotopic fractionation during decomposition that causes gradual 13C enrichment of residual OM (Högberg, 1997). Interpretation of vertical 15N profiles must also consider the existence of a number of N-isotope discriminating processes related to N loss. Volatilization of NH3 and nitrification, followed by leaching or denitrification, alone cause 15N-enrichment in soil (Högberg et al., 1995). The generally most plausible explanation for the positive 15Nsoil shift is plant uptake of N from sources 15Ndepleted relative to the soil, followed by deposition of this isotopically light N on the top of the soil. Another possible explanation could be mineralization-related 15N enrichment in older N (Nadelhoffer and Fry, 1988).

Diffuse Reflectance FT-IR Spectroscopy In untreated/bulk sample similar infrared spectral patterns were found for organic layers at different depths at individual sampling site. A difference between the spectra was observed according to sampling sites (Figures 2-4). However, at all sampling sites protein and carbohydrates represents the major organic components. In the Oh sample (surface layer 7-0 cm) from KL and in the Oh from RA, the presence of quartz was clearly indicated by signals appearing at 800, 779, 696, 539 cm-1 (Pacáková et al, 2000). In parallel the signals corresponding to the Si–O silicate vibrations (at 1035 cm− 1 and 470 cm-1) are in that case clearly evident. The spectra of the mineral horizons (RA and SJ: M5-M40; KL: M5-M80) were characterized with mineral signals (clays, quartz,..). They showed also a decrease of organic component with depth that was indicated by decreasing absorption intensities of aliphatic CH3 and CH2 stretching (2800-3000 cm-1). This is in accordance with the results of elemental analysis (Figure 1) that indicate the decrease of SOC with depth in the sampled soil profile. In

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the case of SJ samples, a decrease of organic fraction content with depth of soil was clearly shown from Ol,f to M30 but in the M40 profile the relative intensities of the absorption peaks indicating the increase in the organic carbon (2800-3000 cm-1, 1430-1450 cm-1) in parallel with the increasing of SOC content (Figure 2). In comparison with horizon M30, the content of SOC was ~1.3-fold greater than that of M30. The signals appearing in the region at 16601620 cm-1 could be attributable to C=O stretching of amide groups (amide I band), to aromatic and olefinic C=C vibrations (around 1650 cm-1) and also to the water deformational mode so the estimation of soil aromatic carbon is difficult. Carbon loss (typical for soils containing substantial amounts of mineral matter) may be related partially to loss of organic fraction bound to the inorganic component i.e. minerals. The slight decrease of the relative absorbance of the band at 1630 cm-1 (carboxylic acids, aromatic and alkene double C=C bonds) was observed, however the evaluation is difficult due to the contribution of water signals. A different element was observed in the spectra of the SJ - M40 horizon, showing two dolomite diagnostic FTIR absorption features at 2626 cm-1 and 730 cm-1. The presence of dolomite at this site area is expected since the bedrock type at SJ is limestone and dolomite (Urbančič et al., 2009). DRIFT analyses of demineralized residues allowed better estimation of changes of organic soil fraction such as the carbohydrate contribution. In spectra of acid treated samples the bands characteristics for quartz and clays greatly decreased or disappeared as it is shown at RA in Figure 5A. Similar observation was also observed at KL. The signal at 915 cm−1 and also 3698 and 3620 cm-1 disappeared, due to the digestion of kaolinite component (Territo et al., 2006). The band seen at around 3340 cm−1 corresponds to the OH and NH groups and the aliphatic stretching vibrations are seen at  2929 and 2854 cm-1. The bending signals of CH2 and CH3 are observed at about 1430 cm-1. Changes in DRIFT spectra clearly indicate a decrease in organic component; especially decreasing absorption intensities of aliphatic CH3 and CH2 stretching (2800-3000 cm-1) throughout the depth soil profile as was also shown in the acid untreated DRIFT spectra. The observed decrease of the aliphatic bend (2929 cm-1) with soil depth may be associated with progressing litter decomposition. A peak around 1730 cm-1 indicating the presence of C=O bonds from carbonyl and/or carboxyl functions and appears as a shoulders on 1633 cm-1 band. These carbonyl and/or carboxyl functions were clearly seen in those spectra and their intensity decreased with profile depth indicating the decrease/loss of more O-containing groups. The later band (1530-1650 cm-1) can be attributed to olefinic and aromatic unsaturations, the stretching vibrations of amides as well as to water deformational modes. The acid treated samples are also highly hygroscopic, preventing the complete desiccation of the KBr sample mixture, so the bands appearing with high intensities at 3500-3200, 1630-1640 and  630-670 cm-1 belong, at least partly, to the stretching, bending and rocking modes of water. DRIFT spectra of demineralized residues of organic layers, M5 and M10 samples clearly feature the 1510-1520 cm-1 peak (lignocellulosic materials, N–H deformation, amide II band, and C=C signals) diminishing in the spectra in deeper layers (i.e. the soil depth; subsoils). The bands at 1100 cm-1 predominantly related to polysaccharides, decreased with depth indicating the decreasing contribution of polysaccharidic fraction (Figure 5A). The decrease of the band areas with soil depth at 2929, 1730, 1630, 1510 and 1160 cm-1 was observed also in the study of bulk soil samples using KBr technique (Djukic et al., 2010). Haberhauter et al. (1998) reported a

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similar trend for spruce-forest litter layers where the intensities of the aliphatic band (2920 cm-1) and the bands in the region 1510-1230 cm-1 decreased. Gerzabek et al. (2006) showed a relative enrichment of carboxylic, aromatic CH and NH groups with increasing OC contents. The absorbance regions i.e. around 2995–2887 cm-1, 1614–1705 cm-1 and 1450 cm-1 could indicate the changes of soil organic carbon, but in our case the comparison spectra of demineralized soils samples did not enable the differentiation of organic fraction at selected sites and confirmed protein and carbohydrates as major components of soil surface material. Better differentiation was observed by CP-MAS 13C NMR spectroscopy. .

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CP-MAS 13C NMR Spectroscopy It was found that in all examinated horizons in RA (Figure 5B) and KL, there is more aromatic carbon and a considerable amount of O-alkyl C, probably from polysaccharides such as hexose and pentose units (the most abundant carbohydrate subunits in the terrestrial environment), indicating a great potential for microbial degradation. The higher content of polysaccharidic material in Ol,f horizon RA (and other layers) was also indicated by DRIFT analysis of the acid treated sample. A prominent signal in the O-aryl C region with a peak around 150 ppm is usually found in plant materials in the first stage of decomposition (KögelKnabner (2002). The splitting of the phenolic group signal in lignin at 147 and 153 ppm is frequently found in lignin from angiosperms (Gil and Pascoal Neto, 1999) which also gives a methoxyl signal at 55-57 ppm (Lorenz et al., 2000). The Ol,f horizon at RA exhibits a methoxyl signal at 56 ppm, while the partially split phenolic region is characteristic of a mixture of lignin and tannin. The typical NMR signals observed in Ol,f horizon in RA are also found in European beech wood and beech litter presented by Kögel-Knabner (2002), but are there more distinct. The spectrum of beech wood has signals that can clearly be attributed to polysaccharides (cellulose and hemicelluloses) as well as to lignin. In addition the beech litter has a signal in the region of alkyl carbon with a maximum at 30 ppm originating from extractable lipids and cutins from the leaf surface. Further, beech litter contains a higher proportion of alkyl and aromatic C than woody material (Kögel-Knabner, 1997). We can therefore conclude that one of the main components of SOM in the Ol,f horizon in RA was beech litter. The aryl C intensity of 37.9 and 37.2% was similar in the organic part of the soil at RA, however the alkyl C/O-alkyl C ratio was higher in Oh horizon indicating a greater extent of decomposition. This suggested a loss of more easily decomposable compounds (e.g. carbohydrates) and a relative accumulation of long chain aliphatic materials (Christensen, 2001) Christensen (2001) also proposed that aromatic compounds can also accumulate in the first stage of litter decomposition. This was not the case in RA and no increase in aromatics was observed. The disagreement might be attributed to the low sensitivity of the CP-MAS 13C NMR technique for aromatic structures (Conte et al., 1997; Skjemstad et al., 1999). The CPMAS 13C NMR indicates that at RA the SOM was more heterogeneous than at KL in the Oh horizon (Figure 6). At KL, lower aromatic signal intensity and higher alkyl C structures were observed, since the surface cover in the organic horizon was a mixture between spruce needles and beech litter. Spruce needle litter is low in aromatic and carbonyl C and contains higher levels of O-aryl C compounds (Hannam et al., 2004). Considering these results higher signal intensities found at 1515 cm-1 and 1420-1430 cm-1 in DRIFT spectra at RA could be related to aromatic structures. The signals in the alkyl C region at 30 ppm, more pronounced in

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the Oh horizon at KL than at RA, can be assigned to C in long chain polymethylene [(CH2)n] structures such as surface waxes, lipids, cutins and resins. This fraction is relatively stable to microorganisms and is thus also present deeper in the soil at both locations. The preservation of lipids could be also supported with the presence of band 1630 cm-1 in all DRIFT spectra. In addition, microbial biomass may also contribute to this signal at KL which could be further supported by the C/N ratio and 15N values in SOM. It was found that microbial material was mostly O-alkyl, alkyl and carboxyl carbon (Kögel-Knabner, 2002; Alarcón-Gutiérrez et al., 2008). Other studies show that SOM associated with the clay fraction (the case at KL) is less aromatic than SOM associated with the silt fraction, and has a larger enrichment of carbohydrates, especially microbe-derived sugars (Solomon et al., 2005), which could explain the presence of the peak at 72 at KL, but not at RA. Deeper in the soil the intensity of signals became lower, indicating preferential degradation of polysaccharides. More rapid degradation was found at KL comparing to RA. This is supported by a higher alkyl C/O-alkyl C ratio of 0.67 for SOM in Oh horizon at KL (Figure 6). This observation contradicts the study by Djukic et al. (2010) where they found that higher pH implies favourable conditions for decomposition. Higher decomposition rates could be related to higher mean annual temperatures, higher microbial activity or quality of organic source material. High temperatures promoted polysaccharide degradation (Alarcón-Gutiérrez et al., 2008). The experiment performed on the decomposition of beech trees and spruce needles shows that spruce needles consistently decompose more quickly than beech leaves (Albers et al., 2004). The results of other studies also indicate that abiotic and microbial community in mixed stands promote decomposition rates and the rates are higher than those found in pure stands of spruce and beech (Sariyildiz et al., 2005; Aneja et al., 2006). These factors have to be investigated more in detail in the future. In addition more favourable decomposition conditions are related to the build-up of SOM at this site.

CONCLUSION 







13C and 15N of SOM suggested isotopic fractionation during decomposition at RA and SJ. On the other hand microbial biomass appears to be the main source of SOM at KL indicated by more pronounced enrichment in 13C and 15N with soil depth and C/N ratios. DRIFT spectral data showed that mineral horizons (of RA and SJ: M5-M40; KL: M5-M80) were characterized with mineral signals mainly by the clays, kaolinite and quartz. At SJ in the M40 horizon the presence of dolomite was indicated. The DRIFT spectra of organic horizons in acid treated samples at all sampling sites did not differ significantly and confirmed protein and carbohydrates as major compound of soil surface material. Changes in DRIFT spectra with depth profiles indicated a decrease in amount of more labile compounds (aliphatic and carboxylic groups) and a relative preservation of lipids in relation to SOC content changes. The structure of SOM in organic layers at both sites RA and KL differed from expected soil dominated contents. The SOM dominated by aryl C (30.4 - 41.2% of total intensity) and O-alkyl C (30.9 - 32.5%) following by alkyl C (20 - 31.2%), while carbonyl C were of minor importance (6.7 - 15.0%).

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In the Oh horizon degradation of polysaccharides was observed by the decrease of Oalkyl region of spectra and increase in alkyl C signal. As a consequence the increase in alkyl C/O-alkyl C ratio in Oh horizon was observed. Degradation of polysaccharides is followed by a partial degradation of aromatic C and a slight increase in aromatic signal is seen. On the other hand lower aromatic signal intensity and higher alkyl C structures at in Oh horizon at KL comparing to RA indicated the presence of spruce needles as a main source of organic material on the surface cover. More rapid degradation of organic material was observed at KL, despite the less favourable C/N ratios and higher content of surface lipids and cutin than at RA. The increased extent of decomposition was also supported by the higher alkyl C/O-alkyl C ratio determined at KL in comparison to RA. This observation could probably be explained by the influence of higher annual temperature, microbial community diversities and difference in vegetation.

ACKNOWLEDGMENTS This research was conducted in the framework of the J7-7397 and L4-2265 project funded by the Slovenian Research Agency (ARRS). Special thanks are given to the Slovenian NMR Centre at National Institute of Chemistry (Slovenia) and to dr. Primož Šket for 13C NMR CPMAS analyses. The authors thank Prof. Roger Pain for linguistic corrections.

