Distribution Of Organic Carbon Research Articles

Soil carbon stocks and nutrient stratification in a volcanically active coffee-dominated landscape in south-central Guatemala

The volcanoclastic mountains of Central America offer elevations ideal for coffee production. Both vulcanism and land use can have significant impacts on soil formation and properties. We evaluated how the interactive impacts of soil formation and coffee-dominated land use modulate soil storage and vertical distribution of organic carbon and nutrient elements in a volcanically active landscape dominated by coffee agriculture in south-central Guatemala. Thirty-seven pedons under coffee production (n = 29), forest cover (n = 5) and pasture (n = 3) were characterized and classified, and concentrations and stocks of organic carbon and macronutrient and micronutrient elements were quantified across genetic horizons. Additionally, soil organic carbon (SOC) stock values calculated using the fixed depth (FD) and equivalent soil mass (ESM) methodologies were compared. The active stratovolcano in the region had a strong effect on the development of andic properties and soil horizon burial, with thirty-one pedons classified as Andisols, three as Inceptisols and three as Entisols. Land use management practices and soil horizon burial by deposition of volcanic material were partly reflected in the vertical distribution of SOC concentrations and stocks. The vertical distribution of macronutrients was generally more sensitive to land use than the vertical distribution micronutrients, which could potentially reflect differences in inputs via fertilizers and vegetation cover and in outputs with biomass harvest. Soil organic carbon stocks were similar when calculated by FD and ESM, reflecting relatively consistent depth-wise bulk density. These results demonstrate that in volcanically active landscapes, land use should be considered in concert with soil-forming factors to comprehensively understand organic carbon and nutrient element storage in soils.

Heavy metals distribution and their ecological risk in the surface sediments of Haizhou Bay, China

A comprehensive analysis of heavy metal concentrations, sources, and pollution status was conducted on thirty surface sediment samples collected from Haizhou Bay, China in 2020. The spatial distributions of Cu, Pb, Zn, Cr, Cd, and total organic carbon (TOC) were found to be analogous. Noteworthy, sporadic pollution effects from Cu, Cr, and As were detected, although heavy metal concentrations remained below the probable effect level (PEL). A suite of analytical methods, including Pearson's correlation coefficient, geoaccumulation index, sediment quality guidelines, potential ecological risk index, and principal component analysis, was employed to elucidate the sources and assess the pollution risks. The results indicated that Hg emerged as the predominant heavy metal pollutant in Haizhou Bay sediments, with several stations showing high pollution levels that require attention. Other heavy metals were mainly of natural origin, indicating no significant pollution in the study area.

Exploring the West African forest island phenomenon: scientific insights gained, successes achieved and capacities strengthened.

Anthropogenic activities around local villages in mesic savanna landscapes of West Africa have resulted in soil improvement and forest establishment outside their climatic zones. Such unique 'forest islands' have been reported to provide ecosystem services including biodiversity conservation. However, the science underpinning their formations is limitedly studied. In 2015 and with funding support from the Royal Society-DFID (now FCDO), we set out to investigate the biogeochemistry of the forest islands in comparison with adjacent natural savanna and farmlands across 11 locations in Burkina Faso, Ghana and Nigeria. Our results showed that the forest islands do not differ significantly from the adjoining ecosystems in soil mineralogy implying that their formation was anthropogenically driven. We observed greater soil organic carbon and nutrient distributions in the forest islands, which also had more stable macro (>500 μm) and meso-aggregates (500-250 μm) than the adjoining agricultural lands. We found that soil micro-aggregate (250-53 μm) stability was climate (precipitation) driven in the West African ecosystems while meso- and macro-aggregate stability was land-use driven. In one of the unique forest islands we studied in the Mole National Park of Ghana, we found its mineral-associated organic carbon over 40% greater than the adjoining natural savanna with potential implications for the achievement of the global initiative of the '4p1000' in West Africa. We conclude that the North-South-South research collaboration has established clearly, the science underlying the age-long West African forest island phenomenon and has, among many successes, led to capacity building of young scientists driving cutting-edge research in climate change adaptation and food systems transformation in the sub-region.

