European Journal of Soil Science最新文献

{"title":"Effect of Microplastics on Soil Water Retention Characteristics","authors":"Helena Soinne, Mari Räty, Johanna Nikama, Janne Kaseva, Rachel Hurley, Salla Selonen, Riikka Keskinen","doi":"10.1111/ejss.70442","DOIUrl":"https://doi.org/10.1111/ejss.70442","url":null,"abstract":"Over the past decades, extensive consumption of plastics has led to the accumulation of microplastic (MP) particles in the environment, including in soils. This MP pollution may affect soil functioning by influencing soil properties such as water retention. Soil pore network, controlling water storage and transport, can be affected by external material inputs via formation of new pores, clogging of existing pores, or alteration of the quality of pore walls. In this study, the effect of linear low‐density polyethylene (LLDPE) and biodegradable starch‐blended polybutylene adipate co‐terephthalate (PBAT) MPs (< 2 mm) on soil pore‐size distribution and water holding capacity were examined in soils with varying textural compositions at concentrations of 0.05, 0.50, and 1.25 (% w/w) concentrations. The MPs affected soil bulk density, the share of pore sizes, and consequently the amount of available water held by the soil, but the magnitude and direction of change varied between MP type and dose and soil. Large initial share of macropores favored a MP filling effect, increasing the water content available for plants, while in soils with few macropores, higher MP concentrations increased the space between particles thus reducing the water holding pore volume. The former effect was enhanced in low and the latter in high MP concentrations. Further, in laboratory experiments, it is important to carefully consider the procedures used to construct experimental units, as well as the choice of expressing moisture content on either a volumetric or a mass basis. To conclude, MP pollution has significant implications for soil hydrological functioning, but the complexity of various interactions complicates predictions of the outcomes in diverse situations.","PeriodicalId":12043,"journal":{"name":"European Journal of Soil Science","volume":"30 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149199006","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":"Transfer and Uncertainty for Soil Spectroscopy: A Parsimonious Approach Using Bayesian Mixed Models and Soil Surveys","authors":"Eric Potash, Colleen Partida, Jose Safanelli, Elizabeth Forbes, Alex Polussa, Tiffany Runge, Matthew Sheffer, Jonathan Sanderman","doi":"10.1111/ejss.70429","DOIUrl":"https://doi.org/10.1111/ejss.70429","url":null,"abstract":"Two challenges that limit the adoption of soil spectroscopy are (1) model transfer to settings with limited data, and (2) uncertainty quantification, especially with correlated errors. Linear mixed models (LMMs) have sucessfully addressed these challenges in other fields, but not in soil spectroscopy. Compared to machine learning transfer algorithms, LMMs are more straightforward and interpretable. LMMs can also leverage auxiliary variables, in our case: farm, field, and soil depth variables; and external soil survey (SSURGO) estimates of pH and texture. But instead of using auxiliary variables to rigidly stratify a dataset into groups and fit separate models, LMMs partially pool the entire dataset to balance local and global modeling. In this study, we predict soil carbon from field‐moist NIR spectra of 459 samples of three soil layers (0–15, 15–30, 30–60 cm) in 155 cores across 18 agricultural fields of 8 farms in Northeastern USA (data and code provided). Using cross validation, we find that our LMM succeeds in model transfer between farms, outperforming existing approaches such as memory‐based learning and Cubist. Moreover, as a probability model, the LMM automatically provides excellent uncertainty quantification, including for aggregated predictions where existing methods fail due to correlated errors. We conclude that LMMs show promise as a parsimonious approach for model transfer and uncertainty quantification in soil spectroscopy.","PeriodicalId":12043,"journal":{"name":"European Journal of Soil Science","volume":"4 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149172566","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":"Long‐Term Effects of Conservation Agriculture on Soil Properties in Calcareous Soils Under a Rice–Maize System","authors":"Peram Nagaseshi Reddy, Sanjay Tiwari, Mukesh Kumar, A. K. Singh, R. K. Jat, Illathur Rajesh Reddy, K. M. Choudhary, Chinthala Mounika, K. C. Kalwania, M. L. Jat, Mahesh K. Gathala","doi":"10.1111/ejss.70432","DOIUrl":"https://doi.org/10.1111/ejss.70432","url":null,"abstract":"Soil degradation, driven by intensive tillage and faulty agronomic management practices, poses a major challenge to sustainable agriculture in South Asia. Conservation agriculture (CA) has been proposed as a viable strategy to restore soil health; however, long‐term evidence from calcareous