Variance In Soil Organic Carbon Research Articles

The hidden risk: Changes in functional potentials of microbial keystone taxa under global climate change jeopardizing soil carbon storage in alpine grasslands

Climate change is endangering the soil carbon stock of alpine grasslands on the Qinghai-Tibetan Plateau (QTP), but the limited comprehension regarding the mechanisms that sustain carbon storage under hydrothermal changes increases the uncertainty associated with this finding. Here, we examined the relative abundance of soil microbial keystone taxa and their functional potentials, as well as their influence on soil carbon storage with increased precipitation across alpine grasslands on the QTP, China. The findings indicate that alterations in precipitation significantly decreased the relative abundance of the carbon degradation potentials of keystone taxa, such as chemoheterotrophs. The inclusion of keystone taxa and their internal functional potentials in the two best alternative models explained 70% and 63% of the variance in soil organic carbon (SOC) density, respectively. Moreover, we found that changes in chemoheterotrophs had negative effects on SOC density as indicated by a structural equation model, suggesting that some specialized functional potentials of keystone taxa are not conducive to the accumulation of carbon sink. Our study offers valuable insights into the intricate correlation between precipitation-induced alterations in soil microbial keystone taxa and SOC storage, highlighting a rough categorization is difficult to distinguish the hidden threats and the importance of incorporating functional potentials in SOC storage prediction models in response to changing climate.

Spatial patterns of historical crop yields reveal soil health attributes in US Midwest fields

Attaining high crop yields and increasing carbon storage in agricultural soils, while avoiding negative environmental impacts on water quality, soil erosion, and biodiversity, requires accurate and precise management of crop inputs and management practices. The long-term analysis of spatial and temporal patterns of crop yields provides insights on how yields vary in a field, with parts of field constantly producing either high yields or low yields and other parts that fluctuate from one year to the next. The concept of yield stability has shown to be informative on how plants translate the effects of environmental conditions (e.g., soil, climate, topography) across the field and over the years in the final yield, and as a valuable layer in developing prescription maps of variable fertilizer rate inputs. Using known relationships between soil health and crop yields, we hypothesize that areas with measured constantly low yield will return low carbon to the soil affecting its heath. On this premises, yield stability zones (YSZ) provide an effective and practical integrative measure of the small-scale variability of soil health on a field relative basis. We tested this hypothesis by measuring various metrics of soil health from commercial farmers’ fields in the north central Midwest of the USA in samples replicated across YSZ, using a soil test suite commonly used by producers and stakeholders active in agricultural carbon credits markets. We found that the use of YSZ allowed us to successfully partition field-relative soil organic carbon (SOC) and soil health metrics into statistically distinct regions. Low and stable (LS) yield zones were statistically lower in normalized SOC when compared to high and stable (HS) and unstable (US) yield zones. The drivers of the yield differences within a field are a series of factors ranging from climate, topography and soil. LS zones occur in areas of compacted soil layers or shallow soils (edge of the field) on steeper slopes. The US zones occurring with high water flow accumulation, were more dependent on topography and rainfall. The differences in the components of the overall soil health score (SHS) between these YSZ increased with sample depth suggesting a deeper topsoil in the US and HS zones, driven by the accumulation of water, nutrients, and carbon downslope. Comparison of the field management provided initial evidence that zero tillage reduces the magnitude of the variance in SOC and soil health metrics between the YSZ.

Mapping soil organic carbon in northern France using adaptive zoning regression kriging based on LUCAS dataset

To improve the accuracy of soil organic carbon (SOC) mapping, an adaptive zoning regression kriging (AZ_RK) framework was proposed, which simultaneously considers spatial heterogeneity and the influence of multiple environmental variables. In AZ_RK, the study area was first adaptively divided into several spatially homogeneous zones. Then, the SOC distribution was mapped in each zone separately considering the relationships between SOC and environmental variables. The results indicated that the influence of environmental variables on SOC in different zones differed. The proposed zoning strategy was proven to be valid, which can account for 36.6% of the spatial variance in SOC. Furthermore, AZ_RK outperformed other methods with the lowest RMSE and the highest R 2 ( R cv 2 = 0.495 and R p 2 = 0.481). We concluded that AZ_RK can effectively cluster spatially homogeneous zones and adaptively map SOC with high estimation accuracy, which can serve as a valuable model reference for precise fertilization in regions characterized by spatial heterogeneity.

