Geoderma Regional最新文献

{"title":"Stocks and stoichiometry of carbon, nitrogen, and phosphorus in agricultural mineral soil profiles with views on the carbon sequestration","authors":"Sichu Wang ,&nbsp;Oona Uhlgren ,&nbsp;Anna-Reetta Salonen ,&nbsp;Sanna Kanerva ,&nbsp;Asko Simojoki ,&nbsp;Tuomas Mattila ,&nbsp;Jussi Heinonsalo","doi":"10.1016/j.geodrs.2026.e01058","DOIUrl":"10.1016/j.geodrs.2026.e01058","url":null,"abstract":"<div><div>The stoichiometric ratios of carbon (C), nitrogen (N) and phosphorus (P) in soils influence nutrient availability for soil microorganisms and thus the efficiency of C sequestration. Subsoil horizons are known to be potential sinks for sequestering substantial amounts of C. However, limited information is available regarding soil C:N:P stoichiometry in the subsoil and its role in regulating soil organic C stocks. This study investigated the vertical variations in C, N and P stocks and their ratios down to one meter in boreal agricultural soils. We further explored the response of soil C:N:P stoichiometry to the soil physical characteristics and the subsequent impacts on C stocks. The stocks of C and N decrease sharply with soil depth, whereas P shows a more gradual decline, resulting in a decrease in the ratios of C:P and N:P. Stoichiometric ratios were more constrained in the topsoil compared with subsoil, and were estimated to be on the average 83:6:1 and 21:2:1 in the topsoil and subsoil, respectively. C stock in the subsoil layers were more strongly limited by stoichiometric ratios (N:P) than those in the topsoil. From the stoichiometric perspective, agricultural soils in Finland exhibit an excess of total P but are limited in C and N for soil microorganisms. Soil compaction amplifies the already existing nutrient imbalance, potentially reducing C stocks in subsoil. This study deepens our understanding of the coupling and interaction among soil C, N and P in relation to soil C sequestration.</div></div>","PeriodicalId":56001,"journal":{"name":"Geoderma Regional","volume":"44 ","pages":"Article e01058"},"PeriodicalIF":3.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146173057","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Validation of three - horizon soil maps based on different soil texture datasets for Denmark","authors":"Alireza Motevalli,&nbsp;Bo V. Iversen,&nbsp;Charles Pesch,&nbsp;Christen Duus Børgesen","doi":"10.1016/j.geodrs.2026.e01049","DOIUrl":"10.1016/j.geodrs.2026.e01049","url":null,"abstract":"<div><div>In arable production and environmental planning, accurate soil maps are crucial for informed decision-making. However, creating precise digital soil maps is challenging due to regional and field spatial variations in soil texture caused by diverse pedogenic factors. This research focuses on evaluating a Danish three-layer root zone (0–120 cm depth) soil map (AC map). Over the last decade, the AC map has served as a key input in diverse applications including soil texture, bulk density, content of organic matter, soil profile classification, maximum rooting depth, and hydraulic parameters across three horizons. Validation was conducted by using two datasets: a dependent dataset comprising data from the Danish textural database and Danish profile database and an independent dataset that never have been used for AC map creation. The dependent dataset contained 37,948 points for the A horizon (0–30 cm), 5892 for the B horizon (35–75 cm), and 1136 for the C horizon (70–120 cm), while the independent dataset included 4879 observation points for the A horizon. For dependent datasets, nested k-fold cross-validation and for independent datasets, all of datasets were applied to calculate mean root mean square error (RMSE) and mean bias error (MBE), alongside difference tests (D-values), cumulative mass functions (CMFs), and residual regression kriging (RRK) comparing measured and predicted values. Results showed that the clay content in the A horizon was well-predicted with low D-values and a low bias in contrast to the horizons in the subsoil that were less good predicted. The independent dataset (A horizon) gave higher ME and D-values than the dependent data, which was expected, but the validation also showed that the AC map remains accurate, unbiased, and operationally reliable soil maps on regional scale and has served as a reliable data source in regional hydrological modelling studies conducted over the past decades in Denmark.