soils is limited. A 17‐year field experiment was conducted to evaluate the effects of CA on soil physical, chemical, and biological properties, and system productivity under a rice–maize system. This study provides novel long‐term evidence from calcareous soils by integrating soil health indicators with multivariate analyses, which remain limited in rice–maize systems. The experiment comprised four treatments in a randomized complete block design: zero tillage with residue (ZT + <jats:italic>R</jats:italic> ; T1), permanent bed with residue (PB + <jats:italic>R</jats:italic> ; T2), permanent bed without residue (PB − <jats:italic>R</jats:italic> ; T3), and conventional tillage (CT; T4). After 17 years, CA treatments (T1 and T2) significantly ( <jats:italic>p</jats:italic> &lt; 0.05) improved soil properties compared with conventional tillage (T4) at two depths (0–15 and 15–30 cm), with the strongest effects under PB + <jats:italic>R</jats:italic> (T2). Bulk density under T2 decreased by 12.1% and 10.3%, while water‐stable aggregates increased by 48.8% and 36.6% at 0–15 and 15–30 cm, respectively. Soil organic carbon increased by 44.1% and 39.8% across the respective depths, accompanied by improved nutrient availability. CA treatments also enhanced cationic micronutrients (Mn, Fe, Cu, and Zn) and reduced soil pH and electrical conductivity relative to T4. Biologically, fluorescein diacetate activity increased by 78.2% and 53.2%, and fungal populations by 174% and 152% at 0–15 and 15–30 cm, respectively. System productivity was highest under T2, with a 40.2% increase over conventional tillage. Soil organic carbon showed strong positive correlations with wet aggregate stability ( <jats:italic>r</jats:italic> = 0.75**), micronutrients (Mn: <jats:italic>r</jats:italic> = 0.81**, Fe: <jats:italic>r</jats:italic> = 0.80**, Cu: <jats:italic>r</jats:italic> = 0.85**, Zn: <jats:italic>r</jats:italic> = 0.65**), fluorescein diacetate activity ( <jats:italic>r</jats:italic> = 0.73**), and bacterial population ( <jats:italic>r</jats:italic> = 0.70**). Multivariate analyses further supported these findings, with principal component analysis explaining 77.4% of total variance and clearly separating CA‐based treatments from conventional systems, while heatmap clustering indicated strong co‐association of soil quality indicators and productivity under PB + <jats:italic>R</jats:italic> . Overall, the study provides long‐term evidence that conservation agriculture, particularly permanent beds with residue retention, influences soil health and productivity in calcareous soils, with implications for sustainable intensification in South Asia.","PeriodicalId":12043,"journal":{"name":"European Journal of Soil Science","volume":"29 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149172567","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":"Colour‐Based Soil Organic Carbon Assessment in Croplands Using In Situ RGB Imaging: A Lab‐in‐the‐Field Approach","authors":"Qi Sun, Jiwen Tian, Lulu Qi, Jun Zhang, Pu Shi","doi":"10.1111/ejss.70436","DOIUrl":"https://doi.org/10.1111/ejss.70436","url":null,"abstract":"Advances in soil colour imaging have positioned colour‐based soil organic carbon (SOC) predictive modelling as a promising tool for direct field assessment. However, previous studies remain confined to controlled laboratory settings, lacking consideration for field‐related challenges such as variable lighting and soil moisture. This study introduces a portable ‘lab‐in‐the‐field’ imaging apparatus that standardizes illumination during data acquisition, enabling consistent RGB imagery regardless of external light conditions. 441 topsoil samples were collected across the black soil region (67,747 km <jats:sup>2</jats:sup> ) of Heilongjiang Province, Northeast China, and soil images were captured against moist field soils as well as two laboratory dry treatments (Lab‐sieved and Lab‐bulk). A set of image colour and texture features were extracted to develop and compare SOC prediction models using four algorithms (Partial Least Squares Regression, Cubist, Random Forest and eXtreme Gradient Boosting). Results show that the custom‐designed apparatus effectively eliminated natural light interference, allowing stable soil imaging across varying weather conditions. Field‐based models consistently outperformed laboratory‐based ones, with Cubist achieving the highest accuracy ( <jats:italic>R</jats:italic> <jats:sup>2</jats:sup> = 0.72, RMSE = 4.37 g/kg) when both colour and texture features were used as predictors. The superior performance of field models revealed that moist soils enhanced SOC‐colour relationships by strengthening correlations with chromaticity and hue parameters, while texture features further improved predictions by incorporating microscale surface roughness and soil aggregation patterns. Finally, we developed a web‐based application tool based on the top‐performing modelling strategy, demonstrating that standardized in situ RGB imaging, combined