Soil最新文献

{"title":"Geochemical predictability quantification and spatial transferability of soil organic carbon in Ganges Delta","authors":"Md Rakib Hasan, Fazla Zawadul Arabi, Mst Anika Khatun Rupa, Shoumik Zubyer, Mohammad Fazle Alam Rabbi, Md Jashim Uddin","doi":"10.5194/egusphere-2026-4799","DOIUrl":"https://doi.org/10.5194/egusphere-2026-4799","url":null,"abstract":"<strong>Abstract.</strong> Deltas are among the least studied but most dynamically active reservoirs that store a significant amount of the world’s soil organic carbon (SOC). This study evaluates the complex dynamics of deltas by combining soil profiles from four geomorphological zones in the Ganges Delta of Bangladesh with 6,652 soil profiles from fourteen major deltas worldwide. These combined profiles test the limits of regional SOC models, showing where local frameworks hold and where they break. Statistical analysis shows that salinity, cation exchange capacity, and moisture correlate most strongly with SOC (<em>r</em> = 0.66, 0.64, and 0.56, respectively), with most saline profiles storing approximately 6.5 times more carbon than freshwater sites. Salinity also exhibits a strict scale-dependent effect of strong correlations across geomorphological zones but effectively vanishing within them. This spatial paradox introduces major implications for digital soil mapping protocols in coastal deltas. Projections from a process model show that mangrove restoration efforts on half of the most saline tracts would increase SOC levels by 26.6 % in 2050, far exceeding baseline model of business-as-usual projections that show a 5.9–11.6 % decline across climate pathways. Model simulations indicate that local management has 4.6 to 7.2 times more influence on SOC storage than the gap between RCP 4.5 and RCP 8.5. To prevent data overlap from multi-depth sampling, the cross-validation had to hold back entire locations to avoid spatial leakage. As a result gradient boosting reached an <em>R</em>² of 0.64, against an inflated 0.91, and deeper neural networks provided no reliable improvement at this sample size. Analyzing every combination of the fifteen deltas exposed a sharp limit: models generalize within a single delta (median <em>R</em>² = +0.25) but fail between deltas, yielding positive scores in only 6 % of 210 pairs (median <em>R</em>² = −0.55). Transfer failed in both directions, even when fourteen deltas were used to predict the fifteenth delta. Unlike statistical weights, the structural framework of the process model transferred well, showing that the form of the model is broadly applicable when parameter tuning remains local site specific. Consequently, gathering data from foreign deltas cannot substitute for local profile measurements. These findings demonstrate that global datasets can guide structural frameworks but effective coastal carbon management ultimately depends on local site-specific observation.","PeriodicalId":48610,"journal":{"name":"Soil","volume":"77 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2026-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148922840","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":"Differences in organic carbon fractions and stability explain limited accumulation in loam and sandy loam under greenhouse conditions","authors":"Boyuan Tan, Lu Yang, Xun Xiao, Chunji Li, Jing Tan, Ning An, Lingxuan Meng, Yanli Yi, Fengkui Qian, Na Li, Xue Liu, Song Li, Wei Han","doi":"10.5194/soil-12-855-2026","DOIUrl":"https://doi.org/10.5194/soil-12-855-2026","url":null,"abstract":"Abstract. Manure is widely applied in greenhouses to enhance soil organic carbon (SOC) and improve fertility. However, how SOC fractions and their chemical stability change under different soil textures and long-term manure inputs remains unclear. We investigated greenhouse soils with 2–50 years of manure application in loam and sandy loam. SOC, easily oxidizable carbon (EOC), microbial biomass carbon (MBC), dissolved organic carbon (DOC), particulate organic carbon (POC), and mineral-associated organic carbon (MAOC) were quantified. The molecular structures of SOC were analyzed via 13C NMR spectroscopy. Results showed that SOC in loam stabilized after about 20 years of manure application, whereas sandy loam reached equilibrium within 2 years. In loam, aromatic C and carbonyl C in SOC increased, raising the aromaticity index (AI); in sandy loam, alkyl C increased, elevating alkyl C to O-alkyl C (A/OA) and the hydrophobicity index (HI). Loam contained higher SOC, EOC, POC, and MAOC contents than sandy loam, with SOC positively correlated with EOC, POC, and MAOC, whereas in sandy loam