European Journal of Soil Science最新文献

{"title":"Stochastic Processes Dominate Prokaryotic Community Assembly Yet Decouple From Nitrogen Cycling in Mediterranean Soils","authors":"Myrto Tsiknia, Stilianos Fodelianakis, Nikolaos P. Nikolaidis, Nikolaos V. Paranychianakis","doi":"10.1111/ejss.70311","DOIUrl":"https://doi.org/10.1111/ejss.70311","url":null,"abstract":"Understanding interactions between pedo‐climatic properties and soil microbial communities is crucial for predicting ecosystem responses to environmental change. However, the ecological processes governing prokaryotic community assembly and whether compositional shifts predict soil functioning, with focus on nitrogen cycling, in Mediterranean ecosystems remain poorly understood. We characterized soil properties, prokaryotic communities (16S rRNA), and net N mineralization rates across 22 sites spanning agricultural and natural land uses, two soil depths (0–15, 15–30 cm), and three consecutive years at Koiliaris Critical Zone Observatory, east from the city of Chania, Crete, Greece. Despite substantial environmental heterogeneity (SOC: 0.59%–5.54%; TN: 0.05%–0.40%; elevation: 0–1100 m), land use, soil depth, and sampling year explained only 8.1% of β‐diversity variance (PERMANOVA). Shannon diversity correlated negatively with SOC ( <jats:italic>r</jats:italic> = −0.32, <jats:italic>p</jats:italic> &lt; 0.01) and positively with pH ( <jats:italic>r</jats:italic> = 0.31, <jats:italic>p</jats:italic> &lt; 0.05) in agricultural soils only. Prokaryotic communities were enriched in stress‐responsive taxa (particularly Actinobacteria), with differential abundance analysis revealing consistent taxa clusters across land uses that may serve as soil health indicators. iCAMP framework revealed stochastic processes dominated community assembly (81%–85%) with drift and dispersal limitation as primary mechanisms. Agricultural soils showed higher stochasticity than natural ecosystems. Net N mineralization rates (−3.5 to 3.1 mgN kg <jats:sup>−1</jats:sup> d <jats:sup>−1</jats:sup> ; CV = 388%) showed no significant correlations with soil properties, α‐diversity, or community turnover (βNTI). This structure–function decoupling challenges deterministic ecosystem models and suggests that functional redundancy buffers process rates against compositional stochasticity in Mediterranean soils. Trait‐based, probabilistic frameworks may provide more reliable predictions for these climate‐sensitive ecosystems.","PeriodicalId":12043,"journal":{"name":"European Journal of Soil Science","volume":"21 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147630894","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":"Modelling Long‐Term Effects of Soil Compaction on Crop Yield, Soil Organic Carbon Stocks and Nitrogen Losses From Soil","authors":"Alejandro Romero‐Ruiz, Lorena Chagas Torres, Mathieu Lamandé, Michael Kuhwald, Thomas Keller","doi":"10.1111/ejss.70314","DOIUrl":"https://doi.org/10.1111/ejss.70314","url":null,"abstract":"Soil compaction is an increasing environmental threat due to agricultural intensification. Compaction negatively affects both agricultural production and key soil environmental functions. In this study, we developed a novel soil‐compaction‐agroecosystem modelling framework to systematically assess the consequences of soil compaction on crop yield, soil organic carbon stocks, nitrous oxide emissions and nitrogen leaching in the long‐term. The modelling was done for different soil textures, different climatic conditions and different soil structure recovery rates, each of them tested comprising three cases. We compared simulations with data from field observations compiled from the literature. The modelling results reproduced most trends reported in the literature. Comparing compacted vs. non‐compacted simulations, the accumulated effects over a 20 year‐long period caused by a single wheeling event (two axle passes with 8 Mg wheel load) on a loamy soil without soil structure recovery and weather conditions of central Europe were estimated to account for an accumulated loss of about 21 Mg ha <jats:sup>−1</jats:sup> in