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investigate the principal structural changes associated with composting of organic materials with diverse origin. Organic Geochemistry 38, 2012-2023. Gerzabek, M.H., Pichlmayer, F., Kirchmann, H., Haberhauter, G., 1997. The response of soil organic matter to manure amendment in a long-term experiment at Ultuna, Sweden. European Journal of Soil Science 48, 273-282. Gerzabek, M.H., Antil, R.S., Kögel-Knabner, I., Knicker, H., Kirchmann, H., Haberhauer, G., 2006. How are soil use and management reflected by soil organic matter characteristics: a spectroscopic approach? European Journal of Soil Science 57, 485-494. Gil, A.M., Pascoal Neto, C., 1999. Solid-state NMR studies of wood and other lignocellulosic materials. Annual Reports on NMR Spectroscopy 37, 75-117. Golchin, A., Clarke, P., Baldock, J.A., Higashi, T., Skjemstad, J.O., Oades, J.M., 1997. The effects of vegetation and burning on the chemical composition of soil organic matter in a volcanic ash soil as shown by 13C NMR spectroscopy. I. Whole soil and humic acid fraction. Geoderma 76, 155-174. Haberhauer, G., Rafferty, B., Strebl, F., Gerzabek, M.H., 1998. Comparison of the forest soil litter derived from three different sites at various decompositional stages using FTIR spectroscopy. Geoderma 83, 331-342. doi: 10.1016/S0016-7061(98)00008-1 Haberhauer, G., Gerzabek, M.H., 1999. Drift and transmission FTIR spectroscopy of forest soils: an approach to determine decomposition processes of forest litter. Vibrational Spectroscopy 19, 413-417. Haberhauer, G., Feigl, B., Gerzabek, M.H., Cerri, C.C., 2000. FTIR spectroscopy of organic matter in tropical soils: changes induced through deforestation. Applied Spectroscopy 54, 221-224. Hannam, K.D., Quieadu, S.A., Oh, S.-W., Kishchuk, B.E., Wasylishen, R.E., 2004. Forest floor composition in Aspen and Spruce-dominated stands of the boreal mixedwood forest. Soil Science Society of American Journal 68, 1735-1743. Högberg, P., Johanisson, C., Högberg, M., Högbom, L., Näshom, T., Hällgren, J.-E., 1995. Measurements of abundances of 15N and 13C as tools in retrospective studies of N balances and water stress in forests: a discussion of preliminary results. Plant Soil 168/169, 125-133. Högberg, P., 1997. 15N natural abundance in soil-plant systems. New Phytologist 137, 179203. ICP, 2006 a. Manual on methods and criteria for harmonized sampling, assessment, monitoring and analysis of the effects of air pollution on forests. Annex 1: Methods for Soil Analysis. International Co-operative Programme on Assessment and Monitoring of Air Pollution Effects on Forests and the Forest Focus, project ‗BioSoil‘. Ispra, 122 pp. IPCC 2003. Good practice guidance for LULUCF. Kanagawa, Japan, IGES, available at: http://www.ipcc-nggip.iges.or.jp/public/gpglulucf/gpglulucf_contents.htm IPCC 2006. Guidelines for National Greenhouse Gas Inventories. Volume 4: Agriculture, Forestry and Other Land Use. Kanagawa, Japan, IGES, available at: http://www.ipccnggip.iges.or.jp/public/2006gl/vol4.htm Ji, J., Ge, Y., Balsam, W., Damuth, J.E., Chen, J., 2009. Rapid identification of dolomite using a Fourier transform infrared spectrophotometer (FTIR): a fast method for identifying Heinrich events in IODP Site U1308. Marine Geology 258, 60-68. doi:10.1016/j.margeo.2008.11.007

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Jobbágy, E.G., Jackson, R.B., 2000. The vertical distribution of soil organic carbon and its relation to climate and vegetation. Ecology Application 10, 423-436. Jones, G. C., Jackson, B., 1993. Infrared Transmission Spectra of Carbonate Minerals, Chapman and Hall, London. Kaiser, M., Ellerbrock, R.H., Gerke, H.H., 2007. Long-term effects of crop rotation and fertilizationon soil organic matter composition. European Journal of Soil Science 58, 1460-1470. Knicker, H., Lüdemann, H.D., 1995. N-15 and C-13 CPMAS and solution NMR studies of N15 enriched plant material during 600 days of microbial degradation. Organic Geochemistry 23, 329-341. Kögel-Knabner, I., 1997. 13C and 15N NMR spectroscopy as a tool in soil organic matter research. Geoderma 80, 243-270. Kögel-Knabner, I., 2000. Analytical approaches for characterizing soil organic matter. Organic Geochemistry 31, 609-625. Kögel-Knabner, I., 2002. The macromolecular organic composition of plant and microbial residues as inputs to soil organic matter. Soil Biology and Biochemistry 34, 139-162. Kölbl, A., Kögel-Knabner, I., 2004. Content and composition of free and occluded particulate organic matter in a differently textured arable Cambisol as revealed by solid-state 13C NMR. Journal of Plant Nutrition and Soil Science 167, 45-53. Leue, M., Ellerbrock, R. H., Gerke, H.H., 2010. DRIFT Mapping of Organic Matter Composition at Intact Soil Aggregate Surfaces. Vadose Zone Journal 9, 317-324. Lima, D.L.D., Santos, S.M., Scherer, H.W., Schneider, R.J., Duarte, A.C., Santos, E.B.H., Esteves, V.I., 2009. Effects of organic and inorganic amendments on soil organic matter properties. Geoderma 150, 38-45. Lorenz, K., Preston, C.M., Raspe, S., Morrison, I.K., Feger, K.H., 2000. Litter decomposition and humus characteristics in Canadian and German spruce ecosystems: information from tannin analysis and 13C CPMAS NMR. Soil Biology and Biochemistry 32, 779-792. Mahieu, N., Powlson, D.S., Randall, E.W., 1999. Statistical analysis of published carbon-13 CPMAS NMR spectra of soil organic matter. Soil Science Society of American Journal 63, 307-319. Marche, T., Schnitzer, M., Dinel, H., Pare, T., Champagne, P., Schulten, H.R. et al., 2003. Chemical changes during composting of a paper in a mill sludge-hardwood sawdust mixture. Geoderma 116, 345-356. Mathers, N. J., Xu, Z., Berners-Price, S.J., Senake Perera, M.C., Saffigna, P.G., 2002. Hydrofluoric acid pre-treatment for improving 13C CPMAS NMR spectral quality of forest soils in south-east Queensland, Australia. Australian Journal of Soil Research 404, 665-674. Moenke, H.H.W., 1974. The infrared spectra of minerals, Mineralogical Society, London. Nadelhoffer, K.J., Fry, B., 1988. Controls of natural nitrogen-15 and carbon-13 abundances in forest soil organic matter. Soil Science Society of American Journal 52, 1633-1640. Oades, J.M., 1995. An overview of processes affecting the cycling of organic carbon in soils, in: Zeep, R.G., Sonntag, C. (Eds.) Role of Nonliving Organic Matter in Earth‘s Carbon Cycle. John Wiley and Sons, New York, pp. 293-303. Pacáková, V., Pockevičite, D., Armalis, S., Štulik, K., Li, J., Vaselý, V., 2000. A study of the distribution of lead, cadmium and copper between water and kaolin, bentonite and river sediment. Journal of Environmental Monitoring 2, 187-191.

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Patel, H.A., Somani, R.S., Bajaj, H.C., Jasra R.V., 2007. Preparation and characterization of phosphonium montmorillonite with enhanced thermal stability, Applied Clay Science 35, 194-200. Preston, C.M., 1996. Application of NMR to soil organic matter analysis: history and prospects. Soil Science 161, 144-166. Preston, C.M. Trofymow, J.A., Niu, J, Fyfe, C.A., 1998. 13C CPMAS-NMR spectroscopy and chemical analysis of coarse woody debris in coastal forests of Vancouver Island. Forest Ecology and Management 111, 51-68. Pretsch, E., Clerc, T., Seibel, J., Simon, W., 1989. Tables of Spectral Data for Structure Determination of Organic Compounds. 2nd edition. Berlin, Springer-Verlag. Qtaitat, M.A., Al-Trawneh, I.N., 2005. Characterization of kaolinite of the Baten El-Ghoul region/south Jordan by infrared spectroscopy, Spectrochimica Acta A61, 1519-1523. Reeves, J.B., McCarty, G.W., Reeves, V.B., 2001. Mid-infrared diffusive reflectance spectroscopy for the quantitative analysis of agricultural soils. Journal of Agricultural and Food Chemistry 49, 766-772. Reeves, J.B., 2003. Mid-infrared diffusive reflectance spectroscopy: Is sample dilution with KBr necessary, and if so, when? American Laboratory 35, 24-25. Reeves, J.B., Francis B.A., Hamilton, S.K., 2005. Specular reflaction and diffuse reflectance spectroscopy of soils. Applied Spectroscopy 59, 39-46. Rumpel, C., Rabia, N., Derenne, S., Quenea, K., Eusterhues, K., Kögel-Knabner, I., Mariotti, A., 2006. Alteration of soil organic matter following treatment with hydrofluoric acid (HF). Organic Geochemistry 37, 1437-1451. Sariyildiz, T., Tüfekçioğlú, A., Küçük, M., 2005. Comparison of Decomposition Rates of Beech (Fagus orientalis Lipsky) and Spruce (Picea orientalis (L.) Link) Litter in Pure and Mixed Stands of Both Species in Artvin, Turkey. Turkish Journal of Agriculture and Forestry 29, 429-438. Sidheswaran, P., Bhat, A.N., Ganguli, P., 1990. Intercalation of Salts of Fatty Acids into Kaolinite. Clays and Clay Minerals 38, 29-32. Sollins, P., Homann, P., Caldwell, B.A., 1996. Satbilization and destabilization of soil organic matter: mechanisms and controls. Geoderma 74, 65-105. Solomon, D., Lehmann, J., Kinyangi, J., Liang, B., Schäfer, T., 2005. Carbon K-Edge NEXAFS and FTIR-ATR Spectroscopic investigation of organic carbon speciation in soils. Soil Science Society of American Journal 69, 107-119. Tatzber, M., Stemmer, M., Spiegel, H., Katzlberger, C., Haberhauter, G., Mentler, A., Gerzabek, M.H., 2007. FTIR-spectroscopic characterization of humic acids in humin fractions obtained by advanced NaOH, Na4P2O7 and Na2CO3 extraction procedure. Journal of Plant Nutrition and Soil Science 170, 522-529. Territo, C., Vieillard, P., Righi, D., Petit, S., Scalenghe, R., 2006. A new simple approach to evaluate pedogenic clay transformation in a Vertic Calcisol, Journal of Geochemical Exploration 88, 345-349. Urbančič, M., Kobal, M., Vilhar, U., Simončič, P., 2009. Zaloge organske snovi v izbranih sestojih na bukovih rastiščih – Evaluation of the organic matter at selected research objects of beech sites. Trajnostna raba lesa v kontekstu sonaravnega gospodarjenja z gozdom, pp. 15-25.

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Wander, M.M., Yang, X., 2000. Influence of tillage on the dynamics of loose and occluded particulate and humified organic matter fraction. Soil Biology and Biochemistry 32, 11511160. Wershaw, R., Leenheer, J.A., Kennedy, K.R., Noyes, T.I., 1996. Use of 13C NMR and FTIR for elucidation of degradation pathways during natural litter composition and composting: I. Early stage leaf degradation. Soil Science 161, 667-679. Williams, M.A., Rice, C.W., Owensby, C.E., 2006. Natural 15N abundance in a tallgrass prairie exposed to 8-years of elevated atmospheric CO2. Soil Biology & Biochemistry 38, 409-412.

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Chapter 5

SOIL ORGANIC CARBON STOCKS IN RELATION TO DIFFERENT LAND-USE TYPES IN A MOUNTAINOUS WATERSHED Víctor Hugo Durán Zuazo1,*, José Ramón Francia Martínez2, Iván García Tejero1 and Armando Martínez Raya2 1

IFAPA Centro ―Las To rres-Tomejil‖, Alcalá del Río, Sevilla, Spain 2 IFAPA Centro ―Ca mino de Purchil‖. Apdo., Granada, Spain

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Land-use change in mountainous areas is often a core problem with serious implications for sustainable resource use and environmental impact. Soils are potential sinks for atmospheric carbon and may significantly help mitigate the effects of climate change. The present study highlights information on C storage of different land-use types in a semiarid Mediterranean agroforestry system, and its potential for the restoration of degraded semiarid ecosystems. We focused on the implications of land-use type (LUT) for soil organic carbon (SOC) sinking and its impact on physico-chemical soil properties. The study area was a small agroforestry watershed (670 ha), located in Lanjaron on the southern flank of the Sierra Nevada Mountains in south-eastern Spain. Five LUTs were monitored: farmland (olive, almond, and cereals), forest (Aleppo pine and Scots pine), shrubland, grassland, and abandoned farmland. The forest with Aleppo and Scots stands, and shrubland had the highest SOC content and consequently the optimal physicochemical soil properties in relation to the remaining LUTs. By contrast, the abandoned farmland had significantly lower SOC stocks than did farmland, grassland, or shrubland, although a progressive plant recolonization took place that offered greater potential capacity for C sequestering. In concrete, the weighted average SOC storage for Aleppo stands, Scots stands, shrubland, grassland, cereals, olive, almond, and abandoned farmland were 99.6, 83.3, 72.2, 63.2, 53.4, 50.8, 48.9, and 27.5 Mg ha-1, respectively. Thus, the watershed C dynamics indicate that due to intense land-use cover change, the watersheds studied are becoming a net source of C to the atmosphere.

