Arable land can be either a source or a sink for atmospheric carbon dioxide depending on its mana... more Arable land can be either a source or a sink for atmospheric carbon dioxide depending on its management. It is important to assess changes in soil organic carbon (SOC) under future climate change scenarios using models at regional or global scales. This paper aims to calibrate the RothC model on non-waterlogged soils in northern China to obtain the necessary model input parameters for later use in large-scale studies. Data sets from three long-term experiments in northern China were used to evaluate the performance of the RothC soil carbon turnover model. The plant carbon input rate, an important model input parameter, was calibrated using experimental data under typical rotation systems with different fertilization. The results showed that RothC accurately simulated the changes in SOC across a wide area of northern China (northeast, north, and northwest China. The modelling error expressed as root mean square error for four treatments (nil, manure, fertilizer, fertilizer + manure) at three sites were less than 20.2%, and less than 7.8% if occasional extreme measured values were omitted. The simulation biases expressed as M (i.e. relative error) for all treatments at the three sites were non-significant. Observed trends in SOC included a decrease for the nil (no fertilizer or manure) treatment and an increase for the treatments which received both manure and fertilizers. The experiments also indicated that manures applied at an appropriate rate were more effective in increasing or maintaining SOC than fertilizers which were more effective in increasing crop yields.
Under the United Nations Framework Convention on Climate Change (UNFCCC), Non-Annex 1 countries s... more Under the United Nations Framework Convention on Climate Change (UNFCCC), Non-Annex 1 countries such as Kenya are obliged to report green house gas (GHG) emissions from all sources where possible, including those from soils as a result of changes in land use or land management. At present, the convention encourages countries to estimate emissions using the most advanced methods possible, given the country circumstances and resources. Estimates of soil organic carbon (SOC) stocks and changes were made for Kenya using the Global Environment Facility Soil Organic Carbon (GEFSOC) Modelling System. The tool conducts analysis using three methods: (1) the Century general ecosystem model; (2) the RothC soil C decomposition model; and (3) the Intergovernmental Panel on Climate Change (IPCC) method for assessing soil C at regional scales. The required datasets included: land use history, monthly mean precipitation, monthly mean minimum and maximum temperatures for all the agro-climatic zones of Kenya and historical vegetation cover. Soil C stocks of 1.4-2.0 Pg (0-20 cm), compared well with a Soil and Terrain (SOTER) based approach that estimated $1.8-2.0 Pg (0-30 cm). In 1990 48% of the country had SOC stocks of <18 t C ha À1 and 20% of the country had SOC stocks of 18-30 t C ha À1 , whereas in 2000 56% of the country had SOC stocks of <18 t C ha À1 and 31% of the country had SOC stocks of 18-30 t C ha À1 . Conversion of natural vegetation to annual crops led to the greatest soil C losses. Simulations suggest that soil C losses remain substantial throughout the modelling period of 1990-2030. All three methods involved in the GEFSOC System estimated that there would be a net loss of soil C between 2000 and 2030 in Kenya. The decline was more marked with RothC than with Century or the IPCC method. In non-hydric soils the SOC change rates were more pronounced in high sandy soils compared to high clay soils in most land use systems. #
National and sub-national scale estimates of soil organic carbon (SOC) stocks and changes can pro... more National and sub-national scale estimates of soil organic carbon (SOC) stocks and changes can provide information land degradation risk, C sequestration possibilities and the potential sustainability of proposed land management plans. Under a GEF co-financed project, 'The GEFSOC Modelling System' was used to determine SOC stocks and projected stock change rates for four case study areas; The Brazilian Amazon, The Indo-Gangetic Plains of India, Kenya and Jordan. Each case study represented soil and vegetation types, climates and land management systems that are under represented globally, in terms of an understanding of land use and land management systems and the effects these systems have on SOC stocks. The stocks and stock change rates produced were based on detailed geo-referenced datasets of soils, climate, land use and management information. These datasets are unique as they bring together national and regional scale data on the main variables determining SOC, for four contrasting non-temperate eco-regions. They are also unique, as they include information on land management practices used in subsistence agriculture in tropical and arid areas. Implications of a greater understanding of SOC stocks and stock change rates in non-temperate areas are considered. Relevance to national land use plans are explored for each of the four case studies, in terms of sustainability, land degradation and greenhouse gas mitigation potential. Ways in which such information will aid the case study countries in fulfilling obligations under the United Nations Conventions on Climate Change, Biodiversity and Land Degradation are also considered. The need for more detailed land management data to improve SOC stock estimates in non-temperate areas is discussed. #
The GEFSOC soil carbon modelling system was built to provide interdisciplinary teams of scientist... more The GEFSOC soil carbon modelling system was built to provide interdisciplinary teams of scientists, natural resource managers and policy analysts (who have the appropriate computing skills) with the necessary tools to conduct regional-scale soil carbon (C) inventories. It allows users to assess the effects of land use change on soil organic C (SOC) stocks, soil fertility and the potential for soil C sequestration. The tool was developed in conjunction with case-studies of land use and management impacts on SOC in Brazil, Jordan, Kenya and India, which represent a diversity of land use and land management patterns and are countries where sustaining soil organic matter and fertility for food security is an on-going problem. The tool was designed to run using two common desktop computers, connected via a local area network. It utilizes open-source software that is freely available. All new software and user interfaces developed for the tool are available in an open source environment allowing users to examine system details, suggest improvements or write additional modules to interface with the system. The tool incorporates three widely used models for estimating soil C dynamics: (1) the Century ecosystem model; (2) the RothC soil C decomposition model; and (3) the Intergovernmental Panel on Climate Change (IPCC) method for assessing soil C at regional scales. The tool interacts with a Soil and Terrain Digital Database (SOTER) built for the specific country or region the user intends to model. A demonstration of the tool and results from an assessment of land use change in a sample region of North America are presented. #