</div></div>","PeriodicalId":56001,"journal":{"name":"Geoderma Regional","volume":"44 ","pages":"Article e01049"},"PeriodicalIF":3.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146173040","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Soil structure and pH shape prokaryotic communities in lowland soils across Denmark","authors":"Anne-Cathrine Storgaard Danielsen ,&nbsp;Charles Pesch ,&nbsp;Cecilie Hermansen ,&nbsp;Caitlin Margaret Singleton ,&nbsp;Thomas Bygh Nymann Jensen ,&nbsp;Per Halkjær Nielsen ,&nbsp;Mogens Humlekrog Greve ,&nbsp;Arka Rudra ,&nbsp;Hamed Sanei ,&nbsp;Peter Lystbæk Weber ,&nbsp;Emmanuel Arthur ,&nbsp;Sebastian Gutierrez ,&nbsp;Per Møldrup ,&nbsp;Signe Normand ,&nbsp;Lis Wollesen de Jonge","doi":"10.1016/j.geodrs.2025.e01016","DOIUrl":"10.1016/j.geodrs.2025.e01016","url":null,"abstract":"<div><div>Agricultural activity in drained lowlands accelerates peat decomposition and greenhouse gas emissions. Rewetting is increasingly adopted across Europe to mitigate these emissions, but its effects on soil microbial communities remain poorly understood. We examined prokaryotic communities and network structure in Danish lowland soils designated for potential rewetting to improve our understanding of these communities and their drivers. We included less-studied soil properties linked to hydrology and structure (soil water content at field capacity, van Genuchten pore-size distribution index (<em>n</em>), and soil water repellency (SWR)) in addition to common properties such as pH and organic carbon (OC). We analysed 113 soil samples across land-use types (grass, fallow, crop, other) spanning mineral to organic soils with gradients in pH (2.0–7.6), OC (0.025–0.499 kg kg^-1), SWR (33.9-71.3 mN m^-1), and soil structure (<em>n</em>: 1.1-1.3). Prokaryotic alpha diversity (Shannon-Wiener index: 2.9–5.7) was best predicted by pH, followed by porosity and <em>n</em>. Together, pH, porosity, <em>n</em>, and OC accounted for 24.5% of the variance in community composition. Hierarchical clustering identified three prokaryotic clusters strongly aligned with pH. Network analysis revealed marginal differences when comparing samples from fallow and grass, while complexity increased progressively across clusters. Interestingly, high-pH soils showed the highest alpha diversity but the least complex networks, while low-pH soils showed the opposite. In conclusion, soil pH emerged as the dominant driver of prokaryotic communities in Danish lowlands, but hydrological and structural properties also played important roles. Network complexity provided complementary insights into ecosystem organisation beyond diversity alone.</div></div>","PeriodicalId":56001,"journal":{"name":"Geoderma Regional","volume":"43 ","pages":"Article e01016"},"PeriodicalIF":3.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145222459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatial prediction of soil organic carbon stocks across contrasting Andean basins, Peru","authors":"Carlos Carbajal ,&nbsp;Merely Tumbalobos-Dextre ,&nbsp;Tatiana Condori-Ataupillco ,&nbsp;Nestor Cuellar-Condori ,&nbsp;Carla Gavilan","doi":"10.1016/j.geodrs.2025.e01026","DOIUrl":"10.1016/j.geodrs.2025.e01026","url":null,"abstract":"<div><div>Soil organic carbon stocks (SOCS) are critical components of the global carbon cycling and play a central role in climate change mitigation. However, their dynamics in high-altitude Andean ecosystems remain poorly understood despite their importance for carbon sequestration. The significant spatial heterogeneity of SOCS in mountainous terrain makes accurate quantification and mapping challenging. This study evaluated the performance of geospatial regression and machine learning (ML) approaches for predicting SOCS in two Peruvian Andean basins: Torobamba and Coata. We compared Geographically Weighted Regression (GWR), GWR with collinearity analysis (GWRC), their kriging-adjusted