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{"title":"Leguminous and non-leguminous shrubs have different effects on the soil microbial co-occurrence networks along a precipitation gradient","authors":"Wanyu Xia ,&nbsp;Hanwen Cui ,&nbsp;Jingwei Chen ,&nbsp;Xuanchen Liu ,&nbsp;Anning Zhang ,&nbsp;Xia Zhao ,&nbsp;Xiaoxuan Jiang ,&nbsp;Zi Yang ,&nbsp;Hongxian Song ,&nbsp;Jiajia Wang ,&nbsp;Ziyang Liu ,&nbsp;Lizhe An ,&nbsp;Sa Xiao ,&nbsp;Shuyan Chen","doi":"10.1016/j.catena.2025.109415","DOIUrl":"10.1016/j.catena.2025.109415","url":null,"abstract":"<div><div>In alpine meadow ecosystems, shrub encroachment alters the structure and co-occurrence network characteristics of soil microbial communities, and these effects vary with precipitation gradients. However, the specific mechanisms underlying the interactive effects of precipitation and shrub encroachment on soil microbial communities remain unclear. Therefore, this study utilized Illumina MiSeq technology to analyze the effects of leguminous and non-leguminous encroachment, precipitation, and their interactive effects on the complexity and stability of soil microbial co-occurrence networks on the Qinghai-Tibet Plateau. Leguminous shrubs increased the diversity of soil bacteria and fungi, while non-leguminous shrubs increased soil bacterial diversity. Co-occurrence network analysis showed that non-leguminous shrubs decreased network complexity. Piecewise structural equation model showed that the interactive effects between leguminous shrubs and precipitation negatively impacted network stability by reducing the indirect effects of nitrate nitrogen and also through direct effects. The interactive effects between non-leguminous shrubs and precipitation had a positive impact on network complexity through direct effects. In summary, under increased precipitation, leguminous shrubs decreased network stability, while non-leguminous shrubs increased network complexity. These findings reveal the regulatory mechanisms of the interactive effects of precipitation and shrub encroachment on soil microbial communities in alpine meadows, provide a scientific basis for addressing the impacts of climate change on ecosystem functions, and aid in developing conservation strategies to maintain ecosystem stability.</div></div>","PeriodicalId":9801,"journal":{"name":"Catena","volume":"260 ","pages":"Article 109415"},"PeriodicalIF":5.7,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145047052","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":"Amplified dust cycle in Central Asia linked to desert expansion and environmental transformations since 1980","authors":"Jian Kang ,&nbsp;Jinbo Zan ,&nbsp;Xiaomin Fang ,&nbsp;Weilin Zhang ,&nbsp;Murodov Azamdzhon","doi":"10.1016/j.catena.2025.109421","DOIUrl":"10.1016/j.catena.2025.109421","url":null,"abstract":"<div><div>Central Asia is experiencing an expansion of desert area. Desert in Central Asia has expanded northward by over 100 km since the 1980s. Shrinking of the Aral Sea and the Caspian Sea has led to the emergence of new and significant dust sources globally. This promotes the increased dust emission with significant climatic impacts. However, spatiotemporal evolutions of the dust cycle over recent decades across this area have rarely been investigated under global warming scenario, therefore resulting in incomplete knowledge regarding the dust transport pathways, spatial structure and deposition processes. Here we combine satellite observations with investigations of the spatial grain-size gradient of loess sediments to reconstruct its dust cycle model. Abundant dust aerosols originating from the western deserts are transported eastward at upper levels and mainly deposited in the piedmont of the Pamir Plateau and Tien Shan. Based on these new knowledge, we examined the dust deposition and loading over Central Asia using multi-source remote sensing data from MERRA-2, MODIS, OMI, and TMOS, and found that its dust cycle has been intensifying since 1980. This increasing trend contrasts with that in NW China, despite both regions being dominated by a broad warming and wetting pattern. We argue that intensively expanding desert area, potentially associated with land surface modifications, may be responsible for intensifying dust activity in Central Asia. These results offer new insights into future trends of dust dynamics in Central Asia and their intricate links with climate change under global warming. Our finding demonstrates the potential of integrating modern satellite observations and paleo-dust records to investigate regional dust dynamics.