Spodosol development and soil organic carbon distribution along a lithosequence in perhumid coastal temperate rainforest

AbstractA dense concentration of old‐growth forest and a wet, cold climate promote mineral weathering and leaching in coastal temperate rainforest soils. Our objective was to assess soil development and soil organic carbon (SOC) distribution across 18 soil profiles in remote, upland terrain of southeast Alaska where pedon data are sparse. We made soil morphological observations, collected samples, and completed laboratory analyses to measure SOC content, pH, and particle size distribution. The survey of upland backslope soils included north‐ and south‐facing hillslopes derived from three lithologies (slate, metavolcanic, and phyllite). The soils across all sites were very gravelly (51.8 ± 20.4% coarse fragments), acidic (mineral soil pH 4.85 ± 0.45), and moderately deep (96.56 ± 37.80 cm); thin, broken E horizons were underlain by thick, carbon‐rich spodic horizons. Soil development was relatively consistent as demonstrated by the Profile Development Index with values from 15 to 26 and Podzolization Index values spanning 8 to 14. A mean pedon SOC stock of 198.02 ± 81.42 Mg C ha−1 (n = 18) was calculated using data collected for all upland organic and mineral soils from our work. The accumulation of SOC was similar among soils formed from contrasting lithologies with averages of 182 ± 15.70 Mg C ha−1 for slate, 188 ± 53.80 Mg C ha−1 for metavolcanic, and 218 ± 124 Mg C ha−1 for phyllite. Our work contributes to soil morphological observations, laboratory data, and SOC stock estimates required to better constrain and model pedogenic processes and SOC stock in remote forests where data sets are limited.

Effects of fertile islands on soil organic carbon density and labile organic carbon distribution in elm (Ulmus macrocarpa Hance)-dominated sparse wood grasslands in southeastern Inner Mongolia, China

In semi-arid savanna grasslands, the sparse distribution of trees often forms what are commonly known as fertile islands. However, the effect of these trees on soil organic carbon (SOC), microbial biomass carbon (MBC), and dissolved organic carbon (DOC), remains poorly understood. In this study, the spatial distribution patterns of SOC, MBC, and DOC were investigated across soil profiles (0–5, 5–10, 10–30, 30–50, and 50–100 cm) at three distances from the tree trunk in an elm-dominated savanna ecosystem in Northeast China. Our results suggest that SOC, MBC, and DOC were significantly influenced by both the distance from the tree and the soil depth. The research provides evidence that elm trees can form fertile island effects, thereby enhancing the contents of SOC and labile organic carbon fractions.

Spatiotemporal distribution patterns of iron, manganese, and arsenic within the river infiltration zone and the potential geochemical activity at key interfaces

The river infiltration zone is a mixed area of surface water and groundwater under the riverbed and along the riverbank, which is greatly affected by river infiltration. Currently, there is a lack of understanding regarding the migration and transformation processes of Fe, Mn, and As, along with their correlation with organic carbon in the river infiltration zone affected by riverbed scouring and siltation processes. In this study, based on techniques such as pore water sampling and the Tessier sequential extraction, the spatiotemporal variations in Fe, Mn, and As concentrations and possible geochemical processes at the riverbed sediment–water interface and along the river infiltration flow path were revealed. The results indicated that the potential geochemical activity of Fe, Mn, and As and the distribution of organic carbon in the riverbed sediment responded to riverbed scouring–siltation processes. Compared to the high water level period, the potential geochemical activity of Fe, Mn, As, and organic carbon in the riverbed sediment generally exhibited an upward trend during the low water level period, indicating more intense Fe and Mn biogeochemical reactions. During river infiltration, the labile organic carbon (LOC) was preferentially utilized, and with increasing depth, the sedimentary organic carbon (SOC) continuously transformed into LOC and dissolved organic carbon (DOC). Affected by riverbed scouring processes, the transition time from oxidizing to reducing conditions in the pore water increased, and the Fe, Mn, and As reduction zones moved deeper and farther from the riverbank, resulting in a significant expansion of the groundwater pollution area. The reductive dissolution of iron and manganese oxides/hydroxides and the oxidation of organic matter–bound Fe, Mn, and As were the main biogeochemical processes contributing to the release of Fe, Mn, and As in the river infiltration zone. These research results have crucial theoretical significance and practical application value for the sustainable utilization of groundwater resources and the remediation of groundwater pollution.

