Geoderma最新文献

{"title":"Mapping soil organic matter contents under the impact of soil erosion intensity","authors":"Ziwei Liu ,&nbsp;Mingchang Wang ,&nbsp;Xingnan Liu ,&nbsp;Fengyan Wang ,&nbsp;Xue Ji ,&nbsp;Xiaoyan Li ,&nbsp;Yilin Bao","doi":"10.1016/j.geoderma.2025.117532","DOIUrl":"10.1016/j.geoderma.2025.117532","url":null,"abstract":"<div><div>Long-term soil erosion exacerbates the progressive depletion of soil organic matter (SOM). Accurate assessment of long-term SOM dynamics therefore requires explicit consideration of erosion as a key factor. This study investigated the spatio-temporal dynamics of SOM in northeastern China by incorporating the effects of varying erosion intensities. Specifically, Landsat time-series data combined with environmental variables were used to map SOM changes over multiple decades. A novel time-series prediction framework was developed, integrating Stacking and local regression strategies. By combining the nonlinear flexibility of machine learning, the spatial adaptivity of geographically weighted regression (GWR), and the feature-learning capacity of convolutional neural networks (CNN), the framework improved SOM mapping accuracy and robustness, raising R² from 0.582 to 0.639 and reducing RMSE from 13.39 g kg⁻¹ to 12.45 g kg⁻¹. Incorporating local regression via zonal modeling of erosion zones further enhanced performance, achieving an R² of 0.715 and an RMSE of 10.83 g kg⁻¹. Moreover, uncertainty was reduced from 1.45 ± 0.05 g kg⁻¹ to 1.26 ± 0.06 g kg⁻¹, significantly improving mapping stability and prediction reliability. These results demonstrate that local regression, by explicitly accounting for erosion heterogeneity, effectively mitigates spatial variability in SOM, particularly under conditions of limited and unevenly distributed training data. This study provides a valuable reference for long-term SOM monitoring and sustainable cropland management.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"462 ","pages":"Article 117532"},"PeriodicalIF":6.6,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145268366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Electron accepting capacity of soil dissolved organic matter increases while electron donating capacity decreases along a temperature gradient","authors":"Shuhan Wang ,&nbsp;Yiman Gao ,&nbsp;Shuwen Hu ,&nbsp;Guoan Wang ,&nbsp;Li Li ,&nbsp;Yufu Jia ,&nbsp;Zixun Chen ,&nbsp;Wenbing Tan","doi":"10.1016/j.geoderma.2025.117541","DOIUrl":"10.1016/j.geoderma.2025.117541","url":null,"abstract":"<div><div>The electron transfer of soil-derived dissolved organic matter (DOM) plays a key role in the biogeochemical redox processes of redox-active substances. Yet the effect of temperature on soil DOM’s electron transfer capacity (ETC) remains poorly unexplored. This study investigates the temperature response of the ETC of soil DOM through an examination of soils collected from sites along a temperature gradient with 400 mm of annual precipitation in China. Our results demonstrate that increasing temperature enhances soil DOM’s electron-accepting capacity (EAC) while reducing its electron-donating capacity (EDC). For every 1 °C increase, EAC rises by 0.034 mmol e⁻ (g soil DOM)⁻¹ while EDC decreases by 0.014 mmol e⁻ (g soil DOM)⁻¹. This reduces the efficiency of electron transfer to redox-active substances, potentially weakening soil DOM’s role in biogeochemical redox processes under warming conditions. The influence of temperature on soil DOM’s ETC was achieved indirectly through modulating soil properties and plant litter composition affecting the traits of soil DOM. These findings provide crucial insights for predicting soil DOM’s response to climate warming.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"462 ","pages":"Article 117541"},"PeriodicalIF":6.6,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145268383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Soil total phosphorus content is a driver of P forms in continuously flooded paddy soils","authors":"Sara Martinengo ,&nbsp;Lia Chilà ,&nbsp;Martina Mazzon ,&nbsp;Barbara Cade-Menun ,&nbsp;Simone Bordignon ,&nbsp;Roberto Gobetto ,&nbsp;Maria Martin ,&nbsp;Veronica Santoro ,&nbsp;Luisella Celi","doi":"10.1016/j.geoderma.2025.117526","DOIUrl":"10.1016/j.geoderma.2025.117526","url":null,"abstract":"<div><div>Redox fluctuations in submerged paddy soils strongly influence the transformation and availability of inorganic (P_i) and organic phosphorus (P_o) forms. However, the extent to which these redox-driven processes affect P_i and P_o pools and speciation, and their contribution to phosphorus (P) availability for rice, remains poorly understood.