</div></div>","PeriodicalId":9801,"journal":{"name":"Catena","volume":"260 ","pages":"Article 109421"},"PeriodicalIF":5.7,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145020544","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":"Reconstructing 60-year soil organic carbon storage in karst watersheds in Southwest China","authors":"Zihao Cao ,&nbsp;Keli Zhang ,&nbsp;Adrian Chappell ,&nbsp;Zhuodong Zhang ,&nbsp;Zhuoli Zhou ,&nbsp;Shizhen Xiao ,&nbsp;Jianghu He ,&nbsp;Yang Cao","doi":"10.1016/j.catena.2025.109434","DOIUrl":"10.1016/j.catena.2025.109434","url":null,"abstract":"<div><div>Soil organic carbon (SOC) dynamics in fragile karst ecosystems critically influence global carbon budgets but remain poorly quantified, particularly regarding deep sediment archives. This study pioneers high-resolution analysis of depression sediment profiles to reconstruct 60 years of SOC storage (SOCS) dynamics in Southwest China’s karst watersheds. Using sediment core analysis and ¹³⁷Cs dating across three peak-cluster depressions (SJP, DJT, CZ), we: (1) characterized vertical SOC distribution, (2) quantified historical SOCS changes, and (3) established land use impacts through a vegetation succession framework. The results showed that sediment profiles in the SJP, DJT and CZ depressions exhibited consistent vertical SOC distribution. Peak concentrations was observed in the topsoil, gradually decreasing with depth and eventually stabilized in deeper layers. However, spatial heterogeneity was pronounced. DJT and CZ showed higher mean SOC with lower variability, contrasting sharply with SJP’s lower SOC and higher variability. Crucially, SOC density (SOCD) trajectories diverged temporally. SJP transitioned from high early growth (222 % pre-1954) to near-zero accumulation post-1963, while DJT and CZ reversed negative trends (−60.2 % and −53.6 %) to strong positive growth (124.4 % and 6.5 %). Cumulative SOCS over the past 60 years reached 100.4 t (SJP), 57.8 t (DJT), and 3.9 t (CZ), dominated by legacy carbon (70–79 % of 0–200 cm deep pools). Quantification of vegetation succession effects showed that agricultural expansion (forest/shrubs and grassland to cropland) reduces SOC deposition rates by 78–85 %, and ecological restoration (cropland to forest/shrubs and grassland) increases rates by 350–550 %. Despite the time-lagged nature of SOC accumulation, this study demonstrated that ecological restoration significantly enhances carbon sink potential in karst watersheds. Collectively, this work advanced the understanding of SOC dynamics in karst systems, offering empirical evidence for optimizing land management to balance agricultural development and ecological restoration.</div></div>","PeriodicalId":9801,"journal":{"name":"Catena","volume":"260 ","pages":"Article 109434"},"PeriodicalIF":5.7,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145020547","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":"Graph-based and machine learning approaches for soil depth prediction in a reservoir landscape: A case study in Dazhou County, Chongqing, China","authors":"Lanbing Yu ,&nbsp;Biswajeet Pradhan ,&nbsp;Yang Wang","doi":"10.1016/j.catena.2025.109425","DOIUrl":"10.1016/j.catena.2025.109425","url":null,"abstract":"<div><div>Reservoir-bank areas are characterized by intense soil erosion and deposition processes, resulting in significant spatial variations in soil thickness that influence landslide occurrence and threaten resident safety. This study presents an adaptive modelling framework to predict soil thickness by capturing the complex spatial relationships inherent in its distribution, significantly improving prediction accuracy. A reservoir-bank area of 1.7 Km² in Dazhou town, Chongqing Province, China, was selected as a study area. A total of 288 soil thickness samples derived from field observation and drilling works, along with 14 environmental factors (such as altitude, slope, relative slope position index (RSPI), and sediment transportation index) were utilized to generate the initial modelling dataset. Subsequently, two graph models were developed based on the feature and geographic similarity, and the extracted graph features were integrated with environmental factors as inputs for machine learning models, including Random Forest (RF), Support Vector Machine, and Gradient Boosting Decision Tree (GBDT), to predict soil thickness maps. The validation results of root-mean-square-error (RMSE), coefficient of determination (R²), and error frequency analysis highlighted two essential conclusions in this study: i) Among the three models, the GBDT model showed the best performance overall, with the highest R² (0.7431 for testing, 0.9569 for training), the lowest RMSE (5.3189 for testing, 2.3001 for training), and the lowest residual skewness value of 0.11. ii) Incorporating graph-based features significantly enhances the accuracy of soil thickness predictions, particularly for nonlinear models (RF and GBDT), by effectively mitigating overestimation issues caused by spatial dependencies among independent variables (such as altitude and RSPI). This study integrates machine learning techniques with graph-based spatial analysis, providing a new path for advancing soil thickness prediction research.