National and sub-national scale estimates of soil organic carbon (SOC) stocks and changes can pro... more National and sub-national scale estimates of soil organic carbon (SOC) stocks and changes can provide information land degradation risk, C sequestration possibilities and the potential sustainability of proposed land management plans. Under a GEF co-financed project, 'The GEFSOC Modelling System' was used to determine SOC stocks and projected stock change rates for four case study areas; The Brazilian Amazon, The Indo-Gangetic Plains of India, Kenya and Jordan. Each case study represented soil and vegetation types, climates and land management systems that are under represented globally, in terms of an understanding of land use and land management systems and the effects these systems have on SOC stocks. The stocks and stock change rates produced were based on detailed geo-referenced datasets of soils, climate, land use and management information. These datasets are unique as they bring together national and regional scale data on the main variables determining SOC, for four contrasting non-temperate eco-regions. They are also unique, as they include information on land management practices used in subsistence agriculture in tropical and arid areas. Implications of a greater understanding of SOC stocks and stock change rates in non-temperate areas are considered. Relevance to national land use plans are explored for each of the four case studies, in terms of sustainability, land degradation and greenhouse gas mitigation potential. Ways in which such information will aid the case study countries in fulfilling obligations under the United Nations Conventions on Climate Change, Biodiversity and Land Degradation are also considered. The need for more detailed land management data to improve SOC stock estimates in non-temperate areas is discussed. #
The GEFSOC Project developed a system for estimating soil carbon (C) stocks and changes at the na... more The GEFSOC Project developed a system for estimating soil carbon (C) stocks and changes at the national and sub-national scale. As part of the development of the system, the Century ecosystem model was evaluated for its ability to simulate soil organic C (SOC) changes in environmental conditions in the Indo-Gangetic Plains, India (IGP). Two long-term fertilizer trials (LTFT), with all necessary parameters needed to run Century, were used for this purpose: a jute (Corchorus capsularis L.), rice (Oryza sativa L.) and wheat (Triticum aestivum L.) trial at Barrackpore, West Bengal, and a rice-wheat trial at Ludhiana, Punjab. The trials represent two contrasting climates of the IGP, viz. semi-arid, dry with mean annual rainfall (MAR) of <800 mm and humid with >1600 mm. Both trials involved several different treatments with different organic and inorganic fertilizer inputs. In general, the model tended to overestimate treatment effects by approximately 15%. At the semi-arid site, modelled data simulated actual data reasonably well for all treatments, with the control and chemical N + farm yard manure showing the best agreement (RMSE = 7). At the humid site, Century performed less well. This could have been due to a range of factors including site history. During the study, Century was calibrated to simulate crop yields for the two sites considered using data from across the Indian IGP. However, further adjustments may improve model performance at these sites and others in the IGP. The availability of more longterm experimental data sets (especially those involving flooded lowland rice and triple cropping systems from the IGP) for testing and validation is critical to the application of the model's predictive capabilities for this area of the Indian sub-continent. #
The GEFSOC soil carbon modelling system was built to provide interdisciplinary teams of scientist... more The GEFSOC soil carbon modelling system was built to provide interdisciplinary teams of scientists, natural resource managers and policy analysts (who have the appropriate computing skills) with the necessary tools to conduct regional-scale soil carbon (C) inventories. It allows users to assess the effects of land use change on soil organic C (SOC) stocks, soil fertility and the potential for soil C sequestration. The tool was developed in conjunction with case-studies of land use and management impacts on SOC in Brazil, Jordan, Kenya and India, which represent a diversity of land use and land management patterns and are countries where sustaining soil organic matter and fertility for food security is an on-going problem. The tool was designed to run using two common desktop computers, connected via a local area network. It utilizes open-source software that is freely available. All new software and user interfaces developed for the tool are available in an open source environment allowing users to examine system details, suggest improvements or write additional modules to interface with the system. The tool incorporates three widely used models for estimating soil C dynamics: (1) the Century ecosystem model; (2) the RothC soil C decomposition model; and (3) the Intergovernmental Panel on Climate Change (IPCC) method for assessing soil C at regional scales. The tool interacts with a Soil and Terrain Digital Database (SOTER) built for the specific country or region the user intends to model. A demonstration of the tool and results from an assessment of land use change in a sample region of North America are presented. #
Soil organic carbon (SOC) plays a vital role in ecosystem function, determining soil fertility, w... more Soil organic carbon (SOC) plays a vital role in ecosystem function, determining soil fertility, water holding capacity and susceptibility to land degradation. In addition, SOC is related to atmospheric CO 2 levels with soils having the potential for C release or sequestration, depending on land use, land management and climate. The United Nations Convention on Climate Change and its Kyoto Protocol, and other United Nations Conventions to Combat Desertification and on Biodiversity all recognize the importance of SOC and point to the need for quantification of SOC stocks and changes. An understanding of SOC stocks and changes at the national and regional scale is necessary to further our understanding of the global C cycle, to assess the responses of terrestrial ecosystems to climate change and to aid policy makers in making land use/management decisions. Several studies have considered SOC stocks at the plot scale, but these are site specific and of limited value in making inferences about larger areas. Some studies have used empirical methods to estimate SOC stocks and changes at the regional scale, but such studies are limited in their ability to project future changes, and most have been carried out using temperate data sets. The computational method outlined by the Intergovernmental Panel on Climate Change (IPCC) has been used to estimate SOC stock changes at the regional scale in several studies, including a recent study considering five contrasting eco regions. This 'one step' approach fails to account for the dynamic manner in which SOC changes are likely to occur following changes in land use and land management.
