European Journal of Soil Science最新文献

{"title":"Response of Soil Organic Carbon and Bacterial Community to Amendments in Saline-Alkali Soils of the Yellow River Delta","authors":"Huili Zhao,&nbsp;Jiaqi Li,&nbsp;Xinqi Li,&nbsp;Qiuli Hu,&nbsp;Xiaohong Guo,&nbsp;Yanwen Wang,&nbsp;Ying Zhao,&nbsp;Gary Y. Gan","doi":"10.1111/ejss.70147","DOIUrl":"https://doi.org/10.1111/ejss.70147","url":null,"abstract":"<div>\u0000 \u0000 <p>The salt-alkali barrier and low fertility of coastal saline soil are bottlenecks that restrict the high-quality development of agriculture, and optimising measures to control salinity and increase carbon content has become an urgent task. The application of gypsum and the retention of straw are increasingly recognised practices aimed at mitigating soil salinization and enhancing soil fertility. However, the combined effects of these practices on soil organic carbon (SOC) sequestration and microbial community remain unclear. A field experiment was performed to analyse the influence of straw (0 and 10 t·ha⁻¹) and desulfurization gypsum (0 and 29 t·ha⁻¹) on soil chemical properties, aggregate-related carbon fractions and bacterial community features. Both straw and straw plus desulfurization gypsum treatments enhanced Shannon and Chao1 indices in all aggregates, though straw plus desulfurization gypsum reduced Chao1 in small macroaggregates compared to straw alone. The multidimensional scaling analysis suggested that the bacterial β-diversity was obviously impacted among different treatments. Both straw and straw plus desulfurization gypsum favoured the growth of <i>Chloroflexi</i>, <i>Actinobacteria</i> in clay-silt aggregates, <i>Planctomycetes</i> in microaggregates, <i>Acidobacteria</i> in microaggregates and clay-silt aggregates, <i>Woeseia</i> in macroaggregates, and inhibited the growth of <i>Proteobacteria</i> in clay-silt aggregates and <i>Bacteroidetes</i> in microaggregates and clay-silt aggregates. Straw plus desulfurization gypsum reduced the inhibitory effect of straw treatment on <i>Gemmatimonadetes</i>, <i>Bacteroidetes</i>, and <i>Tumebacillus</i>. Straw plus desulfurization gypsum decreased soil pH, sodium adsorption ratio and dissolved organic carbon (DOC), and increased sequestered SOC, enzyme activity and mean weight diameter more than only straw addition. Both enhanced microbial biomass carbon (MBC) and reduced exchangeable sodium percentage. MBC, SOC, DOC, and β-glucosidase were closely correlated with bacterial community composition. It is feasible to achieve greater carbon content while enhancing soil aggregate stability through the optimisation of straw incorporation or straw plus desulfurization gypsum in saline-alkali soil. These findings offer significant insights to improve saline-alkali soil.</p>\u0000 </div>","PeriodicalId":12043,"journal":{"name":"European Journal of Soil Science","volume":"76 4","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144740539","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":"The Utility of Laboratory Measurement Uncertainty: A Case-Study Using the Open Soil Spectral Library Service","authors":"Kanchan Grover,&nbsp;José Lucas Safanelli,&nbsp;Jonathan Sanderman,&nbsp;Bryan G. Hopkins,&nbsp;Colby Brungard","doi":"10.1111/ejss.70166","DOIUrl":"https://doi.org/10.1111/ejss.70166","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 &lt;p&gt;Soil spectroscopy offers the promise of rapid and cost-effective alternatives to traditional wet chemistry methods for analyzing soil properties, with broad applicability across soil types and geographic regions. This promise has led to the creation of large spectral libraries and online modeling tools, including the Open Soil Spectral Library (OSSL). While these tools can advance soil spectroscopy, they often rely on the assumption that laboratory reference measurements are error-free. In this study, we evaluated the accuracy of the OSSL engine in predicting 27 soil properties from mid-infrared spectra, explicitly accounting for uncertainty in laboratory measurements. Predicted properties included carbon fractions (total, organic, inorganic), total nitrogen, cation exchange capacity, electrical conductivity, 1:1 pH, 1:2 CaCl&lt;sub&gt;2&lt;/sub&gt; pH, particle-size fractions (clay, silt, sand), NH&lt;sub&gt;4&lt;/sub&gt;OAc-extractable K, Ca, Mg, and Na; KCl-extractable Al; Mehlich III extractable