variants, and ML models (Random Forest, Gradient Boosting). Models were built using key SOCS covariates for each basin and validated through 5-fold cross-validation with Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and coefficient of determination (R²). In Torobamba, GWRC markedly improved performance, reducing the RMSE by 79–90 % and achieving R² up to 0.99. In contrast, Coata, showed only modest improvements (RMSE reductions of 7.8–9.8 %, R² = 0.30–0.39). ML models performed poorly (negative R²), likely due to feature selection, parameter tuning, or limited sample size. Overall, locally weighted regression approaches (GWRK/GWRCK) outperformed conventional ML methods for SOCS prediction in complex mountain environments, particularly with small to medium sample sizes. These results highlight the importance of accounting for spatial non-stationarity in SOCS and provide methodological guidance for SOCS mapping in Andean ecosystems.</div></div>","PeriodicalId":56001,"journal":{"name":"Geoderma Regional","volume":"43 ","pages":"Article e01026"},"PeriodicalIF":3.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145519730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mid-infrared spectral insights into soil hydraulic, physical, and chemical properties across four Moroccan regions","authors":"Mohamed Ghassan ,&nbsp;Reda Mokere ,&nbsp;Adnane Beniaich ,&nbsp;Issam Barra","doi":"10.1016/j.geodrs.2025.e01028","DOIUrl":"10.1016/j.geodrs.2025.e01028","url":null,"abstract":"<div><div>Producing consistent and affordable information on soil functions is crucial for improving agricultural management and assessing land potential and constraints. In this study, we evaluated the prediction ability of mid-infrared (MIR) spectral patterns, using partial least squares regression (PLSR) to predict chemical, i.e. soil organic matter (SOM), physical, i.e. clay, silt, and sand, and hydraulic, viz. gravimetric water content at saturation (Msat), field capacity (Mfc), and permanent wilting point (Mpwp) properties across four agricultural regions of Morocco (Tadla, Doukkala, Gharb-Loukous, and Moulouya), using a dataset of 319 soil samples. Data preprocessing was performed using the standard normal variate (SNV), multiplicative scatter correction (MSC), detrend correction, and Savitzky-Golay smoothing and derivatives. Variable selection was carried out using interval PLS (iPLS) and variable importance in projection (VIP) algorithms. The models were calibrated, tested, and evaluated based on the coefficient of determination of prediction (R²), the root mean square error (RMSE), and the ratio of performance to deviation (RPD). PLSR applied to raw MIR spectra showed good overall performance across all soil properties, except for the SOM, which demonstrated moderate performance (R²_p = 0.59, RMSE_p = 0.672 %, and RPD_p = 1.61). Preprocessing and variable selection techniques led to noticeable improvements for Msat and silt. However, for Mfc, Mpwp, SOM, and sand, little to no improvement was observed compared to predictions from the raw data. For clay, preprocessing alone enhanced the model's accuracy from R²_p = 0.82 and RMSE_p = 6.350 %, to R²_p = 0.86 and RMSE_p = 5.655 %, whereas variable selection techniques did not. Generally, MIR spectroscopy captured the dominant soil functional signal across diverse Moroccan environments, supporting rapid, low-cost assessments of texture, key hydraulic, and chemical attributes. These results position MIR as a practical tool for regional soil monitoring and precision agriculture.</div></div>","PeriodicalId":56001,"journal":{"name":"Geoderma Regional","volume":"43 ","pages":"Article e01028"},"PeriodicalIF":3.