THE ROLE OF LONG-TERM EXPERIMENTS IN VALIDATING TRAIT-BASED APPROACHES TO ACHIEVING MULTIFUNCTIONALITY IN GRASSLANDS

<List> <ListItem><ItemContent> ● Data from the Park Grass Experiment shows inherent trade-offs between species richness, biomass production and soil organic carbon. </ItemContent></ListItem> <ListItem><ItemContent> ● Soil organic carbon is positively correlated with biomass production that increases with fertilizer additions. </ItemContent></ListItem> <ListItem><ItemContent> ● Variance in outcomes can be understood in terms of the dominant ecological strategies of the plant communities indicated by functional traits. </ItemContent></ListItem> <ListItem><ItemContent> ● There was an indication that data on traits associated with the spatiotemporal pattern of resource capture could be used to design species mixtures with greater resource use complementarity, increasing species richness without sacrificing productivity. </ItemContent></ListItem> <ListItem><ItemContent> ● Variance in soil organic carbon was positively correlated with pH. </ItemContent></ListItem></List> Quantifying the relationships between plant functional traits and ecosystem services has been promoted as an approach to achieving multifunctional grassland systems that balance productivity with other regulating, supporting and cultural services. Establishing trade-offs and synergies between traits and services has largely relied on meta-analyses of studies from different systems and environments. This study demonstrated the value of focused studies of long-term experiments in grassland systems that measure traits and services in the same space and time to better understand the ecological constraints underlying these trade-offs and synergies. An analysis is presented that uses data from the Park Grass Experiment at Rothamsted Research on above-ground productivity, species richness and soil organic carbon stocks to quantify the relationships between these three outcomes and the power of variance in plant functional traits in explaining them. There was a trade-off between plots with high productivity, nitrogen inputs and soil organic carbon and plots with high species richness that was explained by a functional gradient of traits that are indicative of contrasting strategies of resource acquisition of resource conservation. Examples were identified of using functional traits to identify opportunities for mitigating these trade-offs and moving toward more multifunctional systems.

Factors controlling soil organic carbon stocks in hardwood floodplain forests of the lower middle Elbe River

We assessed key relationships of soil organic carbon (SOC) stocks to hydromorphic features, soil texture, C/N ratio, pH, and forest age in hardwood floodplain forests. Floodplain ecosystems play a significant role in the global carbon cycle, particularly due to their SOC storage potential. Interactions between heterogeneous micro-relief and anthropogenically affected vegetation and the hydrologic situation of floodplains make predicting SOC stocks difficult without field validation. Especially within hardwood floodplain forests, the controlling factors for SOC storage remain understudied, whereas these floodplain types can be the largest reservoir for carbon and have a substantial SOC sequestration potential. To determine the controlling factors for SOC storage, we selected 38 hardwood floodplain forest and 11 floodplain grasslands of the lower middle Elbe River and categorized them according to vegetation type (grassland, young forest, or old forest) and hydrologic situation (low-lying or high elevated and active or former floodplain). Profile SOC stocks were determined to a depth of 1 m, and topsoil SOC stocks were related to vegetation and soil characteristics, particularly pedological traits (e.g., hydromorphic features).Forest SOC stocks ranged between 99 and 149 t ha−1. SOC stocks decreased with depth throughout all categories and were unaffected by vegetation type within the same hydrologic situation. Vegetation parameters such as age, basal area, or leaf litter carbon stock had no direct effect on SOC stocks. An active connection to the river had the strongest effect on SOC stocks, with former floodplain sites storing 33% less SOC than the active sites. Within the active floodplains, low sites stored 50% more SOC than high sites. This effect was mainly controlled by relief-affected features such as flooding duration and fine texture, which also were the strongest univariate predictors for SOC stocks (R2 = 0.39 and 0.63). A multiple linear regression showed that fine texture, pH, C/N ratio and forest age can be used to explain 86% of variance in SOC stocks.We conclude that proxies for relief and sedimentation (i.e., hydromorphic features, flooding duration, soil texture, C/N ratio, and pH) are the strongest factors controlling SOC stocks in hardwood floodplain forests. Both can be related to allochthonous carbon inputs, increasing SOC stabilization through the accumulation of fine soil particles, and decreasing aerobic carbon mineralization potential through oxygen scarcity, while vegetation plays only a subordinate role.

