Uncertainty in soil carbon accounting due to unrecognized soil erosion

Soil carbon stocks in stable tropical landforms are dominated by geochemical controls and not by land use

Soil organic carbon (SOC) dynamics depend on soil properties derived from the geoclimatic conditions under which soils develop and are in many cases modified by land conversion. However, SOC stabilization and the responses of SOC to land use change are not well constrained in deeply weathered tropical soils, which are dominated by less reactive minerals than those in temperate regions. Along a gradient of geochemically distinct soil parent materials, we investigated differences in SOC stocks and SOC (Δ14 C) turnover time across soil profile depth between montane tropical forest and cropland situated on flat, non-erosive plateau landforms. We show that SOC stocks and soil Δ14 C patterns do not differ significantly with land use, but that differences in SOC can be explained by the physicochemical properties of soils. More specifically, labile organo-mineral associations in combination with exchangeable base cations were identified as the dominating controls over soil C stocks and turnover. We argue that due to their long weathering history, the investigated tropical soils do not provide enough reactive minerals for the stabilization of C input in either high input (tropical forest) or low-input (cropland) systems. Since these soils exceeded their maximum potential for the mineral related stabilization of SOC, potential positive effects of reforestation on tropical SOC storage are most likely limited to minor differences in topsoil without major impacts on subsoil C stocks. Hence, in deeply weathered soils, increasing C inputs may lead to the accumulation of a larger readily available SOC pool, but does not contribute to long-term SOC stabilization.

Application of a combinatorial approach for soil organic carbon mapping in hills

Accurate mapping of soil organic carbon (SOC) is critical to improve C management and develop sustainable management policies. However, it is constrained by local variations of the model parameters under complex topography, especially in hills. This study applied a methodological framework to optimize the spatial prediction of SOC in the hilly areas during 1981-2012 by quantifying the relative importance of environmental factors, which include both qualitative factors and quantitative variables. Results showed that SOC increased twofold with a moderate spatial dependence during the past 32 years. During this period, land use patterns, soil groups, topographic factors, and vegetation coverage had significant impacts on the SOC changes (p < 0.01). Specifically, the impact of land use patterns has exceeded the impact of soil groups and became the dominant factor affecting SOC changes. Meanwhile, impacts from the topographic factors and vegetation coverage have substantially declined. Based on those results, a combinatorial approach (LS_RBF_HASM) was developed to map SOC using radial basis function neural network (RBF) and high accuracy surface modelling (HASM), and to generate more detailed spatial mapping relationships between SOC and the affecting factors. Compared with ordinary kriging (OK), land use-soil group units (LS) and HASM combined (LS_HASM), multiple linear regression (MLR) and HASM combined with LS (LS_MLR_HASM); LS_RBF_HASM showed a better performance with a decline of 6.3%-37.7% prediction errors and more accurate spatial patterns due to the quantitative combination of auxiliary environmental variables and more information on the SOC variations within local factors captured by RBF and HASM. Additionally, MLR may partially undermine the relationship of the internal spatial structure due to the highly nonlinear relation between SOC and environmental variables. This methodological framework highlights the optimization of more environmental factors and the calculation of spatial variability within local factors and provides a more accurate approach for SOC mapping in hills.

Soils' dirty little secret: Depth-based comparisons can be inadequate for quantifying changes in soil organic carbon and other mineral soil properties

Quantifying changes in soil organic carbon (SOC) stocks and other soil properties is essential for understanding how soils will respond to land management practices and global change. Although they are widely used, comparisons of SOC stocks at fixed depth (FD) intervals are subject to errors when changes in bulk density or soil organic matter occur. The equivalent soil mass (ESM) method has been recommended in lieu of FD for assessing changes in SOC stocks in mineral soils, but ESM remains underutilized for SOC stocks and has rarely been used for other soil properties. In this paper, we draw attention to the limitations of the FD method and demonstrate the advantages of the ESM approach. We provide illustrations to show that the FD approach is susceptible to errors not only for quantifying SOC stocks but also for soil mass-based properties such as SOC mass percent, C:N mass ratio, and δ¹³ C. We describe the ESM approach and show how it mitigates the FD method limitations. Using bulk density change simulations applied to an empirical dataset from bioenergy cropping systems, we show that the ESM method provides consistently lower errors than FD when quantifying changes in SOC stocks and other soil properties. To simplify the use of ESM, we detail how the method can be integrated into sampling schemes, and we provide an example R computer script that can perform ESM calculations on large datasets. We encourage future studies, whether temporal or comparative, to utilize sampling methods that are amenable to the ESM approach. Overall, we agree with previous recommendations that ESM should be the standard method for evaluating SOC stock changes in mineral soils, but we further suggest that ESM may also be preferred for comparisons of other soil properties including mass percentages, elemental mass ratios, and stable isotope composition.