with texture‐augmented modelling, provides a low‐cost and accessible pathway for field‐based SOC assessment.","PeriodicalId":12043,"journal":{"name":"European Journal of Soil Science","volume":"27 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149172569","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":"Seeing Mollic or Measuring it? Observer–Instrument Disagreement in Threshold‐Adjacent Soil Colour Assessment","authors":"Kinga Milewska, Marcin Świtoniak","doi":"10.1111/ejss.70437","DOIUrl":"https://doi.org/10.1111/ejss.70437","url":null,"abstract":"Soil colour is a key diagnostic criterion for identifying mollic horizons, yet visual Munsell assessments are affected by observer variability and may lead to different classification outcomes near hard thresholds. This study quantifies differences between visual soil‐colour determination using the Munsell Soil Colour Book and instrumental measurements obtained with a portable X‐Rite RM200QC CAPSURE spectrocolourimeter for humus horizons with potentially borderline mollic colours. Thirty‐five soil samples collected from Ap horizons (0–30 cm) were analysed, representing seven soil classes typical of erosion‐driven soil mosaics on postglacial morainic plateaus in north‐central Poland. Eighteen volunteers (six beginners, six intermediate and six advanced observers) determined Munsell colours under standardised laboratory conditions, and all samples were also measured with CAPSURE in both dry and moist states. Across most samples, interobserver differences clustered within approximately ±1 Munsell unit in Value and Chroma, consistent with expected perceptual variability. In addition, a directional offset was observed: participants frequently recorded colours approximately one unit higher in both Value and Chroma than CAPSURE, that is, visually lighter and more saturated than the instrumental readings. Agreement between visual assessments and CAPSURE was highest for clearly contrasting materials, whereas discrepancies were concentrated in transitional, threshold‐adjacent classes. Observer soil experience level influenced borderline decisions: the advanced group differed most frequently from CAPSURE readings and showed the strongest tendency to record higher Values for threshold‐adjacent samples. In these borderline cases, one‐unit shifts in Value and/or Chroma repeatedly changed whether the WRB mollic colour criterion was fulfilled, potentially leading to reclassification of common soils and substantial changes in the mapped extent of mollic horizons. A field‐site case study illustrated that method‐dependent colour assessments may generate substantial zones of diagnostic uncertainty in soil maps, particularly where mollic horizon identification depends on borderline colour properties. The results support treating mollic colour diagnosis as a high‐sensitivity decision and suggest the use of replicate determinations and/or instrumental verification for threshold‐adjacent horizons to improve reproducibility in soil classification and cartography.","PeriodicalId":12043,"journal":{"name":"European Journal of Soil Science","volume":"30 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149172568","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Soil Physical Degradation and Productivity Responses to Long‐Term Tillage on Sloping Farmland in Northeast China","authors":"Yiming Zhang, Tong Zhai, Liyi Liu, Jinyou Qiao, Jian Sun","doi":"10.1111/ejss.70433","DOIUrl":"https://doi.org/10.1111/ejss.70433","url":null,"abstract":"Sloping farmland is a crucial cultivated land resource in the black soil region of Northeast China, yet long‐term inappropriate tillage practices have intensified soil compaction, constraining crop productivity and profitability. A continuous field experiment was conducted from 2015 to 2019 on a 3.2° slope with upper, middle, and lower slopes, where no‐tillage (NT), rotary tillage (RT), shallow tillage (ST), and deep tillage (DT) were applied annually under maize monocropping. Soil penetration resistance (SPR) within the 0–40 cm soil layer was used as a quantitative proxy for soil physical degradation, while maize yield and economic benefits were evaluated, and their interdependencies were analyzed using partial least squares path modeling (PLS‐PM). Compared with NT, mechanical tillage significantly reduced SPR, with DT exhibiting the most pronounced effect in alleviating deep soil compaction (25–40 cm soil layer) by an average of 39.7% and consistently achieving the highest maize yields across all slope positions. PLS‐PM revealed that the negative path effect of SPR on maize yield increased in magnitude with increasing soil depth. Furthermore, the models revealed a distinct cost–benefit decoupling regulated by slope position. At upper and middle slopes, the substantial yield gains driven by DT successfully outweighed the increased machinery operational costs, increasing net profit by 34.8% and 26.7% relative to NT. In contrast, at the lower slope, the