Predicted soil organic carbon stocks and changes in Kenya between 1990 and 2030

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 similar to .8-2.0 Pg (0-30 cm). In 1990 48% of the country had SOC stocks of < 18 t C ha(-1) and 20% of the country had SOC stocks of 18-30 t C ha(-1), whereas in 2000 56% of the country had SOC stocks of < 18 t C ha(-1) and 31% of the country had SOC stocks of 18-30 t C ha(-1). 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. (C) 2007 Elsevier B.V. All rights reserved.

National and sub-national assessments of soil organic carbon stocks and changes: The GEFSOC modelling system

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, 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. A dynamic modelling approach allows estimates to be made in a manner that accounts for the underlying processes leading to SOC change. Ecosystem models, designed for site scale applications can be linked to spatial databases, giving spatially explicit results that allow geographic areas of change in SOC stocks to be identified. Some studies have used variations on this approach to estimate SOC stock changes at the sub-national and national scale for areas of the USA and Europe and at the watershed scale for areas of Mexico and Cuba. However, a need remained for a national and regional scale, spatially explicit system that is generically applicable and can be applied to as wide a range of soil types, climates and land uses as possible. The Global Environment Facility Soil Organic Carbon (GEFSOC) Modelling System was developed in response to this need. The GEFSOC system allows estimates of SOC stocks and changes to be made for diverse conditions, providing essential information for countries wishing to take part in an emerging C market, and bringing us closer to an understanding of the future role of soils in the global C cycle. (C) 2007 Elsevier B.V. All rights reserved.

Land use and climate change impacts on soil organic carbon stocks in semi-arid Spain

Purpose The sensitivity of soil organic carbon to global change drivers, according to the depth profile, is receiving increasing attention because of its importance in the global carbon cycle and its potential feedback to climate change. A better knowledge of the vertical distribution of SOC and its controlling factors—the aim of this study—will help scientists predict the consequences of global change. Materials and methods The study area was the Murcia Province (S.E. Spain) under semiarid Mediterranean conditions. The database used consists of 312 soil profiles collected in a systematic grid, each 12 km2 covering a total area of 11,004 km2. Statistical analysis to study the relationships between SOC concentration and control factors in different soil use scenarios was conducted at fixed depths of 0–20, 20–40, 40–60, and 60–100 cm. Results and discussion SOC concentration in the top 40 cm ranged between 6.1 and 31.5 g kg−1, with significant differences according to land use, soil type and lithology, while below this depth, no differences were observed (SOC concentration 2.1–6.8 g kg−1). The ANOVA showed that land use was the most important factor controlling SOC concentration in the 0–40 cm depth. Significant differences were found in the relative importance of environmental and textural factors according to land use and soil depth. In forestland, mean annual precipitation and texture were the main predictors of SOC, while in cropland and shrubland, the main predictors were mean annual temperature and lithology. Total SOC stored in the top 1 m in the region was about 79 Tg with a low mean density of 7.18 kg Cm−3. The vertical distribution of SOC was shallower in forestland and deeper in cropland. A reduction in rainfall would lead to SOC decrease in forestland and shrubland, and an increase of mean annual temperature would adversely affect SOC in croplands and shrubland. With increasing depth, the relative importance of climatic factors decreases and texture becomes more important in controlling SOC in all land uses. Conclusions Due to climate change, impacts will be much greater in surface SOC, the strategies for C sequestration should be focused on subsoil sequestration, which was hindered in forestland due to bedrock limitations to soil depth. In these conditions, sequestration in cropland through appropriate management practices is recommended.

Soil organic carbon dynamics under perennial energy crops

The European renewable energy directive 2009/28/EC (E.C. 2009) provides a legislative framework for reducing GHG emissions by 20%, while achieving a 20% share of energy from renewable sources by 2020. Perennial energy crops could significantly contribute to limit GHG emissions through replacing equivalent fossil fuels and by sequestering a considerable amount of carbon into the soil through the large amounts of belowground biomass produced. The objective of this study is to evaluate the effects of land use change that perennial energy crops have on croplands (switchgrass) and marginal grasslands (miscanthus). For that purpose above and belowground biomass, SOC variation and Net Ecosystem Exchange were evaluated after five years of growth. At aboveground level both crops produced high biomass under cropland conditions as well as under marginal soils. At belowground level they also produced large amounts of biomass, but no significant influences on SOC in the upper layer (0-30 cm) were found. This is probably because of the "priming effect" that caused fast carbon substitution. In switchgrass only it was found a significant SOC increase in deeper layers (30-60 cm), while in the whole soil profile (0-60 cm) SOC increased from 42 to 51 ha-1. However, the short experimental periods (for both switchgrass and miscanthus), in which land use change was evaluated, do not permit to determine the real capacity of perennial energy crops to accumulate SOC. In conclusion the large amounts of belowground biomass enhanced the SOC dynamic through the priming effect resulting in increased SOC in cropland but not in marginal grassland.

