993 resultados para Soil monitoring networks, Soil organic carbon, Modeling, Sampling design
Resumo:
Highly weathered soils represent about 3 billion ha of the tropical region. Oxisols represent about 60% of the Brazilian territory (more than 5 million km 2), in areas of great agricultural importance. Soil organic carbon (SOC) can be responsible for more than 80% of the cation exchange capacity (CEC) of highly weathered soils, such as Oxisols and Ultisols. The objective of this study was to estimate the contribution of the SOC to the CEC of Brazilian soils from different orders. Surface samples (0.0 to 0.2 m) of 30 uncultivated soils (13 Oxisols, 6 Ultisols, 5 Alfisols, 3 Entisols, I Histosol, 1 Inceptisol. and I Molisol), under native forests and from reforestation sites from Sao Paulo State, Brazil, were collected in order to obtain a large variation of (electro)chemical, physical, and mineralogical soil attributes. Total content of SOC was quantified by titulometric and colorimetric methods. Effective cation exchange capacity (ECEC) was obtained by two methods: the indirect method-summation-estimated the ECECi from the sum of basic cations (Ca+ Mg+ K+ Na) and exchangeable Al; and the direct ECECd obtained by the compulsive exchange method, using unbuffered BaCl2 solution. The contribution of SOC to the soil CEC was estimated by the Bennema statistical method. The amount of SOC var ied from 6.6 g kg(-1) to 213.4 g kg(-1). while clay contents varied from 40 g kg(-1) to 716 g kg(-1). Soil organic carbon contents were strongly associated to the clay contents, suggesting that clay content was the primary variable in controling the variability of SOC contents in the samples. Cation exchange capacity varied from 7.0 mmol(c) kg(-1) to 137.8 mmol(c) kg(-1) and had a positive Correlation with SOC. The mean contribution (per grain) of the SOC (1.64 mmol(c)) for the soil CEC was more than 44 times higher than the contribution of the clay fraction (0.04 mmol(c),). A regression model that considered the SOC content as the only significant variable explained 60% of the variation in the soil total CEC. The importance of SOC was related to soil pedogenetic process, since its contribution to the soil CEC was more evident in Oxisols with predominance of Fe and Al (oxihydr)oxides in the mineral fraction or in Ultisols, that presented illuviated clay. The influence of SOC in the sign and in the magnitude of the net charge of soils reinforce the importance of agricultural management systems that preserve high levels of SOC, in order to improve their sustainability.
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ABSTRACT The soil carbon under Amazonian forests has an important roles in global changing, making information on the soil content and depths of these stocks are considerable interest in efforts to quantify soil carbon emissions to the atmosphere.This study quantified the content and soil organic carbon stock under primary forest up to 2 m depth, at different topographic positions, at Cuieiras Biological Reserve, Manaus/ ZF2, km 34, in the Central Amazon, evaluating the soil attributes that may influence the permanence of soil carbon. Soil samples were collected along a transect of 850 m on topographic gradient Oxisol (plateau), Ultisol (slope) and Spodosol (valley). The stocks of soil carbon were obtained by multiplying the carbon content, soil bulk density and trickiness of soil layers. The watershed was delimited by using STRM and IKONOS images and the carbon contend obtained in the transects was extrapolated as a way to evaluate the potential for carbon stocks in an area of 2678.68 ha. The total SOC was greater in Oxisol followed by Spodosol and Ultisol. It was found direct correlations between the SOC and soil physical attributes. Among the clay soils (Oxisol and Ultisol), the largest stocks of carbon were observed in Oxisol at both the transect (90 to 175.5 Mg C ha-1) as the level of watershed (100.2 to 195.2 Mg C ha-1). The carbon stocks under sandy soil (Spodosol) was greater to clay soils along the transect (160-241 Mg C ha-1) and near them in the Watershed (96.90 to 146.01 Mg C ha-1).
Resumo:
Judged by their negative nutrient balances, low soil cover and low productivity, the predominant agro-pastoral farming systems in the Sudano-Sahelian zone of West Africa are highly unsustainable for crop production intensification. With kaolinite as the main clay type, the cation exchange capacity of the soils in this region, often less than 1 cmol_c kg^-1 soil, depends heavily on the organic carbon (Corg) content. However, due to low carbon sequestration and to the microbe, termite and temperature-induced rapid turnover rates of organic material in the present land-use systems, Corg contents of the topsoil are very low, ranging between 1 and 8 g kg^-1 in most soils. For sustainable food production, the availability of phosphorus (P) and nitrogen (N) has to be increased considerably in combination with an improvement in soil physical properties. Therefore, the adoption of innovative management options that help to stop or even reverse the decline in Corg typically observed after cultivating bush or rangeland is of utmost importance. To maintain food production for a rapidly growing population, targeted applications of mineral fertilisers and the effective recycling of organic amendments as crop residues and manure are essential. Any increase in soil cover has large effects in reducing topsoil erosion by wind and water and favours the accumulation of wind-blown dust high in bases which in turn improves P availability. In the future decision support systems, based on GIS, modelling and simulation should be used to combine (i) available fertiliser response data from on-station and on-farm research, (ii) results on soil productivity restoration with the application of mineral and organic amendments and (iii) our present understanding of the cause-effect relationships governing the prevailing soil degradation processes. This will help to predict the effectiveness of regionally differentiated soil fertility management approaches to maintain or even increase soil Corg levels.