cereal grain yield, a decrease of nearly 1.8% in soil organic carbon (corresponding to a loss of about 1 Mg ha <jats:sup>−1</jats:sup> ), an increase of 130% in nitrous oxide emissions (about 0.5 kg ha <jats:sup>−1</jats:sup> annual increase) and an increase of 15% in nitrate leaching (annual increase of approximately 8 kg ha <jats:sup>−1</jats:sup> ). This work offers a novel approach for accounting for effects of compaction on interacting soil processes and enables the quantification of long‐term adverse impacts of soil compaction on key soil ecosystem services across diverse pedoclimatic conditions, thereby providing a scientific basis for the design of effective mitigation strategies.","PeriodicalId":12043,"journal":{"name":"European Journal of Soil Science","volume":"18 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147617520","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":"A Classification Framework for Carbon Sequestration Potential: Modelling Soil Carbon Pools With Environmental Data","authors":"Longnan Shi,&nbsp;Sharon O'Rourke,&nbsp;Karen Daly","doi":"10.1111/ejss.70310","DOIUrl":"10.1111/ejss.70310","url":null,"abstract":"<p>This study aimed to develop a comprehensive spatial assessment of soil carbon sequestration potential for supporting future decisions on soil carbon stock monitoring and management. Firstly, the spatial distribution of soil organic carbon (SOC) and mineral associated organic carbon (MAOC) was mapped at the 500 m resolution at the northern half of Ireland using machine learning tools with environmental covariates and soil geochemistry. Random forest models achieved robust estimations of SOC and MAOC, with <i>R</i>² values of 0.69 and 0.73 respectively. Afterwards, carbon sequestration potential was assessed using two complementary approaches: (1) quantile regression to estimate MAOC saturation and deficit, and (2) a data-driven method using agroclimatic-landcover units to estimate achievable SOC levels. These approaches revealed contrasting spatial patterns, reflecting different carbon storage mechanisms constrained by mineralogy versus climate-land cover conditions. Hence, we integrated both methods into a comprehensive framework to support decision-making for carbon farming. Classified by below or above the mean value of estimated SOC_seq and MAOC_seq, a four-classification framework of high/low SOC_seq by high/low MAOC_seq was established and mapped to delineate areas in each class with distinct sequestration potential characteristics and corresponding management strategies. These included dual saturation areas (Low SOC_seq–Low MAOC_seq: 34.87%) requiring protection strategies and dual high potential areas (High SOC_seq–High MAOC_seq: 32.93%) ideal for carbon farming projects, with other areas having specific limitations in either MAOC (High SOC_seq–Low MAOC_seq: 20.24%) or SOC (Low SOC_seq–High MAOC_seq: 11.95%) accumulation. This provides a practical and effective framework that supports targeted policymaking for soil carbon management and climate mitigation.</p>","PeriodicalId":12043,"journal":{"name":"European Journal of Soil Science","volume":"77 2","pages":""},"PeriodicalIF":3.8,"publicationDate":"2026-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://bsssjournals.onlinelibrary.wiley.com/doi/epdf/10.1111/ejss.70310","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147617521","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":"Thirty‐Four Years of Nutrient Management on Quality, Resilience of Surface Soil, and Productivity in Semiarid Vertisols","authors":"Kalyani Patil, Sunanda Biswas, S. D. Jadhao, T. J. Purakayastha, Priya Singh, Riaj Rahaman, Saloni Tripathy","doi":"10.1111/ejss.70317","DOIUrl":"https://doi.org/10.1111/ejss.70317","url":null,"abstract":"Maintaining soil quality and crop productivity in semiarid India is challenging due to low rainfall and high temperatures. The sorghum‐wheat cropping system is predominant on the Vertisols of this region. This study examined the long‐term (34‐year) effects of fertilization and manuring on soil quality and resilience at Dr. Panjabrao Deshmukh Krishi