K, Ca, Mg, Na, Al, Mn, Fe, Cu, and B; and phosphorus extracted by both Bray and Olsen methods. The quality of spectral predictions was evaluated using analytical results from the North American Proficiency Testing (NAPT) program—a geographically diverse dataset comprising standardized soil measurements from multiple laboratories. To quantify predictive performance, OSSL predictions were compared to the median NAPT values using several common statistical metrics, including the Nash–Sutcliffe efficiency coefficient (NSE), concordance correlation coefficient (CCC), ratio of performance to interquartile range (RPIQ), and standardized bias. When compared against median measurements, the carbon and particle size fractions and CEC were predicted well. Total N, 1:1 and 1:2 pH, Mehlich III extractable Ca, Al, and Mg, and NH&lt;sub&gt;4&lt;/sub&gt;OAc exchangeable Mg were moderately well predicted. All other soil properties were not well predicted. To further evaluate the reliability of OSSL predictions in the context of laboratory measurement uncertainty, we assessed the proportion of predicted values falling within predefined tolerance ranges. Specifically, we calculated the percentage of predictions that fell within 2.5 and 4 times the median absolute deviation (MAD) from the median NAPT value. These thresholds are consistent with those used by the NAPT program to identify potentially erroneous laboratory measurements and serve as a proxy for acceptable uncertainty bounds. More than 80% of OSSL predictions were within NAPT-acceptable measurement ranges for CEC, inorganic C, and clay. Silt, total and organic carbon, sand, and total N predictions were within the acceptable ranges more than 50% of the time. Less than 50% of all other soil properties were predicted within acceptable measurement ranges. These results suggest that OSSL predictions could replace CEC measurements for agricultural surface soils. These results highlight the importance of including the uncerta","PeriodicalId":12043,"journal":{"name":"European Journal of Soil Science","volume":"76 4","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144740107","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":"Linking Measurable Phosphorus Pools With Simulations of Soil P Dynamics: Results for the Long-Term Experiment ‘Rostock’","authors":"Michael Herbst,&nbsp;Gihan Mohammed,&nbsp;Bettina Eichler-Löbermann,&nbsp;Wulf Amelung,&nbsp;Jan Vanderborght,&nbsp;Nina Siebers","doi":"10.1111/ejss.70160","DOIUrl":"https://doi.org/10.1111/ejss.70160","url":null,"abstract":"<p>Phosphorus (P) is removed from agroecosystems through harvesting, and sustainable management must include P fertilization as P availability affects crop performance. However, accurate assessment of plant-available P is challenging. In this study, two promising approaches are combined to assess the plant-available P of a 22-year long-term experiment (LTE) near Rostock, Germany. We hypothesize agreement between a modern P test method and process-based model estimates of plant-available P. The diffusive gradients in thin films (DGT) technique offers an accurate P test method because it mimics the diffusion and desorption of soil P in the presence of root uptake. This was applied in a synergetic combination with a state-of-the-art agroecosystem model that was extended with a P cycling module. The simulations and yearly DGT-P analyses comprise 4 treatments: no P fertilization, mineral P fertilization with triple-superphosphate, organic P fertilization with compost, and mineral plus organic P fertilization. Soils at 0–30 cm depth were sampled in four replicates on a yearly basis between 1999 and 2021. In addition, a P fractionation was applied for 2015 using the Hedley approach, which made it possible to link non-plant-available, steady P fractions with the respective model pools. The comparison between DGT-P determined plant-available P up to a depth of 30 cm and that estimated from the pools of the agroecosystem model AgroC showed agreement with respect to the differences between the treatments and with respect to the temporal evolution (<i>R</i>² between 0.65 and 0.7). Less agreement was detected for DGT-P and the respective model pools in deeper soil. A closer match over soil depth was found between grouped Hedley P fractions and AgroC model pools. Both, model and DGT-P analyses indicate that a new plant-available P equilibrium will be established under the new P management after about 12 years for the Rostock site, which points to the resilience of P cycling in agroecosystems. We conclude that the combined application of DGT-P analysis and agroecosystem modeling offers a robust and accurate quantification of plant-available P in the plough layer and can be used to create an agricultural digital twin with respect to soil P availability and its impact on crop yield.