Land Degradation & Development最新文献

{"title":"Ecological Security Zoning Considering Land Degradation Neutrality: A Case Study in Southern Jiangxi Province, China","authors":"Qingwen Hong, Qiulin Xiong, Wenbo Chen, Bifeng Hu, Jutao Liu, Beijie Gao, Guanyu Tu, Rongmei Guo","doi":"10.1002/ldr.70175","DOIUrl":"https://doi.org/10.1002/ldr.70175","url":null,"abstract":"Ecological security serves as a critical metric for assessing regional sustainable development. Climate change and human activities have intensified the deterioration of global ecosystems, which cause deterioration of ecosystem health and land degradation, and threaten ecological security. Consequently, this study addresses land degradation and ecosystem health by employing the United Nations Land Degradation Neutrality (LDN) assessment framework and the Vigor‐Organization‐Resilience‐Service (VORS) model. It visualizes the states of land degradation and ecosystem health from qualitative and quantitative perspectives. Based on the four‐quadrant model, the study investigates the ecological security zoning of the mountainous soil conservation area in southern Jiangxi Province from 2006 to 2022. The results of the study are as follows, (1) land productivity degradation was the dominant factor of land degradation in the study area, while soil organic carbon improvement was the dominant factor of land improvement; (2) The research area exhibited a net gain in land improvement compared with degradation, achieving the goal of LDN advocated by the United Nations, from 2006 to 2022; (3) the area of diseased, sub‐healthy and healthy ecosystems increased by 1.01%, 49.88%, and 1.56%, respectively, and the area of sickness and fragile healthy areas decreased by 2.44% and 49.92%, respectively, from 2006 to 2022; (4) the areas of insecure area and lowly secure area decreased by 6.54% and 42.93%; the areas of moderately secure and secure area increased by 2.25% and 31.15%, from 2006 to 2022. Based on the research results, it is recommended that each administrative region should formulate soil conservation plans according to local conditions, especially by focusing on curbing land degradation and ecosystem deterioration to enhance the regional ecological security. The findings can provide references for controlling soil erosion and improving ecosystem quality in the study area, as well as offer insights into ecological zoning management and restoration in the region.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"46 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145035238","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":"Detect Changes in Marsh Plant Communities Based on Landsat Long Time Series Data and BFAST Model","authors":"Yunlong Yao, Yuna Liu, Yi Fu, Xuguang Zhang, Lei Wang, Renping Liu","doi":"10.1002/ldr.70177","DOIUrl":"https://doi.org/10.1002/ldr.70177","url":null,"abstract":"Due to the combined effects of human activities and climate change, freshwater wetlands, especially in agricultural watersheds, face severe degradation threats. Therefore, it is necessary to explore in depth the changes in plant communities within these wetlands. This study investigates changes in wetland plant communities within these watersheds and assesses the feasibility of the Breaks for Additive Season and Trend (BFAST) method for detecting abrupt shifts in vegetation over long time series. Using long‐term Landsat imagery (1984–2016), annual maximum NDVI values were calculated for the Naolihe Basin Nature Reserve in Northeast China. The BFAST algorithm was then applied to detect NDVI changes in wetland plant communities, with results validated through field surveys. The results revealed four distinct NDVI change trends: no significant change, high‐to‐low shift, low‐to‐high shift, and continuous decline. NDVI deviations ranged from −0.85 to 0.94, with 1 to 5 abrupt changes mainly occurring between 1993 and 2006. The study confirms BFAST's effectiveness in detecting changes in wetland plant communities and, combined with field data, proposes a conceptual model to explain the degradation processes in freshwater wetlands. The model reveals the degradation process of different vegetation types under the influence of water competition and other factors, which contribute to a clearer understanding of vegetation change in freshwater wetlands and provide strong support for its sustainable conservation and management.