National and sub-national scale estimates of soil organic carbon (SOC) stocks and changes can pro... more National and sub-national scale estimates of soil organic carbon (SOC) stocks and changes can provide information land degradation risk, C sequestration possibilities and the potential sustainability of proposed land management plans. Under a GEF co-financed project, 'The GEFSOC Modelling System' was used to determine SOC stocks and projected stock change rates for four case study areas; The Brazilian Amazon, The Indo-Gangetic Plains of India, Kenya and Jordan. Each case study represented soil and vegetation types, climates and land management systems that are under represented globally, in terms of an understanding of land use and land management systems and the effects these systems have on SOC stocks. The stocks and stock change rates produced were based on detailed geo-referenced datasets of soils, climate, land use and management information. These datasets are unique as they bring together national and regional scale data on the main variables determining SOC, for four contrasting non-temperate eco-regions. They are also unique, as they include information on land management practices used in subsistence agriculture in tropical and arid areas. Implications of a greater understanding of SOC stocks and stock change rates in non-temperate areas are considered. Relevance to national land use plans are explored for each of the four case studies, in terms of sustainability, land degradation and greenhouse gas mitigation potential. Ways in which such information will aid the case study countries in fulfilling obligations under the United Nations Conventions on Climate Change, Biodiversity and Land Degradation are also considered. The need for more detailed land management data to improve SOC stock estimates in non-temperate areas is discussed. #
Land use and land cover changes in the Brazilian Amazon have major implications for regional and ... more Land use and land cover changes in the Brazilian Amazon have major implications for regional and global carbon (C) cycling. Cattle pasture represents the largest single use (about 70%) of this once-forested land in most of the region. The main objective of this study was to evaluate the accuracy of the RothC and Century models at estimating soil organic C (SOC) changes under forest-to-pasture conditions in the Brazilian Amazon. We used data from 11 site-specific 'forest to pasture' chronosequences with the Century Ecosystem Model (Century 4.0) and the Rothamsted C Model (RothC 26.3). The models predicted that forest clearance and conversion to well managed pasture would cause an initial decline in soil C stocks (0-20 cm depth), followed in the majority of cases by a slow rise to levels exceeding those under native forest. One exception to this pattern was a chronosequence in Suia-Missu, which is under degraded pasture. In three other chronosequences the recovery of soil C under pasture appeared to be only to about the same level as under the previous forest. Statistical tests were applied to determine levels of agreement between simulated SOC stocks and observed stocks for all the sites within the 11 chronosequences. The models also provided reasonable estimates (coefficient of correlation = 0.8) of the microbial biomass C in the 0-10 cm soil layer for three chronosequences, when compared with available measured data. The Century model adequately predicted the magnitude and the overall trend in d 13 C for the six chronosequences where measured d 13 C data were available. This study gave independent tests of model performance, as no adjustments were made to the models to generate outputs. Our results suggest that modelling techniques can be successfully used for monitoring soil C stocks and changes, allowing both the identification of current patterns in the soil and the projection of future conditions. Results were used and discussed not only to evaluate soil C dynamics but also to indicate soil C sequestration opportunities for the Brazilian Amazon region. Moreover, modelling studies in these 'forest to pasture' systems have important applications, for example, the calculation of CO 2 emissions from land use change in national greenhouse gas inventories. # Temp: mean annual air temperature (8C); Prec: mean annual precipitation (mm); B. briz: Brachiaria brizantha; B. hum: Brachiaria humidicula; B. decum: Brachiaria decumbens; P. max: Panicum maximum.
The GEFSOC Soil Carbon Modeling System was assembled under a co-financed project supported by the... more The GEFSOC Soil Carbon Modeling System was assembled under a co-financed project supported by the United Nations Environment Programme (UNEP) Global Environmental Facility (GEF) and the US Agency for International Development. The tool was built to provide scientists, ...
National and sub-national scale estimates of soil organic carbon (SOC) stocks and changes can pro... more National and sub-national scale estimates of soil organic carbon (SOC) stocks and changes can provide information land degradation risk, C sequestration possibilities and the potential sustainability of proposed land management plans. Under a GEF co-financed project, 'The GEFSOC Modelling System' was used to determine SOC stocks and projected stock change rates for four case study areas; The Brazilian Amazon, The Indo-Gangetic Plains of India, Kenya and Jordan. Each case study represented soil and vegetation types, climates and land management systems that are under represented globally, in terms of an understanding of land use and land management systems and the effects these systems have on SOC stocks. The stocks and stock change rates produced were based on detailed geo-referenced datasets of soils, climate, land use and management information. These datasets are unique as they bring together national and regional scale data on the main variables determining SOC, for four contrasting non-temperate eco-regions. They are also unique, as they include information on land management practices used in subsistence agriculture in tropical and arid areas. Implications of a greater understanding of SOC stocks and stock change rates in non-temperate areas are considered. Relevance to national land use plans are explored for each of the four case studies, in terms of sustainability, land degradation and greenhouse gas mitigation potential. Ways in which such information will aid the case study countries in fulfilling obligations under the United Nations Conventions on Climate Change, Biodiversity and Land Degradation are also considered. The need for more detailed land management data to improve SOC stock estimates in non-temperate areas is discussed. #
Under the United Nations Framework Convention on Climate Change (UNFCCC), Non-Annex 1 countries s... more Under the United Nations Framework Convention on Climate Change (UNFCCC), Non-Annex 1 countries such as Kenya are obliged to report green house gas (GHG) emissions from all sources where possible, including those from soils as a result of changes in land use or land management. At present, the convention encourages countries to estimate emissions using the most advanced methods possible, given the country circumstances and resources. Estimates of soil organic carbon (SOC) stocks and changes were made for Kenya using the Global Environment Facility Soil Organic Carbon (GEFSOC) Modelling System. The tool conducts analysis using three methods: (1) the Century general ecosystem model; (2) the RothC soil C decomposition model; and (3) the Intergovernmental Panel on Climate Change (IPCC) method for assessing soil C at regional scales. The required datasets included: land use history, monthly mean precipitation, monthly mean minimum and maximum temperatures for all the agro-climatic zones of Kenya and historical vegetation cover. Soil C stocks of 1.4-2.0 Pg (0-20 cm), compared well with a Soil and Terrain (SOTER) based approach that estimated $1.8-2.0 Pg (0-30 cm). In 1990 48% of the country had SOC stocks of <18 t C ha À1 and 20% of the country had SOC stocks of 18-30 t C ha À1 , whereas in 2000 56% of the country had SOC stocks of <18 t C ha À1 and 31% of the country had SOC stocks of 18-30 t C ha À1 . Conversion of natural vegetation to annual crops led to the greatest soil C losses. Simulations suggest that soil C losses remain substantial throughout the modelling period of 1990-2030. All three methods involved in the GEFSOC System estimated that there would be a net loss of soil C between 2000 and 2030 in Kenya. The decline was more marked with RothC than with Century or the IPCC method. In non-hydric soils the SOC change rates were more pronounced in high sandy soils compared to high clay soils in most land use systems. #
RothC and Century are two of the most widely used soil organic matter (SOM) models. However there... more RothC and Century are two of the most widely used soil organic matter (SOM) models. However there are few examples of specific parameterisation of these models for environmental conditions in East Africa. The aim of this study was therefore, to evaluate the ability of RothC and the Century to estimate changes in soil organic carbon (SOC) resulting from varying land