Soil Vertical Distribution of Organic Carbon and Sequestration Potential in Ponte de Lima (Alto Minho Region, Northern Portugal)

ABSTRACT Understanding the vertical distributions of organic carbon (OC) is crucial for predicting and simulating the influences of soil units on the terrestrial carbon cycle. The OC in the fine earth fraction was calculated for the soil units Anthrosols, Cambisols, Fluvisols, Leptosols, and Regosols in the municipality of Ponte de Lima, Portugal, at depths of 0–30 cm, 0–100 cm, 0–200 cm, and 0–2590 cm. In the study area, over 40% of the OC is concentrated in the Regosol unit, followed by the Anthrosols with over 23% OC at all depths, and the Leptosols with over 22% OC at all depths. The soil units Cambisols and Fluvisols have a lower representation in the territory, with values below 1.5% and 6.5% respectively at all depths. The obtained results contribute to assessing the potential of the soil units present in the municipality to sequester CO2, promoting the development of carbon inventories and analyzing the distribution of OC through accurate and reliable estimates of current C reserves as an essential tool for analyzing and modeling the effects of different factors involved in the potential of soil OC sequestration.

Spatial–Temporal Variations in Soil Organic Carbon and Driving Factors in Guangdong, China (2009–2023)

Spatial–temporal variation in soil organic carbon is an important factor for national targets to mitigate climate change and land degradation impacts. In this research, we took Guangdong Province of China as the study area, evaluated the spatial–temporal distributions of soil organic carbon using data from three China Geochemical Baseline projects (conducted in 2009, 2016, and 2023, respectively), and quantified the main driving factors of spatial–temporal variations in soil organic carbon using the random forest algorithm, further predicting the density and inventories of soil organic carbon. The results demonstrate that the mean value of SOC in Guangdong in 2009 was 0.81%; in 2016 it was 1.13%; and in 2023 it was 1.02%. The inventories of soil organic carbon (0–30 cm) in Guangdong Province were 0.61 Pg in 2009, 0.74 Pg in 2016, and 0.62 Pg in 2023. Soil in Guangdong acted as a carbon sink from 2009 to 2023 as a whole, and the most important driving force behind spatial–temporal variations in soil organic carbon was temperature, followed by precipitation and vegetation cover.

The dominant influence of muddy bottom currents on organic-rich fine-grained sedimentary rocks: The lower Congo Basin, west Africa

The Madingo Formation in the Lower Congo Basin (LCB) of West Africa is a fine-grained strata, which is considered to be the most promising source interval during the drift stage. Despite the extensive studies of the internal sedimentary characteristics of the Lower Mading Formation (LMF), muddy bottom currents have not been previously identified in this area. Extensive seismic (2D and 3D data), wire - line measurements and cutting samples in the LCB offer a unique opportunity to study the influence of muddy bottom currents depositional system on organic matter, and related depositional environment of the region and its depositional model of organic rich fine-grained strata. This study aims to unravel the influence of muddy bottom currents on organic matter enrichment within the LMF and build a depositional model. In combination with drilling and thin sections analysis, the M-1 member suggests the initiation and cessation of muddy bottom currents. Utilizing 3D seismic data inversion techniques, geochemical analysis, and sedimentological assessment, we studied the effect of muddy bottom currents on organic matter enrichment from the perspectives of paleoproductivity, preservation conditions, terrigenous input, and total organic carbon (TOC) distribution. Results show that muddy bottom currents have a significant impact on the redistribution of shallow water shelf sediments. They promote the transportation of nutrients and organic matter to deep water shelves, improving paleoproductivity. Most notably, terrigenous input is a key factor affecting organic matter distribution, resulting in dilution effects in deep water shelf bottom current influence areas, but conducive to the preservation of deep organic matter in low-lying areas of shallow water shelf. Muddy bottom currents have a weaker influence on the preservation environment of deep water shelves, but they have a significant effect on redox indicators (eg. U/Th, Ni/Co, V/Cr). Specifically, they reduce the enrichment in particulate elements. We established the depositional models of organic-rich fine-grained sedimentary rocks for the M-1 and M-2 members in LCB. These insights not only provide practical depositional models for marine sources rocks in the LCB, but also improves the general understanding of marine organic matter accumulation in muddy bottom currents environments. Furthermore, they serve as a reference for the study of organic-rich fine-grained sedimentary rocks in similar basins.