Land use change to perennial energy crops in Northern Italy: Effects on soil organic carbon sequestration and distribution, soil enzyme activities and microbial communities.

Studies on soil organic carbon (SOC) sequestration in perennial energy crops are available for North-Central Europe, while there is insufficient information for Southern Europe. This research was conducted in the Po Valley, a Mediterranean-temperate zone characterised by low SOC levels, due to intensive management. The aim was to assess the factors influencing SOC sequestration and its distribution through depth and within soil fractions, after a 9-year old conversion from two annual systems to Miscanthus (Miscanthus × giganteus) and giant reed (Arundo donax). The 13C natural abundance was used to evaluate the amount of SOC in annual and perennial species, and determine the percentage of carbon derived from perennial crops. SOC was significantly higher under perennial species, especially in the topsoil (0-0.15 m). After 9 years, the amount of C derived from Miscanthus was 18.7 Mg ha-1, mostly stored at 0-0.15 m, whereas the amount of C derived from giant reed was 34.7 Mg ha-1, evenly distributed through layers. Physical soil fractionation was combined with 13C abundance analysis. C derived from perennial crops was mainly found in macroaggregates. Under giant reed, more newly derived-carbon was stored in microaggregates and mineral fraction than under Miscanthus. A molecular approach based on denaturing gradient gel electrophoresis (DGGE) allowed to evaluate changes on microbial community, after the introduction of perennial crops. Functional aspects were investigated by determining relevant soil enzymes (β-glucosidase, urease, alkaline phosphatase). Perennial crops positively stimulated these enzymes, especially in the topsoil. DGGE profiles revealed that community richness was higher in perennial crops; Shannon index of diversity was influenced only by depth. In conclusion, Miscanthus and giant reed represent a sustainable choice for the recovery of soils exhausted by intensive management, also in Mediterranean conditions and this is relevant mainly because this geographical area is notoriously characterised by a rapid turnover of SOC.

Prediction of soil organic carbon for Ethiopian highlands using soil spectroscopy

Soil spectroscopy was applied for predicting soil organic carbon (SOC) in the highlands of Ethiopia. Soil samples were acquired from Ethiopia’s National Soil Testing Centre and direct field sampling. The reflectance of samples was measured using a FieldSpec 3 diffuse reflectance spectrometer. Outliers and sample relation were evaluated using principal component analysis (PCA) and models were developed through partial least square regression (PLSR). For nine watersheds sampled, 20% of the samples were set aside to test prediction and 80% were used to develop calibration models. Depending on the number of samples per watershed, cross validation or independent validation were used.The stability of models was evaluated using coefficient of determination (R2), root mean square error (RMSE), and the ratio performance deviation (RPD). The R2 (%), RMSE (%), and RPD, respectively, for validation were Anjeni (88, 0.44, 3.05), Bale (86, 0.52, 2.7), Basketo (89, 0.57, 3.0), Benishangul (91, 0.30, 3.4), Kersa (82, 0.44, 2.4), Kola tembien (75, 0.44, 1.9),Maybar (84. 0.57, 2.5),Megech (85, 0.15, 2.6), andWondoGenet (86, 0.52, 2.7) indicating that themodels were stable. Models performed better for areas with high SOC values than areas with lower SOC values. Overall, soil spectroscopy performance ranged from very good to good.

Visible near infra-red (VisNIR) spectroscopy for predicting soil organic carbon in Ethiopia

Over the past few decades, the advantages of the visible-near infra-red (VisNIR) diffuse reflectance spectrometer (DRS) method have enabled prediction of soil organic carbon (SOC). In this study, SOC was predicted using regression models for samples taken from three sites (Gununo, Maybar and Anjeni) in Ethiopia. SOC was characterized in laboratory using conventional wet chemistry and VisNIR-DRS methods. Principal component analysis (PCA), principal component regression (PCR) and partial least square regression (PLS) models were developed using Unscrambler X 10.2. PCA results show that the first two components accounted for a minimum of 96% variation which increased for individual sites and with data treatments. Correlation (r), coefficient of determination (R2) and residual prediction deviation (RPD) were used to rate four models built. PLS model (r, R2, RPD) values for Anjeni were 0.9, 0.9 and 3.6; for Gununo values 0.6, 0.3 and 1.2; for Maybar values 0.6, 0.3 and 0.9, and for the three sites values 0.7, 0.6 and 1.5, respectively. PCR model values (r, R2, RPD) for Anjeni were 0.9, 0.8 and 2.7; for Gununo values 0.5, 0.3 and 1; for Maybar values 0.5, 0.1 and 0.7, and for the three sites values 0.7, 0.5 and 1.2, respectively. Comparison and testing of models shows superior performance of PLS to PCR. Models were rated as very poor (Maybar), poor (Gununo and three sites) and excellent (Anjeni). A robust model, Anjeni, is recommended for prediction of SOC in Ethiopia.

