Geoderma最新文献

{"title":"The global pedogenon map: Combining and spatialising the factors of soil formation","authors":"Nicolas Francos,&nbsp;Amin Sharififar,&nbsp;Trevan Flynn,&nbsp;Quentin Styc,&nbsp;Sandra J. Evangelista,&nbsp;Jose Padarian,&nbsp;Wartini Ng,&nbsp;Damien J. Field,&nbsp;Budiman Minasny,&nbsp;Alex B. McBratney","doi":"10.1016/j.geoderma.2025.117462","DOIUrl":"10.1016/j.geoderma.2025.117462","url":null,"abstract":"<div><div>This study presents the development of a global pedogenon map, which classifies soil units based on similarities in their formation processes while excluding anthropogenic effects, at a high spatial resolution of 90 m. Designed for use by scientists, land managers, and policymakers, this map classifies distinct soil units —called pedogenons—based on key soil-forming factors, including parent material, climate, soil organisms, relief, and inherent soil properties. This study employs a combination of principal component analysis (PCA), non-metric-multidimensional-scaling (NMDS), and an unsupervised classification technique (K-means clustering) to capture the full range of soil formation processes across diverse landscapes of the world yielding an unbiased, globally applicable classification. The global pedogenon map enables soil capacity and condition monitoring on a global scale. This foundation is crucial for future identification of “least disturbed soils” to serve as a reference for any soil around the globe. By integrating this dataset with broader environmental data, the global pedogenon map supports global efforts to enhance soil security and monitor environmental changes.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"460 ","pages":"Article 117462"},"PeriodicalIF":6.6,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144724983","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigating the influence of soil organic carbon on pore structure within aggregates","authors":"Jingjing Liu ,&nbsp;Yu Tian ,&nbsp;Chiara Pasut ,&nbsp;Mark Farrell ,&nbsp;Shenggao Lu","doi":"10.1016/j.geoderma.2025.117463","DOIUrl":"10.1016/j.geoderma.2025.117463","url":null,"abstract":"<div><div>Soil pore structural properties, such as porosity, size distribution and geometry, are crucial for various soil processes and are significantly influenced by soil organic carbon (SOC). SOC plays a vital role in determining soil functionality and ecosystem services and is the primary driver of pore geometry within soil aggregates, yet traditional in-situ analysis methods have fallen short in accurately describing its intricate distribution. This study employed a two-stage approach to analyze soil structure at the pore scale: a hydrogen peroxide fogging system was used to selectively remove organic carbon from soil aggregates, followed by synchrotron radiation micro-computed tomography (SR-μCT) for in-depth three-dimensional imaging. The results revealed that the hydrogen peroxide treatment variably reduced organic carbon in soil aggregates, with Cambisol samples showing a higher removal efficiency (38.58–63.31%) compared to Ultisol samples (27.33–45.74%). Mineral-associated organic carbon (MAOC) was more stable than particle organic carbon (POC). SOC depletion led to consistent changes in pore volume across soil types, but the changes in pore shape distribution varied between Cambisols and Ultisols. In Cambisols, SOC removal was associated with more pronounced shifts in pore morphology, whereas Ultisols showed more heterogeneous responses, likely due to differing mineralogical properties. These findings suggest that SOC contributes differently to pore structure depending on soil type. This study aimed to move beyond the traditional “black box” view of soil by visualizing the complex interactions between soil organic carbon (SOC) and soil structure with a new method. This approach could provide valuable insights into the mechanisms behind soil aggregate formation.