Sensitivity of the DSSAT model in simulating maize yield and soil carbon dynamics in arid Mediterranean climate: Effect of soil, genotype and crop management

• DSSAT model reasonably well simulates crop and soil variables in arid sandy soils. • Global sensitivity analysis is performed using co-inertia analysis and Sobolʹ method. • Soil input parameters largely control simulation of crop variables in low productive systems. • Carbon related crop management factors significantly contribute to modelled SOC variance. Crop models may potentially explore alternative ways to improve agroecosystem resilience in arid regions of Middle East and North Africa. Mapping the outputs behavior as a function of the inputs and quantifying the uncertainty contribution of inputs to the variability of outputs are crucial for understanding and applying complex mathematical models to a new environment. Objectives of present research are (i) to calibrate and evaluate the Decision Support System for Agrotechnology Transfer (DSSAT) cropping system model using detailed experimental datasets on maize production in arid sandy soils (Entisol) and (ii) to determine the model’s sensitivity to soil, genotype and crop management inputs under the currently explored conditions (low fertility and water holding capacity) based on multivariate analysis and variance decomposition methods. The goodness-of-fit statistics between observed and simulated data indicated that the calibrated model reasonably well simulates maize phenology, growth and yield, evapotranspiration, soil water content, grain N concentration, and postharvest soil NO 3 -N in eight year site field experiments. A global sensitivity analysis using the co-inertia method was carried out to link 14 output variables and 25 soil and genotype input parameters. Maize growth and yield variables were strongly correlated with soil hydrological and fertility input parameters such as soil water upper limit (SDUL) and soil organic carbon (SOC), whereas simulation of maize phenology was largely determined by phenological genotype-specific cultivar input parameters. A strong association was also observed between the output variables of yield and soil fertility. The effect of carbon (C) related soil input parameters of initial SOC and stable SOC and crop management factors of maize residue retention and compost application under no-till system on the long-term (10 years) simulation of yield and SOC dynamics was further explored using Sobolʹ method. Simulated grain yield, water productivity, active SOC, and cumulative soil CO 2 efflux were most sensitive to initial stable SOC and compost application. Maize residue retention significantly affected the simulation of cumulative N mineralization, SOC % in 0.2 m depth, and cumulative soil CO 2 efflux through interactions effect, i.e. total-order sensitivity index ( S Ti ) > 0.05, with other inputs. Compost application increased grain yield by 13 %, SOC stock by 5%, and cumulative soil CO 2 efflux by 95 % compared with no application. However, compost application with maize residue retained significantly reduced cumulative soil CO 2 efflux by 12 % compared with compost application with maize residue removed. Therefore, the application of compost with maize residue retained under no-till system is a plausible crop management option for agronomically improved and environmentally sound maize production in arid sandy soils.

Evaluation of the Potential for Soil Organic Carbon Content Monitoring With Farmers

Increasing soil organic carbon (SOC) content is crucial for soil quality and climate change mitigation. SOC monitoring is indispensable to the corresponding policies and should provide results at farm scale to allow for incentives. In Switzerland farmers perform mandatory analyses of the SOC content of the 0-20 cm topsoil of every field, based on a composite sample, at least every ten years. The corresponding results are stored in a database in canton of Geneva. These data may be relevant for topsoil SOC monitoring, in particular for carbon sequestration policies, provided that they show appropriate quality, which is analyzed in this study. The minimum detectable change (MDC) of past results calculated based on the observed SOC changes was 0.013 % g g-1 at canton scale (2700 fields). Based on extended sampling of three representative fields different sampling strategies were simulated to determine the best future sampling guidelines for farmers. Collecting 20 aliquots with a gouge on the field diagonals was considered the best sampling compromise with field MDC of about 0.1 % g g-1 and a sampling duration of 20 mn. Compared to this procedure, former farmers’ sampling was not biased in average but showed a variance of 0.22% g g-1 due to smaller number of aliquots and varying sampling depths. Based on the best sampling results and assumptions on farm-scale SOC variance or SOC differences, the MDCs at farm scale ranged from 0.21 to 0.12 % g g-1 (5 fields) and 0.09 to 0.05 % g g-1 (30 fields), respectively. These MDCs are small compared to published monitoring networks MDCs, and allow determining SOC change rates at farm scale, thus offering perspectives for inexpensive and efficient monitoring in the frame of soil quality or climate mitigation incentives. For the latter, however, additional information with equivalent soil mass and deeper layers carbon content would be necessary.