Meta-Analysis of Long-Term Land Management Effect on Soil Organic Carbon (SOC) in Ethiopia

The role of Soil Organic Carbon (SOC) in mitigating climate change, indicating soil quality and ecosystem function has created research interested to know the nature of SOC at landscape level. The objective of this study was to examine variation and distribution of SOC in a long-term land management at a watershed and plot level. This study was based on meta-analysis of three case studies and 128 surface soil samples from Ethiopia. Three sites (Gununo, Anjeni and Maybar) were compared after considering two Land Management Categories (LMC) and three types of land uses (LUT) in quasi-experimental design. Shapiro-Wilk tests showed non-normal distribution (p = 0.002, a = 0.05) of the data. SOC median value showed the effect of long-term land management with values of 2.29 and 2.38 g kg-1 for less and better-managed watersheds, respectively. SOC values were 1.7, 2.8 and 2.6 g kg-1 for Crop (CLU), Grass (GLU) and Forest Land Use (FLU), respectively. The rank order for SOC variability was FLU>GLU>CLU. Mann-Whitney U and Kruskal-Wallis test showed a significant difference in the medians and distribution of SOC among the LUT, between soil profiles (p<0.05, confidence interval 95%, a = 0.05) while it is not significant (p>0.05) for LMC. The mean and sum rank of Mann Whitney U and Kruskal Wallis test also showed the difference at watershed and plot level. Using SOC as a predictor, cross-validated correct classification with discriminant analysis showed 46 and 49% for LUT and LMC, respectively. The study showed how to categorize landscapes using SOC with respect to land management for decision-makers.

Managing Soil Organic Carbon: A Farm Perspective

Farming practices that lead to declining returns and inputs of carbon to soils pose a threat to key soil functions. The EU FP 7 interdisciplinary project Smart SOIL is using scientific testing and modeling to identify management practices that can optimize soil carbon storage and crop productivity. A consultation with advisors and policymakers in six European case study regions seeks to identify barriers to, and incentives for, uptake of such practices. Results from preliminary interviews are reported. Overall advisor and farmer awareness of management practices specifically directed towards soil carbon. is low. Most production- related decisions are taken in the short term, but managing soil carbon needs a long- term approach. Key barriers to uptake of practices include: perceived scientifi c uncertainty about the effi cacy of practices; lack of real life ?best practice? examples to show farmers; diffi culty in demonstrating the positive effects of soil carbon management practices and economic benefi ts over a long time scale; and advisors being unable to provide suitable advice due to inadequate information or training. Most farmers are unconvinced of the economic benefi ts of practices for managing soil carbon. Incentives are therefore needed, either as subsidies or as evidence of the cost effectiveness of practices. All new measures and advice should be integrated into existing programmes to avoid a fragmented policy approach.

Potential responses of soil organic carbon to global environmental change

Recent improvements in our understanding of the dynamics of soil carbon have shown that 20–40% of the approximately 1,500 Pg of C stored as organic matter in the upper meter of soils has turnover times of centuries or less. This fast-cycling organic matter is largely comprised of undecomposed plant material and hydrolyzable components associated with mineral surfaces. Turnover times of fast-cycling carbon vary with climate and vegetation, and range from <20 years at low latitudes to >60 years at high latitudes. The amount and turnover time of C in passive soil carbon pools (organic matter strongly stabilized on mineral surfaces with turnover times of millennia and longer) depend on factors like soil maturity and mineralogy, which, in turn, reflect long-term climate conditions. Transient sources or sinks in terrestrial carbon pools result from the time lag between photosynthetic uptake of CO2 by plants and the subsequent return of C to the atmosphere through plant, heterotrophic, and microbial respiration. Differential responses of primary production and respiration to climate change or ecosystem fertilization have the potential to cause significant interrannual to decadal imbalances in terrestrial C storage and release. Rates of carbon storage and release in recently disturbed ecosystems can be much larger than rates in more mature ecosystems. Changes in disturbance frequency and regime resulting from future climate change may be more important than equilibrium responses in determining the carbon balance of terrestrial ecosystems.