</div></div>","PeriodicalId":9801,"journal":{"name":"Catena","volume":"260 ","pages":"Article 109425"},"PeriodicalIF":5.7,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145020545","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":"Scale-dependent drivers of water use efficiency across China: integrating stable isotopes, remote sensing, and machine learning","authors":"Feng Jiang ,&nbsp;Xiaoyi Shi ,&nbsp;Fuxi Shi ,&nbsp;Zhenyi Jia ,&nbsp;Xin Song ,&nbsp;Tao Pu ,&nbsp;Yanlong Kong ,&nbsp;Shijin Wang ,&nbsp;Lizong Wu ,&nbsp;Jia Jia ,&nbsp;Zhenzhen Zhang ,&nbsp;Jie Wang ,&nbsp;Wenqing Han","doi":"10.1016/j.catena.2025.109403","DOIUrl":"10.1016/j.catena.2025.109403","url":null,"abstract":"<div><div>Water use efficiency (WUE) serves as a crucial metric for terrestrial carbon–water coupling, yet systematic gaps persist in understanding the spatial patterns and drivers of leaf-level intrinsic WUE (iWUE) versus ecosystem-scale WUE (WUE_Eco). Combining machine learning with 1,446 leaf δ¹³C_p records, we investigated the spatial heterogeneity and main drivers of iWUE and WUE_Eco across different life forms and climate zones in China. Results showed that inverse spatial patterns, where iWUE peaked in arid northwestern grasslands (60.46 μmol mol⁻¹). In contrast, WUE_Eco exhibited maxima in humid southeastern forests (1.82 g C/kg H₂O). Hierarchical partitioning and structural equation modeling revealed that elevation indirectly influenced iWUE (17.72 %) and WUE_Eco (25.64 %) through its modification of climatic conditions. Vegetation factors (e.g., leaf area index) and climatic factors (e.g., relative humidity) emerged as key drivers of iWUE (24.06 %) and WUE_Eco (15.31 %), primarily through their regulation of photosynthesis–transpiration coupling processes. Among four machine learning models, Random Forest has the best performance in iWUE prediction (R² = 0.73, NRMSE = 0.122, MBE =  − 0.078), providing a high-resolution national iWUE dataset. This study highlights the importance of scale in understanding carbon–water interactions and provides a valuable reference for water resource management under climate change.</div></div>","PeriodicalId":9801,"journal":{"name":"Catena","volume":"260 ","pages":"Article 109403"},"PeriodicalIF":5.7,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145020922","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":"Staging effects of biological soil crust-driven coupled soil–water-vegetation mechanisms in vegetation-limited areas","authors":"Yang Ya,&nbsp;Liu Dongdong,&nbsp;Yan Lin","doi":"10.1016/j.catena.2025.109430","DOIUrl":"10.1016/j.catena.2025.109430","url":null,"abstract":"<div><div>Vegetation-limited areas (VLAs), characterized by poor soils, water scarcity, and intense anthropogenic disturbances, pose significant challenges for ecological restoration. Owing to their multifunctional biogeochemical roles, biological soil crusts (BSCs), which are composed of symbiotic communities of algae, lichens, mosses, and microorganisms, have emerged as a pioneering solution for overcoming ecological restoration bottlenecks in VLAs. This review systematically elucidates the cascade effects through which BSCs facilitate ecosystem recovery in VLAs: initially, they initiate soil system reconstruction via physical binding, chemical weathering, and biological carbon–nitrogen fixation, significantly enhancing soil structural stability and nutrient storage capacity; subsequently, BSCs regulate evaporation-infiltration-runoff coupling to reshape hydrological balance, where their porous architecture enhances water retention and surface roughness mitigates erosive forces, creating a synergistic “water-retention and erosion-resistance” effect; finally, BSCs promote vegetation succession through seed entrapment, microhabitat engineering, and allelopathic regulation, fostering robust plant–microbe interaction networks. BSCs’ functional roles exhibit pronounced spatial heterogeneity and successional dynamics, and are modulated by climate regimes, substrate properties, and human activities. Although substantial progress has been made in understanding BSCs’ ecohydrological functions and artificial propagation technologies, challenges persist in integrating multiscale processes, evaluating long-term restoration outcomes, and decoding responses to climate change. Future research should prioritize 1) interdisciplinary integration to bridge molecular metabolism with landscape-scale ecosystem functions; 2) the development of AI-driven dynamic monitoring systems for real-time BSC classification, coverage, and health assessment; and 3) the construction of optimized restoration paradigms that merge natural succession with synthetic biology interventions for increased ecological resilience and sustainability. These efforts will advance both theoretical frameworks and practical applications of BSCs in global ecosystem restoration.