Coarse to superfine: can hyperspectral soil organic carbon models predict higher-resolution information?

Introduction: Modeling and mapping of soil organic carbon concentration and distribution at the pedon scale is a current knowledge gap that can be addressed by laboratory-based hyperspectral imaging and chemometric analysis of soil cores. Despite the advancements in soil organic carbon models based on hyperspectral images, it is not clear how these models will perform upon input with images at higher resolutions than those of their training sets. This study aims to measure the generalizability of a soil organic carbon model based on a test set with higher resolution hyperspectral images than that of its training set.Methods: Organic carbon contents were measured at 10 cm intervals on eight soil cores for use as the training set and at 1 cm intervals on a single core for use as the test set. Three regression models, namely, multilayer perceptron, partial least-squares, and support vector regressions, were trained and tested with the median of each hyperspectral image for each of these intervals as the training and test predictors. Permutation importance analysis was performed to explain the models.Results: The results show that although all three models had the same validation R2 of 0.92 for cross-validation on the 10 cm data, multilayer perceptron regression allowed the best generalization with a test R2 of 0.96 compared to the partial least-squares regression (0.81) and support vector regression (0.86). It was demonstrated that the multilayer perceptron model is more robust to soil surface anomalies and that it predicts soil organic carbon on the test set by learning the spectral features related to soil organic matter chromophore activity in the 950–1,150 nm region along with clay mineralogy derived from peaks at 1,400, 1,900, 2,200, 2,250, and 2,350 nm.Conclusions: This study shows that while the regression models based on hyperspectral images perform well at the 10-cm-resolution cross validation, multilayer perceptron regression shows superior generalization and robustness for a higher 1-cm-resolution test set without much loss of prediction power.

The Application of Percolation Theory in Modeling the Vertical Distribution of Soil Organic Carbon in the Changbai Mountains

A power-law formulation rooted in percolation theory has proven effective in depicting the vertical distribution of soil organic carbon (SOC) in temperate forest subsoils. While the model suggests the solute as the primary factor distributing SOC, this may not hold true in the surface soil in which roots contribute significantly to the SOC. This study in the Changbai Mountains Mixed Forests ecoregion (CMMF) evaluates the SOC profiles in three forests to assess the model’s efficacy throughout the soil column. Prediction of the SOC profile based on the regional average values was also assessed using field data. The observed scaling aligned well with predictions in mixed broadleaved and broadleaved Korean pine mixed forests, but disparities emerged in birch forest, possibly due to waterlogging. The predicted SOC levels correlate strongly with the field data and align well with the normalized average SOC levels. The findings suggest that the model remains applicable in the CMMF when considering root-derived carbon. However, the hindrance of solute transport may have a greater impact than roots do. The spatial heterogeneity of the SOC means that a single predicted SOC value at a specific depth may not fit all sites, but the overall agreement highlights the potential of the model for predicting the average or representative SOC profiles, which could further aid in regional-scale carbon stock estimation.