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145571635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mineralogical controls on the resilience of ferruginous duricrusts in coastal landscapes along Brazil's Atlantic margin: Implications for climate change adaptation","authors":"Marcel Sarcinelli Pimenta ,&nbsp;David Lukas de Arruda ,&nbsp;Marcelo Metri Corrêa ,&nbsp;Salomão Silva Calegari ,&nbsp;Diego Lang Burak ,&nbsp;Oldair Del Arco Vinhas Costa ,&nbsp;Danilo de Lima Camêlo","doi":"10.1016/j.geodrs.2025.e01020","DOIUrl":"10.1016/j.geodrs.2025.e01020","url":null,"abstract":"<div><div>Ferruginous laterites and duricrusts are widespread across Brazil's Coastal Tablelands (Barreiras Formation), yet their genesis and variability remain debated. We investigated ferruginous duricrusts from southeastern and northeastern Brazil to identify mineralogical controls on stability and propose a genetic framework. Using X-ray diffraction (phase assemblages, crystallinity proxies), selective iron extractions (CBD, AAO), magnetic susceptibility, micromorphology/SEM–EDS, and multivariate analyses (principal component analysis and hierarchical clustering), we propose a two–end-member model for Barreiras-related ferruginous systems: (i) autochthonous ferruginous laterites developed in situ that culminate in hematite-dominated ferruginous duricrusts, which are less Al-substituted, with coalesced Fe nodules, and strong Fe-oxide impregnation; and (ii) allochthonous ferruginous laterites composed of reworked pisolithic/nodular material that is comparatively goethite-rich. PCA/HCA discriminate these end members by Fe-oxide indices and elemental composition, confirming distinct mineralogical–geochemical signatures. Regionally, southeastern duricrusts, being more hematitic and exhibiting lower Al substitution in goethite, appear more susceptible to reductive dissolution and metal mobility under enhanced hydrologic variability, whereas northeastern, comparatively goethite-rich and more Al-substituted ferruginous duricrusts show greater resilience, implying different management strategies.</div></div>","PeriodicalId":56001,"journal":{"name":"Geoderma Regional","volume":"43 ","pages":"Article e01020"},"PeriodicalIF":3.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145364039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Distribution and potential of rare earth elements fingerprinting as tracers for carbonate sources in soils developed on contrasting parent materials","authors":"Ferdinand J. Dina Ebouel ,&nbsp;Charles G. Kono Ebede ,&nbsp;Thierry Bineli Betsi ,&nbsp;Peter N. Eze","doi":"10.1016/j.geodrs.2025.e01009","DOIUrl":"10.1016/j.geodrs.2025.e01009","url":null,"abstract":"<div><div>While the use of rare earth elements (REE) to examine soil processes is an increasingly popular approach, very few studies have investigated its application to the study of dominant soil genetic processes at the landscape scale in semi-arid environments. This study analyses the distribution and fractionation of REEs in 12 soil profiles from different lithologies in the Kalahari Basin of Botswana (BKB) and examines their relationships with pedogenetic processes, calcium carbonate origin and pH. The results show significant variability in total REE contents (12.8 - 193.2 mg kg^-1) in the soil profiles, depending on the soil parent material. Total REE abundance within soil profiles show a strong correlation with clay-associated elements, such as Al (r = 0.8) and K (r = 0.7), as well as with iron Fe (r = 0.6). These correlations suggest that clay formation plays a primary role in REE enrichment in the soil profiles. On the other hand, the moderate positive correlation with Ca (r = 0.4) indicates a minor contribution from calcium carbonate accumulation to REE enrichment. pH shows weak positive correlations with REE content across the full soil profile (r &lt; 0.2), reflecting negligeable influence on REE distribution in the study soil profiles. The fractionation ratios between light REEs and heavy REEs (LREEs/HREEs) range from 0.6–1.5 in soil profiles on alluvial and fluvio-lacustrine sediments, 0.4–0.9 from those on basaltic and sandstones rock, and 0.7–1.1 from those on sands, clays, calcretes and silcrete. Given the previously demonstrated preferential complexation of HREEs in pedogenic carbonates, these results suggest a mixed pedogenic and lithogenic origin for calcium carbonates in soil on alluvial and fluvio-lacustrine sediments, and in soils on sands, clays, calcretes and silcretes. Soils on basaltic and sandstone rocks, on the other hand, have a purely pedogenic origin. The results of this study provide a solid baseline for understanding REE distributions in the BKB and tracing the origin of calcium carbonate in semi-arid environments.