</div></div>","PeriodicalId":9801,"journal":{"name":"Catena","volume":"260 ","pages":"Article 109430"},"PeriodicalIF":5.7,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145020546","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":"Contrasting impacts of mid-Holocene natural and future anthropogenic warmings on dune activities in northern China","authors":"Yuxin Xian,&nbsp;Junge Zheng,&nbsp;Xiaoping Yang,&nbsp;Deguo Zhang","doi":"10.1016/j.catena.2025.109426","DOIUrl":"10.1016/j.catena.2025.109426","url":null,"abstract":"<div><div>Deserts’ paleoenvironmental records not only reveal environmental changes during geological periods but also provide a scientific basis for addressing and predicting their response pathways to the ongoing global warming. Nevertheless, comparative studies examining the variability of dune activity in the deserts of northern China under different warming periods triggered by natural and anthropogenic factors remain scarce. Leveraging the Coupled Model Intercomparison Project Phase 6 multimodel ensemble, this study investigates the spatial patterns and underlying climatic drivers of dune activity in the deserts of northern China across distinct climatic epochs: the mid-Holocene (MH) and scenarios under three different future Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, and SSP5-8.5). The results reveal different spatial heterogeneity of dune activity in the deserts of northern China during MH and future scenarios. During the MH, dune activity decreased significantly in the eastern deserts while intensifying in the west. However, under the future scenarios, this trend would be reversed, with enhanced dune activity in the east and diminished activity in the west. The spatial disparities are directly attributable to changes in surface effective moisture and near-surface wind speed induced by large-scale atmospheric circulations. In the eastern sandy lands, a stronger East Asian Summer Monsoon increased surface moisture and limited aeolian processes during MH, while higher evaporation and stronger near-surface wind in the east would intensify dune activity under future scenarios. In the western sand seas, reduced precipitation due to weaker westerlies enhanced dune activity during MH, while increased precipitation and reduced near-surface wind speeds under future scenarios would lead to decrease in dune activity.</div></div>","PeriodicalId":9801,"journal":{"name":"Catena","volume":"260 ","pages":"Article 109426"},"PeriodicalIF":5.7,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145020924","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":"Distribution and lose risks of particulate and mineral-associated organic carbon in soils of Qinghai-Xizang Plateau under global climate change","authors":"Yubin Wang ,&nbsp;Deng Ao ,&nbsp;Baorong Wang ,&nbsp;Yang Hu ,&nbsp;Bicheng Zhang ,&nbsp;Haolin Zhang ,&nbsp;Wei Guo ,&nbsp;Jinshi Jian ,&nbsp;Shaoshan An ,&nbsp;Yakov Kuzyakov","doi":"10.1016/j.catena.2025.109416","DOIUrl":"10.1016/j.catena.2025.109416","url":null,"abstract":"<div><div>Climate warming poses severe threats to soil organic carbon (SOC) stocks, particularly in cryospheric regions exemplified by the Qinghai-Xizang Plateau (QXP). The divergent responses of particulate organic carbon (POC) and mineral-associated organic carbon (MAOC) to global warming necessitate precise pool-specific quantification for robust climate solutions. Here, we sampled soils from 220 field sites and combined with Markov Chain Monte Carlo data assimilation (MCMC) and deep learning modeling, generated high-resolution (1 km × 1 km) POC and MAOC stocks maps in QXP. QXP stores 9.8 Pg POC and 13 Pg MAOC in 0–40 cm soils, with spatial trends primarily governed by temperature gradients. MAOC accumulation reflects C input by vegetation and POC stocks are controlled by microbial decomposition. Warming decreased POC and MAOC in low-temperature regions when ground surface temperature below + 5 ℃ and mean annual temperature under + 3 ℃, respectively. Above this threshold, POC and MAOC increased for enough plant-C inputs and microbial activities. Global warming until 2060 s generate escalating C loss risks, from −1.0 % in SSP1-1.9 to −2.6 % in SSP5-8.5, particularly due to low POC stability and amplified microbial activity. This study advances pool-specific C accounting in cryospheric high elevation ecosystems while quantifying climate vulnerability thresholds critical for adaptive management.