</p>","PeriodicalId":12043,"journal":{"name":"European Journal of Soil Science","volume":"76 4","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/ejss.70160","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144725550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Differential Effects of Salt Anion Type and Contents on Aggregate-Associated C and N in Saline-Alkali Soils","authors":"Yuqi Chen,&nbsp;Lingying Xu,&nbsp;Zhiwang Wang,&nbsp;Xu Zhao","doi":"10.1111/ejss.70167","DOIUrl":"https://doi.org/10.1111/ejss.70167","url":null,"abstract":"<div>\u0000 \u0000 <p>Soil salinization adversely affects the structure of soil aggregates, reducing organic carbon (OC) and nitrogen (TN) pools, and ultimately impairing soil fertility. This study explores how saline-alkali barriers impact the soil aggregate composition and the OC and TN distribution in three typical salt-affected soils in China, primarily comprising soda salt, chloride salt, and sulfate salt, under varying salinity levels (non-saline, mild–moderate, and severe). The results indicated that salinity significantly reduced the proportion of macroaggregates (&gt; 0.25 mm) in soda-salt and chloride-salt-affected soils, while sulfate-salt soils showed minimal change across salinity levels. The mean weight diameter (MWD) and geometric mean diameter (GMD) declined with increasing salinity, primarily influenced by the sodium adsorption ratio (SAR), exchangeable sodium percentage (ESP), and Cl⁻, which are critical limiting factors for aggregate stability. In contrast, soil organic carbon and biological factors, including enzyme activity, significantly enhanced aggregate stability. With increasing salinity, the contribution of microaggregates (0.053–0.25 mm) and silt + clay fractions (&lt; 0.053 mm) to OC and TN increased in soda-salt and chloride-salt soils, whereas the sulfate-salt soils exhibited this change only under severe salinity. Negative impacts on aggregate stability and biological activity arise from HCO₃⁻ + CO₃²⁻ and Cl⁻, whereas SO₄²⁻ primarily affected biological factors. The overall findings suggest that sulfate salt-affected soils are less sensitive to saline-alkali barriers than those affected by soda and chloride salts. Targeted interventions to mitigate saline-alkali barriers and enhance the soil biological environment of soil are essential for improving aggregate stability and nutrient storage. These insights provide important theoretical support to develop nutrient management strategies for saline-alkali lands.</p>\u0000 </div>","PeriodicalId":12043,"journal":{"name":"European Journal of Soil Science","volume":"76 4","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144725551","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":"Selenite Adsorption and Desorption Characteristics in Soils: Effects of Soil Amendments and Underlying Mechanisms","authors":"Hui Zhai,&nbsp;Yumeng Liu,&nbsp;Lei Pan,&nbsp;Yujian Wang,&nbsp;Haotian Gong,&nbsp;Mengqin Ren,&nbsp;Jiacheng Wu","doi":"10.1111/ejss.70164","DOIUrl":"https://doi.org/10.1111/ejss.70164","url":null,"abstract":"<div>\u0000 \u0000 <p>Understanding the adsorption and desorption characteristics of selenium (Se) in soil is crucial for predicting the availability of exogenous Se. Biochar (BC) and sheep manure (SM) are widely used as soil amendments, but their effects on Se adsorption and desorption remain incompletely understood. This study investigated the effects of cotton straw BC and SM on the adsorption-desorption behavior and mechanisms of selenite in gray desert soil and irrigation-silted soil using batch equilibrium experiments, scanning electron microscopy (SEM), X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FTIR). The results indicated that BC and SM addition reduced Se adsorption and increased its desorption rate in both soils, with the highest desorption rate (89%) observed in irrigation-silted soil amended with 5% BC. The Se adsorption kinetics