*

Email corresponding author: [email protected].

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Víctor H. D. Zuazo, José R. F. Martínez, Iván G. Tejero et al.

Keywords: Land-use type, agroforestry watershed, soil organic carbon storage, soil quality

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1. INTRODUCTION Watershed management has become an increasingly vital issue, with an emphasis on finding sustainable approaches for improving the natural scenarios [1]. Assessment of carbon (C) stocks in soil is a basic step in evaluating the C sequestration potential of an ecosystem [2, 3]. Land-use change is the main human factor that may induce substantial alterations to both the quantity and quality of soil organic matter [4]. In this sense, the abandonment of farmlands and the conversion of forest and grassland into farmland is a well-known process in degrading the soil physico-chemical properties, especially reducing soil organic carbon (SOC) and changing the stability of soil aggregates [5, 6]. That is, land-cover dynamics, particularly deforestation, forest fire, and abandoned farmlands, have become a critical concern, having far-reaching implications for systems involving human livelihoods [7, 8]. Therefore, sustainable utilization and conservation of natural resources in agro-forestry systems is considered one of the fundamental components of sustainable rural development, as has been pointed out by many authors [9, 10, 11, 12]. Plant covers have a significant impact on regulating hydrological processes and on declining soil properties because of the destructive forces of rainfall, which can provoke SOC flux, erosion, soil sealing, and crusting [13, 14, 15, 16]. Agroforestry systems are considered to have a higher potential to sequester atmospheric C because of their recognised ability for greater capture and utilization of growth resources such as light, nutrients, and water in comparison to single-species crop or grassland systems. The land use and plant cover strongly control C storage and its distribution within ecosystems, which is regulated by the nature of the vegetation, weather conditions, and physico-chemical properties of the soil [17, 18, 19]. The soil is able to maintain a potential C-storage equilibrium, which results from a balance between C inputs and losses [20]. However, this equilibrium can be upset by land-use change until a new equilibrium is attained in the new ecosystem. In this context, many authors support this contention, which states that the soil may behave either as a C source or sink, depending on the interaction among factors such as land use, cropping systems, and management practices [21, 22, 23]. According to Dumanski [24], agriculture and land-use changes annually contribute about 18-20% of the total human emissions of CO2. Thus, the objective of the present study was to evaluate the physico-chemical properties of the soil, especially organic C stocks in an agroforestry system and of potential changes in its content due to different land uses in a small Mediterranean watershed ― El Salado‖, Granada, (SE Spain).

2. MATERIAL AND METHODS 2.1. Watershed Description The study area is a mountainous watershed of 669.7 ha named ― El Salado‖ located in Sierra Nevada Mountains, Lanjaron, Granada (SE Spain). The elevations of the highest and

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lowest point are 670 m and 2,374 m above mean sea level, respectively, with an average slope exceeding 20% and showing features which are often found in mountain zones of the Mediterranean landscapes (Figure 1A). Figure 1B shows the representative land-use types (LUT), where most of the watershed is under hill forest and upland cultivation. Table 1 lists the dominant plant species in each land use within the watershed. The soils of the watershed have loamy, sandy-loam, and silt-loam textures, which are mapped with the main soil types in the watershed in Figure 1C. The area has a typical Mediterranean type of climate with a mean annual rainfall of 535 mm that is heaviest in autumn and winter, with frequent and intense short-duration storms in spring but rarely in summer, with 15.0 ºC for average annual temperature.

2.2. Sampling, Determination of Soil Properties, and Statistical Analysis

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Soil samples were taken to determine the physico-chemical soil properties. These samples were collected from representative plots of each LUT by taking samples from four randomly assigned sample points (0.20 m x 0.20 m) per sampling plot. Soil texture, bulk density, cation-exchange capacity (CEC), total nitrogen (N), and plant-available phosphorus (P) and potassium (K) were determined using standard methods for the examination of soils [25]. Soil pH was measured by using an electrode pH-meter on saturated soil paste (1:2.5). Soil organic carbon was evaluated using the Walkey and Black method [26]. All these determinations were made in samples from different soil depths (0.10, 0.25, and 0.50 m). A completely randomized design was used, with three replicates, to enable comparisons among selected LUTs. In particular, the amount of organic C stored in the soil was adjusted by soil mass and the stock at each depth and estimated with the following equation: C-stock (Mg ha-1) = A x BD x f C x D where, A is the area (ha); BD the soil bulk density (t m-3); f C the fraction of carbon, D the soil-layer thickness (m). The C stock at the different soil depths of each of the dominant LUTs of the watershed was estimated by multiplying the C content in each unit area by the area covered by a particular land use. Summation of C stocks in each horizon gave the C stock in each LUT of the watershed. In addition, the LUT dynamics were evaluated during 1878 to 2009, studying the relationships between these changes and soil properties in the study area. Analysis of variance (ANOVA) was performed in order to ascertain whether differences in organic C stock among the different LUTs. Differences between individual means were tested using the least significant difference test (LSD) at p < 0.05 using Statgraphics v. 5.1 package program. Also, correlation analysis among physico-chemical soil properties was made in order to evaluate its relationships.

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Figure 1. Altitude (A), dominant land use types (B), soil types (C) within the watershed in Lanjaron, Granada (SE, Spain). Soil Organic Matter: Ecology, Environmental Impact and Management : Ecology, Environmental Impact and Management, Nova Science

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3. RESULTS AND DISCUSSION 3.1. LUTs Dynamics during 1978-2009 Major land-cover changes within the watershed for 31 years are shown in Table 2. The area covered by forest diminished by some of 15.6% (3.4 ha yr-1), this decrease being attributable mainly to forest fires (1989, 1991, and 2005). A similarly decreasing trend in area took place for farmland, with about 16.0% (3.4 ha yr-1). This downward trend from 205.5 to 98.7 ha was due primarily to the abandonment of traditional rainfed crops (i.e. cereals, olive, and almond); also, the major part of almond area was transformed to olive orchards. In addition, during the recent decade, irrigated walnut and cherry orchards were established chiefly on terraces. Table 1. Main plant species for each land-use type (LUT) in the “Salado” watershed LUT Forest

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Rainfed farmland

Irrigated farmland Shrubland

Grassland / Pasture

Abandoned land

Dominant plant-cover types Areas covered with pine stands especially Aleppo and Scots pines among others (Pinus pinaster, Pinus nigra, Pinus pinea, etc.) that formed nearly closed canopies (60-85%). This category included planted forests, mixed with regenerating indigenous species of trees and shrubs: Quercus rotundifolia, Quercus ilex, Adenocarpus decorticans, Juniperus oxycedrus, Juniperus versicolor, Castanea sativa, Ruscus aculeatus, Salix cinerea, Populus alba or Populus nigra, among others. Areas with cultivated crop tree: olive (Olea europaea), almond (Prunus amygdalus), and grapevine (Vitis vinifera L.). For feeding livestock and wild partridges (hunting), especially annual species such as winter wheat (Triticum aestivum L.), oats (Avena sativa), barley (Hordeum vulgare L.), and legumes (Lens esculenta L.). Areas with irrigated tree crops such as walnut (Juglans regia L.), cherry (Prunus cerasus), olives, and horticultural species. Areas covered with shrubs, scrubs, and small trees, with little useful wood, mixed with some grasses: Ulex parviflorus, Genista sp., Adenocarpus decorticans, Brachipodium sp., Cytisus scoparius, Retama sphaerocarpa, Lavandula pedunculata, Halimium viscosum, Psoralea bituminosa, Carlina vulgaris, Dittrichia viscosa and Artemisia campestris. Some areas with aromatic and medicinal shrubs especially thyme (Thymus capitatus, Thymus baeticus Boiss., Thymus zygis), sage (Salvia officinalis L.), lavender (Lavandula stoechas) or rosemary (Rosmarinus officinalis L.). Dry grassy areas used for grazing (goat and sheep) dominated by Poaceae species and other herbaceous plants (non-woody): Festuca granatensis, Agrostis sp., Jurinea humilis, Dactylis sp., Bromus sp., etc., annual and perennial forbs (Stipa tenacissima, Brachypodium soides, etc.) combined with scrub and bare land that has very little or no plant cover (exposed rocks). Areas progressively recolonized with shrubs including herbaceous plants, Ulex parviflorus Pourret, Santolina chamaecyparissus L., Stipa tenacissima L., Phlomis purpurea L., Bromus sp., Dactylis glomerata and Thapsia villosa L.

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An extending trend within the watershed was determined for grassland/degraded land (abandoned land and grassland) and others (roads, firebreaks, and rocky outcrops) by 110.4 and 72.3 ha, respectively. Most of area under shrubland (257.2 ha) corresponds to burnt area; also due to fires (during 1989, 1991, and 2005) and drought years, a large part of rainfed tree crops was turned into shrubland and grassland. Table 2. Area occupied by the different land-use types and variations between 1978 and 2009 at “Salado” watershed Land-use type

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1

Shrubland Others1 Grassland/degraded land Farmland Forest Total watershed

2009 (ha) 257.2 82.2 119.6 98.7 112.0 669.7

(%) 38.4 12.3 17.9 14.7 16.7 100

1978 Area-percentage (ha) (%) 228.6 34.2 10.0 1.5 9.2 1.4 205.5 30.7 216.4 32.2 669.7 100

Change (ha) 28.6 72.3 110.4 -106.8 -104.4 --

(%) 4.3 10.8 16.5 -16.0 -15.6 --

Roads, firebreaks, and rocky outcrops.

Land-use changes are provoked by a number of natural and human impacts [27,28]. Natural impacts such as climate change are felt only over a long period of time, the effects of human activities (agriculture and fires) are immediate and often radical and detrimental until the natural equilibrium is recovered. However, this process over the time has a cost that affects mainly the quality of soil subjected to degradation processes. In this sense, according to Francia [29] and Durán [30] in this type of environment the greatest soil losses are associated with the slopes where the cover of rainfed tree crops (i.e., olive and almond) is discontinuous, and the abandonment of farmland generates significant increases in sediment production and mobilisation until the soil is covered by spontaneous vegetation. On the other hand, according to Trabaud and Lepart [31], fires undergone by Mediterranean ecosystems constitute a major recurring disturbance for the establishment of shrub communities, which are often nearly monospecific stands. Consequently, post-fire regeneration strategies lead to a fast re-colonization of the site by an auto-succession process where the shrubs perform a crucial function in the first stage of post-fire regeneration due to their high resilience as stated by Tárrega et al. [32]. In addition, various studies have analysed the vegetation successions in forest and shrublands after fire in the Mediterranean area [33,34,35], reporting a rapid recovery of vegetation to the pre-fire conditions. In this context, Calvo et al. [36] studied the recovery time of several shrub species after fire and concluded that most species reached their original cover after 4 years, though single species needed about 12 years to recover completely, where many annual species are restricted to early postfire successional stages. In addition, land-use change may be attributed to the change in the spatial location of land because due to abandoned farmland, deforestation or burning in certain zones might have converted the forest into shrubland. In agreement with other authors [37,38], the adaptation of forestland to farmland is known to deteriorate soil physical and chemical parameters, especially depressing soil organic matter and altering the distribution and stability of soil

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aggregates. Moreover, the uncontrolled harvesting in shrublands of native aromatic-medicinal species has negatively repercussions on the environment, baring the soil surface and lowering its fertility while exacerbating water erosion and compaction [39,40]. Land-cover oscillations especially those related to its degradation could influence organic C stocks, as only the plant cover is able to maintain and conserve the soil quality. Moreover, the conservation of native communities or the recovery of ecosystems with native shrub species can be an effective and sustainable measure for reducing the effects of soil degradation, and improving plant diversity and ecosystem resilience.