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"460 ","pages":"Article 117463"},"PeriodicalIF":6.6,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144721525","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Grazing-induced abiotic and resource changes drive distinct responses of soil bacterial and fungal community in temperate meadow steppe: Implications for carbon dynamics","authors":"Cuixia Jiang ,&nbsp;Xiaoping Xin ,&nbsp;Kai Xue ,&nbsp;Zhigang Zhao ,&nbsp;Weixing Liu ,&nbsp;Haonan Guo ,&nbsp;Feng Liu ,&nbsp;Hui Li ,&nbsp;Zihao Li ,&nbsp;Yufan Si ,&nbsp;Ruirui Yan","doi":"10.1016/j.geoderma.2025.117451","DOIUrl":"10.1016/j.geoderma.2025.117451","url":null,"abstract":"<div><div>Soil microbial communities play a crucial role in maintaining grassland ecosystem functions and are strongly influenced by livestock grazing. However, the long-term responses and driving mechanisms of soil microbial communities to grazing intensity gradients, remain largely unexplored. In this study, we investigated the mechanism of different grazing intensities (i.e., ungrazed, light, moderate and heavy grazing) affect the diversity and composition of soil bacteria and fungi in the Hulunbuir <em>Leymus chinensis</em> meadow steppe. Using a Bipartite network to represent indicative species shifts, bacterial community presented a clear succession along the grazing intensity gradient, likely linked to soil abiotic conditions (e.g. soil temperature, silt). In contrast, fungal community exhibited a more discrete shift along the grazing intensity gradient, challenging the traditional view that fungal community is more stable under disturbance. The shifts in fungal community were closely related to the vegetation composition and aboveground biomass, reflecting a typical bottom-up resource-related regulation, which were more dynamic than changes caused by abiotic conditions along the grazing intensity gradient. Interestingly, indicator analysis showed that higher grazing intensity shifted bacterial and fungal composition towards more oligotrophic (e.g. Dothideomycetes, Sordariomycetes, Leotiomycetes, and Chloroflexi, Thermoleophilia) and less copiotrophic (e.g. Saprotrophs, Bacteroides and subgroup_6). This shift reflects the depleted substrate and is consistent with the observed inhibition of ecosystem respiration, implying lower organic matter decomposition. The distinct patterns of bacteria and fungi responses provides novel insights into the mechanisms, through which grazing alters soil bacterial and fungal communities with potential long-term consequences, including future growth-limiting resource and soil environment conditions to withstand future disturbances, which affect soil bacterial and fungal communities differently and consequently modulate soil organic carbon turnover. Moreover, the different substrate affinity of copiotrophic and oligotrophic groups altered available and recalcitrant C decomposition, which may change soil carbon cycling and stocks.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"460 ","pages":"Article 117451"},"PeriodicalIF":6.6,"publicationDate":"2025-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144721524","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Denitrification in the deep vadose zone: implications for nitrate leaching under agricultural managed aquifer recharge","authors":"Hannah Waterhouse,&nbsp;Helen E. Dahlke,&nbsp;William R. Horwath","doi":"10.1016/j.geoderma.2025.117457","DOIUrl":"10.1016/j.geoderma.2025.117457","url":null,"abstract":"<div><div>Managed aquifer recharge on agricultural lands (AgMAR) is an inexpensive and extensive form of recharge compared to dedicated recharge basins and injections wells. However, uncertain nitrogen cycling outcomes concerning nitrate (NO₃^–) transport and fate in the unsaturated zone remain. A combination of laboratory and field experiments were conducted to assess biogeochemical controls on denitrification in surface soils and subsurface sediments during AgMAR. Acetylene block assays were conducted in anaerobic conditions to determine dentification potential rates in the root zone and subsurface sediments collected from an almond orchard down to nine meters in the Central Valley of California. Samples were either amended with carbon (C) and NO₃^– additions (potential assays) or no substrates were added (control) and nitrous oxide (N₂O) was measured over three days. Denitrification potential assays resulted in four times more N₂O production near the surface, and 49x more N₂O production in the subsurface compared to the control. However, even without additions of C, sediments were able to denitrify ∼ 40 % of the NO₃^– present in the subsurface during the incubation. Additionally, δ¹⁵N of NO₃^– was