Vidyapeeth, Akola, India. Soil samples were collected from six selected treatments: control, N, NPK, NPK + FYM <jats:sub>5</jats:sub> , (N + N <jats:sub>FYM</jats:sub> ) PK and FYM <jats:sub>10</jats:sub> at a 0–15 cm depth and analyzed for 27 physical, chemical, and biological properties. The recommended fertilizer dose (RDF) for sorghum, consisting of 100 kg N, 50 kg P <jats:sub>2</jats:sub> O <jats:sub>5</jats:sub> , and 40 kg K <jats:sub>2</jats:sub> O ha <jats:sup>−1</jats:sup> , was applied as urea (46% N), single super phosphate (16% P <jats:sub>2</jats:sub> O <jats:sub>5</jats:sub> ), and muriate of potash (60% K <jats:sub>2</jats:sub> O), which corresponded to actual applied amounts (masses) of 217, 313, and 67 kg ha <jats:sup>−1</jats:sup> , respectively. Minimum data sets (MDS) were identified using a conceptual framework (CF) and principal component analysis (PCA) under productivity (P) and environmental protection (EP) goals. Soil quality indices (SQIs) were developed using both linear (L) and nonlinear (NL) scoring. To enable treatment comparisons, a relative soil quality index (RSQI) was introduced by normalizing SQI values against the highest‐performing treatment. The soil resilience index (SRI) was derived from carbon mineralization with and without substrate addition. Microbial biomass carbon, available sulfur, pH, and respiratory quotient emerged as key indicators. The NPK + FYM <jats:sub>5</jats:sub> treatment recorded the highest SQI (0.87–0.98), resistance (0.89), and resilience (0.90) index. Indicator critical limits were defined at 40% and 80% relative yield thresholds. NL PCA scoring showed the strongest correlation with equivalent wheat yield ( <jats:italic>R</jats:italic> <jats:sup>2</jats:sup> = 0.89) and SRI ( <jats:italic>R</jats:italic> <jats:sup>2</jats:sup> = 0.76), with the best model fit (adjusted <jats:italic>R</jats:italic> <jats:sup>2</jats:sup> = 0.87). The study introduces a combined conceptual and PCA‐based approach to identify key indicators and recommend the best nutrient management practices for farmers to improve surface soil (0–15 cm) quality, resilience, and productivity in semiarid Vertisols, supporting climate‐resilient agriculture.","PeriodicalId":12043,"journal":{"name":"European Journal of Soil Science","volume":"64 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147617428","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":"Straw Incorporation Thresholds for Soil Carbon and Nitrogen Stability in Maize Cropping and Fallow Systems","authors":"Qijian Zhang,&nbsp;Shuangshuang Yan,&nbsp;Xulang Zhang,&nbsp;Tianjiao Ji,&nbsp;Qiulai Song,&nbsp;Chao Yan,&nbsp;Chunmei Ma,&nbsp;Zhenping Gong","doi":"10.1111/ejss.70312","DOIUrl":"10.1111/ejss.70312","url":null,"abstract":"<div>\u0000 \u0000 <p>Straw incorporation (SI) increases soil organic carbon (SOC) and soil total nitrogen (STN). However, the differences in soil C and N fractions between the maize cropping and fallow systems under different SI rates in the black soil region of Northeast China remain unclear. In a 6-year experiment, we examined these two systems by using circular frames with five annual SI rates (0, 9.2, 18.4, 27.6, and 36.8 Mg ha⁻¹) to investigate their effects on soil C and N fractions and storage potential. SI significantly enhanced the SOC and STN concentrations in both systems. Compared to fallow, continuous maize cropping resulted in higher depletion of oxidizable organic C (EOC) and amino sugar N (ASN). However, it maintained greater light fraction organic C (LFOC), particulate organic C (POC), and hydrolyzable unknown N (HUN) concentrations in the 0–15 cm soil layer. Fallow increased the soil C:N ratio and exhibited higher average annual C and N sequestration rates (0.70 and 0.01 Mg ha⁻¹ year⁻¹, respectively) compared to the maize cropping system. However, increasing SI rates did not significantly affect the transformation efficiency of straw-derived nutrients. Conventional SI rates in continuous maize cultivation led to soil C and N losses, while higher SI rates and fallow management effectively retained nutrients. Thus, to prevent concurrent losses of soil C and N pools under continuous maize cropping in the 0–30 cm soil layer under current soil conditions, an annual input of at least 6.8 Mg C ha⁻¹ year⁻¹ and 0.2 Mg N ha⁻¹ year⁻¹ is recommended.