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"33 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145035260","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":"Assessing Natural Resource Carrying Capacity in Xinjiang Using Remote Sensing: Spatiotemporal Patterns and Implications for Future Land Use","authors":"Shuang Zhao, Jianli Ding, Jinjie Wang, Shanshan Meng, Annan Zeng, Junhao Liu, Ruimei Wang, Shaofeng Qin","doi":"10.1002/ldr.70181","DOIUrl":"https://doi.org/10.1002/ldr.70181","url":null,"abstract":"Xinjiang has undergone rapid oasis expansion, leading to significant changes in land use and, consequently, to unsustainable issues regarding natural resources. Most studies on natural resource carrying capacity (NRCC) focus on single resource elements and rarely examine patterns at the pixel scale. Although remote sensing technologies and cloud platforms offer significant advantages in NRCC assessment, this potential remains underutilized. Meanwhile, existing land use simulation (LUS) research mainly emphasizes land suitability or land use patterns under specific development objectives, with a limited understanding of resolving the conflict between NRCC and sustainable land development. To address these gaps, this study constructs a spatiotemporal variation and driving factor analysis framework for NRCC, driven by remote sensing, based on the Google Earth Engine. It also integrates the PLUS model to simulate land use patterns in Xinjiang under different scenarios for 2030. The results show that the NRCC in Xinjiang exhibits a high value in the northwest and a low value in the southeast, with an overall increasing trend from 2001 to 2020. Precipitation and temperature difference are the primary driving factors. Under dynamic NRCC scenarios, the farmland and built‐up land will increase, whereas in static NRCC scenarios, the farmland and water will increase. The LUS framework based on NRCC constraints provides a new approach to alleviating the conflict between limited natural resources and land development in arid regions. This study expands the perspective on LUS in arid areas but also provides practical references for sustainable natural resources and land use management in other areas.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"28 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145017520","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":"Identifying the Relationships Among Ecosystem Services and Their Influencing Pathways in the Jialing River Basin: An Integrated Social‐Ecological Perspective","authors":"Yixu Wang, Jie Gong","doi":"10.1002/ldr.70179","DOIUrl":"https://doi.org/10.1002/ldr.70179","url":null,"abstract":"Exploring the interactive relationships and driving mechanisms of ecosystem services (ESs) is crucial for addressing urgent land use conflicts and related ecological and environmental challenges. Currently, the cross‐scale complex relationships between ESs, along with the intermediate mechanisms and processes that influence ESs, merit further research. This study explored the relationships among typical ESs at the county and small watershed scales. Subsequently, the conceptual framework of the social‐ecological system (SES) was introduced, and the partial least squares‐structural equation model (PLS‐SEM) was employed to comprehensively depict the influence pathways of each potential factor on ESs. Taking the Jialing River Basin (JRB) in the upper reaches of the Yangtze River as a typical study area, the results indicated that during the research period, the direction of the ESs relationships remained consistent at the dual scales, yet the intensities varied. There was a synergistic relationship between water yield (WY) and food production (FP), whereas the relationship between WY and soil conservation (SC), and between SC and FP, shifted from trade‐offs to synergies. Path analysis confirmed that potential factors collectively influence ESs through direct and indirect pathways, with landscape pattern acting as a mediating variable. In addition, the influence pathways at the small watershed scale were more intricate. In summary, this study highlights the need for decision‐makers to consider scale effects and the indirect effects of influencing factors when managing ESs, and offers reference information for guiding cross‐scale sustainable development in the JRB.