measured in the field before and after AgMAR, showing an average absolute increase of 4.0 ‰ in δ¹⁵N across 4 m depth suggesting denitrification following AgMAR. Statistical analysis suggests N₂O production in assays depends on environmental controls or geochemistry of the soils/sediments when C concentrations are low, with iron significantly influencing denitrification in the control, but not in denitrification potential assays. These results from both laboratory incubations and the field demonstrate initial indications that the vadose zone has the potential to attenuate NO₃^– via denitrification, however, our results do not allow exact quantification of denitrified N mass under AgMAR, and more work is needed to determine denitrification rates in-situ. Future studies should focus on quantifying denitrification rates in-situ during and immediately following AgMAR events.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"460 ","pages":"Article 117457"},"PeriodicalIF":5.6,"publicationDate":"2025-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144713283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Increasing ECM tree dominance enhances soil lignin phenols but suppresses microbial necromass contribution to soil organic carbon in a subtropical mountainous forest","authors":"Mengzhen Lu ,&nbsp;Long Chen ,&nbsp;Qiuxiang Tian ,&nbsp;Qing He ,&nbsp;Mi Yang ,&nbsp;Zhiyang Feng ,&nbsp;Feng Liu","doi":"10.1016/j.geoderma.2025.117456","DOIUrl":"10.1016/j.geoderma.2025.117456","url":null,"abstract":"<div><div>Arbuscular mycorrhizal (AM) and ectomycorrhizal (ECM) plants exhibit distinct litter quality characteristics and nutrient uptake strategies that critically influence soil carbon and nitrogen cycling. However, the effect of mycorrhizal type on soil organic carbon (SOC) accumulation remains unclear, particularly in tropical and subtropical forests in China. To address this knowledge gap, this study quantified the SOC content and its components across a gradient of ECM tree dominance (ECM%, defined as the proportion of ECM tree basal area relative to the all trees) in a subtropical mountainous forest. Lignin phenols and amino sugars were used as indicators of plant- and microbial-derived C in the soil, respectively. Plant, soil, and microbial properties were analyzed to explore the underlying mechanisms influencing SOC components across different mycorrhizal types. Our results indicated that ECM% did not affect SOC content but significantly altered SOC composition. Specifically, a higher ECM% promoted plant-derived C accumulation and reduced microbial-derived C. The increase in plant-derived C accumulation with ECM% was primarily owing to lower litter quality and higher C inputs from litter and fine roots. Conversely, microbial-derived C accumulation decreased with ECM%, primarily because of the lower metabolic efficiency and higher degradation rate of microbial necromass, as indicated by metabolic quotient and extracellular enzyme activities, respectively. Overall, these findings improve existing understanding of the mechanisms underlying SOC formation and decomposition along the gradient of ECM tree dominance, providing valuable insights into how shifts in tree mycorrhizal dominance under global change may alter the pathways and composition of SOC accumulation in forest soils.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"460 ","pages":"Article 117456"},"PeriodicalIF":5.6,"publicationDate":"2025-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144711249","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 microbial C:N:P stoichiometry across environmental transects in China’s typical ecologically fragile regions","authors":"Wenjie Cao ,&nbsp;Yun Chen ,&nbsp;Yuqiang Li ,&nbsp;Lilong Wang ,&nbsp;Yulong Duan ,&nbsp;Xiaohui Li","doi":"10.1016/j.geoderma.2025.117454","DOIUrl":"10.1016/j.geoderma.2025.117454","url":null,"abstract":"<div><div>The stoichiometry of soil microbial biomass is closely tied to the terrestrial cycling of carbon (C) and nutrients. Those stoichiometry influences not only soil fertility but also global change mitigation efforts. Ecologically fragile areas are commonly located in the ecotones between different ecosystems, with poor stability, weak ability to resist disturbance, and easy degradation. Yet the biogeographical patterns and