SOC was positively correlated only with EOC and MAOC, and negatively with fine POC (fPOC). In loam, the AI and HI of SOC showed significant positive path relationships with EOC, DOC and POC (coarse POC [cPOC] and fPOC), while the accumulation of both cPOC and fPOC contributed to MAOC formation. In sandy loam, HI was mainly positively associated with EOC and cPOC, while MAOC was primarily related to EOC. Overall, in greenhouses, long-term stability of SOC depends on the transformation of labile carbon into stable fractions, with fine-textured soils exhibiting greater sequestration efficiency due to higher structural stability and greater MAOC accumulation.","PeriodicalId":48610,"journal":{"name":"Soil","volume":"39 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2026-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148922839","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":"Agroforestry enhances the capacity of deep tropical soils to act as nutrient sinks and biogeochemical buffers, thereby improving internal nutrient recycling – insights from incubation experiments","authors":"Zoé Ott, Zoé Favaro, Samuel Abiven, Priscia Oliva, Hugo Pradalier, Jonathan Prunier, Christophe Jourdan, Laurent Ruiz, Baptiste Alran, Sambuddha Misra, Muddu Sekhar, Jean Riotte","doi":"10.5194/egusphere-2026-4848","DOIUrl":"https://doi.org/10.5194/egusphere-2026-4848","url":null,"abstract":"&lt;strong&gt;Abstract.&lt;/strong&gt; The understanding of the interactions between the lower and upper compartments of the Critical Zone (CZ) is of major importance to the maintenance of life across continental landscapes. The extent to which deep root uptake supplies nutrients from depth and redistributes them to the entire ecosystem remains unknown. Identifying the processes at stake and quantifying their effects on nutrients cycles is of paramount importance for assessing ecosystem resilience and designing management practices enhancing biologically mediated CZ processes in agrosystems. The impact of depth and land-use on the decomposition of soil organic matter (SOM; roots free soil) and fine roots (&lt;2 mm) was investigated for a tropical conventional irrigated agriculture plot and an agroforestry one, at two depths (0–15 cm and between 8 and 10 m), through soil incubations in small lysimeters over a period of 115 days. Dynamics of CO&lt;sub&gt;2&lt;/sub&gt; and major soluble species (NO&lt;sub&gt;3&lt;/sub&gt;&lt;sup&gt;-&lt;/sup&gt;, SO&lt;sub&gt;4&lt;/sub&gt;&lt;sup&gt;2-&lt;/sup&gt;, PO&lt;sub&gt;4&lt;/sub&gt;&lt;sup&gt;3-&lt;/sup&gt;, Na&lt;sup&gt;+&lt;/sup&gt;, Ca&lt;sup&gt;2+&lt;/sup&gt;, Mg&lt;sup&gt;2+&lt;/sup&gt;, K&lt;sup&gt;+&lt;/sup&gt;, DOC and DIC) were monitored over the whole incubation period using sodium hydroxide traps and free pore water extraction at each time step, respectively. Soil initial and final C, N and exchangeable stocks were also characterized. During the 115 days that lasted this experiment, more than 90 % of the C fluxes were released as CO&lt;sub&gt;2 &lt;/sub&gt;for all treatments. However, the final cumulative fluxes varied depending on soil depth and land use, both for the decomposition of SOM and for that of fine roots, with a potential priming in soils under conventional agriculture and a legacy effect in agroforestry soils. Cation and anion fluxes varied primarily with depth and could be classified into three groups based on their extraction dynamics: (1) Na and K, preferentially leached from the CEC; (2) nitrate and sulfate, mostly related to OM biological processes i.e. either production of microbial necromass (roots free soils) or immobilization in microbes’ biomass (soils with root OM added), and were mainly compensated in terms of charges by Ca and Mg release; (3) phosphate with a significant impact of the sampling interval on its extraction due to the interaction between phosphates and soil mineral surfaces. However, at equivalent rates of root decomposition, subsoils retained N, S, P, K, and Ca more effectively than topsoils, and this retention was generally stronger under agroforestry than under conventional irrigated agriculture, without perennial deep rooting. Overall, this study supports the view that agroforestry enhances the capacity of deep tropical soils to act as nutrient sinks and biogeochemical buffers, thereby improving internal nutrient recycling and potentially increasing the resilience of the agrosystem. It also highlights the importance of taking into account the multiple correlations among the various major elements found in i","PeriodicalId":48610,"journal":{"name":"Soil","volume":"78 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2026-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148922634","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":"Unravelling the Drivers of Soil Health: A Standardised Typology and Evidence Synthesis Across Europe","authors":"Shaswati Chowdhury, Maria von Post, Roger Roca Vallejo, Karen Naciph Mora, Jenni Hultman, Taina Pennanen, Antti-Jussi Lindroos, Davide Geneletti, Chiara Cortinovis, Silvia Frezzi, Laura Zara, Katarina Hedlund, Katharina Helming","doi":"10.5194/egusphere-2026-4955","DOIUrl":"https://doi.org/10.5194/egusphere-2026-4955","url":null,"abstract":"<strong>Abstract.