followed a pseudo-second-order model, and the adsorption isotherms were well described by the Freundlich model. Characterization results revealed that organic compounds (e.g., aromatic compounds, carboxyl compounds, and ethers) in BC and SM influenced the adsorption process. Additionally, phosphate ions released from BC in gray desert soil and carbonate ions released from BC in irrigation-silted soil both competed with Se for adsorption sites. This study systematically elucidates the effects of BC and SM on selenite adsorption-desorption behavior in soils, providing a theoretical basis for understanding Se biogeochemical behavior and supporting the safe production of Se-enriched crops.</p>\u0000 </div>","PeriodicalId":12043,"journal":{"name":"European Journal of Soil Science","volume":"76 4","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144725613","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":"AI as a Catalyst for Cross-Disciplinary Breakthroughs in Soil Carbon Sequestration Research","authors":"Budiman Minasny,&nbsp;Alex. B. McBratney,&nbsp;Cornelia Rumpel","doi":"10.1111/ejss.70165","DOIUrl":"https://doi.org/10.1111/ejss.70165","url":null,"abstract":"<p>AI models have been proposed for generating scientific hypotheses; thus, our aim was to test their ability to drive novel research in soil science. We used an AI multiagent platform to generate research ideas for (innovative) practices capable of increasing Mineral-Associated Organic Carbon (MAOC) in soils. We assigned the AI multiagent system Manus two tasks: a general research-generation task and a specific task that required cross-disciplinary approaches. For the general task, the AI proposed well-documented strategies such as no-till farming, crop diversification, integrated crop-livestock systems, and organic and other amendments. More notably, the cross-disciplinary task generated novel ideas from materials science, bioengineering, chemistry, medical science, physics, marine science, geology, and computer science. The AI system prioritized three research areas: (1) Engineered mineral surface modifications to optimize carbon binding, (2) Controlled-release carbon delivery systems, inspired by medical drug delivery technologies, and (3) Biomimetic mineral engineering mimicking high-carbon natural environments. We critically assessed the proposals and determined that while some are plausible and align with concepts in soil science, others offer the potential to open new research avenues through interdisciplinary collaboration. Our findings suggest that AI can generate “outside-the-box” hypotheses and help test new scientific ideas, demonstrating its potential to drive innovation in soil science. We suggest a workflow for using AI for hypothesis generation to ensure scientific rigour and epistemic responsibility.</p>","PeriodicalId":12043,"journal":{"name":"European Journal of Soil Science","volume":"76 4","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/ejss.70165","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144725552","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multidisciplinary Soil Science for Sustainability","authors":"Yonghong Wu,&nbsp;Tida Ge,&nbsp;Xiaorong Wei,&nbsp;Yuji Jiang","doi":"10.1111/ejss.70162","DOIUrl":"https://doi.org/10.1111/ejss.70162","url":null,"abstract":"&lt;p&gt;Soils are the foundation of terrestrial ecosystems, underpinning a wide array of essential ecosystem services that sustain life on Earth. They support agricultural productivity by facilitating the production of food and fibre, regulate hydrological and geochemical cycles, sequester carbon, and provide habitat for a vast diversity of organisms (Blum &lt;span&gt;2005&lt;/span&gt;; Kopittke et al. &lt;span&gt;2019&lt;/span&gt;). Given their central role in ecosystem functioning, soils are indispensable to achieving several United Nations Sustainable Development Goals (SDGs), particularly those related to food security (SDG 2), climate action (SDG 13), clean water (SDG 6), and life on land (SDG 15). Despite this importance, soils face increasing threats from various forms of degradation, including erosion, organic matter depletion, contamination, compaction, salinisation, and biodiversity loss (IPCC &lt;span&gt;2019&lt;/span&gt;). These threats are exacerbated by climate change, land-use change, and unsustainable management practices (Yang et al. &lt;span&gt;2024&lt;/span&gt;). Alarmingly, soils often remain marginalised in policy agendas—perceived more as passive recipients of environmental stressors than as active agents of climate and biodiversity solutions (Gonzalez Lago et al. &lt;span&gt;2019&lt;/span&gt;). This disconnect underscores a critical need to elevate the status of soils within global sustainability and policy frameworks.