potential mechanistic drivers of soil microbial biomass stoichiometry and its homeostasis in fragile ecosystems remain unclear. In this study we set three transects in typical ecologically fragile areas of China from which topsoil (0 − 20 cm depth) samples were collected to measure their microbial biomass carbon (MBC), nitrogen (MBN), and phosphorus (MBP). The results revealed much lower MBC (190.1 mg kg⁻¹), MBN (20.5 mg kg⁻¹), and MBP (7.1 mg kg⁻¹) concentrations than their corresponding global and Chinese averages, but higher MBC:MBN (9.7), MBC:MBP (48.4), and MBN:MBP (4.3) ratios. The stoichiometric homeostasis (<em>H</em>, calculated by nonlinear fitting of microbial and soil stoichiometry) of MBC, MBN, and MBP concentrations ranged from 1.4 to 2.3, being weakly plastic to weakly homeostatic, while their ratios were generally homeostatic (with <em>H</em> ranged from 4.2 to 45.5). The MBC:MBN:MBP ratio was approximately 48:4:1. Overall, soil microbes were vulnerable to soil nitrogen and phosphorus limitations, compared to soil carbon. Soil MBC:MBN:MBP stoichiometry changed nonlinearly along the latitudinal gradient. Soil chemical and vegetation properties contributed the majority of variance explanations (&gt; 62 %) to microbial biomass stoichiometry. Altogether, these findings provide new insight into the patterns and homeostasis of soil MBC:MBN:MBP stoichiometry in fragile ecosystems.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"460 ","pages":"Article 117454"},"PeriodicalIF":5.6,"publicationDate":"2025-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144711283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Relict charcoal hearth magnetic fingerprints in the forest topsoil","authors":"Marcin Szuszkiewicz ,&nbsp;Jarosław Lasota ,&nbsp;Maria Magdalena Szuszkiewicz ,&nbsp;Ewa Błońska","doi":"10.1016/j.geoderma.2025.117458","DOIUrl":"10.1016/j.geoderma.2025.117458","url":null,"abstract":"<div><div>The relationship between the magnetic properties and fire-affected soil is crucial for environmental inference, especially in the case of soil magnetic enhancement by thermal transformation of iron minerals. Generally, there are no studies reporting relict charcoal hearths using magnetic analyses. This gap is addressed in our work. Moreover, we also fill the gap regarding how long fire-related magnetic enhancement may persist in soils. Hence, the data may also influence the development of research on pyrogenic magnetic enhancement of soils. The preliminary research was aimed at verifying the possibility of using some environmental magnetism parameters to detect differences in the soil magnetic signal with and without relict charcoal hearth (RCH). Consequently, to understand and describe the mechanism of pyrogenic magnetic enhancement in charcoal-enriched horizon (CEH), research into its magnetic features was initiated. This work was carried out on three soil profiles <em>(Albic Brunic Arenosols</em>), both RCHs and reference. The magnetic data obtained during the study showed variable contribution of magnetic particles in soil horizons, which indicates pyrogenic magnetic enhancement related to the presence of superparamagnetic (SP) grains in the charcoal particles from CEH in the RCHs soil profile. Despite the oxidation of SP grains of ferrimagnetic minerals over time (200–250 years) superparamagnetic magnetite and/or maghemite are still responsible for the pyrogenic magnetic enhancement in soil.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"460 ","pages":"Article 117458"},"PeriodicalIF":5.6,"publicationDate":"2025-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144711282","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Moisture-driven shifts in microbial nitrogen limitation under biochar and nitrification inhibitors co-application in tropical soils","authors":"Lijun Liu ,&nbsp;Qilin Zhu ,&nbsp;Xiaoqian Dan ,&nbsp;Huanyu Bao ,&nbsp;Tongbin Zhu ,&nbsp;Lei Meng ,&nbsp;Ahmed S. Elrys ,&nbsp;Christoph Müller ,&nbsp;Jinbo Zhang","doi":"10.1016/j.geoderma.2025.117455","DOIUrl":"10.1016/j.geoderma.2025.117455","url":null,"abstract":"<div><div>Biochar and nitrification inhibitors (NIs) are crucial in improving soil nitrogen (N) availability and decreasing its environmental consequences in agroecosystems. Soil microbes can regulate soil N dynamics through metabolic