The Yinshan Mountain region features are complex and have a diverse topography, geomorphology, and climate types. Investigating the spatiotemporal variations, trade‐offs/synergies, and driving mechanisms of ecosystem services (ESs) in this area is critical for scientific ecosystem management and enhancing ecosystem service functionality. In this study, we used the InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) model to quantitatively estimate carbon storage (CS), soil conservation (SC), wind and sand fixation (WSF), habitat quality (HQ), water yield (WY), and food production (FP) in the Yinshan Mountain region. Furthermore, we analyzed pairwise ES trade‐offs/synergies and identified their socioecological drivers. The results reveal that the spatial patterns of ESs in the Yinshan Mountain region remained generally stable but exhibited localized dynamics. CS, HQ, and SC displayed highly similar spatial distributions, with core zones persistently concentrated in the central Yinshan Mountain and the northern foothills, serving as critical ecological barriers. High‐value FP areas were consistently clustered along the southern fringe and eastern agropastoral ecotone, whereas WY gradually expanded southwestward since 2000. In contrast, the spatial gravity center of WSF shifted from the northern and southern slopes toward the western desert‐steppe zone. Regarding driving mechanisms, topographic factors primarily governed the spatial differentiation of SC and CS, while vegetation coverage significantly regulated HQ and FP. Climatic variables predominantly explained the spatial variations in WSF and WY. This study provides a comprehensive analysis of ES spatiotemporal dynamics and their drivers, deepening our understanding of ES interactions and offering targeted policy insights and precise management strategies for ecological sustainability in the Yinshan Mountain region.
阴山地区地貌复杂，地形地貌多样，气候类型多样。研究该地区生态系统服务的时空变化、权衡/协同效应和驱动机制，对科学管理生态系统和增强生态系统服务功能具有重要意义。本研究采用InVEST （Integrated Valuation of Ecosystem Services and Tradeoffs）模型对阴山地区的碳储量（CS）、土壤保持（SC）、风沙固结（WSF）、生境质量（HQ）、水量（WY）和粮食产量（FP）进行了定量估算。此外，我们两两分析了ES的权衡/协同效应，并确定了它们的社会生态驱动因素。结果表明，阴山地区生态系统空间格局总体上保持稳定，但表现出局域动态特征。中央区、中央区和中央区空间分布高度相似，核心区持续集中在阴山中部和北麓，具有重要的生态屏障作用。高价值FP区一直集中在南部边缘和东部农牧交错带，而WY自2000年以来逐渐向西南扩展。相反，WSF的空间重心由南北斜坡向西部荒漠草原地带转移。在驱动机制上，地形因子主要控制着土壤水分和土壤水分的空间分异，而植被覆盖度对土壤水分和土壤水分的空间分异具有显著调节作用。气候变量是解释WSF和WY空间变化的主要因素。本研究全面分析了生态系统的时空动态及其驱动因素，加深了对生态系统相互作用的理解，为银山地区生态可持续发展提供了有针对性的政策见解和精准的管理策略。
{"title":"Mechanistic Drivers and Sustainability Implications of Ecosystem Service Interactions in the Yinshan Mountain Region","authors":"Yinghan Zhao, Youfu Wu, Peidong Han, Zhongming Wen, Zongsen Wang, Yangyang Liu, Ercha Hu, Haijing Shi, Zhenqian Wang","doi":"10.1002/ldr.70466","DOIUrl":"https://doi.org/10.1002/ldr.70466","url":null,"abstract":"The Yinshan Mountain region features are complex and have a diverse topography, geomorphology, and climate types. Investigating the spatiotemporal variations, trade‐offs/synergies, and driving mechanisms of ecosystem services (ESs) in this area is critical for scientific ecosystem management and enhancing ecosystem service functionality. In this study, we used the InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) model to quantitatively estimate carbon storage (CS), soil conservation (SC), wind and sand fixation (WSF), habitat quality (HQ), water yield (WY), and food production (FP) in the Yinshan Mountain region. Furthermore, we analyzed pairwise ES trade‐offs/synergies and identified their socioecological drivers. The results reveal that the spatial patterns of ESs in the Yinshan Mountain region remained generally stable but exhibited localized dynamics. CS, HQ, and SC displayed highly similar spatial distributions, with core zones persistently concentrated in the central Yinshan Mountain and the northern foothills, serving as critical ecological barriers. High‐value FP areas were consistently clustered along the southern fringe and eastern agropastoral ecotone, whereas WY gradually expanded southwestward since 2000. In contrast, the spatial gravity center of WSF shifted from the northern and southern slopes toward the western desert‐steppe zone. Regarding driving mechanisms, topographic factors primarily governed the spatial differentiation of SC and CS, while vegetation coverage significantly regulated HQ and FP. Climatic variables predominantly explained the spatial variations in WSF and WY. This study provides a comprehensive analysis of ES spatiotemporal dynamics and their drivers, deepening our understanding of ES interactions and offering targeted policy insights and precise management strategies for ecological sustainability in the Yinshan Mountain region.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"133 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146146033","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}
The impact of economic growth on carbon emissions plays a crucial role in shaping national development strategies, particularly in low-income Asian countries where economic transformation is driving employment, foreign exchange earnings, and overall development. This study explores the relationship between economic expansion and CO2 emissions in low-income Asian countries from 2001 to 2020, using advanced analytical methods including multiple regression, moment quantile regression, and wavelet analysis to identify threshold points for sustainable development. Key factors such as forest area, natural resource rents, foreign direct investment (FDI), population density, and GDP are analyzed for their influence on CO2 emissions. The moment quantile regression results show that forest area and natural resource rents have a significant positive effect on CO2 emissions, particularly at higher quantiles, indicating intensified environmental pressure with industrialization. The heterogeneous impacts of FDI, GDP, and population density across quantiles suggest that their influence varies by development stage. Further, wavelet transform coherence (WTC) analysis reveals strong co-movements between emissions and economic indicators, especially FDI, while cross wavelet transform (XWT) results confirm that increases in FDI and GDP often precede higher emissions, underscoring the growth–emissions trade-off in low-income Asian economies. To mitigate these effects, the study proposes strategies such as promoting green infrastructure, fostering eco-friendly development, and implementing carbon offset programs, complemented by robust regulations and digital technologies. These measures can help reduce environmental impact while supporting continued economic growth in these nations.