</strong> Diverse and dynamic drivers shape European soils, and with most soils considered unhealthy, understanding these drivers is essential for effective soil management. Yet inconsistent terminology and classification across studies limit comparison and synthesis of evidence. This study addresses this gap through a systematic synthesis of 451 studies and an iterative standardisation process involving expert-based classification of soil health drivers, resulting in a standardised typology. The typology groups drivers into six categories: technology and management, nature and environment, demography, policy and institutional arrangements, socio-cultural context, and economy, and provides a basis for examining patterns in driver representation across land use types, locations, and Soil Health Objectives (SHOs) defined by the Horizon Europe Soil Mission. Technology and management drivers, together with climate-related drivers within the nature and environment category, are the most frequently represented across agriculture, forest, nature, and urban land uses. The evidence base is geographically uneven, revealing where research attention has concentrated across Europe: Mediterranean countries are strongly represented, while Baltic, Balkan, and Eastern European countries remain comparatively underrepresented. Driver categories are also shown to interact rather than operate in isolation. For example, policy instruments such as the Nitrates Directive have stimulated the development and adoption of fertiliser recovery and replacement technologies, illustrating how institutional drivers can influence technological and management responses relevant to soil health. By providing a standardised typology and evidence map, this study reduces conceptual fragmentation, identifies concrete regional and thematic gaps, and provides an empirical basis for more integrated soil health research, monitoring, and governance.","PeriodicalId":48610,"journal":{"name":"Soil","volume":"17 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2026-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148922841","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":"From in situ to remote sensing: a framework for quantifying boundary-condition sensitivity in soil organic carbon models across diverse European sites","authors":"Yue Zhou, Maria Costanza Andrenelli, Quentin Beauclaire, Eyal Ben-Dor, Sara Bergante, Javier Bravo-García, David de la Fuente Blanco, Asa Gholizadeh, David Čejka, Sabine Chabrillat, Bernard Heinesch, Laura Hernandez Mateo, Kevin Kuehl, Bernard Longdoz, Carlos Lozano Fondón, Petr Maca, Robert Milewski, Stefano Monaco, Dimitra Palantza, Francesco Palazzi, Maria Fantappiè, Roberta Farina, Marmar Sabetizadeh, Benjamin Sanchez, Inés Santín, Jonti Evan Shepherd, Judit Torres, Marta Gómez-Giménez, Bas van Wesemael, Bertrand Guenet","doi":"10.5194/egusphere-2026-4735","DOIUrl":"https://doi.org/10.5194/egusphere-2026-4735","url":null,"abstract":"<strong>Abstract.</strong> Process-based soil organic carbon (SOC) models are widely used for carbon accounting and assessments. For applications beyond experimental sites, remote sensing–derived inputs are often used to complement or replace in situ boundary conditions. This substitution introduces additional sensitivity that has rarely been explicitly quantified. Here, we propose a general framework to quantify boundary-condition sensitivity in SOC modelling, distinguishing between dynamic sensitivity, which reflects deviations in the temporal trajectory of SOC stocks, and endpoint sensitivity, which captures differences in estimated SOC changes over defined reporting periods. Sensitivity is quantified by comparing substitution simulations, in which boundary conditions are replaced one by one with remote sensing–derived spatial datasets, against a baseline simulation driven by in situ observations. The framework is applied to 16 long-term experimental sites across Europe, covering diverse land-use types and environmental conditions. Boundary-condition