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Estimates of soil organic carbon (SOC) stocks and changes under different land use systems can help determine vulnerability to land degradation. Such information is important for countries in and areas with high susceptibility to desertification. SOC stocks, and predicted changes between 2000 and 2030, were determined at the national scale for Jordan using The Global Environment Facility Soil Organic Carbon (GEFSOC) Modelling System. For the purpose of this study, Jordan was divided into three natural regions (The Jordan Valley, the Uplands and the Badia) and three developmental regions (North, Middle and South). Based on this division, Jordan was divided into five zones (based on the dominant land use): the Jordan Valley, the North Uplands, the Middle Uplands, the South Uplands and the Badia. This information was merged using GIS, along with a map of rainfall isohyets, to produce a map with 498 polygons. Each of these was given a unique ID, a land management unit identifier and was characterized in terms of its dominant soil type. Historical land use data, current land use and future land use change scenarios were also assembled, forming major inputs of the modelling system. The GEFSOC Modelling System was then run to produce C stocks in Jordan for the years 1990, 2000 and 2030. The results were compared with conventional methods of estimating carbon stocks, such as the mapping based SOTER method. The results of these comparisons showed that the model runs are acceptable, taking into consideration the limited availability of long-term experimental soil data that can be used to validate them. The main findings of this research show that between 2000 and 2030, SOC may increase in heavily used areas under irrigation and will likely decrease in grazed rangelands that cover most of Jordan giving an overall decrease in total SOC over time if the land is indeed used under the estimated forms of land use. (C) 2007 Elsevier B.V. All rights reserved.
Modelled soil organic carbon stocks and changes in the Indo-Gangetic Plains, India from 1980 to 2030
Resumo:
The Global Environment Facility co-financed Soil Organic Carbon (GEFSOC) Project developed a comprehensive modelling system for predicting soil organic carbon (SOC) stocks and changes over time. This research is an effort to predict SOC stocks and changes for the Indian, Indo-Gangetic Plains (IGP), an area with a predominantly rice (Oryza sativa) - wheat (Triticum aestivum) cropping system, using the GEFSOC Modelling System and to compare output with stocks generated using mapping approaches based on soil survey data. The GEFSOC Modelling System predicts an estimated SOC stock for the IGP, India of 1.27, 1.32 and 1.27 Pg for 1990, 2000 and 2030, respectively, in the top 20 cm of soil. The SOC stock using a mapping approach based on soil survey data was 0.66 and 0.88 Pg for 1980 and 2000, respectively. The SOC stock estimated using the GEFSOC Modelling System is higher than the stock estimated using the mapping approach. This is due to the fact that while the GEFSOC System accounts for variation in crop input data (crop management), the soil mapping approach only considers regional variation in soil texture and wetness. The trend of overall change in the modelled SOC stock estimates shows that the IGP, India may have reached an equilibrium following 30-40 years of the Green Revolution. This can be seen in the SOC stock change rates. Various different estimation methods show SOC stocks of 0.57-1.44 Pg C for the study area. The trend of overall change in C stock assessed from the soil survey data indicates that the soils of the IGP, India may store a projected 1.1 Pg of C in 2030. (C) 2007 Elsevier B.V. All rights reserved.
Resumo:
Currently we have little understanding of the impacts of land use change on soil C stocks in the Brazilian Amazon. Such information is needed to determine impacts'6n the global C cycle and the sustainability of agricultural systems that are replacing native forest. The aim of this study was to predict soil carbon stocks and changes in the Brazilian Amazon during the period between 2000 and 2030, using the GEFSOC soil carbon (C) modelling system. In order to do so, we devised current and future land use scenarios for the Brazilian Amazon, taking into account: (i) deforestation, rates from the past three decades, (ii) census data on land use from 1940 to 2000, including the expansion and intensification of agriculture in the region, (iii) available information on management practices, primarily related to well managed pasture versus degraded pasture and conventional systems versus no-tillage systems for soybean (Glycine max) and (iv) FAO predictions on agricultural land use and land use changes for the years 2015 and 2030. The land use scenarios were integrated with spatially explicit soils data (SOTER database), climate, potential natural vegetation and land management units using the recently developed GEFSOC soil C modelling system. Results are presented in map, table and graph form for the entire Brazilian Amazon for the current situation (1990 and 2000) and the future (2015 and 2030). Results include soil organic C (SOC) stocks and SOC stock change rates estimated by three methods: (i) the Century ecosystem model, (ii) the Rothamsted C model and (iii) the intergovernmental panel on climate change (IPCC) method for assessing soil C at regional scale. In addition, we show estimated values of above and belowground biomass for native vegetation, pasture and soybean. The results on regional SOC stocks compare reasonably well with those based on mapping approaches. The GEFSOC system provided a means of efficiently handling complex interactions among biotic-edapho-climatic conditions (> 363,000 combinations) in a very large area (similar to 500 Mha) such as the Brazilian Amazon. All of the methods used showed a decline in SOC stock for the period studied; Century and RothC simulated values for 2030 being about 7% lower than those in 1990. Values from Century and RothC (30,430 and 25,000 Tg for the 0-20 cm layer for the Brazilian Amazon region were higher than those obtained from the IPCC system (23,400 Tg in the 0-30 cm layer). Finally; our results can help understand the major biogeochemical cycles that influence soil fertility and help devise management strategies that enhance the sustainability of these areas and thus slow further deforestation. (C) 2007 Elsevier B.V. All rights reserved.
Resumo:
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.
Resumo:
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.
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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.
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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.
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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.
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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.