Analyzing and modelling the effect of long-term fertilizer management on crop yield and soil organic carbon in China

This study analyzes the influence of various fertilizer management practices on crop yield and soil organic carbon (SOC) based on the long-term field observations and modelling. Data covering 11 years from 8 long-term field trials were included, representing a range of typical soil, climate, and agro-ecosystems in China. The process-based model EPIC (Environmental Policy Integrated Climate model) was used to simulate the response of crop yield and SOC to various fertilization regimes. The results showed that the yield and SOC under additional manure application treatment were the highest while the yield under control treatment was the lowest (30%–50% of NPK yield) at all sites. The SOC in northern sites appeared more dynamic than that in southern sites. The variance partitioning analysis (VPA) showed more variance of crop yield could be explained by the fertilization factor (42%), including synthetic nitrogen (N), phosphorus (P), potassium (K) fertilizers, and fertilizer NPK combined with manure. The interactive influence of soil (total N, P, K, and available N, P, K) and climate factors (mean annual temperature and precipitation) determine the largest part of the SOC variance (32%). EPIC performs well in simulating both the dynamics of crop yield (NRMSE = 32% and 31% for yield calibration and validation) and SOC (NRMSE = 13% and 19% for SOC calibration and validation) under diverse fertilization practices in China. EPIC can assist in predicting the impacts of different fertilization regimes on crop growth and soil carbon dynamics, and contribute to the optimization of fertilizer management for different areas in China.

Spatial variation in soil organic carbon and nitrogen at two field sites under crop and pasture rotations in southern New South Wales, Australia

Estimating the likely variance in soil organic carbon (OC) at the scale of farm fields or smaller monitoring areas is necessary for developing sampling protocols that allow temporal change to be detected. Given the relatively low anticipated soil OC sequestration rates (&amp;lt;0.5 Mg/ha.0.30 m/year) for dryland agriculture it is important that sampling strategies are designed to reduce any cumulative errors associated with measuring soil OC. The first purpose of this study was to evaluate the spatial variation in soil OC and nitrogen (N), in soil layers to 1.50 m depth at two monitoring sites (Wagga Wagga and Yerong Creek, 0.5 ha each) in southern New South Wales, Australia, where crop and pasture rotations are practiced. Four variogram models were tested (linear, spherical, Gaussian and exponential); however, no single model dominated across sites or depths for OC or N. At both sites, the range was smallest in surface soil, and on a scale suggesting that sowing rows (stubble) may dominate the pattern of spatial dependence, whereas the longer ranges appeared to be associated with horizon boundaries. The second purpose of the study was to obtain an estimate of the population mean with 1%, 5% and 10% levels of precision using the calculated variance. The number of soil cores required for a 1% precision in estimation of the mean soil OC or N was impractical at most depths (&amp;gt;500 per ha). About 30 soil cores per composite sample to 1.50 m depth, each core being at least 10 m apart, would ensure at least an average of 10% precision in the estimation of the mean soil OC at these two sites, which represent the agriculture of the region.

Does long-term plastic film mulching really decrease sequestration of organic carbon in soil in the Loess Plateau?