processes, such as the secretion of extracellular enzymes, which affect both N production and turnover. However, how and why soil microbial N limitation (MNL) responds to biochar-NIs co-application is poorly understood, especially in tropical regions under different moisture contents. Here, an incubation study was conducted on soils from a long-term rice-vegetable rotation to investigate the effects of five treatments including control (no biochar or NIs), 2 % biochar, 2 % biochar plus 5 % dicyandiamide (DCD), 2 % biochar plus 1 % 3,4 dimethylpyrazole phosphate (DMPP), and 2 % biochar plus 2.5 % DCD and 0.5 % DMPP, at 60 % and 100 % water holding capacity (WHC) on MNL and N availability. Biochar derived from rice straw was applied at a rate of 40 Mg ha⁻¹. All treatments, including the control, received 150 mg N kg⁻¹ as urea, with NIs added proportionally to the applied N mass. The vector-threshold element ratio was applied to evaluate MNL, while δ¹⁵N and net N transformation rates were measured to evaluate N availability. The vector-threshold model results indicated severe MNL in studied soils, and that biochar, alone or with NIs, increased δ¹⁵N and alleviated the MNL under unsaturated conditions, while the opposite was observed under saturated conditions. Biochar increased the particulate and dissolved organic carbon contents, which in turn increased the net N mineralization rate, thereby alleviating MNL under unsaturated conditions. Relative to biochar, biochar-NIs co-application increased net N mineralization rate under unsaturated conditions. The lower nitrate production in response to biochar, alone or with NIs, decreased δ¹⁵N and aggravated MNL under saturated conditions. Among all NIs treatments, biochar + DMPP showed the highest net N mineralization rate, but the lowest MNL at 60 % WHC and the highest MNL at 100 % WHC. Nitrous oxide emissions increased in response to biochar alone, but decreased under biochar-NIs co-application in unsaturated and saturated soils, with the lowest emissions observed for biochar + DCD at 60 % WHC and biochar + DCD + DMPP at 100 % WHC. Our results indicated that soil moisture conditions control the response of MNL and N losses to biochar and NIs in the tropics.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"460 ","pages":"Article 117455"},"PeriodicalIF":5.6,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144711248","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel method for soil organic carbon prediction using integrated ‘ground-air-space’ multimodal remote sensing data","authors":"Yilin Bao ,&nbsp;Xiangtian Meng ,&nbsp;Huanjun Liu ,&nbsp;Mengyuan Xu ,&nbsp;Mingchang Wang","doi":"10.1016/j.geoderma.2025.117453","DOIUrl":"10.1016/j.geoderma.2025.117453","url":null,"abstract":"&lt;div&gt;&lt;div&gt;High-accuracy maps of soil organic carbon (SOC) content are essential for agricultural management and ecosystem services. However, traditional remote sensing data can hardly balance spatial and spectral resolution, resulting in the inability to simultaneously obtain high-resolution spatial distribution of SOC and detailed spectral features, thus restricting the comprehensive resolution of soil detail information. To address this challenge, we propose an innovative multimodal remote sensing data integration framework, ResoCroS-Net, which integrates ground (soil samples), air (unmanned aerial vehicle (UAV) images), and space (satellite images) data, realized effective integration of multimodal data at different resolutions, with particular innovations in hierarchical design and data-processing logic. Specifically, ground samples and air images are combined to generate high accuracy SOC maps, which serve as the ’spatial’ baseline for ResoCroS-Net used as a reference for subsequent high-resolution image generation. Next, low spatial resolution images (ZY1-02D, Sentinel-2A) are downscaled to high spatial resolution images using Enhanced Super-Resolution Generative Adversarial Network models within adversarial networks. Meanwhile, typical spectral features in ZY1-02D satellite data were extracted, and a spectral dictionary was constructed for accurate reduction of details in low spectral resolution images. Using spectral unmixing networks and sparse representation networks, low spectral resolution images are downscaled to high