substitution affected both SOC trajectories and endpoint estimates, although the magnitude and form of these effects varied among inputs. Initial SOC, vegetation-derived carbon inputs, and climate data were the dominant drivers of dynamic sensitivity. Fixed endpoint sensitivity was generally small relative to measured SOC changes, supporting the use of remote sensing–derived spatial datasets as scalable boundary-condition proxies for SOC modelling. Rolling endpoint sensitivity further revealed that SOC change assessments depend not only on SOC dynamics but also on the selected reporting window. Short reporting periods were more affected by short-term variability, whereas longer periods were more susceptible to accumulated deviations. A reporting window of approximately 15–30 years provided a practical balance between these effects. Overall, the framework enables a systematic quantification of sensitivity arising from boundary-condition substitution, enabling evaluation of both trajectory and reporting robustness. These findings highlight the importance of jointly considering critical boundary conditions and reporting-window design when applying remote sensing–driven SOC modelling for regional carbon accounting.","PeriodicalId":48610,"journal":{"name":"Soil","volume":"51 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2026-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148909171","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":"Dynamic vegetation–soil–water feedbacks as an under-recognised source of structural uncertainty in digital soil mapping","authors":"Odunayo David Adeniyi, Yushu Xia, Calogero Schillaci, Jamal-Eddine Ouzemou, Fuat Kaya, Abdelhakim Amazirh, Michael Maerker","doi":"10.5194/egusphere-2026-4516","DOIUrl":"https://doi.org/10.5194/egusphere-2026-4516","url":null,"abstract":"<strong>Abstract.</strong> Digital soil mapping (DSM) produces spatially continuous soil information for land-use planning, carbon accounting, and Earth system analysis, resting on the SCORPAN framework and its use of remote-sensing and terrain covariates as indicators of soil-forming processes. Similar approaches estimate ecological and hydrological conditions from vegetation, moisture, and climate data. Two assumptions receive little scrutiny: that soil-covariate relationships stay constant in space and time, and that covariates act as independent predictors. In reality vegetation, soil, and water form a coupled system in which each influences the others, and the strength and even the direction of these interactions vary across landscapes and shift over time. We argue that these dynamic relationships are an important but under-recognised source of structural uncertainty, distinct from the sampling, measurement, and model-fitting error usually partitioned in DSM. Drawing on wetlands, drylands, sloping farmland, burned watersheds, drought-affected forests, and thawing permafrost, we show how the feedbacks break the assumptions behind DSM, why the same problem affects land-surface, ecological, and hydrological models, and how mapping might be made feedback-aware.","PeriodicalId":48610,"journal":{"name":"Soil","volume":"29 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2026-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148898911","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 impacts of remediation techniques on soil functions: a review","authors":"Paul Drenning, Kristiina Nuottimäki, Nazaré Couto, Virginie Derycke","doi":"10.5194/egusphere-2026-4977","DOIUrl":"https://doi.org/10.5194/egusphere-2026-4977","url":null,"abstract":"<strong>Abstract.</strong> Soil contamination is a major driver of soil degradation in Europe, and remediation practices are increasingly expected to support not only risk reduction but also the recovery of soil health and ecosystem services. In line with the European Soil Monitoring and Resilience Directive, this review evaluates how commonly applied remediation techniques impact key soil functions that underpin soil health. A structured narrative review of the literature was conducted to assess the impacts of conventional (physical and chemical) and low‑impact (biological and nature‑based) remediation techniques on six aggregated soil functions: organic matter storage and transformation, water regulation, nutrient cycling, contaminant retention and degradation, physical stability, and habitat provision. The analysis shows that conventional remediation techniques such as thermal treatment, soil washing, in‑situ chemical oxidation/reduction, and stabilization/solidification frequently achieve effective contaminant