Soil organic carbon fractions and storage potential in Finnish arable soils

AbstractUnderstanding the factors affecting the total amount and distribution of soil organic carbon (OC) across different functional carbon pools is important to better define the future management of soil OC stocks. The interactions between soil management practices, local physicochemical soil properties and climate are essential for determining the OC content of the soil. Nevertheless, how these factors affect the total amount of OC and its distribution across carbon pools, i.e., more labile particulate (POC) and more stable mineral‐associated (MAOC) organic carbon, is only partly known. In this study, we assessed topsoil (0–20 cm) samples from 93 arable farms in the southern half of Finland to determine the total amount of OC, and its distribution in MAOC and POC, along with relevant soil properties (amount of clay and silt, aluminium and iron oxides and pH), climate (precipitation and temperature) and fertilization (mineral versus organic). The fertilization did not affect the total soil carbon content (12–58 g OC kg−1 soil). The share of OC in the MAOC fraction (on average 86% of total OC) was relatively stable across the large range of OC contents and clay contents (2%–68%). We assessed the highest feasible MAOC of the soils with boundary line analyses and their OC saturation state with Hassink's equation (Hassink, 1997). Only soils with the lowest clay content (<10% clay) were assumed to be carbon‐saturated, suggesting that most of the studied soils have a capacity to accrue more MAOC. Simple linear regression showed that clay, aluminium and iron oxides explained 9%, 21% and 22% of the variation in MAOC, respectively. Multiple regression analyses including the amount of clay, clay+silt, aluminium and iron oxides, pH, type of fertilization, precipitation and temperature as explanatory variables explained 33%–53% of the variation in OC and MAOC. In all soils, aluminium oxides were important explanatory variable for MAOC, whereas Fe oxides were significant only in soils with higher clay content (>30%). In soils with a low clay content (<30%), pH had added value in explaining MAOC. Altogether, it seems that various climatic, edaphic and soil management‐related factors are context‐dependently controlling OC and that soil textural information alone is not necessarily an adequate predictor to assess the MAOC saturation state of the soil.

Profile distribution and edaphic controls of soil organic carbon in dominant soil orders of Chitwan, Nepal

Soil profile distribution of soil organic carbon (SOC) in different soil types provides information about the carbon (C) dynamics in terrestrial ecosystems, and is also important for understanding climate feedback mechanisms and for developing a proper farm level SOC management decision. However, there are limited studies on it when we consider soil horizons of dominant soil orders of Nepal, which mostly use a fixed depth approach rather than horizon-based approach while studying profile SOC distribution. We collected soils from master horizons (0 to 100 cm) of three dominant soil orders (Alfisols, Entisols, and Inceptisols) in Chitwan district of Nepal, to understand the controlling factors of SOC accumulation. Dominant soil order regions were identified using a soil map prepared by the National Land Use Planning Project where a pit of 1 m3 was dug for each soil order and replicated four times. The highest SOC concentration (10.1 ± 0.6 g kg−1) was found in Alfisols followed by Entisols (8.8 ± 0.3 g kg−1) and Inceptisols (7.2 ± 8.9 g kg−1). Similarly, the highest SOC stock was found in the soil profile of Alfisols (200.01 ± 15.97 t ha−1) followed by Entisols (124.67 ± 12.20 t ha−1) and Inceptisols (113.27 ± 10.30 t ha−1) horizons. Surface (A) horizons of all three-soil order had significantly higher SOC than sub-surface (B and C) horizons. Regression analysis showed significant variability in SOC to clay content (R2 = 0.45, p < 0.0001), sand (R2 = 0.19, p < 0.001), and total nitrogen (N; R2 = 0.835, p < 0.001). Principal component analysis showed that the controlling edaphic factors differ with the soil types considering SOC change in the whole soil profile. Overall, we found that soil pH, N, clay and sand contents are the major controlling factors that drive the SOC accrual in dominant soil orders of Nepal.Graphical

Whether Wheat–Maize Rotation Influenced Soil Organic Carbon Content in Sushui River Basin

Enhancing soil organic carbon (SOC) content in farmland is crucial for soil quality maintenance and food security. However, the relationship between crop rotation and SOC sequestration remains unclear. We used sample data on SOC, collected in September of every year, from cultivated land for quality monitoring from 2017 to 2021, combined with spatially extracted planting system information, and focused on the effects of wheat–maize crop rotation on SOC in the Sushui River Basin. An analysis of variance (ANOVA) indicated that the SOC content was only significantly different between wheat monoculture and maize monoculture. Among the three cropping systems, wheat–maize rotation did not show absolute superiority. The Geodetector analysis showed that the planting system dominated the spatial distribution of soil organic carbon (p = 0.05), but its explanatory factor was only 5%, and the explanatory power was significantly improved after interaction with other factors. Geographically weighted regression showed that wheat–maize rotation had a trade-off effect with elevation and synergistic effects with rainfall and pH. It displayed a synergistic effect with temperature in the southwest and a trade-off effect in the northeast. The degrees of trade-offs and synergy varied spatially among all interacting factors. We focused on the spatial heterogeneity of soil organic carbon in a small watershed, and the results had scientific significance for the layout of planting systems according to local conditions and the improvement in soil organic carbon levels.