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3.2. Impact of LUTs on Soil Properties Table 3 shows the main soil properties under the LUTs studied. The soils under Aleppo pine had the highest amount of clay (155 g kg-1) and the lowest for shrubland (68.0 g kg-1). As stated by Lal [41] and Narain et al. [42], soil erosion normally increases with deforestation, leading to selective transport of clay particles by runoff. This is consistent with our findings, where clay content decreased in the soils lacking of vegetation cover (71.0 g kg-1), also the loss of clay was associated with the conversion of forest soils to other land uses [43,44]. The organic C values determined was significantly high under Aleppo pine (22.9 g kg-1), followed by Scots pine and shrubland, in contrast to farmland uses, the lowest content being found in abandoned land (6.7 g kg-1). A similar pattern was detected for N content and, in relation to plant-available P and K contents, but no major differences were found for any of the LUTs studied. The lowest soil bulk density of 0.91 and 1.0 Mg m-3 and the highest cationexchange capacity of 25.5 and 12.0 cmolC kg-1 were found for both pines Aleppo pine and Scots pine, respectively. It is well-known that organic matter helps to bind soil together, and therefore increases permeability for absorbing rainfall water and controlling soil erosion. Thus it is important to maintain and improve soil quality by preserving or augmenting the C stocks in soil. By contrast the export of organic C is expected to result in soil aggregates being easily broken down and the finer particles being transported by runoff. In this process the pine needles fell and decomposed underneath the trees, adding high amounts of organic matter, in contrast to the remaining LUTs. In this sense, Jeddi and Chaieb [45] reported the capability of forests with Aleppo pine for restoring soil quality by increasing organic C, total N, and soil-available P. The nitrogen-fixing tree species present in these forests presumably contributed to the higher N storage in the foliage that later falls as litter. The dense canopy cover and its role in increasing soil N could be credited with atmospheric N interception, as was contended by Prescott [46]. In addition, according to Rodríguez et al. [47], the C incorporation into soils was due to decomposition of plant litter in shrublands dominated by diverse plant species. The opposite trend was recorded in farmland with lower C contents presumably due to its export by watererosion process. The depletion of the organic C pool from farmland and abandoned soils can presumably be attributed to the following processes: 1) oxidation/mineralization due to breakdown of aggregates leading to exposure of C, 2) leaching and translocation as dissolved organic C or particulate organic C, and 3) accelerated soil erosion by runoff.

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Table 3. Soil characteristics for each land-use type (LUT) at 0.25 m soil depth Land use

Altitude (m)

Slope (%)

Sand (g kg-1)

Silt

Clay

SOC

TN

P K (mg kg-1)

pH

BD (Mg m-3)

Soil type

Forest - Aleppo pine

CEC (cmolC kg-1)

1,080

28 30 35

2.38 ± 0.08 0.64 ± 0.04 0.63 ± 0.04

4.4 ± 2 6.8 ± 3 5.8 ± 1

86.5 ± 19 70.4 ± 22 55.7 ± 25

6.2 ± 0.4 6.5 ± 0.3 7.7 ± 0.2

0.91 ± 0.03 1.04 ± 0.04 1.12 ± 0.05

II

1,480

22.9 ± 4 17.8 ± 6 13.5 ± 3

12.0 ± 5

Shrubland

155 ± 8 140 ± 8 68 ± 18

I

1,805

173 ± 21 320 ± 39 349 ± 22

25.5 ± 8

- Scots pine

672 ± 22 540 ± 28 583 ± 52

7.2 ± 3

II

1,480

35

10.0 ± 2 8.5 ± 5

33 35

II

1,400

25

1.16 ± 0.06 1.19 ± 0.04 1.17 ± 0.04 1.11 ± 0.06 1.27 ± 0.05

7.4 ± 3

Abandoned land

7.6 ± 0.5 7.5 ± 0.2 7.4 ± 0.1 7.9 ± 0.2 8.2 ± 0.3

IV

1,480

78.4 ± 31 90.4 ± 12 68.7 ± 26 60.8 ± 13 65.7 ± 18

15.8 ± 4

Grassland

6.3 ± 3 4.6 ± 1 6.4 ± 2 5.8 ± 3 4.1 ± 2

IV

920

0.60 ± 0.02 0.58 ± 0.02 0.45 ± 0.03 0.85 ± 0.07 0.58 ± 0.04

10.2 ± 4

- Almond trees

96 ± 10 133 ± 9 88 ± 12 97 ± 18 71 ± 21

III

26

250 ± 48 200 ± 17 215 ± 32 260 ± 42 224 ± 22

7.9 ± 2

830

654 ± 24 667 ± 31 697 ± 65 643 ± 33 705 ± 32

7.0 ± 5

III

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Farmland - Rainfed cereals - Olive trees

8.4 ± 2 9.6 ± 2 6.7 ± 3

± Standard deviation; SOC, soil organic carbon; TN, total nitrogen; BD, bulk density; CEC, cation-exchange capacity; I, Chromic cambisols; II, Haplic phaenozems; III, Eutric cambisols; IV, Eutric regosols [49].

t.com/lib/multco/detail.action?docID=3021482.

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Figure 2. Relationship among bulk density (BD) with soil organic carbon (SOC) (A), cation-exchange capacity (CEC) (B), and C:N ratio (C); and CEC and SOC (D). **, significant at p < 0.01.

Therefore, eroded soil in these LUTs contained considerably less C pool than uneroded by degradative processes (i.e. physical, chemical, and biological), which lowered biomass Soil Organic Matter: Ecology, Environmental Impact and Management : Ecology, Environmental Impact and Management, Nova Science

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production and the amount returned to the soil. Accordingly, soil C is rapidly lost by erosion and ploughing, enhancing soil C pool in an extremely slow process. The soil pH records in LUTs were within the range for normal plant-growth conditions. However, the higher soil pH determined in abandoned soils could be associated to low organic C and soil-water contents [48]. On the contrary, the pine litter has an acidifying effect on the soil, leading to slow decomposition and accumulation process on the forest floor. The variability in soil-bulk density among the LUTs is determined by the soil management, as the continual cultivation in farmland caused the structure to decline. However, the shrubland and grassland registered lower bulk-density values due to the minimal soil damage and because the vegetation adds organic matter, pores, and higher microbial population, all contributing to a healthier structure. In this sense, the forest soils recorded the lowest bulk density due to minimal disturbance, in agreement with the highest organic-C accumulationHajabbasi et al. [50] reported that deforestation and subsequent soil tillage (0.30 m soil depth) increased bulk density by 20% and decreased organic C by 50%. According to Dunjo et al. [51] soil tillage in farmland enhances the degradation of organic matter. Figure 2 shows the significant relationships among soil physico-chemical parameters. Significant negative correlations were found for bulk density with soil organic C (r = - 0.81), CEC (r = - 0.64), and C:N ratio (r = - 0.57). And CEC was correlated positively with organic C (r = 0.85). In agreement with results by several studies the soil bulk density was negatively correlated with SOC [4,50,52]. Therefore, a different degree of soil compaction among land uses due to management, ranging from a minimum under forest to a maximum in soil under cultivation and abandoned land, contributed to this relationship. The organic matter itself encourages soil resistance to compaction by many mechanisms such as strengthening of binding forces among particles and aggregates, and higher elasticity of aggregates under compression, which promotes a higher porosity with lower soil bulk density [53]. The high correlation of SOC with CEC (r = 0.85) indicate that soil organic matter contributed to boost soil CEC and available plant nutrient retention under forest in comparison with farmlands. A similarly high relationship between CEC and organic C (r = 0.96) has been reported by Syers et al. [54] for sandy soils as well as for other soil textures [55,56]. Our results (y = 0.089 x - 0.250, r = 0.788) are consistent with the earlier studies reporting that organic C and total N are strongly correlated [57,58,59]. On the other hand, the average soil C:N ratio for Scots pine, shrubland, almond, cereals, and olive was of 27.8, 21.4, 18.7, 16.7, and 14.7, respectively, contrasting with Aleppo pine, grassland, and abandoned land abandoned of 9.6, 11.3, and 11.6, respectively. A C:N ratio above 12-14 is considered indicative of a shortage of N in the soil, and the higher values in our study area could be related to a lower clay content in soils (< 100 g kg-1) [60]. In general, the spatial variability of organic C and total nitrogen was significant due to the effect of plant cover type, land use and management, and soil farming practices such as incorporation of crop residues into soil. These findings suggest that the land use under farmland and abandoned land in mountain areas degraded the soil properties, causing greater susceptibility to erosion. Overall, the soil health of LUTs follows the order: forest, shrubland, grassland, farmland, and abandoned land.

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121

C-stock (Mg ha-1) 120

a a

-1

SOC (Mg ha )

100

a

80 60

b

40 20 0 Aleppo pine 70

a

60

Scots pine

Shrubland

ab

ab

Cereals

Olive

Abandoned land

ab

-1

SOC (Mg ha )

50 40 30 20

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10 0 Grassland

Almond

Figure 3. Average soil organic carbon stock at 0.5 m depth under different LUTs. Vertical bars represent standard deviation; Different letters are statistically different by LSD analysis at p < 0.05.

3.3. Soil Organic Carbon Stocks under LUTs Figure 3 shows the weighted average of organic C stocks at 0.5 m depth for all LUTs in the watershed, being significantly highest for forest in relation to the remaining land uses, in concrete for Aleppo pine, Scots pine, shrubland, grassland, cereals, olive, almond, and abandoned land of 99.6, 83.3, 72.2, 63.2, 53.4, 50.8, 48.9, and 27.5 Mg ha-1, respectively. These findings demonstrated that C pools are highly vulnerable to significant land-use changes. Therefore, oxidation of organic C resulting in a release of CO2 into the atmosphere took place as a result of land-use changes, which affects not only the overall C balance, but also soil fertility. In addition, the results clearly suggested that soil beneath the pines and shrubland create fertility where C contents are greater with lower bulk densities. This promotes the stability of soil aggregates and under this condition the rainfall water infiltration increases, significantly reducing the runoff and soil erosion, and thereby enhancing the

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hydrological functioning of this type of environment. In this context, Janssens et al. [61] for Belgian forest with Scots pine stands reported higher values for C stored in soils (114.7 Mg ha-1), which is expected due to the climate conditions. In agreement with Pérez et al. [62] the soil C stocks of native and afforested arid Mediterranean shrubland amounted to 32.4 and 19.8 Mg ha-1, respectively, which is lower than those in the present experiment under semiarid conditions. The decreasing trend in SOC stocks for cultivated soils, compared to forest, shrubland, and pasture soils was of 62, 34, and 6%, respectively. In this context, Celik [4] reported a similar reduction trend in organic C for farmland in relation to forest and pasture soils by 44 and 48%, respectively. In this context, the land-use conversion from farmland to shrubland, or grassland, could have contributed to boost the SOC storage and sequestration, and consequently the improvement of soil nutrients [63]. SOC (Mg ha-1) 300

Forest-shrubland system

250

r = - 0.710**

200 150 100

A

50 0 Copyright © 2012. Nova Science Publishers, Incorporated. All rights reserved.

0

500

1000

1500

2000

2500

Altitude (m a.s.l.)

80

Agricultural system

70

r = 0.684**

60 50 40 30

B

20 10 0 0

200

400

600

800

1000

1200

1400

1600

1800

Altitude (m a.s.l.)

Figure 4. Relationship between soil organic carbon (SOC) and altitude in a forest-scrubland system (A), and in agricultural system (B). **, significant at p < 0.01.

The low SOC contents, such as those measured under farmland (8.9 g kg-1) and abandoned land (6.7 g kg-1), are generally indicative of soil degradation; according to the Soil Organic Matter: Ecology, Environmental Impact and Management : Ecology, Environmental Impact and Management, Nova Science

Soil Organic Carbon Stocks ...

123

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Commission of the European Communities [64], soils with less than 10 g kg -1 (~ 1.7% organic matter) are considered to be in a stage of pre-desertification. Afforestation can increase C influx through a higher and more efficient use of resources for primary production by improving soil fertility [65]. That is, the deep root distribution of trees can allow the absorption of soil water at depths not reached by the existing shrubland and grassland plant species. The changes in soil-surface conditions are related in this study to a contribution of organic matter by the leaves and roots of both annual and perennial species inhabiting the vegetation patches especially in abandoned soils, where a slowly and progressive process of plant succession took place. This suggests that the ground and canopy cover in grassland and shrubland besides attenuating the erosive forces of the rainfall and runoff could be considered as the main precursor in maintaining and minimizing the export of organic C from their soils. The exhaustion of the C stock is ascribed to various circumstances such as: decrease in the amount biomass returned to the soil, change in soil-water content, and temperature regimes which underline the decomposition of organic matter, differences in the C:N ratio, tillage, decrease in soil aggregation, and increase in soil erosion. Accordingly, farmland soils and especially eroded agricultural soils usually hold lower C stock than their potential capacity, as was recorded in olive, almond, and cereal soils. In this sense, Martínez et al. [66] pointed out that the contribution of soil erosion to total C soil losses in the abandoned lands was lower than those recorded in olive orchards, the labile organic C fraction being lost from soil in the cultivated area was due mainly to the impact of cultivation (low biomass production and residue return with high C mineralization) rather than to water erosion. Abandoned land 6%

Grassland 13%

[ 27.5 ]

Forest 36%

[ 63.2 ]

[ 182.9 ]

Shrubland 14% [ 72.2 ]

Farmland 31% [ 153.1 ] Figure 5. Percentage distribution of soil organic C stocks under different land uses at ― Salado‖ watershed. Values in brackets are Mg of C per hectare.

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Víctor H. D. Zuazo, José R. F. Martínez, Iván G. Tejero et al.