Abstract Plastic film mulching (PM) is used extensively in China to increase the productivity of food crops, especially in the arid and semi-arid regions, although a recent concern is whether the practice decreases soil organic carbon (SOC). A process-based biogeochemical model applied in the Loess Plateau, where PM is widespread, examined the status of SOC over 30 years of maize cultivation with PM. The model explained 96% of the observed variance in SOC. The root mean square error was 0.39 g kg −1 , the mean absolute error was 0.32 g kg −1 , and the bias value from the SOC simulation was −0.006 g kg −1 . The model’s projections showed that PM has no significant impact on the overall average content of SOC across the entire study area compared to the fields without mulching, or control (CK), assuming that 5% of the crop residue was ploughed back into soil. However, based on individual simulation points in the 0–50 cm soil profile after 30 years of PM, 59.29% of the points, mainly on the western parts of the Loess Plateau, showed significantly higher SOC than that in CK, 8.30% showed significantly lower, and 32.41%, mainly on the south-eastern part of the Plateau, showed no significant difference between sites with PM and without it. Mulching increased the biomass, rhizodeposition, and the speed of turnover of SOC significantly, compared to the corresponding values in CK. High biomass in PM led to more carbon (C) being retained in soil and lowered the depletion of SOC. Ploughing the crop residues back into soil increased SOC, the greater the percentage of residue thus returned to soil, the higher the SOC. For a given residue return percentage, PM could increase more SOC than the CK. At 15%, which is the current average residue return ratio in the Loess Plateau, SOC levels remained stable or even increased in 77% of the study area if it adopted PM; in CK, the corresponding figure was only 63%. In regions such as the Loess Plateau where biomass is in great demand as a fuel or animal feed, PM provides greater biomass, which also means that more of it is available to be returned to soil—PM thus promotes the sequestration of SOC.

Spatial variability of organic carbon and total nitrogen in the soils of a subalpine forested catchment at Mt. Taiyue, China

Soil organic carbon (SOC) and total nitrogen (TN) are critical indicators of soil quality and play a pivotal role in key biogeochemical process (i.e. soil carbon and nutrient cycling). Many studies have assessed soil organic matter and nutrients individually in different ecosystems. However, appropriate sampling density for accurate estimation of the spatial distribution of SOC in subalpine forests and quantification of the relative importance of influencing factors remains uncertain. In this study, a combination of conventional analytical and geostatistical methods was used to analyze the spatial variability and patterns of SOC and TN along a soil profile. A total of 444 soil samples, taken from three layers down to 60cm, were collected from the Jieshigou catchment area (5.64km2) of Mount Taiyue in northern China. Results show that a large spatial variability of SOC and TN appears in upper 40cm along an elevation and vegetation gradient, while strong spatial autocorrelation is present below 40cm (40-60cm). Range and degree of spatial autocorrelation for SOC were slightly larger than those of TN; All the same, both showed clustered spatial distribution. A distribution map of Kriging revealed that both SOC and TN concentrations in the Jieshigou catchment area decreased from west to east along the direction of the valley, which coincides with the overlay of topographic features. More than 40% of the variance in SOC and TN contents could be explained by topographical indices and normalized difference vegetation index (NDVI). SOC and TN significantly increased (from 23.6 to 56.8gkg−1) with age of larch plantations in the surface layer. Our results suggest that a stratified random sampling was proved a sufficiently reliable way for estimating the spatial distribution of SOC and TN.

Soil organic carbon distribution in roadside soils of Singapore

Soil is the largest pool of organic carbon in terrestrial systems and plays a key role in carbon cycle. Global population living in urban areas are increasing substantially; however, the effects of urbanization on soil carbon storage and distribution are largely unknown. Here, we characterized the soil organic carbon (SOC) in roadside soils across the city-state of Singapore. We tested three hypotheses that SOC contents (concentration and density) in Singapore would be positively related to aboveground tree biomass, soil microbial biomass and land-use patterns. Overall mean SOC concentrations and densities (0–100 cm) of Singapore's roadside soils were 29 g kg−1 (4–106 g kg−1) and 11 kg m−2 (1.1–42.5 kg m−2) with median values of 26 g kg−1 and 10 kg m−2, respectively. There was significantly higher concentration of organic carbon (10.3 g kg−1) in the top 0–30 cm soil depth compared to the deeper (30–50 cm, and 50–100 cm) soil depths. Singapore's roadside soils represent 4% of Singapore's land, but store 2.9 million Mg C (estimated range of 0.3–11 million Mg C). This amount of SOC is equivalent to 25% of annual anthropogenic C emissions in Singapore. Soil organic C contents in Singapore's soils were not related to aboveground vegetation or soil microbial biomass, whereas land-use patterns to best explain variance in SOC in Singapore's roadside soils. We found SOC in Singapore's roadside soils to be inversely related to urbanization. We conclude that high SOC in Singapore roadside soils are probably due to management, such as specifications of high quality top-soil, high use of irrigation and fertilization and also due to an optimal climate promoting rapid growth and biological activity.