</div><div>This study examined P_i and P_o dynamics in twelve paddy soils with different total P (TP) content, classified as high-P (&gt;800 mg P kg⁻¹), medium-P (500–800 mg P kg⁻¹), and low-P (&lt;500 mg P kg⁻¹). Soils were analysed before and after 60 days of rice growth using sequential P fractionation, liquid-state ³¹P nuclear magnetic resonance (³¹P NMR) spectroscopy, and phosphomonoesterase activity assays to assess P pools (soluble, exchangeable, redox-sensitive, and residual), organic P composition, and enzymatic hydrolysis potential.</div><div>Redox-sensitive P_i and P_o were the dominant pools across all soils, accounting for ∼50 % and ∼18 % of total P, respectively. Soluble and exchangeable P pools remained minor. Concentrations of P_i and P_o were highest in high-P soils and lowest in low-P soils. In high-P soils, orthophosphate monoesters dominated and remained quite stable during plant growth, likely due to selective accumulation of inositol phosphates under repeated Fe redox cycles. In contrast, orthophosphate diesters in medium- and low-P soils represented the most labile component of P_o and were rapidly hydrolyzed during rice growth to alleviate P limitation.</div><div>These findings highlight how TP content modulates the contribution of P_i and P_o pools to rice nutrition, emphasizing the need to account for P_o dynamics when evaluating P availability in paddy systems under fluctuating redox conditions.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"462 ","pages":"Article 117526"},"PeriodicalIF":6.6,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145269010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Positive effects of amendments on crop yield and organic carbon in sandy soils are regulated by aridity: A global meta-analysis","authors":"Tianhong Liu ,&nbsp;Lei Wu ,&nbsp;Shuirong Tang ,&nbsp;Muhammad Shaaban ,&nbsp;Lei Meng ,&nbsp;Minggang Xu ,&nbsp;Wenju Zhang","doi":"10.1016/j.geoderma.2025.117540","DOIUrl":"10.1016/j.geoderma.2025.117540","url":null,"abstract":"<div><div>Organic and inorganic amendment application is regarded as an effective management strategy for improving sandy soil health, thus enhancing agricultural productivity and ensuring food security. However, the comprehensive assessment of changes in crop yield and its association with soil organic carbon (SOC) induced by amendments into sandy soil has been poorly quantified. Herein, a global <em>meta</em>-analysis based on 843 observations from 151 field-based studies was conducted to evaluate the patterns and key controlling factors of crop yield and its linkage with SOC in response to organic and inorganic amendments into sandy soil. Results showed that amendment application strongly increased crop yield by 39 % and SOC by 62 % on average in sandy soils, with the greatest yield increase by composite amendments (+92 %), followed by inorganic amendments (+62 %) and organic amendments (+36 %). The inorganic amendment led to the highest increase in SOC (+133 %), followed by composite (+59 %) and organic amendments (+48 %). The linkage between the responses of crop yield and SOC was climate–dependent, with a strongly positive correlation in humid regions (aridity index &lt; 0.5), while no significant relationship was observed in arid regions. The crop yield response positively correlated with mean annual temperature, amendment amount, and initial contents of soil sand and SOC, but decreased with aridity index, amendment duration and soil pH. Random forest analysis revealed that climate (aridity index) and soil properties (initial SOC and pH) were key factors regulating crop yield response, collectively explaining 48 % of the variation. Moreover, aridity index was the key driver indirectly affecting crop yield response via regulating SOC and nutrient availability. Crop yield increase by amendment application was significantly larger (50–56 %) under humid regions with high SOC relative to cold and arid regions with low SOC (30–35 %). Our findings suggest that crop yield response to amendment application strongly depends on soil properties and climate, highlighting the importance of site choices for prioritizing the use of appropriate amendments, so as to maximize the beneficial strategies for improving the fertility and productivity of sandy soils.