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"7 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145017523","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":"Integrated Nitrogen Fertilization Using Plant Growth Promoting Rhizobacteria, Farmyard Manure and Panchagavya Formulation Improves Soil Health, Crop Quality, and Yield of Fodder Maize","authors":"Santosh Onte, Dileep Kumar, Shiva Dhar, Sudhir Kumar, Sourabh Kumar, Vijendra Kumar Meena, Dhruba Malakar, Shailendra Singh, Balendu Shekher Giri, Mahendra Vikram Singh Rajawat, Sanjeev Kumar","doi":"10.1002/ldr.70187","DOIUrl":"https://doi.org/10.1002/ldr.70187","url":null,"abstract":"Organic farming often relies on slow‐releasing nitrogen sources like farmyard manure (FYM), which frequently fail to meet the rapid nitrogen demands of nutrient‐exhaustive crops such as fodder maize. This nitrogen deficiency results in reduced growth, lower biomass, and diminished forage quality, ultimately affecting livestock nutrition and farm productivity. We hypothesized that integrating FYM with plant growth‐promoting rhizobacteria (PGPR) and a 3% foliar spray of panchagavya could enhance soil health, nutrient availability, and energy fractions, thereby improving the yield and quality of fodder maize under biofarming conditions. The objective of this study was to evaluate the impact of this integrated nutrient management approach (treatment T<jats:sub>7</jats:sub>) on soil properties, microbial activity, energy content, and fodder maize yield over a three‐year period (2018–2020). Key findings revealed that treatment T<jats:sub>7</jats:sub> (100% recommended dose of nitrogen through FYM + PGPR +3% foliar spray of panchagavya) significantly improved soil organic carbon (5%–15%), soil organic matter (4.85%–14.56%), available nutrients (1.75%–18.84%), microbial populations (65.4%–137.65%), and enzymatic activities (56.6%–167.6%) compared to the control treatment (T<jats:sub>1</jats:sub>) using recommended chemical fertilizers. Although T<jats:sub>7</jats:sub> resulted in a modest reduction in green fodder (8%–12%) and dry fodder yield (9%–13%) relative to chemical fertilizers, the ecological benefits—including enhanced soil health, nutrient cycling, and microbial activity—justify this trade‐off. These results recommend T<jats:sub>7</jats:sub> as a viable strategy for organic fodder production, promoting long‐term soil sustainability while balancing yield and ecological benefits under biofarming systems.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"72 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145017171","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":"Dual Consequences of Reclamation: Enhanced Ammonia Oxidation and Carbon Sink Dynamics Versus Escalated Nitrous Oxide Production in Estuarine Wetlands","authors":"Zihao Wang, Rixuan Gao, Chenqingfeng Gao, Yanshu Wang, Jing Li, Qingyan Wang, Dongfan Tian, Xinru Zeng, Nian Wu, Feifei Yan, Dongyao Sun, Wei Du, Weifang Hu, Xianbiao Lin","doi":"10.1002/ldr.70178","DOIUrl":"https://doi.org/10.1002/ldr.70178","url":null,"abstract":"Reclamation activities have dramatically altered the biogeochemical cycling of nitrogen (N) and carbon (C) in estuarine and coastal wetlands. However, how reclamation affects sediment ammonia oxidation processes mediated by ammonia‐oxidizing archaea (AOA) and bacteria (AOB), and associated nitrous oxide (N<jats:sub>2</jats:sub>O) production remains unclear. Here, different potential ammonia oxidation rates (PAR), N<jats:sub>2</jats:sub>O production rates, associated functional gene abundances, and driving factors were examined in surface sediment (0–5 cm) from estuarine wetlands (reed) and adjacent agricultural lands (aquaculture pond, paddy field, and vegetable field) on Chongming Island, China. We found that land‐use changes from reed marshes to paddy and vegetable fields significantly promoted PAR by 58% and PAR<jats:sub>AOA</jats:sub> by 119% (<jats:italic>p</jats:italic> &lt; 0.05), whereas the PAR<jats:sub>AOB</jats:sub> was not significantly affected. Although reclamation activities suppressed the abundances of ammonia oxidizers, the N<jats:sub>2</jats:sub>O production rates were significantly promoted (<jats:italic>p</jats:italic> &lt; 0.05). Season and land use type changes jointly influenced spatiotemporal variations in PAR and N<jats:sub>2</jats:sub>O production rates (<jats:italic>p</jats:italic> &lt; 0.05); these variations were driven by the complex interaction between environmental factors (temperature, water content, and organic matter) and microbial activities. Overall, reclamation activities enhanced sediment N turnover through ammonia oxidation, and the elevated C pumping flux resulting from nitrification in the Yangtze Estuary (0.95–17.58 × 10<jats:sup>3</jats:sup> t CO<jats:sub>2</jats:sub> year<jats:sup>−1</jats:sup>) could potentially act as a significant contributor to the C sink in estuarine and coastal wetlands. However, reclamation activities also resulted in a marked increase in N<jats:sub>2</jats:sub>O production by 363%, which should be carefully considered when estimating global greenhouse gas emissions.