</p>\u0000 </div>","PeriodicalId":12043,"journal":{"name":"European Journal of Soil Science","volume":"77 2","pages":""},"PeriodicalIF":3.8,"publicationDate":"2026-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147586527","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":"Development of Carbon Pools and Enzyme Activities in Constructed Urban Soils","authors":"Pasquale Napoletano,&nbsp;Maha Deeb,&nbsp;Sara Perl Egendorf,&nbsp;Brooke Singer,&nbsp;Zhongqi Cheng,&nbsp;Erika Di Iorio,&nbsp;Anna De Marco,&nbsp;Claudio Colombo,&nbsp;Peter Groffman","doi":"10.1111/ejss.70315","DOIUrl":"10.1111/ejss.70315","url":null,"abstract":"<div>\u0000 \u0000 <p>Constructed soils (CSs) are important for rehabilitation of degraded lands, carbon (C) sequestration, and urban agriculture, but little is known about the development and dynamics of organic matter pools in these soils. In this study, we tracked these pools over 21 months in CSs (1/3 compost and 2/3 fine glacio-fluvial sediments) planted with eight different vegetation treatments with densimetric and enzymatic approaches. Time was the main driver influencing soil parameters, followed by vegetation. A high diversity “All” treatment had a significant impact on soil development, notably enriching mineral/sand-associated organic carbon (MSOC) and nitrogen (MSON) by 15% and 12%, respectively, compared to a non-vegetated “Bare” treatment. The presence of sunflower (<i>Helianthus annuus</i> L.) in the vegetation treatment was associated with low values of nitrate-N, particulate organic N (PON), hot-water extractable carbon (HWEC), and β-glucosidase. These CSs appear to be undergoing rapid soil development driven by organic matter accumulation processes that facilitate nutrient cycling and accumulation of stable MSOC.</p>\u0000 </div>","PeriodicalId":12043,"journal":{"name":"European Journal of Soil Science","volume":"77 2","pages":""},"PeriodicalIF":3.8,"publicationDate":"2026-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147577676","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":"Optimal Calibration Sizes for Predicting Soil Properties Using Vis-NIR Spectra Across Scales","authors":"Yin Zhou,&nbsp;Yechen Jin,&nbsp;Lingju Dai,&nbsp;Zheng Wang,&nbsp;Xi Wang,&nbsp;Jiangjia Zhao,&nbsp;Furong Zhou,&nbsp;Zhongxing Chen,&nbsp;Zhou Shi,&nbsp;Songchao Chen","doi":"10.1111/ejss.70316","DOIUrl":"10.1111/ejss.70316","url":null,"abstract":"<div>\u0000 \u0000 <p>Soil visible near-infrared (vis-NIR) spectroscopy has demonstrated significant potential in providing accurate soil information in a cost-effective manner, which is crucial for providing updated soil information. However, building a comprehensive soil spectral library requires substantial financial resources, making it essential to balance cost and accuracy for soil spectroscopic predictions. Despite its importance, there has been no systematic comparison of how soil properties, calibration models, and spatial scales impact the optimal calibration size for these predictions using a consistent soil spectral library. This study addresses this gap by utilizing LUCAS Soil 2009 data to determine the optimal calibration size for soil organic carbon (SOC), pH, clay, and cation exchange capacity (CEC) using Partial Least Squares Regression (PLSR), Cubist and Random Forest (RF), Convolutional Neural Network (CNN), and Memory-Based Learning (MBL) algorithms at regional, national, and continental scales. Our findings indicate that MBL and Cubist consistently outperformed other algorithms across all scales, particularly at larger spatial scales, while CNN showed comparable performance at national and continental scales when using large calibration sample sizes. The optimal calibration size (the minimal number of calibration samples that reach the plateau of model performance) was influenced by the specific soil property, calibration algorithm, and scale: (1) plateau calibration sizes were identified as 150–250, 600–1000, and 2000–6000 samples for regional, national and continental scales, respectively; (2) SOC, clay and CEC required more calibration samples than pH at national and continental scales; (3) CNN required more samples for superior performance than MBL and Cubist at larger extents (national to continental) while it has the potential to perform better with larger calibration size. These outcomes offer valuable guidance for the cost-effective design of soil sampling strategies that support sustainable soil management across different spatial scales.