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"462 ","pages":"Article 117540"},"PeriodicalIF":6.6,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145269009","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting the proportion of centennially stable soil organic carbon using mid-infrared spectroscopy","authors":"Lorenza Pacini ,&nbsp;Marcus Schiedung ,&nbsp;Marija Stojanova ,&nbsp;Pierre Roudier ,&nbsp;Pierre Arbelet ,&nbsp;Pierre Barré ,&nbsp;François Baudin ,&nbsp;Aurélie Cambou ,&nbsp;Lauric Cécillon ,&nbsp;Jussi Heinonsalo ,&nbsp;Kristiina Karhu ,&nbsp;Sam McNally ,&nbsp;Pascal Omondiagbe ,&nbsp;Christopher Poeplau ,&nbsp;Nicolas P.A. Saby","doi":"10.1016/j.geoderma.2025.117536","DOIUrl":"10.1016/j.geoderma.2025.117536","url":null,"abstract":"<div><div>Recent work has shown that it is possible to quantify the proportion of centennially stable soil organic carbon (SOC) by using Rock-Eval® thermal analysis results as input variables for PARTYsoc, a learning model calibrated on long term experiments data. This method of quantifying SOC biogeochemical stability holds promise for improving projections of SOC stock evolutions. Here, we assessed the potential of mid-infrared spectroscopy (MIR) as a lower-cost, higher-throughput technique to facilitate its wide-scale deployment.</div><div>We compiled a spectral library of over 1,800 records obtained through the scanning of samples from the French Réseau de Mesure de la Qualité des Sols to calibrate a model using MIR data to predict the proportion of centennially stable SOC. The model gave accurate predictions (RMSE = 0.06, RPD = 2.21, RPIQ = 3.26), suggesting that MIR spectra contain relevant information on SOC biogeochemical stability. We then tried to transfer this model directly to datasets acquired using another MIR spectrometer on German and Finnish soil samples. The accuracy of the predictions was degraded, even when using the CORAL data alignment method to harmonise the different spectral datasets.</div><div>Our results show that it is possible to predict the proportion of centennially stable carbon determined by the PARTYsoc model using MIR spectroscopy. However, we found that the transfer of such models to different soils, scanned with different instruments or different protocols, is difficult. Large-scale deployment of such models will require careful calibration transfer, probably associated to local calibration within a similar spectral space.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"462 ","pages":"Article 117536"},"PeriodicalIF":6.6,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145268999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rock powder amendment mitigates microplastic induced destabilization of soil organic carbon by modulating molecular composition and microbial assembly","authors":"Zhidong Zhou ,&nbsp;Jipeng Wang ,&nbsp;Yongbo Wu ,&nbsp;Jianhui Xue ,&nbsp;Jianfeng Hua ,&nbsp;Chaoguang Yu","doi":"10.1016/j.geoderma.2025.117534","DOIUrl":"10.1016/j.geoderma.2025.117534","url":null,"abstract":"<div><div>Microplastic contamination poses a significant threat to soil organic carbon (SOC) stability, while enhanced weathering via rock powder application is a promising carbon sequestration technology that enhances SOC through mineral protection. To investigate rock powder’s potential for mitigating microplastic-induced soil degradation, we conducted a controlled soil column experiment with four treatments: control (CK), microplastic (MP), rock powder (RP), and microplastic plus rock powder (MPRP). We analyzed SOC fractions, molecular composition, microbial diversity, carbon-cycling functional genes, and ecological assembly processes. MP treatment substantially decreased mineral-associated organic carbon and altered dissolved organic carbon composition toward higher aromaticity and molecular complexity. RP amendment effectively counteracted these adverse effects, with MPRP treatment showing the highest SOC content and enhanced thermodynamic stability. MP exposure significantly modified microbial community composition and reduced diversity, while RP maintained community structure closer to CK and enhanced carbon-cycling gene abundance. Ecological process analysis revealed that RP increased heterogeneous selection and and homogenizing dispersal processes compared to MP treatment. Structural equation modeling demonstrated that soil physicochemical properties influenced SOC indirectly through microbial communities and organic carbon molecular properties. These findings demonstrate that rock powder amendment effectively mitigates microplastic-induced soil degradation by enhancing SOC content and stability through modulating organic carbon molecular composition, microbial community structure, and ecological assembly processes. This provides a promising nature-based solution for addressing microplastic contamination in soils, though potential environmental and economic trade-offs require further evaluation.