spectral resolution. Then, joint spatial-spectral features were extracted by 3D convolutional neural network. Based on this framework, we developed Model (i), which integrates SOC data with spatial-spectral resolution downscaling (SSD) image; Model (ii), which integrates SOC data, UAV image with spatial resolution downscaling (SD) image; and Model (iii), which integrates SOC data, UAV image with SSD image. We also evaluated the performance of various algorithms (e.g., Random Forest (RF), Convolutional Neural Networks (CNN), Graph Neural Networks (GNN), and Multi-Layer Perceptron (MLP)) across these models. The SOC prediction experiments conducted in Youyi, the largest state farm in China, demonstrate that Model (iii) achieves the highest accuracy with the GNN model. This model improves coefficient of determination (R&lt;sup&gt;2&lt;/sup&gt;) and ratio of performance to interquartile distance (RPIQ) by 0.09 and 0.28, respectively, and reduces root mean square error (RMSE) by 0.52 g kg&lt;sup&gt;−1&lt;/sup&gt; compared to Model (ii). In addition, using UAV data as the baseline layer significantly improves prediction accuracy, with R&lt;sup&gt;2&lt;/sup&gt; and RPIQ increasing by 0.17 and 0.58, respectively, and RMSE decreasing by 1.09g kg&lt;sup&gt;−1&lt;/sup&gt;. Regarding model performance in SOC content prediction, GNN is more suitable for Model (i) and Model (iii), while CNN is more appropriate for Model (ii). In conclusion, ResoCroS-Net achieved collaborative opti","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"460 ","pages":"Article 117453"},"PeriodicalIF":5.6,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144695219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The impact of direct and indirect digital soil mapping approaches on spatial uncertainty","authors":"Gábor Szatmári,&nbsp;László Pásztor","doi":"10.1016/j.geoderma.2025.117448","DOIUrl":"10.1016/j.geoderma.2025.117448","url":null,"abstract":"<div><div>While numerous studies have compared different mapping approaches (or inference trajectories) in digital soil mapping (DSM), their impact on uncertainty quantification and propagation has received less attention. The objective of this study was to investigate key questions related to uncertainty quantification and propagation, which may influence the applicability of DSM products. Including, how do different mapping approaches and assumptions made in DSM affect uncertainty quantification and propagation? What are the pros and cons of the mapping approaches from the perspective of uncertainty? Such questions were examined on the example of mapping soil organic carbon (SOC) in the Great Hungarian Plain, Hungary, by combining machine learning with univariate and multivariate geostatistics. Two cases were investigated: in Case 1, the goal was to map SOC stock for the year 2016 using both direct and indirect mapping approaches and to quantify and compare prediction uncertainty at various spatial aggregation levels. In Case 2, the objective was similar, but focused on mapping SOC stock change between 1992 and 2016. A wide range of inference trajectories (e.g., “calculate then model”, “model then calculate”), prior data transformations (e.g., square root, standard normalization), and uncertainty propagation techniques (e.g., Taylor method, analytical solution) were applied and compared from the perspective of both prediction accuracy (e.g., mean error, root mean square error) and uncertainty (e.g., prediction interval coverage probability plot, interval scores). The results showed that both the chosen inference trajectories and the assumptions made in DSM significantly impact uncertainty estimates not only at point support but also at larger supports. It also highlighted the importance of accounting for the correlation of interpolation errors when conducting uncertainty propagation. Additionally, this research emphasized the need to identify and quantify the contribution of different error sources in uncertainty propagation, as this can be the key to reduce the overall uncertainty associated with the given soil property or function of interest.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"460 ","pages":"Article 117448"},"PeriodicalIF":5.6,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144686819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}