marginal yield increase under DT (2.7%) could not offset its high machinery operational costs, making NT with low inputs the most profitable option (outperforming DT by 7.5%). These findings indicate that implementing tillage practices adapted to slope position, with DT at upper and middle slopes and NT at the lower slope, is essential for mitigating soil physical degradation and promoting sustainable land management in black soil regions.","PeriodicalId":12043,"journal":{"name":"European Journal of Soil Science","volume":"69 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149151808","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":"Interpretable Additive Modeling of Soil Organic Carbon and Its Fractions From Mid‐Infrared Spectra Using MCR ‐ ALS","authors":"Mikhail Borisover, David Yalin, William Mlelwa, Nadezhda Bukhanovsky, Dan Yakir, José M. Grünzweig","doi":"10.1111/ejss.70435","DOIUrl":"https://doi.org/10.1111/ejss.70435","url":null,"abstract":"Modeling soil organic carbon (OC) contents from mid‐infrared (MIR) spectra remains challenging, and conventional multivariate spectroscopic models often lack chemical interpretability. The objective of this study was to examine whether an additive model based on non‐negative multivariate curve resolution—alternating least squares (MCR‐ALS) could reproduce variations in OC contents of whole soils and size‐separated fractions while providing a chemically interpretable description of that variation. The approach was implemented on MIR spectra of forest and woodland soils in Israel, including fine (&lt; 50 μm) and coarse (&gt; 50 μm) fractions representing mineral‐associated organic matter (MAOM) and particulate organic matter (POM), respectively. The OC content was represented as a sum of contributions from nonnegative MCR‐ALS spectral components, and the effects of soil fractionation and spectral range selection (4000–400 cm <jats:sup>−1</jats:sup> versus optimized subranges) were evaluated. Using the full MIR spectral range, the additive model reproduced OC contents more effectively for the POM‐associated fraction than for the whole soils, explaining 71.7% and 38.2% of the observed variance, respectively, whereas no improvement was obtained for the MAOM‐associated fraction (16.1%). Optimization of the spectral range increased the explained variance to 69.1% for the whole soils and 56.1% for the MAOM‐associated fraction. Leave‐one‐out cross‐validation indicated the predictive capability of the optimized models ( <jats:italic>Q</jats:italic> <jats:sup>2</jats:sup> = 0.625, 0.526 and 0.512 for the POM‐associated fraction, whole soils and the MAOM‐associated fraction, respectively), while bootstrap analysis supported the stability of several optimized parameter estimates. These results demonstrate the potential of spectral range optimization for effective OC modeling using nonnegative MCR‐ALS. Analysis of model performance versus the number of MCR components revealed transition‐like behavior, supporting the identification of chemically meaningful components. Overall, this study establishes a physically grounded and interpretable framework for MCR‐ALS‐based modeling of soil OC from MIR spectra, highlighting the roles of soil fractionation, optimization of continuous spectral windows, and interpretability of spectral components.","PeriodicalId":12043,"journal":{"name":"European Journal of Soil Science","volume":"53 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149151807","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":"Correction to “Soil Organic Carbon Stocks and Saturation Deficit in Mediterranean Olive Groves: Effects of Intensification and Management Practices”","authors":"","doi":"10.1111/ejss.70440","DOIUrl":"https://doi.org/10.1111/ejss.70440","url":null,"abstract":"","PeriodicalId":12043,"journal":{"name":"European Journal of Soil Science","volume":"80 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149130275","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":"Assessment of Soil Organic Matter Quality in Vineyards With Cover Crops and Conventional Tillage in the Mediterranean Area","authors":"Marco Antonio Jiménez‐González, Pilar Carral, Juan Pedro Martín‐Sanz, Mariela Navas, Carlos García‐Delgado, Juan Emilio Herranz‐Luque, Blanca Sastre, María José Marqués","doi":"10.1111/ejss.70439","DOIUrl":"https://doi.org/10.1111/ejss.70439","url":null,"abstract":"Cover crops are widely considered as a sustainable management strategy to enhance soil quality and resilience in Mediterranean agroecosystems. This study evaluates the long‐term effects of spontaneous cover crops on soil organic matter (SOM) quantity, chemical composition, and biological activity in a vineyard under semiarid Mediterranean conditions in central Spain. Two adjacent plots with identical crop systems but contrasting management histories, 20 years of continuous cover crops (CC) and conventional tillage (TILL) were compared at depths of 0–10 and 10–30 cm. Results showed that CC significantly