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"462 ","pages":"Article 117534"},"PeriodicalIF":6.6,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145269008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Compound drought-heat legacies promote the contribution of comammox Nitrospira to N2O emissions: as evidenced from both acidic and alkaline soils","authors":"Keyi Zhang,&nbsp;Shuoshuo Wu,&nbsp;Wangying Ding,&nbsp;Jun Li,&nbsp;Baowei Hu,&nbsp;Rui Tao,&nbsp;Guixin Chu","doi":"10.1016/j.geoderma.2025.117527","DOIUrl":"10.1016/j.geoderma.2025.117527","url":null,"abstract":"<div><div>The responses of complete ammonia oxidization (comammox) to compound drought and heat and their contributions to post-drought nitrous oxide (N₂O) emissions remain unclear. Through selective inhibition coupled with qPCR quantification, we partitioned N₂O production from ammonia-oxidizing archaea (AOA), bacteria (AOB), and comammox <em>Nitrospira</em> in acidic red and alkaline calcareous soils under three treatments: (i) control (CK): 60 % water holding capacity (WHC), 25 °C; (ii) drought (D): 3 % WHC, 25 °C; and (iii) compound drought and heat (CDH) stress: 3 % WHC, 45 °C. Comammox <em>Nitrospira</em> exhibited faster recovery rates than AOA and AOB during the 28-day rewetting phase. AOA dominated N₂O emissions in red soil, contributing 34.41 % in CK, 43.91 % in D, and 42.97 % in CDH. AOB dominated N₂O emissions in calcareous soil, accounting for 81.78 % in CK, 76.46 % in D, and 69.77 % in CDH. D stress elevated comammox-driven N₂O contributions by 10.43 % in red soil and 1.67 % in calcareous soil compared with CK, while CDH stress increased them by 18.24 % and 4.27 % in these soils, respectively. These results highlight comammox <em>Nitrospira</em> as pivotal and non-negligible regulators in post-drought nitrification, particularly when heat and drought conditions coincide.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"462 ","pages":"Article 117527"},"PeriodicalIF":6.6,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145217825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Long-term no-tillage farming mitigates waterlogging during extreme rainfall events in black soil (Mollisols) region of Northeast China","authors":"Shijie Qin ,&nbsp;Zhuo Liu ,&nbsp;Meng Tian ,&nbsp;Lin Liu ,&nbsp;Wei Hu ,&nbsp;Richard Whalley ,&nbsp;Tusheng Ren ,&nbsp;Weida Gao","doi":"10.1016/j.geoderma.2025.117542","DOIUrl":"10.1016/j.geoderma.2025.117542","url":null,"abstract":"<div><div>The increasing frequency of extreme rainfall events intensifies waterlogging-induced aeration stress on crops, highlighting the urgency for adaptive agricultural practices. This study evaluates the potential of long-term no-tillage (NT) farming to mitigate waterlogging risks on a silty clay loam in Northeast China by comparing with traditional moldboard plough (MP) farming using an 11-year field experiment. Rainfall simulation (40 mm h⁻¹) and dye-tracing were employed to study the dynamics water infiltration, and X-ray computed tomography (CT) was applied to examine soil pore characteristics (0–60 cm depth) and their responses (0–5 cm layer) to raindrop splashing. Results demonstrated that NT significantly enhanced water infiltration capacity, with a 161 % higher maximum infiltration depth (<em>MID</em>), an 65 % increase in total stained area (<em>TSA</em>), and 95 % less surface ponding compared to MP. Although MP exhibited higher total porosity (<em>ε</em>_total), macroporosity (&gt;0.04 mm pores, <em>ε</em>_X-ray), and increased pore connectivity in the 0–20 cm layer, it had fewer biopores and greater vertical stratification of macroporosity compared to NT across the 0–60 cm profile. During rainfall events, the MP plot experienced a 28 % reduction in porosity of pores sized 0.2–1.0 mm and a 19 % increase in porosity of pores &lt;0.2 mm in the surface layer, likely due to raindrop splashing, while NT maintained pore integrity through straw mulching. We conclude that long-term NT is effective in enhance soil resilience to waterlogging by developing continuous vertical pore networks and maintaining surface mulch, thereby improving climate adaptability in the black soil region of Northeast China.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"462 ","pages":"Article 117542"},"PeriodicalIF":6.6,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145268386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep Learning-Based GPR interpretation of soil thickness in headwater hillslopes","authors":"Xiaole Han ,&nbsp;Jintao Liu ,&nbsp;Jian Ye ,&nbsp;Zihe Wang ,&nbsp;Pengfei Wu ,&nbsp;Hai Yang","doi":"10.1016/j.geoderma.2025.117530","DOIUrl":"10.1016/j.geoderma.2025.117530","url":null,"abstract":"<div><div>Soil thickness strongly influences eco-hydrological and geomorphic processes, yet conventional measurements such as auger drilling are invasive, labor-intensive, and unsuitable for large-scale surveys. Ground-penetrating radar (GPR) provides a non-invasive alternative, but its manual interpretation remains slow and prone to observer bias. To address this challenge, we developed a fully automated framework that couples a hybrid CNN-Transformer deep learning architecture