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"39 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145017274","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":"Combined Effects of Human Activity and Rainfall Shape the Differentiated Relationships of Concentration–Discharge in the Yangtze and Yellow River Basin, China","authors":"Xi Jiang, Xiaoli Zhao, Minmin Qiang, Zongyao Li, Zhenhao Yang, Erjuan Yang, Yue Zhang, JiaLing Wang, Jianqiao Han","doi":"10.1002/ldr.70188","DOIUrl":"https://doi.org/10.1002/ldr.70188","url":null,"abstract":"Concentration–discharge (C–Q) relationships provide valuable insights into spatial variation in hydrological processes and catchment dynamics. However, research on the influence of catchment characteristics and constituents across large spatial scales remains limited. Furthermore, the key factors that shape C–Q relationships for solutes vary considerably across different geographical regions. This study analyzed water‐quality data collected from 2021 to 2023 from 32 catchments in the Yangtze and Yellow River basins (YRZB and YRB) in China. The focus is on understanding the spatial variability of dissolved oxygen (DO), turbidity (TU), total phosphorus (TP), and total nitrogen (TN) concentrations. Conclusions are as follows: (1) TU and DO exhibit consistent behavior across both river basins. TU is characterized by enrichment (<jats:italic>b</jats:italic> &gt; 0 and CV<jats:sub>C</jats:sub>/CV<jats:sub>Q</jats:sub> &gt; 0.5), while DO shows consistent dilution (<jats:italic>b</jats:italic> &lt; −0.2 and CV<jats:sub>C</jats:sub>/CV<jats:sub>Q</jats:sub> &lt; 0.5). These enrichment/dilution patterns are more pronounced in the Yellow River Basin compared to the Yangtze River Basin. (2) In contrast, the Yellow River Basin exhibits TN enrichment (<jats:italic>b</jats:italic> &gt; −0.2), while TP behaves chemostatically (−0.2 &lt; <jats:italic>b</jats:italic> &lt; 0.2). (3) Spatial variation in rainfall regime is the primary driver of differences in solute export (DO, TU) across catchments, with concentrated rainfall in specific Yellow River catchments leading to more pronounced enrichment or dilution effects. (4) Urbanization significantly influences TP enrichment in the Yangtze River Basin, while agricultural activities drive TN enrichment in the Yellow River Basin. These findings enhance the understanding of the relative importance of solute properties and catchment characteristics in shaping the hydrological and biogeochemical functions of basins affected by urbanization and agriculturalization.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"3 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145008987","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":"Prediction of Soil pH Improvement Through Biochar: A Machine Learning Based Solution","authors":"Chenxi Zhao, Hang Yang, Yiming Zhang, Qi Xia, Wenjing Yue, Aihui Chen, Xiaogang Liu","doi":"10.1002/ldr.70186","DOIUrl":"https://doi.org/10.1002/ldr.70186","url":null,"abstract":"Biochar has achieved good results in improving soil properties. The rapid development of machine learning technology makes it possible to predict soil physicochemical properties. The objective of this study was to investigate the underlying mechanisms impacting soil pH in biochar‐improved soil using machine learning models. This study, based on the Lightweight Gradient Boosting Machine (LightGBM) and Deep Neural Network (DNN) algorithms, established machine learning models of soil pH after biochar addition and explored the influence of different input combinations of biochar information on the accuracy and performance of the model. The results show that biochar pH and biochar cation exchange capacity have a significant influence on model accuracy. Compared to the DNN model, the LightGBM model was more appropriate for predicting soil pH, and the LightGBM_a model performed the best, with <jats:italic>R</jats:italic><jats:sup>2</jats:sup> of 0.92, MAE of 0.291, and RMSE of 0.539. Shapley additive explanations (SHAP) value analysis, Partial Dependence Plot (PDP) analysis, and Individual Conditional Expectation (ICE) analysis further indicated that biochar electrical conductivity and biochar cation exchange capacity were important characteristics that have an extremely significant impact on model accuracy. The simultaneous citation of biochar pH, biochar cation exchange capacity, and biochar electrical conductivity has a synergistic effect. At the same time, it provides a reference for predicting other physical and chemical properties of soil after biochar is added.