removal but often cause substantial and sometimes irreversible degradation of soil structure, organic matter, microbial activity, and habitat quality. In contrast, low‑impact remediation approaches, including bioremediation, phytoremediation, monitored natural attenuation, and immobilization with organic or selected inorganic amendments tend to preserve or enhance soil functions, although typically at slower contaminant removal rates and with strong site specificity. The review highlights critical knowledge gaps, particularly regarding limited information on specific remediation techniques and impacts on soil fauna, the limited availability of quantitative thresholds for when a soil can be considered healthy or unhealthy for performing various functions, and limited soil health assessments in urban and industrial context. Hybrid and adaptive remediation strategies that combine risk reduction with rehabilitation measures are identified as key to balancing risk reduction and soil functionality while also planning for refunctionalization at the onset as part of the soil health trajectory. Overall, embedding soil health as a central management objective is essential for sustainable contaminated land management aligned with European policy goals.","PeriodicalId":48610,"journal":{"name":"Soil","volume":"35 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2026-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148870250","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":"Field application of rice straw–sewage sludge compost in Mediterranean citrus orchards: effects on soil properties, nutrient status and fruit quality","authors":"Isabel Rodríguez-Carretero, Rodolfo Canet, Ana Pérez-Piqueres, Ana Quiñones","doi":"10.5194/soil-12-841-2026","DOIUrl":"https://doi.org/10.5194/soil-12-841-2026","url":null,"abstract":"Abstract. Intensive agricultural practices have degraded soil fertility and polluted natural resources in Spanish citrus orchards, highlighting the need for more sustainable management strategies. Composting rice straw (RS) and sewage sludge (SS), two residues that are difficult to manage in Mediterranean regions, offers an environmentally sound alternative for residue valorisation and soil fertility restoration. This study assessed the agronomic performance of two industrial-scale composts produced from pruning residues (PR)/SS and RS/SS in a commercial Mediterranean citrus orchard. The effects of compost application at two rates were evaluated through analyses of soil physical, chemical, and biological properties, as well as foliar nutrient concentrations, yield, and fruit quality. RS/SS compost contained higher nutrient levels, particularly P, suggesting its potential as a P-rich organic fertiliser. Compost application reduced soil pH and slightly increased electrical conductivity without exceeding critical thresholds. Soil organic matter, organic N, available P and K, and Zn contents generally increased following compost application, while improvements in soil biological indicators were mainly observed during the first growing season. Effects on foliar nutrient status, yield, and fruit quality were limited. These results indicate that industrial-scale RS/SS compost application represents a sustainable strategy for residue valorisation and soil fertility improvement in Mediterranean citrus systems. Moreover, successive compost applications improved several soil fertility indicators and support the partial replacement of mineral P fertilisation under similar conditions.","PeriodicalId":48610,"journal":{"name":"Soil","volume":"9 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2026-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148870251","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":"Potential of common extraction procedures to evaluate organic carbon association with different species of metal(loid)s in soils","authors":"Bright E. Amenkhienan, Feike A. Dijkstra, Charles Warren, Balwant Singh","doi":"10.5194/egusphere-2026-2843","DOIUrl":"https://doi.org/10.5194/egusphere-2026-2843","url":null,"abstract":"<strong>Abstract.