13C evidence for the selective loss of active and inert organic carbon in soil aggregates under rain-induced overland flow erosion

Due to the hierarchical structure of aggregates, raindrops cause changes in the composition, distribution and state of aggregate-wrapped organic carbon (OC) fractions during erosion, greatly affecting soil carbon turnover and sequestration. To explore these regulatory mechanisms, the selective transport of light (LFoc) and heavy (HFoc) fraction OC within aggregates of varying sizes was traced via the 13C/12C carbon isotope ratio (δ13C) under splash and sheet erosion conditions. A “three-zone” variable-slope soil pan was filled with loess soil with a high aggregate concentration to monitor rainfall erosion on a slope. The OC aggregate composition, aggregate stripping and δ13C values of the sediment aggregates of various particle sizes were measured. When the erosion intensity was low, the splash-eroded sediment was mainly enriched in 13C-rich HFoc, and as the rainfall intensity increased, the concentrations of 12C-rich LFoc and HFoc gradually increased. That is, under heavy rainfall, aggregate fragmentation exposed more large fragments rich in younger HFoc and LFoc, and these fragments underwent saltation. There was no obvious correlation between the trends in splash erosion and OC, so runoff transport was an important factor influencing the correlation between δ13C and OC (P < 0.05). Raindrop impact exposed HFoc-rich aggregate fragments of different sizes, e.g., stable mineral-associated OC. Runoff promoted the obvious preferential transport of LFoc and the redistribution of particulate OC (POC) among different sediment particles. Mineral-associated OC and 2–0.05 mm easily decomposable LFoc or POC were preferentially transported, causing OC with the highest and median δ13C values to be preferentially transported. Overall, the transport order of aggregate-exposed OC particles was clay + silt particle-bonded OC, POC, POC-bonded aggregate fragments and silt-bonded aggregate fragments. These results verified the selective loss of aggregate-detached OC fragments during erosion, which led to a change in the OC sequestration and reaggregation potential of OC in the eroded and deposited soil.

Rubber Plantation Age Affects Soil Aggregate Stability, Organic Carbon, and Nitrogen Distribution in Hainan Island, China

Rubber Plantation Age Affects Soil Aggregate Stability, Organic Carbon, and Nitrogen Distribution in Hainan Island, China

Mapping Soil Properties in the Haihun River Sub-Watershed, Yangtze River Basin, China, by Integrating Machine Learning and Variable Selection.

Mapping soil properties in sub-watersheds is critical for agricultural productivity, land management, and ecological security. Machine learning has been widely applied to digital soil mapping due to a rapidly increasing number of environmental covariates. However, the inclusion of many environmental covariates in machine learning models leads to the problem of multicollinearity, with poorly understood consequences for prediction performance. Here, we explored the effects of variable selection on the prediction performance of two machine learning models for multiple soil properties in the Haihun River sub-watershed, Jiangxi Province, China. Surface soils (0-20 cm) were collected from a total of 180 sample points in 2022. The optimal covariates were selected from 40 environmental covariates using a recursive feature elimination algorithm. Compared to all-variable models, the random forest (RF) and extreme gradient boosting (XGBoost) models with variable selection improved in prediction accuracy. The R2 values of the RF and XGBoost models increased by 0.34 and 0.47 for the soil organic carbon, by 0.67 and 0.62 for the total phosphorus, and by 0.43 and 0.62 for the available phosphorus, respectively. The models with variable selection presented reduced global uncertainty, and the overall uncertainty of the RF model was lower than that of the XGBoost model. The soil properties showed high spatial heterogeneity based on the models with variable selection. Remote sensing covariates (particularly principal component 2) were the major factors controlling the distribution of the soil organic carbon. Human activity covariates (mainly land use) and organism covariates (mainly potential evapotranspiration) played a predominant role in driving the distribution of the soil total and soil available phosphorus, respectively. This study indicates the importance of variable selection for predicting multiple soil properties and mapping their spatial distribution in sub-watersheds.