The terrestrial biosphere is an important global carbon (C) sink, with the potential to drive lar... more The terrestrial biosphere is an important global carbon (C) sink, with the potential to drive large positive climate feedbacks. Thus a better understanding of interactions between land use change, climate change and the terrestrial biosphere is crucial in planning future land management options. Climate change has the potential to alter terrestrial C storage since changes in temperature, precipitation and carbon dioxide (CO 2 ) concentrations could affect net primary production (NPP), C inputs to soil, and soil C decomposition rates. Climate change could also act as a driver for land use change, thus further altering terrestrial C fluxes. The net balance of these different effects varies considerably between regions and hence the case studies presented in this paper (the GEFSOC project countries Kenya, Jordan, Brazil, and India) provide a unique opportunity to study climate impacts on terrestrial C storage. This paper first presents predicted changes in climate for the four case study countries from a coupled climate-C cycle Global Circulation Model (HadCM3LC), followed by predicted changes in vegetation type, NPP and soil C storage. These very coarse assessments provide an initial estimate of large-scale effects. A more detailed study of climate impacts on soil C storage in the Brazilian Amazon is provided as an example application of the GEFSOC system. Interestingly in the four cases studied here precipitation seems to control the sign of the soil C changes under climate change with wetter conditions resulting in higher soil C stocks and drier conditions in lower soil C stocks, presumably because increased NPP in wetter conditions here will override any increase in respiration. In contrast, globally, it seems to be temperature that controls changes in C stocks under climate change. Even if there is a slight increase in precipitation globally, a decrease in C stocks is predicted-in other words, the regional response to precipitation differs from the global response. The reason for this may be that whilst temperature increases under climate change were predicted everywhere, the nature of precipitation changes varies greatly between regions. Crown
The GEFSOC Project developed a system for estimating soil carbon (C) stocks and changes at the na... more The GEFSOC Project developed a system for estimating soil carbon (C) stocks and changes at the national and sub-national scale. As part of the development of the system, the Century ecosystem model was evaluated for its ability to simulate soil organic C (SOC) changes in environmental conditions in the Indo-Gangetic Plains, India (IGP). Two long-term fertilizer trials (LTFT), with all necessary parameters needed to run Century, were used for this purpose: a jute (Corchorus capsularis L.), rice (Oryza sativa L.) and wheat (Triticum aestivum L.) trial at Barrackpore, West Bengal, and a rice-wheat trial at Ludhiana, Punjab. The trials represent two contrasting climates of the IGP, viz. semi-arid, dry with mean annual rainfall (MAR) of <800 mm and humid with >1600 mm. Both trials involved several different treatments with different organic and inorganic fertilizer inputs. In general, the model tended to overestimate treatment effects by approximately 15%. At the semi-arid site, modelled data simulated actual data reasonably well for all treatments, with the control and chemical N + farm yard manure showing the best agreement (RMSE = 7). At the humid site, Century performed less well. This could have been due to a range of factors including site history. During the study, Century was calibrated to simulate crop yields for the two sites considered using data from across the Indian IGP. However, further adjustments may improve model performance at these sites and others in the IGP. The availability of more longterm experimental data sets (especially those involving flooded lowland rice and triple cropping systems from the IGP) for testing and validation is critical to the application of the model's predictive capabilities for this area of the Indian sub-continent. #
Land use and land cover changes in the Brazilian Amazon have major implications for regional and ... more Land use and land cover changes in the Brazilian Amazon have major implications for regional and global carbon (C) cycling. Cattle pasture represents the largest single use (about 70%) of this once-forested land in most of the region. The main objective of this study was to evaluate the accuracy of the RothC and Century models at estimating soil organic C (SOC) changes under forest-to-pasture conditions in the Brazilian Amazon. We used data from 11 site-specific 'forest to pasture' chronosequences with the Century Ecosystem Model (Century 4.0) and the Rothamsted C Model (RothC 26.3). The models predicted that forest clearance and conversion to well managed pasture would cause an initial decline in soil C stocks (0-20 cm depth), followed in the majority of cases by a slow rise to levels exceeding those under native forest. One exception to this pattern was a chronosequence in Suia-Missu, which is under degraded pasture. In three other chronosequences the recovery of soil C under pasture appeared to be only to about the same level as under the previous forest. Statistical tests were applied to determine levels of agreement between simulated SOC stocks and observed stocks for all the sites within the 11 chronosequences. The models also provided reasonable estimates (coefficient of correlation = 0.8) of the microbial biomass C in the 0-10 cm soil layer for three chronosequences, when compared with available measured data. The Century model adequately predicted the magnitude and the overall trend in d 13 C for the six chronosequences where measured d 13 C data were available. This study gave independent tests of model performance, as no adjustments were made to the models to generate outputs. Our results suggest that modelling techniques can be successfully used for monitoring soil C stocks and changes, allowing both the identification of current patterns in the soil and the projection of future conditions. Results were used and discussed not only to evaluate soil C dynamics but also to indicate soil C sequestration opportunities for the Brazilian Amazon region. Moreover, modelling studies in these 'forest to pasture' systems have important applications, for example, the calculation of CO 2 emissions from land use change in national greenhouse gas inventories. # Temp: mean annual air temperature (8C); Prec: mean annual precipitation (mm); B. briz: Brachiaria brizantha; B. hum: Brachiaria humidicula; B. decum: Brachiaria decumbens; P. max: Panicum maximum.
The GEFSOC soil carbon modelling system was built to provide interdisciplinary teams of scientist... more The GEFSOC soil carbon modelling system was built to provide interdisciplinary teams of scientists, natural resource managers and policy analysts (who have the appropriate computing skills) with the necessary tools to conduct regional-scale soil carbon (C) inventories. It allows users to assess the effects of land use change on soil organic C (SOC) stocks, soil fertility and the potential for soil C sequestration. The tool was developed in conjunction with case-studies of land use and management impacts on SOC in Brazil, Jordan, Kenya and India, which represent a diversity of land use and land management patterns and are countries where sustaining soil organic matter and fertility for food security is an on-going problem. The tool was designed to run using two common desktop computers, connected via a local area network. It utilizes open-source software that is freely available. All new software and user interfaces developed for the tool are available in an open source environment allowing users to examine system details, suggest improvements or write additional modules to interface with the system. The tool incorporates three widely used models for estimating soil C dynamics: (1) the Century ecosystem model; (2) the RothC soil C decomposition model; and (3) the Intergovernmental Panel on Climate Change (IPCC) method for assessing soil C at regional scales. The tool interacts with a Soil and Terrain Digital Database (SOTER) built for the specific country or region the user intends to model. A demonstration of the tool and results from an assessment of land use change in a sample region of North America are presented. #
Arable land can be either a source or a sink for atmospheric carbon dioxide depending on its mana... more Arable land can be either a source or a sink for atmospheric carbon dioxide depending on its management. It is important to assess changes in soil organic carbon (SOC) under future climate change scenarios using models at regional or global scales. This paper aims to calibrate the RothC model on non-waterlogged soils in northern China to obtain the necessary model input parameters for later use in large-scale studies. Data sets from three long-term experiments in northern China were used to evaluate the performance of the RothC soil carbon turnover model. The plant carbon input rate, an important model input parameter, was calibrated using experimental data under typical rotation systems with different fertilization. The results showed that RothC accurately simulated the changes in SOC across a wide area of northern China (northeast, north, and northwest China. The modelling error expressed as root mean square error for four treatments (nil, manure, fertilizer, fertilizer + manure) at three sites were less than 20.2%, and less than 7.8% if occasional extreme measured values were omitted. The simulation biases expressed as M (i.e. relative error) for all treatments at the three sites were non-significant. Observed trends in SOC included a decrease for the nil (no fertilizer or manure) treatment and an increase for the treatments which received both manure and fertilizers. The experiments also indicated that manures applied at an appropriate rate were more effective in increasing or maintaining SOC than fertilizers which were more effective in increasing crop yields.