</div></div>","PeriodicalId":56001,"journal":{"name":"Geoderma Regional","volume":"43 ","pages":"Article e01009"},"PeriodicalIF":3.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145098700","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Do Chernozems occur in Poland? Distribution, properties and regional variation of black soils in the loess belt of Poland","authors":"Cezary Kabala ,&nbsp;Beata Labaz ,&nbsp;Adam Bogacz ,&nbsp;Michał Dudek ,&nbsp;Dariusz Gruszka ,&nbsp;Szymon Młynek ,&nbsp;Jarosław Waroszewski","doi":"10.1016/j.geodrs.2025.e01007","DOIUrl":"10.1016/j.geodrs.2025.e01007","url":null,"abstract":"<div><div>Although Chernozems have appeared on Polish soil maps since the late 19th century, their occurrence in Poland is omitted from global and regional soil maps and the reports of foreign authors. This paper aims to verify the occurrence, abundance and properties of soils that meet the criteria for Chernozems as defined by the World Reference Base for Soil Resources (WRB) in five ‘chernozemic’ regions in the loess belt of southern Poland. This analysis identified Chernozems in 15–55 % of the studied soil profiles in four of the five ‘chernozemic’ regions, while the major accompanying soils in all regions were Phaeozems. Most Phaeozems have chernic horizons; therefore, the crucial characteristics allowing classification as a Chernozem or Phaeozem were the presence and depth of secondary carbonates. The spatial variation of Haplic and Calcic Chernozems, which prevail in the (south) central and eastern regions, was strongly affected by erosion, while clay illuviation was relatively poorly indicated in soil profiles. Soils in the fore-mountain regions were extensively leached of carbonates and often had argic horizons, which implies a predominance of Luvic Phaeozems. Gleyic/Stagnic Luvic Chernozems/Phaeozems prevailed in the westernmost region, which is characterised by plain topography and imperfect water drainage. The topsoil pH, soil organic carbon and clay contents of Polish Chernozems and Phaeozems decreased from the easternmost region towards the west and south, where the humid ‘oceanic influences’ or ‘mountain influences’, respectively, are considered responsible for more intense soil leaching during the Holocene period. The soil organic carbon (regional mean values in a range of 1.7–2.8 %), clay (11–21 %) and pH (6.4–7.4) values in Chernozems and Phaeozems developed from loess in southern Poland are lower compared to Chernozems of the steppe zone of southern Russia, Ukraine and Moldova, but comparable with their values reported from neighbouring Central European countries (northwestern Ukraine, Slovakia, Czechia and Germany). The presence of chernic horizons in all studied regions affirms (a) the polygenetic origin of Chernozems and Phaeozems with subsurface argic horizons, and (b) the large potential of regenerative or conservative agriculture in combating erosion and restoring humus-rich and biologically active topsoil layers, which can preserve Chernozems and Phaeozems against further decay in southern Poland.</div></div>","PeriodicalId":56001,"journal":{"name":"Geoderma Regional","volume":"43 ","pages":"Article e01007"},"PeriodicalIF":3.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145098699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mapping sub-surface distribution of soil organic carbon stocks in South Africa's arid and semi-arid landscapes: Implications for land management and climate change mitigation","authors":"Omosalewa Odebiri ,&nbsp;Onisimo Mutanga ,&nbsp;John Odindi ,&nbsp;Rob Slotow ,&nbsp;Paramu Mafongoya ,&nbsp;Romano Lottering ,&nbsp;Rowan Naicker ,&nbsp;Trylee Nyasha Matongera ,&nbsp;Mthembeni Mngadi","doi":"10.1016/j.geodrs.2025.e01022","DOIUrl":"10.1016/j.geodrs.2025.e01022","url":null,"abstract":"<div><div>Soil organic carbon (SOC) stocks are critical for land management strategies and climate change mitigation. However, understanding SOC distribution in South Africa's arid and semi-arid regions remains a challenge due to data limitations, and the complex spatial and