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"27 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145008992","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":"Unraveling the Dynamics of Cropland Abandonment in Guangdong Province, China: A Social‐Ecological Systems Perspective","authors":"Yuzhu Zang, Chumiao Mai, Shougeng Hu","doi":"10.1002/ldr.70169","DOIUrl":"https://doi.org/10.1002/ldr.70169","url":null,"abstract":"Land abandonment, a significant contributor to cropland loss, has garnered growing global attention. However, the identification of abandoned land remains challenging due to limitations in high‐resolution data and the absence of universally applicable methodologies. Moreover, current research mainly focuses on mapping abandonment patterns, yet it lacks a comprehensive theoretical framework for analyzing the underlying causes, processes, and impacts. To address these gaps, this study introduces a place‐based methodology that integrates remote sensing technology with machine learning techniques to identify abandoned land, while also employing the social‐ecological systems (SES) framework to analyze the mechanisms and outcomes of cropland abandonment. Guangdong Province—a region in southern China characterized by complex topography and diverse socioeconomic conditions—was selected as the case study. The findings revealed that: (1) Between 2018 and 2022, abandoned croplands were predominantly concentrated in the underdeveloped hilly regions of Guangdong Province, accounting for about 12% of the total cropland annually. (2) The proportion of the primary industry and agricultural employment, abundance of cultivated land, population outflow, and effective irrigated area were positively correlated with cropland abandonment, whereas population density and road density were negatively correlated. (3) The most significant impacts of land abandonment on ecosystem services, characterized by a decline in food production and nutrient cycling, were observed in the coastal and estuarine areas, particularly in the Pearl River Delta. These findings highlight the need for targeted policy interventions to mitigate the impacts of cropland abandonment and promote sustainable land use strategies that balance agricultural productivity with ecological conservation.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"125 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145009156","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":"Dissolved Organic Matter Drives Soil Carbon Mineralization Efficiency and Indirectly Affects Stocks After Converting Forest Swamps to Cropland","authors":"Wei Wang, Gaoxiang Li, Jianwei Li, Yixinfei Lin, Bian Hongfeng, Yong Wang, Chunguang He","doi":"10.1002/ldr.70183","DOIUrl":"https://doi.org/10.1002/ldr.70183","url":null,"abstract":"Forest swamps, unique ecosystems with large amounts of organic matter, are seriously threatened by agricultural cultivation. As the most active component of soil, dissolved organic matter (DOM) is susceptible to environmental changes. However, the carbon dynamics of forest swamps after agricultural cultivation and the role of DOM in this process remain unclear. We collected topsoil (0–20 cm) and subsoil (20–40 cm) across forest swamps and post‐cultivation paddy and maize fields to investigate the DOM characteristics and carbon mineralization efficiency (CME). The results indicated that CME increased (from 0.08 ± 0.004 to 0.15 ± 0.004 g CO<jats:sub>2</jats:sub>‐C/g SOC in topsoil; from 0.03 ± 0.001 to 0.11 ± 0.002 g CO<jats:sub>2</jats:sub>‐C/g SOC in subsoil), and carbon stocks significantly decreased (from 87.71 ± 1.98 to 36.21 ± 0.65 Mg/ha in topsoil; from 57.38 ± 1.44 to 25.26 ± 0.72 Mg/ha in subsoil) after the conversion of forest swamps to cropland. The conversion significantly reduced the relative proportion of humic‐like components and humification degree (<jats:italic>p</jats:italic> &lt; 0.01), while significantly increasing the ligninase:cellulase ratio (<jats:italic>p</jats:italic> &lt; 0.01). Linear regression analyses revealed that microbial enzymatic strategies reduced the relative proportions of recalcitrant DOM components (<jats:italic>R</jats:italic><jats:sup>2</jats:sup> = 0.67, <jats:italic>p</jats:italic> &lt; 0.01), with changes in DOM composition being the major driver of increased CME (<jats:italic>R</jats:italic><jats:sup>2</jats:sup> = 0.88, <jats:italic>p</jats:italic> &lt; 0.01), resulting in carbon loss indirectly after cultivation. Our study emphasizes the vital role of DOM in the soil carbon dynamics and provides new insights into carbon cycling under agricultural encroachment.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"18 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145002913","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}