Soil organic carbon and total nitrogen stocks under different land uses in a hilly ecological restoration area of North China

In hilly area of North China, massive deforestation of natural forests and extensive use of agricultural lands have resulted in severe soil degradation. Soil organic carbon (SOC) and total nitrogen (STN) are crucial to soil quality. However, knowledge on the efficiency of changes in SOC under various land uses in these areas is very limited. To address this problem, a study was conducted in Songjiagou Catchment of Mount. Taiyue to evaluate the impact of land use change on SOC sequestration and STN accumulation. The results showed that compared with cropland, the SOC stock of shrub land was 10.8% higher and that of forestland 39.8% higher. Comparative values were 55.9% and 64.7% higher for nitrogen accumulation over the entire soil profile. Among that, the topsoil layer in cropland contained 40.7% of the SOC stock and this layer of the secondary shrub 43.6%. It appears that inappropriate tillage practices and anthropogenic disturbances imply a considerable loss of carbon sequestration. Ground litter biomass and live biomass were considered as the main influence factors of STN and SOC variance in surface soil. As well, soil properties, such as bulk density and pH value, were found to have significant and negative effect on SOC and STN concentrations. Therefore, we conclude that the change of land use from cropland to secondary shrub and restoration of forest plantation can improve SOC and STN concentrations and stocks.

Characterizing scale-specific environmental factors affecting soil organic carbon along two landscape transects.

Soil organic carbon (SOC) is one of the most important soil properties affecting many other soil and environmental properties and processes. In order to understand and manage SOC effectively, it is important to identify the scale-specific main factors affecting SOC distributions, which in this study occurred in a watershed on the Loess Plateau. Two transects were selected that passed along the upper slopes on each side of the main gully of the Liudaogou watershed. Transect 1 (3411-m length) had 27 sampling sites at 131-m intervals; transect 2 (3597m length) had 30 sampling sites at 124-m intervals. The two transects were chosen in order to compare landscape patterns of differing complexity that were in close proximity, which reduced the effects of factors that would be caused by different locations. The landscape of transect 1 was more complex due to the greater diversity in cultivation. Multivariate empirical mode decomposition (MEMD) decomposed the total variation in SOC and five selected environmental factors into four intrinsic mode functions (IMFs) and a residual according to the scale of occurrence. Scale-specific correlation analysis was used to identify significant relationships between SOC and the environmental factors. The dominant scales were those that were the largest contributors to the total SOC variance; for transect 1, this was the IMF 1 (scale of 403m), whereas for transect 2, it was the medium scale of the IMF 2 (scale of 688m). For both transects, vegetation properties (vegetation cover and aboveground biomass) were the main factors affecting SOC distributions at their respective dominant scales. At each scale, the main effective factors could be identified although at the larger scales, their contributions to the overall variance were almost negligible. The distributions of SOC and the factors affecting it were found to be scale dependent. The results of this study highlighted the suitability of the MEMD method in revealing the main scale-specific factors that affect SOC distributions, which is necessary in understanding and managing this important soil property.

Impacts of Rotational Grazing on Soil Carbon in Native Grass-Based Pastures in Southern Australia.