Under the United Nations Framework Convention on Climate Change (UNFCCC), Non-Annex 1 countries s... more Under the United Nations Framework Convention on Climate Change (UNFCCC), Non-Annex 1 countries such as Kenya are obliged to report green house gas (GHG) emissions from all sources where possible, including those from soils as a result of changes in land use or land management. At present, the convention encourages countries to estimate emissions using the most advanced methods possible, given the country circumstances and resources. Estimates of soil organic carbon (SOC) stocks and changes were made for Kenya using the Global Environment Facility Soil Organic Carbon (GEFSOC) Modelling System. The tool conducts analysis using three methods: (1) the Century general ecosystem model; (2) the RothC soil C decomposition model; and (3) the Intergovernmental Panel on Climate Change (IPCC) method for assessing soil C at regional scales. The required datasets included: land use history, monthly mean precipitation, monthly mean minimum and maximum temperatures for all the agro-climatic zones of Kenya and historical vegetation cover. Soil C stocks of 1.4-2.0 Pg (0-20 cm), compared well with a Soil and Terrain (SOTER) based approach that estimated $1.8-2.0 Pg (0-30 cm). In 1990 48% of the country had SOC stocks of <18 t C ha À1 and 20% of the country had SOC stocks of 18-30 t C ha À1 , whereas in 2000 56% of the country had SOC stocks of <18 t C ha À1 and 31% of the country had SOC stocks of 18-30 t C ha À1 . Conversion of natural vegetation to annual crops led to the greatest soil C losses. Simulations suggest that soil C losses remain substantial throughout the modelling period of 1990-2030. All three methods involved in the GEFSOC System estimated that there would be a net loss of soil C between 2000 and 2030 in Kenya. The decline was more marked with RothC than with Century or the IPCC method. In non-hydric soils the SOC change rates were more pronounced in high sandy soils compared to high clay soils in most land use systems. #
National and sub-national scale estimates of soil organic carbon (SOC) stocks and changes can pro... more National and sub-national scale estimates of soil organic carbon (SOC) stocks and changes can provide information land degradation risk, C sequestration possibilities and the potential sustainability of proposed land management plans. Under a GEF co-financed project, 'The GEFSOC Modelling System' was used to determine SOC stocks and projected stock change rates for four case study areas; The Brazilian Amazon, The Indo-Gangetic Plains of India, Kenya and Jordan. Each case study represented soil and vegetation types, climates and land management systems that are under represented globally, in terms of an understanding of land use and land management systems and the effects these systems have on SOC stocks. The stocks and stock change rates produced were based on detailed geo-referenced datasets of soils, climate, land use and management information. These datasets are unique as they bring together national and regional scale data on the main variables determining SOC, for four contrasting non-temperate eco-regions. They are also unique, as they include information on land management practices used in subsistence agriculture in tropical and arid areas. Implications of a greater understanding of SOC stocks and stock change rates in non-temperate areas are considered. Relevance to national land use plans are explored for each of the four case studies, in terms of sustainability, land degradation and greenhouse gas mitigation potential. Ways in which such information will aid the case study countries in fulfilling obligations under the United Nations Conventions on Climate Change, Biodiversity and Land Degradation are also considered. The need for more detailed land management data to improve SOC stock estimates in non-temperate areas is discussed. #
The GEFSOC soil carbon modelling system was built to provide interdisciplinary teams of scientist... more The GEFSOC soil carbon modelling system was built to provide interdisciplinary teams of scientists, natural resource managers and policy analysts (who have the appropriate computing skills) with the necessary tools to conduct regional-scale soil carbon (C) inventories. It allows users to assess the effects of land use change on soil organic C (SOC) stocks, soil fertility and the potential for soil C sequestration. The tool was developed in conjunction with case-studies of land use and management impacts on SOC in Brazil, Jordan, Kenya and India, which represent a diversity of land use and land management patterns and are countries where sustaining soil organic matter and fertility for food security is an on-going problem. The tool was designed to run using two common desktop computers, connected via a local area network. It utilizes open-source software that is freely available. All new software and user interfaces developed for the tool are available in an open source environment allowing users to examine system details, suggest improvements or write additional modules to interface with the system. The tool incorporates three widely used models for estimating soil C dynamics: (1) the Century ecosystem model; (2) the RothC soil C decomposition model; and (3) the Intergovernmental Panel on Climate Change (IPCC) method for assessing soil C at regional scales. The tool interacts with a Soil and Terrain Digital Database (SOTER) built for the specific country or region the user intends to model. A demonstration of the tool and results from an assessment of land use change in a sample region of North America are presented. #