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Figure 6. Spatial and potential C storage in soils (A) and total nitrogen (B) under different LUTs within the ― Salado‖ watershed in Lanjaron, Granada (SE, Spain)

Abandoned farmland soils have lower organic C stock than their real potential capacity, the smaller amounts of organic C evidencing the consequences of its conversion from forest or farmland as well as after fire. Under these conditions the soil organic C is depleted by erosion, although, the soil C sequestration as a result of progressive plant recolonization may not contribute much to C budgets in a short-term period. Thus, the natural and progressive succession of abandoned land by spontaneous native species, appropriate soil-management systems in farmland (i.e. no-tillage, reduced tillage, plant strips, etc.), and management of forestland and scrubland can enhance the organic C stock through C sequestration. The estimated soil C stock in studied LUTs are close to those reported by other authors in mountain agroecosystems of south-eastern Spain of reforested pine stands < 60 years old (Aleppo pine), shrubs (shrubland), and crops (almond, olive, and cereals) of 72.5, 64.7, and 51.8 Mg ha-1, respectively [67]. On the other hand, the SOC in forest-shrubland system was inversely correlated (r = 0.71) with altitude (Figure 4A), but positively (r = 0.68) with agricultural system (Figure 4B). The relationship between SOC and altitude has also been studied by Sánchez [67] and Sims and Nielsen [69], who reported a positive correlation, presumably due to the influence of elevation on rainfall. In addition, Martin et al. [19] reported the significant influence of altitude and climate rather than vegetation type or landform at higher altitudes (>1700 m a.s.l.) more than at lower altitudes (900-1700 m a.s.l), and higher C storage was estimated in soils under oak forests as compared to those under pine forests having similar altitudes. This suggests that the variation in the amounts of SOC is explained by the climate, or is due to the influence of predominant stands and plant species related to an altitudinal gradient. Sakrabani and Hollis [70] reported that the amounts of C stocks are dynamic in nature and respond to

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changes in land use, land-use management, and climate. According our results C storage in the soil depends heavily on physical attributes (i.e. climate, altitude, and LUTs). Overall, in terms of land use, the C storage in soil were in order of Forest > Farmland > Shrubland > Grassland > Abandoned land (Figure 5). Figure 6 shows the spatial maps of potential organic C and total N storage by soils with the most representative LUTs in the agroforestry watershed. This information can be used to design and implement effective measures in terms of land-use change as well as soil and water conservation, based on the quantitative spatial variability of SOC associated with land use and soil types. Clearly, the areas where the C stocks are low (farmlands), is where soil-C sequestration could be maximized by adopting sustainable soil-management techniques. The finding of the present study denotes that the C storage in the soil is highly dependent on physical attributes such as vegetation type, physiographic position, and altitude within the watershed. The higher organic C stock under forest suggests the low rate of organic-matter mineralization and favourable conditions for higher C sequestration. After transformation from forest to other uses, soil-C content sharply decreases and C flux relative to storage increases. Thus, global food security is closely related to high soil quality, which depends on an adequate level of soil organic C, so that its sequestration in agricultural soils is key in the environmental context, raising soil quality and agronomic productivity, improving water quality, and diminishing the risks of accelerating the greenhouse effect.

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CONCLUSION The present study has shown the importance of the impact of land-use types on SOC storage, and its close relationship with the degree of plant coverage. Higher potential risk of soil erosion was found in abandoned lands and farmlands, which are characterized by low plant and ground cover. Similarly, but with lesser risk of loss of organic carbon by soil erosion in shrubland and grassland, with higher plant diversity. In particular, the conventional tillage on sloping lands with rainfed tree crops (olive and almond) promoted substantial soil degradation. On the contrary, the forest can unequivocally protect the soils with its dense canopy structure, which more effectively reduced rainfall erosivity. Therefore, land-use change from forest to farmland significantly reduced the organic C accumulation in soil. The findings suggest that Aleppo and Scots pines are able to store and sequester the organic C in soils, explaining the relative role of climate over vegetation on C stocks at higher altitudes and that of vegetation type and physiographic situation at lower altitudes. Suitable soil organic carbon storage and sequestration especially in agricultural soils demands a permanent change in management, with implementation techniques adjusted to local soil, climate, and management features in order to maximize the C-sequestering potential or to maintain C stocks. Thus, agroforestry systems need to understand the intricacies in C budgeting and its maintenance in soils, and adopt sustainable land-use measures that yield significant ecosystem C gains under a given type of environment.

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ACKNOWLEDGMENTS The research work that leads to this publication was sponsored by following research project ― Hydrological and erosive processes, biomass assessment, and organic carbon sequestering under different land uses in the Mediterranean agrarian watershed El Salado, Lanjaron‖ (SE Spain) (RTA2007-00008-00-00) granted by INIA, Spain and cofinanced by FEDER funds (European Union). Also the authors thanks to the Direction of Natural and National Park of Sierra Nevada for infrastructure and reliable support.

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[46] Prescott, CE. (2002). The influence of the forest canopy on nutrient cycling. Tree Physiology 22, 1193-1200. [47] Rodríguez, PCR.; Durán, ZVH; Muriel, FJL; Peinado, MFJ; Franco, TD. (2009). Litter decomposition and nitrogen release in a sloping Mediterranean subtropical agroecosystem on the coast of Granada (SE, Spain): Effects of floristic and topographic alteration on the slope. Agric. Ecosyst. Environ. 134, 79-88. [48] Rezaei, SA; Gilkes, RJ. (2005). The effects of landscape attributes and plant community on soil chemical properties in Rangelands. Geoderma 125, 167-176. [49] FAO, (1998). World Reference Base for Soil Resources. World Soil Resources Report 84. Rome, Italy. [50] Hajabbasi, MA; Lalalian, A; Karimzadeh, HR.. (1997). Deforestation effects on soil physical and chemical properties, Lordegan, Iran. Plant Soil 190, 301-308. [51] Dunjo, G; Pardini, G; Gispert, M. (2003). Land use change effects on abandoned terraced soil in a Mediterrian catchment, NE Spain. Catena 52, 23-37. [52] Abbasi, MK; Rasool, G. (2005). Effects of different land use types on soil quality in the hilly area of Rawalakot Azad Jammu and Kashmir. Acta Agriculturae Scandinavica, Section B-Plant Soil Science 55, 221-228. [53] Soane, BD. (1990). The role of organic matter in soil compactibility: a review of some practical aspects. Soil and Tillage Research 16, 179-201. [54] Syers, JK; Campbell, AD; Walker, TW. (1970). Contribution of organic carbon and clay to cation exchange capacity in chronosequence of sandy soils. Plant and Soil 33, 104-112. [55] Saikh, H; Varadachari, C; Ghosh, K. (1998). Effects of deforestation and cultivation on soil CEC and contents of exchangeable bases: A case study in Simlipal National Park, India. Plant and Soil 204, 175-181. [56] Oorts, K; Vanlauwe, B; Cofie, O; Sanginga, N; Merckx, R. (2000). Charge characteristics of soil organic matter fractions in a Ferric Lixisol under some multipurpose trees. Agroforestry Systems 48, 169-188. [57] Bationo, A; Buerkert, A. (2001). Soil organic carbon management for sustainable land use in Sudano-Sahelian West Africa. Nutr. Cycl. Agroecosys. 61, 131-142. [58] Yimer, F; Ledin, S; Abdelkadir, A. (2006). Soil organic carbon and total nitrogen stocks as affected by topographic aspect and vegetation in the Bale Mountains, Ethiopia. Geoderma 135, 335-344. [59] Moges, A; Holden, NM. (2008). Soil fertility in relation to hillslope position and agricultural land use: a case study of Umbulo Catchment in southern Ethiopia. Environ. Manage. 42, 753-763. [60] Vejre, H; Callesen, I; Vesterdal, L; Raulund, RK. (2003). Carbon and nitrogen in Danish forest soils—contents and distribution determined by soil order. Soil Sci. Soc. Am. J. 67, 335-343. [61] Janssens, IA; Sampson, DA; Cermak, J; Meiresonne, L; Riguzzi, F; Overloop, S; Ceulemans, R. (1999). Above- and belowground phytomass and carbon storage in a Belgian Scots pine stand. Ann. For. Sci. 56, 81-90. [62] Pérez, QJF; Delpiano, CA; Snyder, KA; Johnson, DA.; Franck, N. (2011). Carbon pools in an arid shrubland in Chile under natural and afforested conditions. J. Arid Environ. 75, 29-37.

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[63] Liu, X; Li, FM; Liu, DQ; Sun, GJ. (2010). Soil organic carbon, carbon fractions and nutrients as affected by land use in semi-arid region of Loess Plateau of China. Pedosphere 20, 146-152. [64] Commission of the European Communities. (2002). Towards a Thematic Strategy for Soil Protection. COM 179 final, Brussels, Belgium. [65] Fernández, OE; Rojo, SL; Jiménez, NM; Navarro, BF; Díez, M; Martín, F; Fernández, J; Martínez, FJ; Roca, A; Aguilar, J. (2010). Afforestation improves soil fertility in south-eastern Spain. Eur. J. Forest Res. 129, 707-717. [66] Martínez, MM; Lopez, J; Almagro, M; Boix, FC; Albaladejo, J. (2008). Effect of water erosion and cultivation on the soil carbon stock in a semiarid area of South-East Spain. Soil and Tillage Research 1, 119-129. [67] Miralles, I; Ortiga, R; Almendros, G; Sánchez, MM; Soriano, M. (2009). Soil quality and organic carbon ratios in mountain agroecosystems of South-east Spain. Geoderma 150, 120-128. [68] Sánchez, B. (1969). Relaciones cuantitativas entre la altitud, la acidez, y la material orgánica en suelos cultivados. An. Edafol. Agrobiol. 28, 355-365. [69] Sims, ZR; Nielsen, GA. (1986). Organic carbon in Montana soils as related to clay content and climate. Soil Sci. Soc. Am. J. 50, 1269-1271. [70] Sakrabani, R; Hollis, J. (2006). Predicting changes in soil organic carbon in different land uses for England and Wales under current and future climatic conditions using CENTURY 5. In: Abstracts 18th World Congress of Soil Science. International Union of Soil Sciences (IUSS), USA, Synthesis, Modeling, and Applications of Disciplinary Soil Science Knowledge for Soil-Water-Plant-Environment Systems Paper 70-5.

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Chapter 6

EFFECTS OF SOIL ORGANIC MATTER ON THE TRANSPORT OF NON- AQUEOUS PHASE LIQUID IN SOILS Junko Nishiwaki*,1, Yoshishige Kawabe2, Yasuhide Sakamoto2, Takeshi Komai2 and Ming Zhang2 1

2

Ibaraki University, 3-21-1, Chuo, Ami-cho, Inashiki-gun, Ibaraki, Japan National Institute of Advanced Industrial Science and Technology, Onogawa, Tsukuba, Ibaraki, Japan

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ABSTRACT Understanding the transport and fate of gasoline components in soils is of fundamental importance for protecting human health from possible risks. A series of column experiments were performed to investigate the effects of soil organic matter, on the transport of total petroleum hydrocarbons (TPH) and the paraffin (n-paraffin and isoparaffin), olefin, naphthene, and aromatic (PONA) components in 2 typical Japanese soils. The results of this study illustrated the following observations: 1) The remaining mass of regular gasoline in a soil is time-dependent. 2) The major degradation mechanism of regular gasoline in soils would be volatilization. 3) The sorption of regular gasoline by soil organic matter might be one of the major reasons that causes regular gasoline remaining in Kuroboku soil. 4) Aromatic and isoparrafine components are tended to remain in soils.

Keywords: Gasoline, total petroleum hydrocarbon, PONA components, soil type, soil organic matter

*

E-mail: [email protected]; Tel. & Fax: +81-29-888-8591.

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INTRODUCTION Petroleum hydrocarbons are one of the major contaminants that may cause groundwater and soil pollution. With increased awareness of the risks to human health associated with oil pollution, the Ministry of the Environment, Japan, issued guidelines for the investigation of oil contaminations and to address the assessment of risk of oil contamination, including gasoline, in 2006 (Central Council for Environment, Japan, 2006). Gasoline is a mixture of multiple hydrocarbons. Its behavior in soils is very complicated and difficult to predict because many factors related to the physicochemical properties of soil, gasoline itself, and environmental conditions may affect transport and degradation of gasoline in soils (e.g., Gidda et al. 1999). In addition, different components are known to have different risks to human health (Edwards et al. 1997). It is necessary to understand the fate of gasoline or make a risk assessment for protecting human health from possible risks. However, the knowledge associated with the transport or fate of gasoline in soils is very limited. Volatilization is an important behavior of gasoline that may determine the transport of gasoline components in soils, the reduction of gasoline concentration in soils, selection of an appropriate technology for remediation, and/or assessment of environmental risks. A Pprevious study by Nishiwaki et al. (2011) showed that volatilization is influenced by the content of soil organic matter, but the experiments were performed by a simple setup. Although there also have been a number of other studies on volatilization of gasoline in soils, they were very limited in scope (Johnson and Perott, 1990; Donaldson et al., 1992; Arthurs et al., 1995; Gidda et al., 1999; Galin et al., 1990; Fine and Yaron, 1993; Jarsjö et al., 1994; Spencer et al. 1982). To obtain additional experimental data that may provide insight into the fate of regular gasoline in soils, especially those containing soil organic matter, a series of column experiments were performed. This paper presents some preliminary results obtained from our new experimental studies.