sub-surface variability in SOC stocks driven by desertification and land degradation. To support soil and land-use management practices, as well as advance climate change mitigation efforts, there is an urgent need to provide more precise SOC stock estimates within South Africa's arid and semi-arid regions. Hence, this study adopted remote-sensing approaches to determine the spatial sub-surface distribution of SOC stocks and the influence of environmental co-variates at four soil depths (i.e., 0-30 cm, 30-60 cm, 60-100 cm, and 100-200 cm). Using Extreme Gradient Boosting (XGBoost) and Random Forest (RF) regression-based algorithms, the study found the former (RMSE values ranging from 10.50 t/ha to 16.60 t/ha) to be a superior model of SOC than the latter (RMSE values ranging from 10.83 t/ha to 18.25 t/ha). Thereafter, using a variable importance analysis, the study demonstrated the influence of topo-climatic and soil texture on SOC stocks at different depths. The study further demonstrated that the top 100 cm of the soil profile contained more than 70 % of the total SOC stocks, with the topsoil (0–30 cm) accounting for 34 % of the total SOC. The models exhibited a general decreasing trend in SOC stocks across the first three soil depth intervals. Additionally, the study revealed substantial spatial variability in SOC stocks, with greater accumulation in the topsoil observed in central and northern regions, while deeper SOC storage was more pronounced in the eastern parts of the study area. Overall, these findings enhance the understanding of SOC dynamics in South Africa's arid and semi-arid landscapes and emphasizes the importance of considering site specific topo-climatic characteristics for sustainable land management and climate change mitigation.</div></div>","PeriodicalId":56001,"journal":{"name":"Geoderma Regional","volume":"43 ","pages":"Article e01022"},"PeriodicalIF":3.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145684586","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Territorial mapping of soil type and land cover influence on ecosystem services","authors":"Clémentine Chirol ,&nbsp;Delphine Derrien ,&nbsp;Laurent Saint-André ,&nbsp;Paul-Olivier Redon ,&nbsp;Geoffroy Séré","doi":"10.1016/j.geodrs.2025.e01008","DOIUrl":"10.1016/j.geodrs.2025.e01008","url":null,"abstract":"<div><div>The delivery of soil-based ecosystem services (ES) is of increasing importance for spatial planners. Soils are complex and heterogeneous systems, therefore synthesizing pedological expertise into decision support maps presents ongoing challenges. Our approach considers the properties of the entire pedon to assess the contribution of different soil types and land covers to ES delivery at the territorial scale.</div><div>This study adapts the Destisol decision support tool, initially developed for urban soils and therefore adapted to a high variety of pedons influenced by human activities, to a rural setting containing croplands, grasslands and forests. 86 soil profiles from the study territory are grouped into eight dominant soil types. Nine ES are evaluated based on the horizon-specific physico-chemical properties of each soil type, and mapped following a territorial 1/50,000 pedological map.</div><div>The study territory has a high potential for ES provision with a mean score of 2 +/− 0.2 (min: 1.7, max: 2.7) on a scale of 0 to 3. Soil type is shown to have a significant impact on ES supply under the same land cover. Eutric Cambisols rank highly for provisioning and regulating services, Gleysols rank poorly for water quality but highly for global climate mitigation, and shallow rocky soils rank poorly for most services except water infiltration. Mapping results and soil-type specific ES scores can be used as spatial planning tools to quantify the impact of a given scenario of land cover change on ES scores, and thereby contribute to efforts towards no net loss of soil functionality.</div></div>","PeriodicalId":56001,"journal":{"name":"Geoderma Regional","volume":"43 ","pages":"Article e01008"},"PeriodicalIF":3.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145098701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}