Vertical distribution of microplastics in an agricultural soil after long-term treatment with sewage sludge and mineral fertiliser

Sewage sludge applications release contaminants to agricultural soils, such as potentially toxic metals and microplastics (MPs). However, factors determining the subsequent mobility of MPs in long-term field conditions are poorly understood. This study aimed to understand the vertical distribution of MPs in soils amended with sewage sludge in comparison to conventional mineral fertiliser for 24 years. The depth-dependent MP mass and number concentrations, plastic types, sizes and shapes were compared with the distribution of organic carbon and metals to provide insights into potentially transport-limiting factors. Polyethylene, polypropylene and polystyrene mass concentrations were screened down to 90 cm depth via pyrolysis-gas chromatography/mass spectrometry. MP number concentrations, additional plastic types, sizes, and shapes were analysed down to 40 cm depth using micro-Fourier transform-infrared imaging. Across all depths, MP numbers were twice and mass concentrations 8 times higher when sewage sludge was applied, with a higher share of textile-related plastics, more fibres and on average larger particles than in soil receiving mineral fertiliser. Transport of MPs beyond the plough layer (0–20 cm) is often assumed negligible, but substantial MP numbers (42 %) and mass (52 %) were detected down to 70 cm in sewage sludge-amended soils. The initial mobilization of MPs was shape- and size-dependent, because the fractions of fragmental-shaped and relatively small MPs increased directly below the plough layer, but not at greater depths. The sharp decline of total MP concentrations between 20 and 40 cm depth resembled that of metals and organic matter suggesting similar transport limitations. We hypothesize that the effect of soil management, such as ploughing, on soil compactness and subsequent transport by bioturbation and via macropores drives vertical MP distribution over long time scales. Risk assessment in soils should therefore account for considerable MP displacement to avoid underestimating soil exposure.

Assessing the 3D distribution of soil organic carbon by integrating predictions of water and tillage erosion into a digital soil mapping-approach: a case study for silt loam cropland (Belgium)

Although agricultural intensification has generally increased crop yields, it also resulted in a range of environmental issues. These include increased erosion rates and declined soil organic carbon (SOC) stocks. In order to improve our understanding on how erosion impacts the overall SOC storage capacity of croplands, this study analyses the 3D distribution of SOC as a function of water and tillage erosion in a conventionally ploughed field in the Belgian silt loam region. We present a novel methodological framework to integrate the output of an advanced erosion model as a co-variate within a Digital Soil Mapping (DSM) approach with the objective to create detailed SOC maps. More precisely, we combined (i) the Water and Tillage Erosion Model and Sediment Delivery Model (WaTEM/SEDEM), simulating spatial patterns of soil erosion and sediment deposition due to water and tillage erosions, with (ii) a SOC sampling campaign, resulting in a SOC spatial distribution model that considers both types of erosion. The results show that, as compared to plateaus, SOC stocks are nearly half as large along eroding slopes (i.e. convex slope positions affected by tillage erosion and steep slopes affected by water erosion). Yet, they are up to twice as large in areas characterized by sediment deposition (i.e. concave positions due to tillage erosion and foot slope positions due to water erosion). Our results further show that tillage erosion has a significant influence on the SOC stocks in the top 0.7 m and in particular on the top 0.4 m. The influence of water erosion is less strong but mostly significant along the entire depth profile. Overall, this work demonstrates the relevance of considering different erosion processes when aiming to predict spatial patterns of SOC. Considering the top 1 m and a WaTEM/SEDEM application at a resolution of 10 m our 3D SOC modelling approach obtained a coefficient of determination (R2) of 0.62, a relative root mean square error (RRMSE) of 30.5 % and a relative mean absolute error (RMAE) of 26.0 %. While future work may likely lead to further improvements e.g. a more detailed SOC sampling network along the foot slopes and thalwegs in order to obtain a more spatially detailed prediction of the area characterized by depositions due to water erosion, we demonstrate the great potential of existing erosion and deposition models in doing so.

Iron-bound Organic Carbon Distribution in Freshwater Wetlands with Varying Vegetation and Hydrological Regime

Iron-bound Organic Carbon Distribution in Freshwater Wetlands with Varying Vegetation and Hydrological Regime