increased soil organic carbon (SOC) in topsoil compared with TILL management. Improvements in phosphorus and organic nitrogen availability were also observed in the topsoil under CC management. While general physicochemical properties (bulk density, pH, water holding capacity, granulometry) remained largely unchanged, SOM fractionation revealed greater stabilization of organic carbon under CC, whereas TILL soils exhibited higher extractability, suggesting reduced organo‐mineral associations. Spectroscopic analyses indicated similar humification levels across treatments but highlighted an enrichment of polysaccharide‐like structures in CC soils. Biological indicators further supported these findings, with higher enzymatic activities and greater microbial abundance (bacteria, fungi, and archaea) under CC, especially in surface layers. Functional genes related to carbon, nitrogen, and phosphorus cycling were also more abundant in CC soils, reflecting enhanced biogeochemical functioning. Overall, long‐term cover cropping improved SOC accumulation, SOM quality, and soil biological activity, contributing to enhanced soil health and stability. These findings highlight the potential of cover crops as a key strategy for sustainable vineyard management under Mediterranean climatic constraints.","PeriodicalId":12043,"journal":{"name":"European Journal of Soil Science","volume":"9 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149130274","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":"Mediterranean Climate‐Change Scenarios Threaten Winter Cover‐Crop Establishment and Soil‐Health Indicators","authors":"Derlis Enciso‐Santacruz, Chiquinquirá Hontoria, Fernando Peregrina, Mariela Navas, Javier Pérez‐Esteban, Ignacio Mariscal‐Sancho","doi":"10.1111/ejss.70434","DOIUrl":"https://doi.org/10.1111/ejss.70434","url":null,"abstract":"Agricultural systems increasingly face challenges posed by climate change, particularly rising temperatures and altered rainfall patterns. This study evaluated how cover crops (CCs) and soil health indicators respond to six plausible climate change scenarios for the Mediterranean region. Three CC species from the most representative families: barley ( <jats:styled-content style=\"fixed-case\"> <jats:italic>Hordeum vulgare</jats:italic> </jats:styled-content> L.), vetch ( <jats:styled-content style=\"fixed-case\"> <jats:italic>Vicia sativa</jats:italic> </jats:styled-content> L.) and camelina ( <jats:styled-content style=\"fixed-case\"> <jats:italic>Camelina sativa</jats:italic> </jats:styled-content> L.), together with its mixture and with bare soil as the control were considered. Temperature was raised by +1.5°C and + 3.0°C above historical averages recorded in the central Iberian Peninsula using controlled growth chambers. Precipitation was adjusted to three plausible future regimes: −20%, −5% and +10% relative to the historical regional average. Key soil parameters, including organic carbon, electrical conductivity, pH, nutrient availability, mycelial length and microbial abundance, together with plant parameters such as above‐ground and root biomass were evaluated at the end of CCs establishment phase. Results revealed that temperature strongly modulated the responses of the studied parameters to the CC type and precipitation levels, with the +3°C scenario amplifying the contrasts among species and precipitation levels across most plant and soil parameters, thereby shaping both crop performance and soil health indicators. Aboveground biomass declined under +3°C warming, particularly in vetch and camelina, whereas barley exhibited greater resilience. In contrast, root biomass increased at +3°C, suggesting a reallocation of resources to the belowground system as a stress‐induced adjustment to elevated temperatures during CC establishment. Increased precipitation enhanced biomass production and nutrient uptake, while water deficit restricted biomass and microbial abundance in soil. Covered soils maintained higher soil organic carbon contents and exhibited reduced salt accumulation compared with the control. Overall, the temperature increases from October to December negatively affected aboveground growth of cover crops and overall soil health indicators. Fungal and bacterial abundances showed average decline markedly of 61% and 49%, respectively, from +1.5°C to +3.0°C, although the magnitude of these declines varied among precipitation treatments. In contrast, archaeal abundance displayed greater thermal resistance. However, the implementation of those cover crops adapted to specific scenarios, such as barley under +3°C conditions, proved effective in mitigating the impact of rising temperatures, thereby enhancing agroecosystem resilience.","PeriodicalId":12043,"journal":{"name":"European Journal of Soil Science","volume":"52 1","pages":""},"PeriodicalIF":4.2,"publicationDate":"2026-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149130277","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}