MATERIALS AND METHODS Materials In this study, a commercially available regular gasoline (RG) with a specific gravity of 0.73 g/mL was used as the mineral oil contaminant. Characterization of the chemical composition was performed in advance by gas chromatographic (GC) analysis and indicated that this RG contained more than 100 types of hydrocarbon with carbon numbers from 4 to 13. The weight percentages of the paraffin (n-paraffin and isoparaffin), olefin, naphthene, and aromatic (PONA) fractions within the RG are summarized in Table 1. Table 1. Fractions of PONA components within regular gasoline Table 1 Fractions of PONA components within regular gasoline (100 L of RG dissolved into 50 mL of CS2) PONA wt%

n-Paraffin Isoparaffin 9.21

28.47

Olefin 19.33

Naphthene Aromatic 5.22

37.77

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Two types of typical Japanese soils were used for the experiments. Toyoura standard sand (d50=106 m) was used as a typical sandy soil with very little organic matter. Kuroboku soil is a top soil that exists near the ground surface and is rich in organic matter. Kuroboku soil was sieved and sorted with a 2-mm screen. The contents of soil organic matter in Toyoura standard sand and Kuroboku soil were analyzed in advance to be 0.36% and 21.63%, respectively, by the method proposed by Nakano et al. (1995). The soils were air dried within the laboratory at room temperature for one month prior to the experiments.

Experimental Setup and Preparation Procedure

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To investigate a set of basic, but fundamentally important volatilization properties of gasoline from unsaturated soils, a column experimental setup was developed and used (Figure 1). The column can be dismantled into ten short rings having 50mm in depth by 85 mm in inner diameter. A fine, stainless steel wire mesh screen was set at the bottom of the column to prevent soils from effluence. One short ring was equipped with an oil inlet and fine, stainless steel wire mesh screen for injecting oil into the soil sample uniformly. The oil inlet was set at 175 mm in depth from the top of column.

Figure 1 Experimental setup.

In each experiment, the column was filled with the soil to be tested with a given volumetric water contentabout 11%. The porosities of Toyoura sand and Kuroboku soil filled in the column were 38% and 66%, respectively. The column was then set into a temperaturecontrolled room at 15° Cover night for temperature homogenization. A300 mL of RG was injected into the column using a pump at a constant flow rate of 10 mL min-1 from the oil inlet. After that, the top of the column was opened for a given time period for volatilization. The column was finally dismantled into 10 short rings and the residuals within the soil

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samples in individual rings were then extracted and analyzed with the procedures described below.

Extraction and Analysis Procedures The residual concentrations of total petroleum hydrocarbons (TPH) and individual PONA components within the soil samples were extracted and analyzed at different time steps with the procedures similar to those used in our previous study (Nishiwaki et al., 2011). TPH (mg/kg) 0

5000

10000

15000

20000

0

Depth (mm)

100

200

300

0 day 2 days 5 days 7 days 10 days 30 days

400

500

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Figure 2. Time-dependent variations of TPH remaining in Toyoura sand.

Anhydrous sodium sulfate and carbon disulfide (CS2) were used to dehydrate the gasoline and to extract the gasoline components in soil samples, respectively. Anhydrous sodium sulfate (30 g) was first added to the vial for dehydration. CS2 was then added to the vial, which was subsequently shaken for 5 minutes to extract the gasoline components. The vial was left to stand for 15 minutes and the supernatant was collected. This extraction process was repeated 3 times, and the total volume of extracted solution was finally adjusted to 50 mL by directly adding CS2 into the extracted solution. Analyses of the TPH and PONA components were performed using GC-2014 and GC2010 (Shimadzu Co.), respectively. Aliquots of 1 L of the extracted solution were used for GC analyses.

RESULTS AND DISCUSSION Concentrations of TPH and PONA components remaining in samples were all timedependent. The results of time-dependent variations of TPH remaining in Toyoura sand are illustrated in Figure 2. It seems that the injected RG (injection port level is 175 mm below the top) sank first towards the lower direction in the unsaturated soil sample, and then volatilized and dispersed in shallower depth. The sink of RG in unsaturated soil is due to the

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gravitational force, and dispersion of RG in shallow depth is considered mainly due to volatilization, because gasoline is highly volatile and the top of the column was opened. Concentrations of TPH remaining in different depths within different soils after 30 day sare illustrated in Figure 3. The concentrations of residual RG remaining in Kuroboku soil were much higher than those remaining in Toyoura sand. Such a difference may due to the differences in air permeability between the two soils that may directly affect the rate of volatilization, and differences in soil organic matter that may absorb petroleum hydrocarbons and decay the rate of volatilization. Although air permeability is not a simple function of porosity, the porosity of Kuroboku soil (66%) was higher than that of Toyoura sand (38%). A Pprevious study using batch experiments by Nishiwaki et al. (2011) also illustrated that soil organic matter had a relatively significant effect on the volatilization of gasoline from unsaturated soils.

Figure 3. TPH remaininged in each soil column after 30 days.

Figure 4. PONA component remaininged in Toyourasand after 30 days. Soil Organic Matter: Ecology, Environmental Impact and Management : Ecology, Environmental Impact and Management, Nova Science

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Figure 5. PONA component remaininged in Kuroboku soil after 30 days.

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Concentration distributions of PONA components in different depths after 30 days from the start of experiments using Toyoura sand and Kuroboku soil are illustrated in Figure 4 and Figure 5, respectively. These figures show that aromatic components are easily remain in both soils, especially in Kuroboku soil. In addition, isoparaffin is also tended to remain in soils compared to the other 3 components. The concentrations of n-paraffin, olefin and naphthene remaininged in both Toyoura sand and Kuroboku soil are very low compared to the residual concentrations of aromatic and isoparaffin components remaining in Kuroboku soil and, the effects of both the type of hydrocarbon component and soil organic matter could be more significant compared to air permeability of the soils.

CONCLUSION Understanding the fate of gasoline in soils is of fundamental importance for the evaluation of contaminant transport within soils, the design of strategies for effective remediation, and assessment of possible risks to human health. In this study, a series of column experiments were performed to investigate the fate of TPH and PONA components in soils. The results obtained in this study can be summarized as follows: 1. The remaining mass, or concentration, of RG in unsaturated soils is time-dependent. 2. The major mechanism for the decrease of concentration of RG in unsaturated soils would be volatilization. 3. The sorption of RGby soil organic matter might be one of the main reasons for the RG remaining in soils. 4. Compared to other components, aromatic and isoparrafine components are tended to remain in soils. Further detailed studies are required to obtain a better understanding of the correlation between the soil organic matter and remaining tendency of RG in soils.

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ACKNOWLEDGMENTS The authors wish to acknowledge the financial support of the Ministry of the Environment, Japan. We are also grateful to Ms. Keiko Ogawa of AIST, Japan, for her assistance with experiments and analyses.

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REFERENCES Arthurs P, Stiver W H, Zytner R G (1995) Passive volatilization of gasoline from soil. J Soil Contam 4: 123-135. Central Council for Environment, Japan (2006) A Guideline for Countermeasures of Soil Oil Pollution. pp.220 (In Japanese). Donaldson S G, Miller G C, Miller W W (1992) Remediation of gasoline-contaminated soil by passive volatilization. J Environ Qual 21: 94-102. EdwardsD A, AndriotMD, AmorusoMA, TummeyAC, BevanCJ, Tveit A, HayesLA, YoungrenSH, NaklesDV (1997) Total Petroleum Hydrocarbon Criteria Working Group Series Vol. 4 Development of Fraction Specific Reference Doses (RfDs) and Reference Concentrations (RfCs) for Total Petroleum Hydrocarbons (TPH). Amherst Scientific Publishers. Fine P, Yaron B (1993) Outdoor experiments on enhanced volatilization by venting of kerosene component from soil. J Contam Hydrol 12: 355-374. Galin T, McDowell C, Yaron B (1990) The effect of volatization on the mass flow of a nonaqueous pollutant liquid mixture in an inert porous medium: experiments with kerosene. J Soil Sci 41: 631-641. Gidda T, Stiver W H, Zytner R G (1999) Passive volatilization behavior of gasoline in unsaturated soils. J Contam Hydro 39: 137-159. Jarsjö J, Destouni G, Yaron B (1994) Retention and volatilization of kerosene: laboratory experiments on glacial and post-glacial soils. J Contam Hydro 17: 167-185. Johnson R L, Perott M (1990) Gasoline vapor transport through a high-water-content soil. J Contam Hydrol 8: 317-334. Nakano M, Miyazaki T, Shiozawa S, Nishimura T (1995) Methodologies for Measuring Soil Environments, The University of Tokyo Press, pp 59-60. Nishiwaki J, Kawabe Y, Sakamoto Y, Komai T, Zhang M (2011) Volatilization properties of gasoline components in soils, Environmental Earth Sciences 63(1): 87-95. Spencer W F, Farmer W J, Jury W A (1982) Behavior of organic chemicals at soil, air, water interfaces as related to predicting the transport and volatilization of organic pollutants. Environ Toxicol Chem 1: 17-26.

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INDEX

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A accessibility, 51, 90 accounting, ix, 89 acid, 58, 92, 93, 98, 102, 103, 104, 107, 108 acidity, 95 activity of soil organisms, vii, 1, 22 AD, 129 adaptation, 31, 49, 116 adsorption, 90, 93 adverse effects, 51 Africa, 60, 61, 126 age, 50, 73, 74, 75, 76, 86 aggregate formation, vii, 1 aggregation, 10, 36, 45, 123 agrichemicals, vii, 1 agriculture, viii, 2, 3, 7, 8, 29, 31, 36, 39, 40, 42, 49, 57, 59, 60, 65, 73, 77, 84, 87, 112, 116, 127, 128 air quality, 26 air temperature, ix, 52, 56, 64, 76, 79 alcohols, 94 aldehydes, 99 alfalfa, 18, 19, 25 aliphatic compounds, 34 alkalinity, 58 ambient air, 94 amine, 97 amine group, 97 annual rate, 24 ANOVA, 113 appropriate technology, 132 aquatic systems, 51 Argentina, 17, 46, 58 aromatic compounds, 14, 103 aromatics, 103 Asia, 86 assessment, 33, 34, 54, 107, 126, 132, 136 assimilation, 55

atmosphere, viii, x, 3, 4, 6, 8, 9, 15, 17, 19, 39, 41, 43, 45, 49, 80, 83, 112, 121 awareness, 132 B base, 8 beef, 26 beetles, 27 Belgium, 87, 130 bending, 102 beneficial effect, viii, 40, 49 benefits, viii, 10, 16, 25, 26, 40, 46 benzene, 99 biodegradation, 90 biodiesel, 25 biodiversity, 8, 26, 34, 82, 83, 88 bioenergy, 2 biofuel, 8, 15 biological activity, 14 biological processes, 2, 18, 50 biomass, vii, viii, ix, 1, 2, 4, 5, 6, 14, 15, 17, 31, 40, 41, 42, 44, 47, 48, 49, 50, 51, 52, 53, 54, 56, 57, 58, 60, 61, 62, 83, 89, 92, 101, 104, 106, 120, 123, 126, 128 biomolecules, 93 biotic, 60 bonds, 102 Brazil, v, vii, 1, 2, 3, 7, 8, 9, 10, 11, 12, 13, 15, 16, 17, 19, 21, 24, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 55 breakdown, 43, 45, 119 buffer capacity, vii, 1 bulk density, vii, viii, 1, 21, 39, 40, 43, 57, 66, 68, 113, 117, 118, 119, 120 burn, 6, 34