&lt;/p&gt;&lt;p&gt;Effectively addressing these challenges demands a multidisciplinary research approach that integrates the physical, chemical, biological, ecological, and socio-economic dimensions of soil systems. Bridging traditional disciplinary boundaries enables a more comprehensive understanding of the complex and dynamic interactions that govern soil functions across spatial and temporal scales. For instance, ecological studies have illuminated the fundamental role of soil biota in nutrient cycling and ecosystem resilience (Qu et al. &lt;span&gt;2024&lt;/span&gt;). Multidisciplinary soil science fosters systems-level insights that are essential for designing sustainable land management strategies that enhance productivity, preserve soil health, mitigate climate change, and protect biodiversity. Integrating soil science with fields such as agronomy, hydrology, microbiology, economics, and data science opens new avenues—such as optimising trade-offs between carbon sequestration and crop yields, or developing predictive models to guide decision-making under changing environmental conditions (Cai et al. &lt;span&gt;2023&lt;/span&gt;). The &lt;i&gt;European Journal of Soil Science&lt;/i&gt; (EJSS) special issue on “Multidisciplinary Soil Science for Sustainability” highlights recent advances in this domain and emphasises its pivotal role in addressing global sustainability goals, with contributions ranging from microbial ecology to computational modelling.&lt;/p&gt;&lt;p&gt;Soil is a complex and dynamic ecosystem where physical properties, chemical reactions, and biological interactions converge to shape its fertility, resilience","PeriodicalId":12043,"journal":{"name":"European Journal of Soil Science","volume":"76 4","pages":""},"PeriodicalIF":4.0,"publicationDate":"2025-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/ejss.70162","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144716649","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improved Broad-Scale Modelling of Soil Organic Carbon Dynamics Following Land-Use Changes","authors":"Daria Seitz,&nbsp;Rene Dechow,&nbsp;David Emde,&nbsp;Florian Schneider,&nbsp;Axel Don","doi":"10.1111/ejss.70159","DOIUrl":"https://doi.org/10.1111/ejss.70159","url":null,"abstract":"<p>Land-use changes (LUCs) strongly impact soil organic carbon (SOC) stocks over decades. However, there are too few long-term field experiments where these SOC dynamics have been observed long enough to validate process-based models for large-scale use. We have developed a new data-driven space-for-time approach for model validation using empirical data from over 3000 sites in the German Agricultural Soil Inventory, including 212 sites with LUC between cropland and grassland. Machine-learning models trained on sites under permanent land use were used to predict equilibrium SOC stocks for similar sites with changed land use. We used this derived data set to assess how well the process-based model RothC describes SOC dynamics following LUC. The default version of RothC struggled to capture the fast changes in SOC following LUC since it was mainly driven by differences in carbon input quantity and quality. Losses in SOC after converting grassland into cropland occurred faster than modelled, and SOC accrual after converting cropland to grassland was faster than simulated. This suggested an additional carbon stabilisation mechanism connected to grassland land use. We extended the RothC model with an additional carbon pool that builds up rapidly after grassland establishment, similar to aggregate-protected SOC. This improved the model efficiency from 0.49 to 0.80 for transitional croplands and from −3.39 to 0.90 after establishing grassland. This improved model version, RothC-LUC, is suitable for simulating SOC dynamics following LUC between cropland and grassland on a broad scale, such as in national inventory reports on greenhouse gas emissions.