Rotational grazing management strategies have been promoted as a way to improve the sustainability of native grass-based pasture systems. From disturbance ecology theory, rotational grazing relative to continuous grazing can increase pasture productivity by allowing vegetation to recover after short intense grazing periods. This project sought to assess whether soil organic carbon (SOC) stocks would also increase with adoption of rotational grazing management. Twelve pairs of rotationally and continuously grazed paddocks were sampled across a rainfall gradient in South Australia. Pasture productivity approximated as the normalized difference vegetation index (NDVI) was on average no different between management categories, but when the data from all sites were aggregated as log response ratios (rotational/continuous) a significant positive trend of increasing NDVI under rotational grazing relative to continuous grazing was found (R2 = 0.52). Mean SOC stocks (0–30 cm) were 48.3 Mg C ha-1 with a range of 20–80 Mg C ha-1 across the study area with no differences between grazing management categories. SOC stocks were well correlated with rainfall and temperature (multiple linear regression R2 = 0.61). After removing the influence of climate on SOC stocks, the management variables, rest periods, stocking rate and grazing days, were found to be significantly correlated with SOC, explaining 22% of the variance in SOC, but there were still no clear differences in SOC stocks at paired sites. We suggest three reasons for the lack of SOC response. First, changes in plant productivity and turnover in low-medium rainfall regions due to changes in grazing management are small and slow, so we would only expect at best small incremental changes in SOC stocks. This is compounded by the inherent variability within and between paddocks making detection of a small real change difficult on short timescales. Lastly, the management data suggests that there is a gradation in implementation of rotational grazing and the use of two fixed categories (i.e. rotational v. continuous) may not be the most appropriate method of comparing diverse management styles.

Analysing soil organic C gradients in a smallholder farming village of East Zimbabwe

We set out to map the soil organic carbon (SOC) content, as an indicator of soil fertility, at the village scale, and to relate the SOC content to farm scale management and landscape scale characteristics. Topsoil samples were taken at 100 random locations in the Murewa smallholder farming area in Zimbabwe and analysed for organic carbon. Using digital soil mapping techniques and Landsat TM images we could explain 50% of the observed SOC variance. The average SOC content was estimated to be 1.5%, although the sandy cropping area had a much lower average of 0.8% and the red clays and valleys had higher average of 1.8%. The SOC variability could not be linked to farm management. No fertility gradients were observed, mostly due to a strong dominance of clay content on the spatial distribution of SOC. Clay content was able to explain 57% of the SOC variance, while farm area and labour size, typically used for farmer typology, were able to explain only an additional minor part of the SOC variance. This strong landscape scale effect needs to be included in future village-scale studies. We conclude that digital soil mapping of soil fertility gradients at the village scale has several scale issues that need to be addressed if the envisioned global digital soil map is to be relevant for smallholder farmers in sub-Saharan Africa.

Soil properties under natural forest in the Alicante Province of Spain

For millennia, land use in the Mediterranean region has led to situations in which soil has been severely degraded showing high risks of erosion and impoverishment. Thus, the establishment of soil quality indices is considered to be of crucial importance in determining the state of degradation and recovery of soils. Soils from stable forest ecosystems have specific physical, chemical and biological properties due to the conditions in which they developed. Hence, modelling the balance established among different key soil properties from stable forest ecosystems could be used as a soil quality index, because disturbance practices lead to changes in that natural balance. Here we report the establishment of two soil quality indices under Mediterranean semiarid conditions for forest soils in SE Spain, based on the use of multiple linear regressions integrating different physical, chemical and biochemical properties. As we observed the strong influence that climatic factors have on the values of the different soil properties and their relationships, mean annual precipitation was also incorporated in the regression models as a categorical explanatory variable. Model 1, that explains 92% of the variance in soil organic carbon (SOC), showed that SOC can be calculated by a linear combination of 6 physical, chemical and biochemical properties (acid phosphatase, water holding capacity (WHC), electrical conductivity (EC), available phosphorus (P), cation exchange capacity (CEC) and aggregate stability (AS)). Model 2 explains 89% of the variance in SOC, which can be calculated by means of 7 chemical and biochemical properties (urease, phosphatase and β-glucosidase activities, pH, EC, P and CEC). Our results confirm that a balance exists between the soil organic carbon of high quality soils and some other properties widely recognised in soil quality assessments, due to their sensitivity and the information they provide about the functionality of soils. As disturbance practices should be accompanied by the loss of this balance, SOC calculated by the models (SOCc) is no longer an accurate estimation of the actual SOC determined in laboratory (SOCa). Thus, it is possible to obtain a soil quality index by the calculation of the model residuals: Soil Quality Index = model residual = SOCc – SOCa. For a non-disturbed soil, the soil quality index should be 0 (SOCc = SOCa). In contrast, for disturbed soils, SOCc should be lower or higher than the actual SOC, with values in the soil quality index < 0 or > 0.