with optimized signal filtering to predict soil thickness directly from GPR profiles. The convolutional layers extract local waveform features, while the attention mechanism captures long-range dependencies. Using field data from a steep headwater hillslope (H1) in the Taihu Basin, China, we compared five filtering strategies—median, Savitzky-Golay, Gaussian, moving average, and none—and found that median filtering yielded the most accurate results (R² up to 0.92, CCC of 0.96, RMSE near 10 cm). We further identified optimal filter window sizes (61–101 samples) and a training duration threshold (≥500 epochs) that ensured stable and accurate predictions. Cross-site validation on an independent hillslope (H2) without retraining showed that the pretrained CNN-Transformer model achieved the highest R² (0.80), CCC (0.89), and lowest RMSE (11.3 cm), outperforming traditional machine learning models (CNN, MLP, RF, SVM) in transferability. These findings demonstrate that integrating CNN-Transformer architectures with appropriate signal filtering enables scalable, accurate, and objective soil thickness mapping in complex terrain. The proposed approach also holds promise for broader GPR-based subsurface applications, including soil horizon delineation and root system detection.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"462 ","pages":"Article 117530"},"PeriodicalIF":6.6,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145268382","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The main causes of the variation in the soil aggregate proportion and stability along gradient of natural forests in the outer Western Carpathians, Czech Republic","authors":"Gabriela Tomášová ,&nbsp;Pavel Samec ,&nbsp;Lenka Pavlů ,&nbsp;Ladislav Holík","doi":"10.1016/j.geoderma.2025.117543","DOIUrl":"10.1016/j.geoderma.2025.117543","url":null,"abstract":"<div><div>In soils, the proportion and stability of aggregates tends to differ with local relief and/or plant cover. In this study, we assess the dependence of forest soil aggregation on physical, physicochemical and (bio)chemical properties in a) topsoil and subsurface horizons, and b) between reference soil groups, altitudes and natural vegetation, in the Outer Western Carpathians (Czech Republic). Relationships between soil properties were modelled using multiple logistic regression, while impacts of habitat divisions were assessed through discriminant analysis. Overall, soil properties impacted aggregate stability indices more (R² 0.40–0.57) than aggregate proportion (R² 0.12–0.58) with diameter &lt; 3 mm. Aggregate stability in topsoil was mainly influenced by clay content, total organic carbon, microbial biomass carbon, base saturation and activity of the enzymes acid phosphomonoesterase and urease. In deeper horizons, the influence of biogenic activity was reduced, with aggregation controlled mainly by sorption processes such as pH, base saturation and catalase activity. Bulk density was most affected by biogenic components in topsoil, which indirectly influenced porosity, total organic carbon and acid phosphomonoesterase activity. Water-holding capacity and porosity, closely linked to aggregate structure, better predicted macroaggregation than microaggregation. Thus, in natural forests, soil aggregation is most correlated with distribution of soil properties. Aggregate proportion differed markedly between broadleaved and coniferous forests, while aggregate stability differed most between marginal forest-steppe conditions and temperate forests from floodplains to mountains. Importantly, the results strongly support the main hypothesis that vegetation (forest community) has a stronger influence on soil aggregation than natural factors such as soil type or altitude. In contrast, presence of natural forest accounted for 59.9–71.9 % of soil aggregate proportion (SAP) in topsoil or subsurface horizons, and 54.0–75.0 % of aggregate stability (AS), Altitude affected 63.3–85.4 % of SAP and 53.9–64.6 % of AS, and soil group 57.3–81.3 % of SAP and 51.8–71.3 % of AS. These patterns reflect strong ecosystem gradients, with mixed and broadleaved forests supporting deeper, more stable aggregation than coniferous or marginal forest-steppe. Our findings highlight the fact that soil microbial activity and enzymatic functions, enhanced by species-rich vegetation, are the drivers of carbon sequestration and soil structure resilience, and that mixed forests promote aggregation across horizons, increasing carbon retention and ecosystem adaptability under changing habitat conditions.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"462 ","pages":"Article 117543"},"PeriodicalIF":6.6,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145311715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}