</p>","PeriodicalId":12043,"journal":{"name":"European Journal of Soil Science","volume":"76 4","pages":""},"PeriodicalIF":4.0,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/ejss.70159","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144635405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep Carbon: A Multiscale Feature-Time Fusion Approach for Field Level Digital Soil Organic Carbon Mapping","authors":"Ayan Das,&nbsp;Manoj K. Mishra,&nbsp;Somsubhra Chakraborty,&nbsp;Bimal K. Bhattacharya,&nbsp;Rucha Dave,&nbsp;Dileep Kumar,&nbsp;Khushvadan Patel,&nbsp;Raj Setia,&nbsp;David C. Weindorf","doi":"10.1111/ejss.70161","DOIUrl":"https://doi.org/10.1111/ejss.70161","url":null,"abstract":"<div>\u0000 \u0000 <p>Soil organic carbon (SOC) plays a key role in soil health and ecosystem services. This study introduces Deep Carbon, a modelling framework that integrates static and time-series environmental covariates for high-resolution SOC prediction at the field scale. Time-series data were encoded using a stacked long short-term memory (LSTM) neural network to extract temporal patterns of dynamic features. These encoded time-series representations were combined with static covariates and used as inputs to train machine learning models at multiple spatial resolutions (5 km to 10 m). Individual predictions at each scale were then fused using a partial least squares regression (PLSR) model to generate SOC maps at 10 m resolution. The best accuracy was observed at 5 km scale (<i>R</i>² = 0.75; RMSE = 0.30% in log scale), while the fused 10 m prediction yielded a testing <i>R</i>² of 0.58 and RMSE of 0.44%. Fusion modelling identified 30 and 250 m resolutions as the most influential predictors. The approach successfully captured both high- and low-frequency SOC variations and demonstrated good transferability when tested on new observations from 2022. This multi-scale feature-time fusion approach uses legacy ground samples and satellite data to enable scalable and accurate digital SOC mapping.</p>\u0000 </div>","PeriodicalId":12043,"journal":{"name":"European Journal of Soil Science","volume":"76 4","pages":""},"PeriodicalIF":4.0,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144624280","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":"Aridity Index Explains the Accumulation of Soil Organic Carbon Sources in Grassland Ecosystem","authors":"Jinpeng Ma,&nbsp;Lin Chen,&nbsp;Danbo Pang,&nbsp;Mengyao Wu,&nbsp;Yaqi Zhang,&nbsp;Yinglong Chen,&nbsp;Xuebin Li","doi":"10.1111/ejss.70158","DOIUrl":"https://doi.org/10.1111/ejss.70158","url":null,"abstract":"<div>\u0000 \u0000 <p>Plant-derived carbon (PDC) and microbial-derived carbon (MDC) are the crucial sources of soil organic carbon (SOC), and their contributions strongly affect the stability and turnover of soil organic matter. However, the mechanism underlying the contribution of PDC and MDC to SOC across different grassland types is poorly understood. In this study, we selected four grassland types in Ningxia, China, at a regional scale, including meadow steppe, typical steppe, desert steppe, and steppe desert. We analysed the characteristics of PDC and MDC in topsoil (0–20 cm) and subsoil (20–40 cm) across different grassland types and their contributions to SOC. Our results showed PDC and MDC contents in meadow steppe were significantly larger than those in the other grassland types (<i>p</i> &lt; 0.05), while the contribution of PDC and MDC to SOC in desert steppe was greatest (<i>p</i> &lt; 0.05), and bigger in subsoil than in topsoil. Vanillyl phenols-derived carbon (19%) and fungal necromass carbon (69%) were the main contributors to PDC and MDC, respectively. In addition, random forest model results showed that climate, vegetation, and soil explained 55% and 85% of the variation in PDC and MDC, respectively (<i>p</i> &lt; 0.001). A structural equation model revealed that aridity index was the primary factor influencing SOC sources in grassland ecosystems. This study examined the contributions of PDC and MDC to SOC across different grassland types, as well as the underlying mechanisms of SOC sequestration, providing insights into the carbon cycle processes within grassland ecosystems.</p>\u0000 </div>","PeriodicalId":12043,"journal":{"name":"European Journal of Soil Science","volume":"76 4","pages":""},"PeriodicalIF":4.0,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144615317","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}