Soil organic carbon across scales

Mechanistic understanding of scale effects is important for interpreting the processes that control the global carbon cycle. Greater attention should be given to scale in soil organic carbon (SOC) science so that we can devise better policy to protect/enhance existing SOC stocks and ensure sustainable use of soils. Global issues such as climate change require consideration of SOC stock changes at the global and biosphere scale, but human interaction occurs at the landscape scale, with consequences at the pedon, aggregate and particle scales. This review evaluates our understanding of SOC across all these scales in the context of the processes involved in SOC cycling at each scale and with emphasis on stabilizing SOC. Current synergy between science and policy is explored at each scale to determine how well each is represented in the management of SOC. An outline of how SOC might be integrated into a framework of soil security is examined. We conclude that SOC processes at the biosphere to biome scales are not well understood. Instead, SOC has come to be viewed as a large-scale pool subjects to carbon flux. Better understanding exists for SOC processes operating at the scales of the pedon, aggregate and particle. At the landscape scale, the influence of large- and small-scale processes has the greatest interaction and is exposed to the greatest modification through agricultural management. Policy implemented at regional or national scale tends to focus at the landscape scale without due consideration of the larger scale factors controlling SOC or the impacts of policy for SOC at the smaller SOC scales. What is required is a framework that can be integrated across a continuum of scales to optimize SOC management.

Modelling the impact of agricultural management on soil carbon stocks at the regional scale: the role of lateral fluxes

Agricultural management has received increased attention over the last decades due to its central role in carbon (C) sequestration and greenhouse gas mitigation. Yet, regardless of the large body of literature on the effects of soil erosion by tillage and water on soil organic carbon (SOC) stocks in agricultural landscapes, the significance of soil redistribution for the overall C budget and the C sequestration potential of land management options remains poorly quantified. In this study, we explore the role of lateral SOC fluxes in regional scale modelling of SOC stocks under three different agricultural management practices in central Belgium: conventional tillage (CT), reduced tillage (RT) and reduced tillage with additional carbon input (RT+i). We assessed each management scenario twice: using a conventional approach that did not account for lateral fluxes and an alternative approach that included soil erosion-induced lateral SOC fluxes. The results show that accounting for lateral fluxes increased C sequestration rates by 2.7, 2.5 and 1.5 g C m(-2)  yr(-1) for CT, RT and RT+i, respectively, relative to the conventional approach. Soil redistribution also led to a reduction of SOC concentration in the plough layer and increased the spatial variability of SOC stocks, suggesting that C sequestration studies relying on changes in the plough layer may underestimate the soil's C sequestration potential due to the effects of soil erosion. Additionally, lateral C export from cropland was in the same of order of magnitude as C sequestration; hence, the fate of C exported from cropland into other land uses is crucial to determine the ultimate impact of management and erosion on the landscape C balance. Consequently, soil management strategies targeting C sequestration will be most effective when accompanied by measures that reduce soil erosion given that erosion loss can balance potential C uptake, particularly in sloping areas.

Soil CO₂ dynamics in a tree island soil of the Pantanal: the role of soil water potential

The Pantanal is a biodiversity hotspot comprised of a mosaic of landforms that differ in vegetative assemblages and flooding dynamics. Tree islands provide refuge for terrestrial fauna during the flooding period and are particularly important to the regional ecosystem structure. Little soil CO₂ research has been conducted in this region. We evaluated soil CO₂ dynamics in relation to primary controlling environmental parameters (soil temperature and soil water). Soil respiration was computed using the gradient method using in situ infrared gas analyzers to directly measure CO₂ concentration within the soil profile. Due to the cost of the sensors and associated equipment, this study was unreplicated. Rather, we focus on the temporal relationships between soil CO₂ efflux and related environmental parameters. Soil CO₂ efflux during the study averaged 3.53 µmol CO₂ m⁻² s⁻¹, and was equivalent to an annual soil respiration of 1220 g C m⁻² y⁻¹. This efflux value, integrated over a year, is comparable to soil C stocks for 0–20 cm. Soil water potential was the measured parameter most strongly associated with soil CO₂ concentrations, with high CO₂ values observed only once soil water potential at the 10 cm depth approached zero. This relationship was exhibited across a spectrum of timescales and was found to be significant at a daily timescale across all seasons using conditional nonparametric spectral Granger causality analysis. Hydrology plays a significant role in controlling CO₂ efflux from the tree island soil, with soil CO₂ dynamics differing by wetting mechanism. During the wet-up period, direct precipitation infiltrates soil from above and results in pulses of CO₂ efflux from soil. The annual flood arrives later, and saturates soil from below. While CO₂ concentrations in soil grew very high under both wetting mechanisms, the change in soil CO₂ efflux was only significant when soils were wet from above.