National and sub-national scale estimates of soil organic carbon (SOC) stocks and changes can pro... more National and sub-national scale estimates of soil organic carbon (SOC) stocks and changes can provide information land degradation risk, C sequestration possibilities and the potential sustainability of proposed land management plans. Under a GEF co-financed project, 'The GEFSOC Modelling System' was used to determine SOC stocks and projected stock change rates for four case study areas; The Brazilian Amazon, The Indo-Gangetic Plains of India, Kenya and Jordan. Each case study represented soil and vegetation types, climates and land management systems that are under represented globally, in terms of an understanding of land use and land management systems and the effects these systems have on SOC stocks. The stocks and stock change rates produced were based on detailed geo-referenced datasets of soils, climate, land use and management information. These datasets are unique as they bring together national and regional scale data on the main variables determining SOC, for four contrasting non-temperate eco-regions. They are also unique, as they include information on land management practices used in subsistence agriculture in tropical and arid areas. Implications of a greater understanding of SOC stocks and stock change rates in non-temperate areas are considered. Relevance to national land use plans are explored for each of the four case studies, in terms of sustainability, land degradation and greenhouse gas mitigation potential. Ways in which such information will aid the case study countries in fulfilling obligations under the United Nations Conventions on Climate Change, Biodiversity and Land Degradation are also considered. The need for more detailed land management data to improve SOC stock estimates in non-temperate areas is discussed. #
The GEFSOC Project developed a system for estimating soil carbon (C) stocks and changes at the na... more The GEFSOC Project developed a system for estimating soil carbon (C) stocks and changes at the national and sub-national scale. As part of the development of the system, the Century ecosystem model was evaluated for its ability to simulate soil organic C (SOC) changes in environmental conditions in the Indo-Gangetic Plains, India (IGP). Two long-term fertilizer trials (LTFT), with all necessary parameters needed to run Century, were used for this purpose: a jute (Corchorus capsularis L.), rice (Oryza sativa L.) and wheat (Triticum aestivum L.) trial at Barrackpore, West Bengal, and a rice-wheat trial at Ludhiana, Punjab. The trials represent two contrasting climates of the IGP, viz. semi-arid, dry with mean annual rainfall (MAR) of <800 mm and humid with >1600 mm. Both trials involved several different treatments with different organic and inorganic fertilizer inputs. In general, the model tended to overestimate treatment effects by approximately 15%. At the semi-arid site, modelled data simulated actual data reasonably well for all treatments, with the control and chemical N + farm yard manure showing the best agreement (RMSE = 7). At the humid site, Century performed less well. This could have been due to a range of factors including site history. During the study, Century was calibrated to simulate crop yields for the two sites considered using data from across the Indian IGP. However, further adjustments may improve model performance at these sites and others in the IGP. The availability of more longterm experimental data sets (especially those involving flooded lowland rice and triple cropping systems from the IGP) for testing and validation is critical to the application of the model's predictive capabilities for this area of the Indian sub-continent. #
The GEFSOC soil carbon modelling system was built to provide interdisciplinary teams of scientist... more The GEFSOC soil carbon modelling system was built to provide interdisciplinary teams of scientists, natural resource managers and policy analysts (who have the appropriate computing skills) with the necessary tools to conduct regional-scale soil carbon (C) inventories. It allows users to assess the effects of land use change on soil organic C (SOC) stocks, soil fertility and the potential for soil C sequestration. The tool was developed in conjunction with case-studies of land use and management impacts on SOC in Brazil, Jordan, Kenya and India, which represent a diversity of land use and land management patterns and are countries where sustaining soil organic matter and fertility for food security is an on-going problem. The tool was designed to run using two common desktop computers, connected via a local area network. It utilizes open-source software that is freely available. All new software and user interfaces developed for the tool are available in an open source environment allowing users to examine system details, suggest improvements or write additional modules to interface with the system. The tool incorporates three widely used models for estimating soil C dynamics: (1) the Century ecosystem model; (2) the RothC soil C decomposition model; and (3) the Intergovernmental Panel on Climate Change (IPCC) method for assessing soil C at regional scales. The tool interacts with a Soil and Terrain Digital Database (SOTER) built for the specific country or region the user intends to model. A demonstration of the tool and results from an assessment of land use change in a sample region of North America are presented. #
Soil organic carbon (SOC) plays a vital role in ecosystem function, determining soil fertility, w... more Soil organic carbon (SOC) plays a vital role in ecosystem function, determining soil fertility, water holding capacity and susceptibility to land degradation. In addition, SOC is related to atmospheric CO 2 levels with soils having the potential for C release or sequestration, depending on land use, land management and climate. The United Nations Convention on Climate Change and its Kyoto Protocol, and other United Nations Conventions to Combat Desertification and on Biodiversity all recognize the importance of SOC and point to the need for quantification of SOC stocks and changes. An understanding of SOC stocks and changes at the national and regional scale is necessary to further our understanding of the global C cycle, to assess the responses of terrestrial ecosystems to climate change and to aid policy makers in making land use/management decisions. Several studies have considered SOC stocks at the plot scale, but these are site specific and of limited value in making inferences about larger areas. Some studies have used empirical methods to estimate SOC stocks and changes at the regional scale, but such studies are limited in their ability to project future changes, and most have been carried out using temperate data sets. The computational method outlined by the Intergovernmental Panel on Climate Change (IPCC) has been used to estimate SOC stock changes at the regional scale in several studies, including a recent study considering five contrasting eco regions. This 'one step' approach fails to account for the dynamic manner in which SOC changes are likely to occur following changes in land use and land management.