CLIMATIC/EDAPHIC CONTROLS ON SOIL CARBON/NITROGEN RESPONSE TO SHRUB ENCROACHMENT IN DESERT GRASSLAND

The proliferation of woody plants in grasslands over the past 100+ years can alter carbon, nitrogen, and water cycles and influence land surface-atmosphere interactions. Although the majority of organic carbon in these ecosystems resides belowground, there is no consensus on how this change in land cover has affected soil organic carbon (SOC) and total nitrogen (TN) pools. The degree to which duration of woody plant occupation, climate, and edaphic conditions have mediated SOC and TN responses to changes in life-form composition are poorly understood. We addressed these issues at a desert grassland site in Arizona, USA, where the leguminous shrub velvet mesquite (Prosopis velutina) has proliferated along an elevation/precipitation/temperature gradient and on contrasting soil morphologic surfaces. On sandy loam complexes of mid-Holocene origin, mean SOC and TN of soils in the grassland matrix increased approximately 68% and approximately 45%, respectively, with increasing elevation. Soil organic carbon pools were comparable and TN pools were approximately 23% higher in Pleistocene-aged clay loam complexes co-occurring with Holocene-aged soils at the upper elevation/climatic zone. Across the site, belowground resources associated with large Prosopis plants were 21-154% (SOC) and 18-127% (TN) higher than those in the grassy matrix. The variance in SOC and TN pools accounted for by Prosopis stem size (a rough surrogate for time of site occupation) was highest at the low- and mid-elevation sites (69-74%) and lowest at the upper elevation site (32-38%). Soil delta15N values ranged from 5.5 per thousand to 6.7 per thousand across the soil/elevation zones but were comparable in herbaceous and shrub-impacted soils and exhibited a weak relationship with Prosopis basal stem diameter (r2 < 0.1) and TN (r2 < 0.08). The SOC delta13C values decreased linearly with increasing Prosopis basal diameter, suggesting that size and isotopic composition of the SOC pool is a function of time of Prosopis site occupation. Isotopic mixture models indicate that encroachment of C3 woody plants has also promoted SOC additions from C4 plant sources, indicative of long-term herbaceous facilitation. Grassy sites in contrasting soil/elevation combinations, initially highly distinctive in their SOC pool size and delta13C, appear to be converging on similar values following approximately 100 years of woody plant proliferation.

SOIL CARBON RELATIONSHIPS WITH TERRAIN ATTRIBUTES, ELECTRICAL CONDUCTIVITY, AND A SOIL SURVEY IN A COASTAL PLAIN LANDSCAPE

Soil organic carbon (SOC) estimation at the landscape level is critical for assessing impacts of management practices on C sequestration and soil quality. We determined relationships between SOC, terrain attributes, field scale soil electrical conductivity (EC), soil texture and soil survey map units in a 9 ha coastal plain field (Aquic and Typic Paleudults) historically managed by conventional means. The site was composite sampled for SOC (0-30 cm) within 18.3 × 8.5-m grids (n = 496), and two data sets were created from the original data. Ordinary kriging, co-kriging, regression kriging and multiple regression were used to develop SOC surfaces that were validated with an independent data set (n = 24) using the mean square error (MSE). The SOC was relatively low (26.13 Mg ha−1) and only moderately variable (CV = 21%), and showed high spatial dependence. Interpolation techniques produced similar SOC maps but the best predictor was ordinary kriging (MSE = 9.11 Mg2 ha−2) while regression was the worst (MSE = 20.65 Mg2 ha−2). Factor analysis indicated that the first three factors explained 57% of field variability; compound topographic index (CTI), slope, EC and soil textural fractions dominated these components. Elevation, slope, CTI, silt content and EC explained up to 50% of the SOC variability (P ≤ 0.01) suggesting that topography and historical erosion played a significant role in SOC distribution. Field subdivision into soil map units or k-mean clusters similarly decreased SOC variance (about 30%). The study suggests that terrain attributes and EC surveys can be used to differentiate zones of variable SOC content, which may be used as bench marks to evaluate field-level impact of management practices on C sequestration.