</p>\u0000 </div>","PeriodicalId":12043,"journal":{"name":"European Journal of Soil Science","volume":"77 2","pages":""},"PeriodicalIF":3.8,"publicationDate":"2026-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147577678","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":"Maize-Green Manure Intercropping Enhances Soil Health and Water Storage on Newly-Built Terraces of the Loess Plateau","authors":"Haolei Zhang,&nbsp;Jiaxuan Wen,&nbsp;Han Wang,&nbsp;Jinchao Li,&nbsp;Hao Feng,&nbsp;Qin'ge Dong","doi":"10.1111/ejss.70306","DOIUrl":"10.1111/ejss.70306","url":null,"abstract":"<div>\u0000 \u0000 <p>Newly-built terraces on the Chinese Loess Plateau have low soil organic carbon (SOC), weak structure, and chronic water limitation. This study hypothesized that during the maize-green manure co-growth stage, when maize is at the seedling stage with relatively low water demand, intercropped green manure can utilize soil moisture and convert it into biomass with limited additional water stress on maize. Green manure root growth and returned aboveground biomass increase SOC input, promote soil aggregates formation and stability, thereby enhancing soil structure, porosity and soil water-holding capacity. Consequently, during the maize-independent growth stage, soil can store more water, providing a more stable water supply for the later growth stages of maize. A two-year (2023–2024) field experiment was implemented in Yan'an City, Shaanxi Province, and five treatments were set up: maize monocropping (M), maize-hairy vetch intercropping (M-H), maize-rape intercropping (M-O), maize-ryegrass intercropping (M-R), and maize-soybean intercropping (M-S). This experiment measured soil aggregates size distribution and stability, SOC within aggregates, SOC, soil water storage (SWS), biomass, and yield. Intercropping increased SOC relative to monocropping (2.34%–6.19%) and shifted SOC from silt-clay to macroaggregates pools; M-R treatment consistently produced the highest macroaggregates proportion and stability indices. Maize yields under M-H, M-R, and M-S treatments improved by 17.78%, 18.43%, and 9.06%, respectively, compared to the M treatment over the two-year average. However, yields under the M-O treatment decreased relative to the M treatment, reflecting more intense competition for water in the early growth stages. SWS decreased during the maize-green manure co-growth stage (“water-for-carbon” trade-off) but increased during the maize-independent growth stage, especially under M-R treatment, indicating a “structure-for-water” benefit. Overall, M-R is a practical option to enhance SOC, improve soil structure, increase late-season SWS, and raise maize yield on water-limited newly-built terraces.</p>\u0000 </div>","PeriodicalId":12043,"journal":{"name":"European Journal of Soil Science","volume":"77 2","pages":""},"PeriodicalIF":3.8,"publicationDate":"2026-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147577677","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":"A Simple Statistical Tool to Correct the Daily Temperature Effect on Dielectric Soil Matric Potential Sensor Readings","authors":"Sebastián Bravo Peña,&nbsp;Meindert Commelin,&nbsp;Ole Wendroth","doi":"10.1111/ejss.70313","DOIUrl":"10.1111/ejss.70313","url":null,"abstract":"<p>High-resolution time series recorded by soil water dielectric sensors are often affected by other processes. Dielectric soil matric potential sensors, such as the TEROS 21, exhibit temperature sensitivity, resulting in deviations of readings from the true value due to soil