</div></div>","PeriodicalId":9801,"journal":{"name":"Catena","volume":"260 ","pages":"Article 109416"},"PeriodicalIF":5.7,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145020923","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":"Critical role of mid-elevation in microbial regulation of soil carbon dynamics on the southern foothills of the Qinling Mountains","authors":"Ermao Ding ,&nbsp;Fanglin Shen ,&nbsp;Tengyue Du ,&nbsp;Xian Ren ,&nbsp;Shichen Wang ,&nbsp;Lirong Zhao ,&nbsp;Liping Hu ,&nbsp;Jie Yang ,&nbsp;Yue Hu ,&nbsp;Weibo Shen","doi":"10.1016/j.catena.2025.109429","DOIUrl":"10.1016/j.catena.2025.109429","url":null,"abstract":"<div><div>Soil microbial communities play a crucial role in regulating the spatial distribution of soil carbon along elevational gradients in mountain ecosystems. However, consensus remains limited on how habitats at different elevations influence microbial regulation of soil organic carbon (SOC) and its constituent fractions. In this study, we investigated microbial and environmental controls on SOC dynamics along an elevational gradient (1100–2200 m a.s.l.) on the southern foothills of the Qinling Mountains, China. We assessed the composition and abundance of soil microbial communities, key carbon fractions (dissolved organic carbon [DOC], microbial biomass carbon [MBC], easily oxidizable carbon [EOC], and recalcitrant organic carbon [ROC]), and associated environmental parameters across three soil depths (0–20, 20–40, and 40–60 cm). Regression analyses revealed that SOC, MBC, EOC, and ROC exhibited quadratic (concave-down) relationships with elevation across all soil layers. In contrast, DOC concentrations remained relatively stable in surface soils (0–20 cm) but increased with elevation in deeper layers (40–60 cm). Soil microbial communities displayed distinct spatial patterns along the elevational gradient. Redundancy analysis and stepwise regression models indicated that DOC variation was more strongly regulated by soil physicochemical properties than by biological factors. Soil total nitrogen, soil moisture, bacteria, and fungi were identified as important regulators of other SOC fractions. Notably, fungi demonstrated greater environmental tolerance than bacteria, and stable mid-elevation habitats promoted soil C accumulation by fungi. However, surface runoff loss and microbial consumption of available substrates were greater at both high and low elevations, leading to decreased soil C contents at these elevations. Overall, this study highlights the importance of comprehending the role of elevational gradients in regulating microbe-mediated soil C sequestration in mountain ecosystems in response to climate change.</div></div>","PeriodicalId":9801,"journal":{"name":"Catena","volume":"260 ","pages":"Article 109429"},"PeriodicalIF":5.7,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145020921","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 organic carbon dynamics in Northeast China under water erosion: Spatiotemporal patterns and driving mechanisms","authors":"Qi Tang ,&nbsp;Li Hua ,&nbsp;Zhe Yang ,&nbsp;Long Jiang ,&nbsp;Qian Wang ,&nbsp;Yunfei Cao ,&nbsp;Yanqing Xu ,&nbsp;Tianwei Wang ,&nbsp;Chongfa Cai","doi":"10.1016/j.catena.2025.109393","DOIUrl":"10.1016/j.catena.2025.109393","url":null,"abstract":"<div><div>Soil organic carbon (SOC) changes driven by soil erosion directly influence the terrestrial carbon cycle. However, the erosion processes are complex. The interaction of multiple influencing factors introduces substantial uncertainty into SOC dynamics in cropland. Northeast China is a vital commercial grain-producing region that is vulnerable to erosion. This makes it urgent to identify patterns of SOC loss in erosion-prone croplands and understand their driving mechanisms. In this study, we mapped the spatiotemporal distribution of SOC in stable croplands with random forest models by applying remote sensing images and multi-source environmental data. We further integrated the China Soil Loss Equation (CSLE) with several machine learning (ML) methods. This allowed us to explore spatial patterns of erosion-prone SOC loss and determine its drivers. The main findings were as follows: (1) The random forest models showed strong performance for SOC mapping by selecting an optimal set of spectral indices and environmental covariates, with an R² of 0.87 for the training set and 0.63 for the validation set. (2) Cropland pixels exhibiting increased water erosion and SOC loss made up 53.92% of all pure cropland pixels, and 39% of these pixels were located in black soil regions, forming a distinct belt. (3) The primary drivers of SOC loss were the interactions between soil types and multiple factors, including rainfall erosivity trends (0.19), temperature trends (0.17), increased fertilizer use (0.16), and planting patterns (0.15). These findings provided valuable insights for promoting the sustainable carbon management of cropland under erosion.</div></div>","PeriodicalId":9801,"journal":{"name":"Catena","volume":"260 ","pages":"Article 109393"},"PeriodicalIF":5.7,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145010736","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}