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140

Index

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C Ca2+, 52 cadmium, 108 calcium, 11 carbohydrate, 57, 93, 102, 103 carbohydrates, ix, 89, 101, 103, 104 carbon dioxide, 2, 8, 15, 40, 45, 53, 57, 60, 71, 88 carbon emissions, 4, 7, 32, 127 carbonyl groups, 97, 98 carboxyl, 94, 102, 104, 106 carboxylic acid, 99, 102 carboxylic acids, 99, 102 carboxylic groups, 14, 104 case study, ix, 56, 64, 129 cation, vii, 1, 11, 22, 113, 117, 118, 119, 129 cattle, 26, 46 C-C, 15, 94 CEC, 113, 118, 119, 120, 129 cellulose, 10, 103 challenges, 60 chemical, ix, 2, 6, 11, 15, 17, 18, 41, 47, 48, 50, 52, 56, 57, 58, 59, 61, 73, 90, 93, 94, 106, 107, 109, 111, 112, 113, 114, 116, 120, 128, 129, 132 chemical characteristics, 6, 90 chemical interaction, 18 chemical properties, 56, 58, 112, 129 chemicals, 17 Chile, 53, 58, 129 China, 16, 55, 56, 59, 61, 70, 71, 80, 82, 87, 127, 130 chromatography, 106 cities, 26 classification, 42, 59, 67, 84 clay minerals, 34 climate, viii, ix, 2, 3, 36, 39, 42, 50, 59, 66, 83, 86, 87, 90, 108, 111, 113, 116, 122, 124, 125, 127, 130 climate change, ix, 2, 3, 86, 90, 111, 116, 127 climates, viii, 40, 47 C-N, 94 CO2, viii, 2, 7, 8, 9, 13, 14, 15, 17, 18, 19, 25, 32, 34, 39, 40, 41, 45, 46, 47, 48, 49, 52, 53, 54, 55, 57, 59, 64, 83, 86, 87, 110, 112, 121, 127 coefficient of variation, 68 coffee, 25 colonization, 5, 105, 116 color, vii, 1, 72 combined effect, 48 combustion, 9, 15 communities, 116, 117, 128 community, 22, 92, 128, 129 compaction, 7, 117, 120 complexity, 3

composition, ix, 17, 18, 83, 89, 90, 91, 95, 106, 107, 108, 110, 132 compost, viii, 40, 45, 48, 57, 91 composting, 105, 107, 108, 110 compounds, 13, 48, 52, 90, 97, 99, 103, 104 compression, 120 conceptual model, 41 condensation, 14 confinement, 26 congress, 84 CONGRESS, 36, 85, 86, 130 conservation, vii, 1, 3, 8, 10, 19, 33, 34, 43, 45, 46, 54, 57, 58, 80, 82, 83, 85, 88, 112, 117, 125, 126, 127, 128 consumption, 8, 82 contact time, 94 contaminant, 132, 136 contaminated soil, 137 contamination, 132 controversial, 49 Conventional tillage (CT), viii, 39 COOH, 97 cooling, 42 copper, 108 correction factors, 7 correlation, 12, 76, 114, 120, 136 correlation analysis, 114 correlations, 120 cost, 6, 9, 90, 116 Costa Rica, 22 cotton, 25, 45, 52, 60 covering, 67 crop, vii, viii, ix, 2, 7, 8, 9, 10, 13, 14, 15, 16, 17, 18, 19, 23, 24, 25, 26, 28, 31, 32, 33, 35, 37, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 53, 54, 55, 56, 57, 58, 60, 61, 64, 65, 73, 80, 84, 106, 108, 112, 115, 120, 128 crop production, vii, viii, 26, 39 crop residue, viii, ix, 14, 17, 18, 23, 28, 35, 39, 40, 41, 42, 43, 44, 45, 46, 49, 53, 54, 64, 65, 73, 81, 84, 120 crop rotations, 17, 23, 25, 47, 54, 61 crops, 2, 17, 19, 23, 25, 26, 28, 33, 35, 42, 47, 48, 49, 60, 115, 116, 124, 125 CRP, 80 CSA, 87 CT, viii, 17, 18, 19, 21, 22, 23, 24, 25, 39, 40 cultivation, 7, 16, 19, 27, 28, 43, 46, 54, 66, 73, 77, 80, 113, 120, 123, 129, 130 cultural practices, 17 culture, 19 cutin, 105 CV, 68, 69, 76, 77, 79

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Index cycles, 3, 7, 18, 22, 60, 90 cycling, 14, 32, 33, 36, 41, 56, 64, 82, 84, 86, 90, 108, 129

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D data analysis, 61 data set, vii, 1, 55 database, ix, 4, 63, 64, 66 decay, 14, 135 decomposition, viii, ix, 2, 10, 17, 18, 19, 22, 27, 28, 33, 39, 40, 41, 43, 44, 45, 46, 48, 50, 51, 61, 82, 89, 91, 94, 101, 102, 103, 104, 105, 106, 107, 108, 117, 120, 123, 129 decoupling, 94 deficiency, 48 deforestation, 2, 3, 4, 5, 6, 8, 25, 26, 27, 30, 31, 33, 107, 112, 116, 117, 120, 129 deformation, 97, 102 degradation, ix, x, 2, 43, 44, 46, 48, 55, 65, 82, 90, 103, 105, 108, 110, 116, 117, 120, 123, 125, 126, 128, 131, 132 degradation mechanism, x, 131 degradation process, 43, 46, 116 degradation rate, 48 dehydrate, 134 dehydration, 134 denitrification, 53, 101 density values, 43, 120 Department of Agriculture, 33 deposition, 10, 30, 51, 86, 101 depth, ix, 5, 7, 10, 11, 12, 13, 14, 15, 18, 19, 43, 46, 50, 57, 58, 60, 64, 66, 68, 69, 70, 71, 72, 75, 76, 77, 78, 79, 80, 81, 82, 83, 91, 94, 96, 98, 99, 101, 102, 104, 105, 113, 118, 120, 121, 133, 134 desiccation, 102 detectable, 47 developing countries, 32 deviation, 118 diffuse reflectance, ix, 89, 109 digestion, 98, 102 dispersion, 51, 135 distribution, viii, 12, 13, 15, 43, 44, 49, 58, 62, 63, 64, 68, 72, 79, 81, 82, 85, 87, 88, 108, 112, 116, 123, 128, 129 diversity, 3, 25, 55, 105, 117, 125, 128 DOI, 29 drainage, 52 drought, 3, 53, 116 dry matter, 10 drying, 22

141 E

Easter, 29, 30 ecology, vii economic incentives, 26 economic values, 82 ecosystem, 2, 6, 27, 41, 52, 56, 57, 58, 82, 83, 88, 90, 112, 117, 125 editors, 88 electrical conductivity, 51 electron, 27 elucidation, 110 emission, 2, 6, 8, 9, 14, 15, 29, 32, 34, 41, 45, 53, 54, 57, 59, 60, 65, 82 energy, 41, 44, 46, 90 England, 56, 130 environment, viii, 22, 33, 40, 42, 45, 46, 47, 52, 54, 58, 103, 116, 117, 122, 125, 127 environmental change, 61, 127 environmental conditions, 41, 132 environmental degradation, 71 environmental factors, 76 environmental impact, vii, ix, 26, 111 environmental quality, vii, 1, 2, 15, 19 environmental stress, 51 environmental stresses, 51 environments, vii, viii, 25, 39, 45, 46, 47, 48, 49, 50, 52, 91 enzyme, 52, 54, 105 enzymes, 49, 51, 90 equilibrium, 6, 45, 112, 116 erosion, vii, viii, 10, 16, 39, 41, 51, 112, 117, 120, 121, 123, 124, 125, 126, 127, 128, 130 ester, 94 ethanol, 8, 9, 15, 31, 34 ethers, 97 Europe, 65, 74, 87 European Union, 2, 126 evaporation, 44 evapotranspiration, viii, 39, 42 evidence, 8, 17, 18, 19, 36, 61, 106 evolution, 52 exclusion, 106 exposure, 10, 22, 51, 119 externalities, 126 extraction, 9, 109, 134 extracts, 90 F farmers, 17, 42, 48, 126 farmland, x, 65, 111, 112, 115, 116, 117, 119, 120, 121, 122, 123, 124, 125, 126

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142

Index

fauna, 126 fertility, 6, 9, 11, 28, 41, 42, 46, 47, 48, 52, 54, 55, 61, 117, 122, 123, 126, 129, 130 fertilization, viii, 30, 37, 40, 49, 54, 55, 56, 58, 59, 60, 61, 73 fertilizers, viii, 9, 10, 13, 16, 19, 40, 42, 48, 49, 58, 59, 61, 73, 86 fiber, 17, 26 financial, 26, 137 financial support, 26, 137 fires, 116 fixation, 19, 49 flank, x, 111 flocculation, 51 flooding, 77 food, 2, 26, 32, 57, 87, 125 food production, 2, 26 food security, 32, 57, 87, 125 forbs, 115 forest ecosystem, 82, 83, 85 forest fire, ix, 64, 83, 84, 91, 112, 115 forest management, 8, 82, 84 forest resources, 85 formation, vii, 1, 10, 17, 22, 27, 36, 48, 94 fragments, 44, 66 France, 88 freezing, 42 FTIR, 90, 91, 96, 97, 98, 99, 102, 106, 107, 109, 110 FTIR spectroscopy, 90, 91, 107 fuel consumption, 17 funds, 126 fungi, 48

greenhouse gas emissions, 2, 8, 29, 43, 59 greenhouse gases, 3, 6, 8, 9, 15, 36, 43, 45, 53, 65, 80 groundwater, 132 growth, 8, 18, 25, 36, 44, 45, 49, 52, 57, 82, 85, 112, 120 guidance, 107 guidelines, 132 H habitat, 126 hair, 18 hardwood forest, 85 harvesting, vii, 2, 3, 9, 10, 12, 80, 82, 117 health, 51, 121 heterogeneity, 83 history, 109 HM, 126 Holocene, 30, 127 House, 126 human, x, 27, 65, 71, 112, 116, 126, 127, 131, 132, 136 human activity, 71 human health, x, 131, 132, 136 humus, vii, 1, 27, 51, 71, 87, 108 hunting, 115 hydrocarbons, x, 131, 132, 134, 135 hydrofluoric acid, 109 hydrolysis, 93 I

G geology, 82, 91 Georgia, 60 Germany, 27, 34, 86 germination, 10 GHG, 9, 15 GIS, 79 global climate change, viii, 32, 57, 63, 87 global warming, 3, 11, 14, 15, 31, 52 grass, ix, 5, 64, 87 grasses, 6, 115 grasslands, 6 gravitational force, 135 grazing, 7, 46, 115 greenhouse, 2, 3, 6, 8, 9, 15, 17, 28, 29, 31, 36, 43, 45, 53, 57, 59, 64, 65, 80, 86, 87, 125 greenhouse gas, 2, 3, 6, 8, 9, 15, 17, 28, 29, 31, 36, 43, 45, 53, 59, 65, 80 greenhouse gas (GHG), 17

ICS, 24 identification, 107 immobilization, 10, 19 imports, 8 India, 8, 16, 30, 59, 60, 128, 129 indirect effect, 47 infrared spectroscopy, 106, 109 infrastructure, 126 initial state, 5 integration, 94 integrity, 60 investment, 8 ions, 95 IR spectra, 93 IR spectroscopy, ix, 89 Iran, 126, 129 iron, 71 irrigation, 42, 51, 60, 73, 87 isotope, ix, 30, 89, 91, 93, 101 issues, 56

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Index Italy, 39, 42, 43, 129 J Japan, 16, 86, 107, 131, 132, 137 Jordan, 30, 109 K K+, 48 KBr, 94, 102, 109 Kenya, 30, 48 kerosene, 137 ketones, 97, 99 Kyoto protocol, 65, 82, 127 Kyoto Protocol, 8

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L lakes, 51 Land Use Policy, 126, 127 landscape, 32, 51, 71, 87, 126, 129 landscapes, 27, 42, 85, 113 Latin America, 28, 32 leaching, 41, 51, 95, 101, 119 lead, viii, 3, 23, 40, 43, 44, 47, 65, 77, 80, 108, 116 legume, 19, 24, 37, 46, 47, 55 life cycle, 33 light, vii, 1, 44, 101, 112 lignin, 10, 18, 33, 98, 103, 106 limestone, 94, 102 lipids, 94, 103, 104, 105 lithology, 50 livestock, 2, 7, 26, 29, 33, 115 longevity, 10 LSD, 114, 121 Luo, 9, 33, 43, 44, 49, 58 lying, 51 M machinery, 10 magnesium, 11 magnitude, 2, 3, 45 majority, 42, 48 management, vii, viii, ix, 1, 2, 3, 6, 7, 8, 10, 11, 12, 13, 14, 15, 16, 17, 22, 23, 24, 26, 27, 28, 30, 31, 33, 35, 39, 40, 41, 42, 44, 49, 52, 54, 55, 56, 57, 58, 64, 65, 77, 80, 82, 85, 86, 88, 90, 91, 106, 107, 112, 120, 124, 125, 126, 127, 128, 129 manure, 9, 13, 16, 19, 41, 47, 48, 52, 54, 56, 58, 61, 80, 106, 107

143

mapping, viii, 63 MARCO, 86 marsh, 52, 57 Marx, 54 MAS, ix, 89, 91, 94, 98, 99, 100, 103, 106 mass, x, 91, 92, 98, 113, 131, 136, 137 materials, ix, 27, 32, 40, 47, 51, 71, 89, 92, 97, 102, 103, 107 matrix, 27 matter, vii, viii, x, 1, 6, 10, 14, 26, 27, 31, 35, 39, 54, 56, 58, 91, 93, 102, 106, 120, 125, 131, 133, 135 MBP, 40, 45 measurement, 56, 94 measurements, 55, 93, 94 Mediterranean, v, vii, viii, ix, 39, 40, 42, 45, 48, 50, 52, 53, 57, 58, 59, 87, 105, 111, 112, 113, 116, 122, 126, 127, 128, 129 Mediterranean climate, viii, 40, 42, 127 meta analysis, 55, 86 meta-analysis, 43, 58, 80 metal ion, 18 metal ions, 18 meter, 113 methodology, 44 methyl group, 94, 98 methyl groups, 94, 98 Mexico, 16, 32, 128 microbial communities, 15, 58 microbial community, ix, 55, 90, 104, 105 microclimate, 45, 82 micrometer, 18 micronutrients, 11 microorganisms, viii, 15, 18, 19, 36, 39, 41, 43, 44, 52, 104 Middle East, 16 migration, 26 mineralization, vii, viii, 1, 13, 16, 32, 39, 50, 52, 53, 54, 58, 61, 80, 101, 119, 123, 125 missions, 17 mixing, viii, 39, 51, 101 modelling, 54 models, 6, 23, 41, 128 modifications, vii, 2, 3, 7 MODIS, 31 moisture, viii, 10, 22, 39, 44, 45, 47, 48, 66, 74, 85 moisture content, viii, 39 molecules, 90 Montana, 130 N Na+, 48 NaCl, 51