National and sub-national scale estimates of soil organic carbon (SOC) stocks and changes can pro... more National and sub-national scale estimates of soil organic carbon (SOC) stocks and changes can provide information land degradation risk, C sequestration possibilities and the potential sustainability of proposed land management plans. Under a GEF co-financed project, 'The GEFSOC Modelling System' was used to determine SOC stocks and projected stock change rates for four case study areas; The Brazilian Amazon, The Indo-Gangetic Plains of India, Kenya and Jordan. Each case study represented soil and vegetation types, climates and land management systems that are under represented globally, in terms of an understanding of land use and land management systems and the effects these systems have on SOC stocks. The stocks and stock change rates produced were based on detailed geo-referenced datasets of soils, climate, land use and management information. These datasets are unique as they bring together national and regional scale data on the main variables determining SOC, for four contrasting non-temperate eco-regions. They are also unique, as they include information on land management practices used in subsistence agriculture in tropical and arid areas. Implications of a greater understanding of SOC stocks and stock change rates in non-temperate areas are considered. Relevance to national land use plans are explored for each of the four case studies, in terms of sustainability, land degradation and greenhouse gas mitigation potential. Ways in which such information will aid the case study countries in fulfilling obligations under the United Nations Conventions on Climate Change, Biodiversity and Land Degradation are also considered. The need for more detailed land management data to improve SOC stock estimates in non-temperate areas is discussed. #
Land use and land cover changes in the Brazilian Amazon have major implications for regional and ... more Land use and land cover changes in the Brazilian Amazon have major implications for regional and global carbon (C) cycling. Cattle pasture represents the largest single use (about 70%) of this once-forested land in most of the region. The main objective of this study was to evaluate the accuracy of the RothC and Century models at estimating soil organic C (SOC) changes under forest-to-pasture conditions in the Brazilian Amazon. We used data from 11 site-specific 'forest to pasture' chronosequences with the Century Ecosystem Model (Century 4.0) and the Rothamsted C Model (RothC 26.3). The models predicted that forest clearance and conversion to well managed pasture would cause an initial decline in soil C stocks (0-20 cm depth), followed in the majority of cases by a slow rise to levels exceeding those under native forest. One exception to this pattern was a chronosequence in Suia-Missu, which is under degraded pasture. In three other chronosequences the recovery of soil C under pasture appeared to be only to about the same level as under the previous forest. Statistical tests were applied to determine levels of agreement between simulated SOC stocks and observed stocks for all the sites within the 11 chronosequences. The models also provided reasonable estimates (coefficient of correlation = 0.8) of the microbial biomass C in the 0-10 cm soil layer for three chronosequences, when compared with available measured data. The Century model adequately predicted the magnitude and the overall trend in d 13 C for the six chronosequences where measured d 13 C data were available. This study gave independent tests of model performance, as no adjustments were made to the models to generate outputs. Our results suggest that modelling techniques can be successfully used for monitoring soil C stocks and changes, allowing both the identification of current patterns in the soil and the projection of future conditions. Results were used and discussed not only to evaluate soil C dynamics but also to indicate soil C sequestration opportunities for the Brazilian Amazon region. Moreover, modelling studies in these 'forest to pasture' systems have important applications, for example, the calculation of CO 2 emissions from land use change in national greenhouse gas inventories. # Temp: mean annual air temperature (8C); Prec: mean annual precipitation (mm); B. briz: Brachiaria brizantha; B. hum: Brachiaria humidicula; B. decum: Brachiaria decumbens; P. max: Panicum maximum.
The GEFSOC Soil Carbon Modeling System was assembled under a co-financed project supported by the... more The GEFSOC Soil Carbon Modeling System was assembled under a co-financed project supported by the United Nations Environment Programme (UNEP) Global Environmental Facility (GEF) and the US Agency for International Development. The tool was built to provide scientists, ...
National and sub-national scale estimates of soil organic carbon (SOC) stocks and changes can pro... more National and sub-national scale estimates of soil organic carbon (SOC) stocks and changes can provide information land degradation risk, C sequestration possibilities and the potential sustainability of proposed land management plans. Under a GEF co-financed project, 'The GEFSOC Modelling System' was used to determine SOC stocks and projected stock change rates for four case study areas; The Brazilian Amazon, The Indo-Gangetic Plains of India, Kenya and Jordan. Each case study represented soil and vegetation types, climates and land management systems that are under represented globally, in terms of an understanding of land use and land management systems and the effects these systems have on SOC stocks. The stocks and stock change rates produced were based on detailed geo-referenced datasets of soils, climate, land use and management information. These datasets are unique as they bring together national and regional scale data on the main variables determining SOC, for four contrasting non-temperate eco-regions. They are also unique, as they include information on land management practices used in subsistence agriculture in tropical and arid areas. Implications of a greater understanding of SOC stocks and stock change rates in non-temperate areas are considered. Relevance to national land use plans are explored for each of the four case studies, in terms of sustainability, land degradation and greenhouse gas mitigation potential. Ways in which such information will aid the case study countries in fulfilling obligations under the United Nations Conventions on Climate Change, Biodiversity and Land Degradation are also considered. The need for more detailed land management data to improve SOC stock estimates in non-temperate areas is discussed. #
Under the United Nations Framework Convention on Climate Change (UNFCCC), Non-Annex 1 countries s... more Under the United Nations Framework Convention on Climate Change (UNFCCC), Non-Annex 1 countries such as Kenya are obliged to report green house gas (GHG) emissions from all sources where possible, including those from soils as a result of changes in land use or land management. At present, the convention encourages countries to estimate emissions using the most advanced methods possible, given the country circumstances and resources. Estimates of soil organic carbon (SOC) stocks and changes were made for Kenya using the Global Environment Facility Soil Organic Carbon (GEFSOC) Modelling System. The tool conducts analysis using three methods: (1) the Century general ecosystem model; (2) the RothC soil C decomposition model; and (3) the Intergovernmental Panel on Climate Change (IPCC) method for assessing soil C at regional scales. The required datasets included: land use history, monthly mean precipitation, monthly mean minimum and maximum temperatures for all the agro-climatic zones of Kenya and historical vegetation cover. Soil C stocks of 1.4-2.0 Pg (0-20 cm), compared well with a Soil and Terrain (SOTER) based approach that estimated $1.8-2.0 Pg (0-30 cm). In 1990 48% of the country had SOC stocks of <18 t C ha À1 and 20% of the country had SOC stocks of 18-30 t C ha À1 , whereas in 2000 56% of the country had SOC stocks of <18 t C ha À1 and 31% of the country had SOC stocks of 18-30 t C ha À1 . Conversion of natural vegetation to annual crops led to the greatest soil C losses. Simulations suggest that soil C losses remain substantial throughout the modelling period of 1990-2030. All three methods involved in the GEFSOC System estimated that there would be a net loss of soil C between 2000 and 2030 in Kenya. The decline was more marked with RothC than with Century or the IPCC method. In non-hydric soils the SOC change rates were more pronounced in high sandy soils compared to high clay soils in most land use systems. #