</strong> A strong association of organic carbon (OC) with metal oxides, especially iron (Fe) and aluminium (Al) oxides has been reported in several studies. However, the role of various species of Fe, Al, manganese (Mn) and silicon (Si) in the stabilisation of OC in Fe-rich and phosphorus (P) deficient soils, common in tropical and sub-tropical regions, remains poorly understood. To address this, we collected topsoil (0–20 cm) and subsoil (20–40 cm) samples from 37 sites across agricultural regions of New South Wales, Australia. Soil samples were subjected to three separate chemical extractions, i.e., sodium pyrophosphate (PP) to extract organo-metal complexes, ammonium oxalate (OX) to extract poorly crystalline and short-range order (SRO) minerals and dithionite citrate bicarbonate (DCB) to extract total metal oxides, to determine OC associated with each of the extractions. Soil organic carbon (SOC) was extracted in the sequence: C_PP&gt;C_DCB&gt;C_OX,with a mean of 62±0.16 %, 41±0.19 % and 28±0.21 %, respectively, of the total C extracted from soils. The extraction sequence for Fe was: Fe_DCB&gt;Fe_OX&gt;Fe_PP, with a mean of 49±0.18 %, 9±0.05 % and 3±0.03 %, respectively, of the total Fe extracted from soils. Aluminium was extracted in the same sequence as Fe, with a mean value of 4.0±0.02 % for Al_DCB, 3.9±0.02 % for Al_OX and 2.0±0.01 % for Al_PP of the total Al. Manganese extraction occurred in the sequence - Mn_OX&gt;Mn_DCB&gt;Mn_PP, with an average of 78±1.58 %, 65±1.10 % and 43±1.23 %, respectively, of the total Mn extracted. All extractants dissolved &lt;1 % of the total Si. All extractable forms of Fe and Al showed significant positive correlations with extractable C, which suggested their potential role in the preservation of SOC. The large fraction of OC extracted by PP suggested that organic-Fe/Al complexes constituted a large fraction of the total SOC in the studied soils. The significant amount of OC associated with OX extraction also indicated that a substantial portion of the SOC was associated with SRO and poorly crystalline Fe oxides, while a relatively small proportion of the total OC was extracted by DCB suggested a limited role of crystalline Fe/Al oxides in the OC stabilisation.","PeriodicalId":48610,"journal":{"name":"Soil","volume":"15 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2026-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148870253","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":"Ensemble agroecosystem modeling enhances predictions of crop yields and soil carbon across the United States","authors":"Sagar Gautam, Chang Gyo Jung, Rattan Lal, Klaus Lorenz, Jinyun Tang, DeAnn Ricks Presley, Alan J. Franzluebbers, Umakant Mishra","doi":"10.5194/soil-12-821-2026","DOIUrl":"https://doi.org/10.5194/soil-12-821-2026","url":null,"abstract":"Abstract. Accurately estimating crop yields and soil organic carbon (SOC) dynamics is essential for agricultural planning, carbon accounting, and sustainable land management. However, process-based agroecosystem models often produce divergent estimates due to variations in model structure, parameterization, and underlying assumptions. In this study, we developed a multi-model ensemble framework that integrates three widely used process-based models-Daily Century (DAYCENT), DeNitrification DeComposition (DNDC), and Ecosystem model (ECOSYS)-to simulate crop yields and SOC stock changes (0–30 cm) across cultivated lands of the continental United States (CONUS) at 4 km2 spatial resolution. Each model was parameterized using harmonized environmental, soil, and management datasets and evaluated using observed crop yields from the National Agricultural Statistics Service and measured SOC data from the Rapid Carbon Assessment. For the baseline period (2014–2023) under conventional corn–soybean rotation, the ensemble mean showed strong agreement with observations (corn: 7.7 vs. 8.5 Mg ha−1, RMSE = 3.0 Mg ha−1; soybean: 2.5 vs. 3.0 Mg ha−1, RMSE = 1.0 Mg ha−1), while simulated SOC stocks (5.5 vs. 4.8 kg C m−2, RMSE = 2.5 kg C m−2) closely matched measured data. Spatially, the ensemble model projected SOC gains in the Midwest and Southeastern regions and losses in the Great Plains and Western United States, underscoring the importance of region-specific management practices. Overall, the ensemble framework characterizes structural uncertainty by capturing the range of plausible model responses, while the ensemble mean provides a more reliable estimate of system behavior than any individual model. By integrating diverse model perspectives, this approach enhances predictive robustness and reduces dependence on model-specific assumptions. Consequently, it offers a scalable and data-driven framework for assessing soil carbon dynamics and crop productivity across US agroecosystems, while explicitly characterizing and communicating uncertainties associated with model variability.","PeriodicalId":48610,"journal":{"name":"Soil","volume":"14 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2026-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148870241","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}