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144

Index

naphthene, x, 131, 132, 136 National Academy of Sciences, 32 native species, 124 natural resources, 26, 112 Natural Resources Conservation Service, 88 negative effects, 49, 82 Netherlands, 127 New England, 85 New Zealand, 56 nitrification, 101 nitrogen, 9, 10, 13, 19, 27, 29, 30, 32, 33, 34, 35, 36, 37, 40, 44, 46, 54, 56, 58, 59, 60, 61, 84, 85, 86, 87, 88, 92, 95, 108, 113, 117, 118, 120, 124, 129 nitrogen fixation, 13 nitrous oxide, 8, 15 NMR, ix, 89, 90, 91, 94, 98, 99, 100, 103, 105, 106, 107, 108, 109, 110 no tillage systems, viii, 39 North America, 65 Norway, 87, 127 Norway spruce, 87 NRCS, 2, 36, 37 nuclear magnetic resonance, ix, 27, 89, 90, 105, 106 Nuclear Magnetic Resonance, 106 nuclei, 94 nutrient, vii, viii, 9, 14, 16, 22, 39, 40, 41, 42, 57, 61, 83, 84, 90, 120, 126, 129 nutrients, 10, 36, 41, 44, 47, 48, 53, 58, 82, 112, 122, 130 nutrition, 48 nutritional imbalance, 52 O OH, 57, 97, 102 oil, 8, 21, 24, 25, 33, 41, 92, 108, 131, 132, 133 Oklahoma, 59 olefin, x, 131, 132, 136 operations, 6, 9, 13, 17, 43 opportunities, 34, 60 ores, 120 organic chemicals, 137 organic compounds, ix, 18, 47, 89 osmotic stress, 51 overlap, 93 oxidation, 44, 66, 119, 121 P Pacific, 59 Paraguay, 17, 35 parallel, 101, 102

pasture, vii, 2, 3, 5, 6, 7, 8, 26, 27, 29, 30, 31, 32, 33, 34, 65, 122, 127 pastures, 2, 5, 6, 7, 8, 25, 26, 36 pathways, 110 PCR, 126, 127, 128, 129 permeability, 51, 117, 135, 136 permit, 91 Peru, 16 pesticide, 17 pests, 46 petroleum, x, 9, 131, 134, 135 Petroleum, 132, 137 pH, vii, 1, 11, 92, 94, 104, 113, 118, 120 phenol, 97 phosphorous, 61 phosphorus, 11, 28, 40, 113 photodegradation, 27 photosynthesis, 49 physical characteristics, 10 physical properties, 29, 47, 58, 126 physico-chemical parameters, 120 physicochemical properties, 132 Pinus halepensis, 50, 128 plant growth, 47, 51 plants, 40, 46, 48, 49, 115 playing, 42 PM, 127 polar, 42 polarization, ix, 89, 90, 94 policy, 26, 77 pollutants, 90, 137 pollution, 107, 132 polysaccharide, 97, 104 polysaccharides, 94, 98, 102, 103, 105 pools, ix, 18, 22, 24, 34, 36, 41, 44, 50, 59, 61, 64, 65, 70, 80, 83, 121, 129 population, 26, 51, 55, 77, 120 population size, 55 porosity, viii, 10, 40, 43, 120, 135 positive correlation, ix, 64, 76, 124 potassium, 11, 16, 113 potential benefits, 8 poultry, 52 precipitation, viii, 2, 10, 39, 42, 75, 79, 84 preparation, 2, 90, 92 preservation, vii, 104 prevention, 16, 127, 128 priming, 48 principles, 16 producers, 9 project, 105, 107, 126 protection, 14, 18, 25, 27, 32, 34, 56 proteins, 94, 99

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Index runoff, 17, 117, 120, 122, 123, 127, 128 rural development, 112

protons, 94 public opinion, 82 Q quantification, 94 quartz, 93, 96, 101, 102, 104 Queensland, 54, 108 R

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145

rain forest, 128 rainfall, 17, 22, 42, 53, 91, 112, 113, 117, 122, 123, 124, 125, 127 recovery, 116, 117, 128 recycling, ix, 10, 64 redistribution, 44, 45 regeneration, 116 regions of the world, 51 regression, 64, 76 regression model, 64, 76 regrowth, 9, 10 rehabilitation, 55 reliability, viii, 40, 42 remediation, 61, 132, 136 remote sensing, 81, 84 renewable energy, 2 repellent, 48 requirements, 17, 25 residuals, 133 residues, 2, 13, 14, 16, 17, 18, 19, 22, 23, 33, 35, 36, 41, 44, 46, 47, 48, 80, 98, 102, 108 resilience, 2, 116, 117 resins, 104 resistance, 57, 120 resolution, 32, 85, 98, 100 resource management, 59 resources, 46, 58, 65, 85, 112, 123 respiration, 15, 47, 48, 50, 61, 62, 87 response, 22, 49, 52, 107 restoration, ix, 32, 57, 86, 111, 127 rings, 94, 133 risk, 42, 125, 132 risk assessment, 132 risks, x, 82, 125, 131, 132, 136 room temperature, 93, 133 root, 17, 18, 24, 25, 34, 35, 44, 47, 49, 57, 58, 59, 60, 65, 73, 123 root growth, 44, 58 root system, 59 roots, 18, 24, 27, 47, 80, 123 rotations, 19, 35, 37, 45, 46, 47, 50, 53, 54, 61, 80 Royal Society, 33, 59

S salinity, 50, 51, 52, 58 salt concentration, 52 salts, 50, 51 sanctions, 82 saturation, 23, 24, 36, 41, 48, 52, 60, 61, 127 sawdust, 108 science, 26, 56, 87 scope, 132 Scots pine, x, 111, 115, 117, 118, 120, 121, 125, 129 sea level, 75, 113 seasonal flu, 45 security, 28 sediment, 108, 116 seeding, 5, 35 semiarid Mediterranean environments, vii, 52 senescence, 44 sensing, 7 sensitivity, 34, 91, 103 services, 40 sheep, 115 shock, 8 shoot, 18, 24, 35 shoots, 18 shortage, 49, 120 showing, 9, 15, 100, 102, 113 shrubland, x, 111, 116, 117, 120, 121, 122, 123, 124, 125, 129 shrubs, 50, 53, 115, 116, 124 signals, 96, 98, 101, 102, 103, 104 signal-to-noise ratio, 94 simulation, 7, 84 simulations, 7 skeleton, 85 sludge, 108 SMS, 74, 75 sodium, 11, 50, 134 soil components, vii, 1, 70 soil erosion, 10, 16, 51, 117, 120, 122, 123, 125, 127, 128 soil information system (SIS), viii, 63 soil pollution, 132 soil type, ix, 2, 6, 7, 12, 24, 63, 86, 92, 113, 114, 125, 131 solubility, 51 solution, 19, 51, 92, 106, 108, 134 sorption, vii, x, 1, 131, 136 South Africa, 13 sowing, 17

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146

Index

SP, 1, 33 Spain, x, 43, 45, 52, 53, 55, 57, 58, 111, 112, 113, 114, 124, 126, 127, 128, 129, 130 spatial location, 116 speciation, 109 species, 9, 17, 19, 30, 46, 50, 59, 75, 76, 82, 92, 94, 105, 112, 113, 115, 116, 117, 123, 124, 128 specific gravity, 132 spectroscopic techniques, 23 spectroscopy, 90, 100, 103, 107, 108, 109 spin, 27 Sri Lanka, 61 SS, 74, 126 stability, 6, 10, 23, 28, 51, 58, 83, 90, 112, 116, 122, 128 stabilization, 17, 22, 23, 30, 34, 41, 48, 90 stabilization efficiency, 41 standard deviation, 73, 121 state, 6, 8, 9, 11, 12, 13, 15, 17, 23, 29, 41, 54, 65, 73, 105, 106, 107, 108, 127 states, 6, 16, 17, 33, 40, 112 steel, 133 stimulation, 44 stock, viii, 2, 3, 5, 7, 10, 12, 13, 23, 54, 63, 67, 69, 70, 71, 77, 78, 79, 83, 85, 88, 113, 121, 123, 124, 125, 126, 130 stock value, 13 storage, ix, 2, 4, 17, 19, 21, 24, 27, 28, 30, 46, 48, 49, 52, 56, 60, 64, 65, 70, 76, 77, 78, 79, 80, 81, 82, 84, 86, 111, 112, 117, 122, 124, 125, 127, 129 storms, 42, 113 stratification, 56, 57 stress, 15, 26, 44, 51, 52, 61, 107 stretching, 96, 97, 101, 102 structural changes, 107 structure, vii, viii, 10, 17, 22, 39, 41, 53, 61, 82, 83, 90, 91, 96, 100, 104, 106, 120, 125 substitution, 15, 19 substrate, 18, 51, 58 substrates, 45, 51 succession, 7, 18, 21, 31, 116, 123, 124, 128 sucrose, 93 sugarcane, vii, 2, 3, 8, 9, 10, 11, 12, 13, 14, 15, 25, 27, 28, 29, 30, 31, 33, 34, 35, 36, 77, 80, 81, 82 sulfate, 134 sulfur, 10 sulfuric acid, 95 Sun, 58, 82, 88, 130 surface area, 44 surface layer, 5, 7, 45, 51, 98, 101 susceptibility, 10, 121 sustainability, vii, 1, 2, 3, 8, 57, 59, 61, 82, 84, 126 Sustainable Development, 57

Sweden, 107 Switzerland, 37 synthesis, 52, 127 T Taiwan, v, viii, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 77, 79, 80, 81, 82, 83, 84, 85, 86, 88 taxes, 26 techniques, viii, 6, 39, 81, 91, 125 technology, 26 temperature, viii, 2, 10, 22, 34, 39, 44, 45, 47, 50, 56, 59, 66, 74, 75, 84, 85, 90, 91, 105, 113, 123, 133 tempo, 37 temporal variation, 65 terraces, ix, 64, 74, 115, 127 terrestrial ecosystems, 41 territory, 15 texture, ix, 13, 22, 23, 25, 89, 91, 113 thermal stability, 109 thinning, ix, 64, 82, 84, 87 timber production, 82, 88 time series, 31 tissue, 18 total petroleum hydrocarbons (TPH), x, 131, 134 training, 5 transformation, 40, 77, 106, 109, 125 transformation processes, 40 transformations, 6, 53, 105 translocation, 51, 119 transmission, 107 transport, vii, x, 117, 131, 132, 136, 137 treatment, ix, 43, 45, 51, 64, 65, 92, 93, 94, 98, 108, 109 tropical forests, 3, 28 Turkey, 109, 126 turnover, 28, 36, 41, 44, 45, 47, 56, 60, 106 U UK, 85, 127 United, 2, 17, 31, 32, 85, 87, 127 United Kingdom, 87 United Nations, 31 United States, 2, 17, 32, 85, 127 USA, 53, 57, 60, 65, 73, 80, 84, 88, 127, 128, 130 USDA, 2, 36, 37, 88 V vapor, 137 variations, 22, 65, 90, 116, 134

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Index varieties, 46 vegetation, viii, ix, 2, 3, 4, 5, 6, 7, 13, 15, 16, 30, 31, 39, 50, 52, 75, 76, 84, 89, 90, 91, 105, 107, 108, 112, 116, 117, 120, 123, 124, 125, 128, 129 vegetative cover, 128 vehicles, 9 velocity, 17 velvet, 24 vibration, 97 vinasse, 13, 28, 30 vision, 17 volatilization, x, 131, 132, 133, 135, 136, 137

147

water evaporation, 10 water quality, 125 water retention, vii, 1 watershed, vii, x, 111, 112, 113, 114, 115, 116, 121, 123, 124, 125, 126 West Africa, 58, 129 wetting, 22, 51 Wisconsin, 55, 86 wood, 5, 103, 107, 115 woodland, 57 World Trade Organization, 37 worldwide, 2 WTO, 2, 37

W Y yield, 16, 30, 82, 125

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Wales, 130 Washington, 31, 36, 88 water, vii, 1, 10, 18, 22, 26, 35, 41, 42, 44, 45, 47, 48, 49, 50, 61, 90, 93, 97, 102, 107, 108, 112, 117, 120, 122, 123, 125, 126, 130, 133, 137

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