RothC and Century are two of the most widely used soil organic matter (SOM) models. However there... more RothC and Century are two of the most widely used soil organic matter (SOM) models. However there are few examples of specific parameterisation of these models for environmental conditions in East Africa. The aim of this study was therefore, to evaluate the ability of RothC and the Century to estimate changes in soil organic carbon (SOC) resulting from varying land
The terrestrial biosphere is an important global carbon (C) sink, with the potential to drive lar... more The terrestrial biosphere is an important global carbon (C) sink, with the potential to drive large positive climate feedbacks. Thus a better understanding of interactions between land use change, climate change and the terrestrial biosphere is crucial in planning future land management options. Climate change has the potential to alter terrestrial C storage since changes in temperature, precipitation and carbon dioxide (CO 2 ) concentrations could affect net primary production (NPP), C inputs to soil, and soil C decomposition rates. Climate change could also act as a driver for land use change, thus further altering terrestrial C fluxes. The net balance of these different effects varies considerably between regions and hence the case studies presented in this paper (the GEFSOC project countries Kenya, Jordan, Brazil, and India) provide a unique opportunity to study climate impacts on terrestrial C storage. This paper first presents predicted changes in climate for the four case study countries from a coupled climate-C cycle Global Circulation Model (HadCM3LC), followed by predicted changes in vegetation type, NPP and soil C storage. These very coarse assessments provide an initial estimate of large-scale effects. A more detailed study of climate impacts on soil C storage in the Brazilian Amazon is provided as an example application of the GEFSOC system. Interestingly in the four cases studied here precipitation seems to control the sign of the soil C changes under climate change with wetter conditions resulting in higher soil C stocks and drier conditions in lower soil C stocks, presumably because increased NPP in wetter conditions here will override any increase in respiration. In contrast, globally, it seems to be temperature that controls changes in C stocks under climate change. Even if there is a slight increase in precipitation globally, a decrease in C stocks is predicted-in other words, the regional response to precipitation differs from the global response. The reason for this may be that whilst temperature increases under climate change were predicted everywhere, the nature of precipitation changes varies greatly between regions. Crown
The GEFSOC Project developed a system for estimating soil carbon (C) stocks and changes at the na... more The GEFSOC Project developed a system for estimating soil carbon (C) stocks and changes at the national and sub-national scale. As part of the development of the system, the Century ecosystem model was evaluated for its ability to simulate soil organic C (SOC) changes in environmental conditions in the Indo-Gangetic Plains, India (IGP). Two long-term fertilizer trials (LTFT), with all necessary parameters needed to run Century, were used for this purpose: a jute (Corchorus capsularis L.), rice (Oryza sativa L.) and wheat (Triticum aestivum L.) trial at Barrackpore, West Bengal, and a rice-wheat trial at Ludhiana, Punjab. The trials represent two contrasting climates of the IGP, viz. semi-arid, dry with mean annual rainfall (MAR) of <800 mm and humid with >1600 mm. Both trials involved several different treatments with different organic and inorganic fertilizer inputs. In general, the model tended to overestimate treatment effects by approximately 15%. At the semi-arid site, modelled data simulated actual data reasonably well for all treatments, with the control and chemical N + farm yard manure showing the best agreement (RMSE = 7). At the humid site, Century performed less well. This could have been due to a range of factors including site history. During the study, Century was calibrated to simulate crop yields for the two sites considered using data from across the Indian IGP. However, further adjustments may improve model performance at these sites and others in the IGP. The availability of more longterm experimental data sets (especially those involving flooded lowland rice and triple cropping systems from the IGP) for testing and validation is critical to the application of the model's predictive capabilities for this area of the Indian sub-continent. #
Land use and land cover changes in the Brazilian Amazon have major implications for regional and ... more Land use and land cover changes in the Brazilian Amazon have major implications for regional and global carbon (C) cycling. Cattle pasture represents the largest single use (about 70%) of this once-forested land in most of the region. The main objective of this study was to evaluate the accuracy of the RothC and Century models at estimating soil organic C (SOC) changes under forest-to-pasture conditions in the Brazilian Amazon. We used data from 11 site-specific 'forest to pasture' chronosequences with the Century Ecosystem Model (Century 4.0) and the Rothamsted C Model (RothC 26.3). The models predicted that forest clearance and conversion to well managed pasture would cause an initial decline in soil C stocks (0-20 cm depth), followed in the majority of cases by a slow rise to levels exceeding those under native forest. One exception to this pattern was a chronosequence in Suia-Missu, which is under degraded pasture. In three other chronosequences the recovery of soil C under pasture appeared to be only to about the same level as under the previous forest. Statistical tests were applied to determine levels of agreement between simulated SOC stocks and observed stocks for all the sites within the 11 chronosequences. The models also provided reasonable estimates (coefficient of correlation = 0.8) of the microbial biomass C in the 0-10 cm soil layer for three chronosequences, when compared with available measured data. The Century model adequately predicted the magnitude and the overall trend in d 13 C for the six chronosequences where measured d 13 C data were available. This study gave independent tests of model performance, as no adjustments were made to the models to generate outputs. Our results suggest that modelling techniques can be successfully used for monitoring soil C stocks and changes, allowing both the identification of current patterns in the soil and the projection of future conditions. Results were used and discussed not only to evaluate soil C dynamics but also to indicate soil C sequestration opportunities for the Brazilian Amazon region. Moreover, modelling studies in these 'forest to pasture' systems have important applications, for example, the calculation of CO 2 emissions from land use change in national greenhouse gas inventories. # Temp: mean annual air temperature (8C); Prec: mean annual precipitation (mm); B. briz: Brachiaria brizantha; B. hum: Brachiaria humidicula; B. decum: Brachiaria decumbens; P. max: Panicum maximum.
The GEFSOC soil carbon modelling system was built to provide interdisciplinary teams of scientist... more The GEFSOC soil carbon modelling system was built to provide interdisciplinary teams of scientists, natural resource managers and policy analysts (who have the appropriate computing skills) with the necessary tools to conduct regional-scale soil carbon (C) inventories. It allows users to assess the effects of land use change on soil organic C (SOC) stocks, soil fertility and the potential for soil C sequestration. The tool was developed in conjunction with case-studies of land use and management impacts on SOC in Brazil, Jordan, Kenya and India, which represent a diversity of land use and land management patterns and are countries where sustaining soil organic matter and fertility for food security is an on-going problem. The tool was designed to run using two common desktop computers, connected via a local area network. It utilizes open-source software that is freely available. All new software and user interfaces developed for the tool are available in an open source environment allowing users to examine system details, suggest improvements or write additional modules to interface with the system. The tool incorporates three widely used models for estimating soil C dynamics: (1) the Century ecosystem model; (2) the RothC soil C decomposition model; and (3) the Intergovernmental Panel on Climate Change (IPCC) method for assessing soil C at regional scales. The tool interacts with a Soil and Terrain Digital Database (SOTER) built for the specific country or region the user intends to model. A demonstration of the tool and results from an assessment of land use change in a sample region of North America are presented. #
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