temperature fluctuations. However, methods for correcting this effect remain limited. The objective of this study was to create a straightforward, scale-based statistical approach to mitigate the influence of daily temperature oscillations on matric potential dielectric readings. The temperature sensitivity correction function (TSCF) identifies, quantifies, and smooths diurnal fluctuations caused by soil temperature dynamics. We provide a detailed description of the algorithm, including freely accessible and easily transferable computer codes suitable for implementation in any programming language. The method was developed for a main dataset collected by TEROS 21 and validated using two additional datasets from sensors MPS-2 and TEROS 21, all installed in volcanic ash soils in southern Chile. The diurnal deviations reached up to approximately ±720 and ±1440 kPa at suction head values larger than 1500 kPa in the main and validation datasets, respectively. Using wavelet analysis to describe the characteristic scales in the evaluated data, the global wavelet spectrum and the wavelet coherence analysis demonstrated that TSCF effectively removes diurnal temperature effects while preserving soil matric potential dynamics. Additionally, key statistical properties (i.e., mean, median, and the first and third quartiles) were conserved across all datasets. Finally, we assessed the impact of correcting diurnal deviations on soil water retention properties, including soil water content time series.</p>","PeriodicalId":12043,"journal":{"name":"European Journal of Soil Science","volume":"77 2","pages":""},"PeriodicalIF":3.8,"publicationDate":"2026-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://bsssjournals.onlinelibrary.wiley.com/doi/epdf/10.1111/ejss.70313","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147536426","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":"A Two-Part Framework for Depth to Bedrock Prediction and Uncertainty Assessment in Sweden","authors":"Yiqi Lin,&nbsp;Gustaf Peterson,&nbsp;Cecilia Karlsson,&nbsp;Florian Westphal,&nbsp;William Lidberg,&nbsp;Anneli M. Ågren","doi":"10.1111/ejss.70308","DOIUrl":"10.1111/ejss.70308","url":null,"abstract":"<p>Accurate mapping of depth to bedrock (DTB) in complex post-glacial landscapes is challenging due to high spatial variability and the prevalence of bedrock outcrops, which introduce “structural zeros” that violate standard regression modelling assumptions. To address this, we developed a two-part machine learning framework that separates bedrock outcrop classification from continuous depth prediction and applied it to a Swedish case study. The binary classifier effectively distinguished outcrops from sediment-covered areas (AUC = 0.96, F1-score = 0.83), whereas the regression component provided reliable DTB estimates in non-outcrop areas (<i>R</i>² = 0.68, RMSE = 5.74 m). The final fused model (<i>R</i>² = 0.67, RMSE = 5.80 m) outperformed both the existing national Inverse Distance Weighting interpolation model (<i>R</i>² = 0.61, RMSE = 6.61 m) and a global model evaluated over the study area (<i>R</i>² = 0.23, RMSE = 9.03 m). The two-part model remains robust in data-sparse regions. However, a depth-stratified uncertainty analysis revealed miscalibration in the uncertainty estimates of the regression component: in shallow ranges (2–15 m), the model overestimates uncertainty and produces overly wide prediction intervals. In deep ranges (&gt; 30 m), it underestimates uncertainty while systematically underpredicts (mean error = 12.44 m). Our findings emphasize that zero-inflated datasets require special consideration in modeling approaches, and that depth-stratified evaluation is essential for understanding model reliability.</p>","PeriodicalId":12043,"journal":{"name":"European Journal of Soil Science","volume":"77 2","pages":""},"PeriodicalIF":3.8,"publicationDate":"2026-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://bsssjournals.onlinelibrary.wiley.com/doi/epdf/10.1111/ejss.70308","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147536425","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}