{"title":"Analyzing Forest Land and Environmental Degradation: Evidence From Land Management in Low-Income, Degraded Ecosystem Economies","authors":"Bekpulatov Farrukh, Waheed Ullah Shah, Himani Gupta, Cheng Longsheng","doi":"10.1002/ldr.70440","DOIUrl":"https://doi.org/10.1002/ldr.70440","url":null,"abstract":"The impact of economic growth on carbon emissions plays a crucial role in shaping national development strategies, particularly in low-income Asian countries where economic transformation is driving employment, foreign exchange earnings, and overall development. This study explores the relationship between economic expansion and CO<sub>2</sub> emissions in low-income Asian countries from 2001 to 2020, using advanced analytical methods including multiple regression, moment quantile regression, and wavelet analysis to identify threshold points for sustainable development. Key factors such as forest area, natural resource rents, foreign direct investment (FDI), population density, and GDP are analyzed for their influence on CO<sub>2</sub> emissions. The moment quantile regression results show that forest area and natural resource rents have a significant positive effect on CO<sub>2</sub> emissions, particularly at higher quantiles, indicating intensified environmental pressure with industrialization. The heterogeneous impacts of FDI, GDP, and population density across quantiles suggest that their influence varies by development stage. Further, wavelet transform coherence (WTC) analysis reveals strong co-movements between emissions and economic indicators, especially FDI, while cross wavelet transform (XWT) results confirm that increases in FDI and GDP often precede higher emissions, underscoring the growth–emissions trade-off in low-income Asian economies. To mitigate these effects, the study proposes strategies such as promoting green infrastructure, fostering eco-friendly development, and implementing carbon offset programs, complemented by robust regulations and digital technologies. These measures can help reduce environmental impact while supporting continued economic growth in these nations.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"9 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146146473","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}
Heavy metal contamination in agricultural soils threatens ecosystem stability and food safety. Rapid and accurate estimation of arsenic (As), cadmium (Cd), and lead (Pb) is therefore essential for environmental protection and soil remediation. Near‐field sensing technologies provide a fast and cost‐efficient alternative to laboratory analysis, yet single‐spectrum approaches often suffer from limited information coverage and reduced prediction accuracy. This study investigates the capability of Ultraviolet (UV), Visible–Near Infrared (Vis–NIR), and portable X‐ray fluorescence (pXRF) spectral data—individually and in combination—for predicting soil heavy metal concentrations using 110 farmland samples from Chabuqiaer Xibo Autonomous County. Seven preprocessing methods were employed to optimize spectral data quality, in conjunction with principal component analysis (PCA) for feature dimension reduction. Three fusion strategies and four machine learning models were employed for modeling and prediction. The results showed that the Parallel Concatenation Fusion of Multi‐Sensor Data Based on Self‐Attention Mechanism (PCFMS‐SAM) fusion strategy performed best in modeling the three heavy metal elements, with the best model for As being Random Forests (RF) ( R2 = 0.92), for Cd being VPPSO‐SVM ( R2 = 0.79), and for Pb being RF‐XGB ( R2 = 0.84). The consistency correlation coefficients (LCCC) of all optimal models were above 0.8, reflecting a strong alignment between model outputs and observed values. The integration of multi‐source spectral data resulted in a considerable improvement in prediction accuracy over single‐sensor models, underscoring its potential for rapid assessment of soil heavy metals.
{"title":"Unveiling the Advantages of UV −Vis/ NIR − pXRF Data Fusion for Precise Estimation of Soil Heavy Metals in Farmland","authors":"Susu Gao, Xiang Li, Jianli Ding, Bingnan Li, Xiaowen Wu, Junjie Tian, Xiangyu Ge, Chuanmei Zhu, Jinjie Wang, Zipeng Zhang","doi":"10.1002/ldr.70488","DOIUrl":"https://doi.org/10.1002/ldr.70488","url":null,"abstract":"Heavy metal contamination in agricultural soils threatens ecosystem stability and food safety. Rapid and accurate estimation of arsenic (As), cadmium (Cd), and lead (Pb) is therefore essential for environmental protection and soil remediation. Near‐field sensing technologies provide a fast and cost‐efficient alternative to laboratory analysis, yet single‐spectrum approaches often suffer from limited information coverage and reduced prediction accuracy. This study investigates the capability of Ultraviolet (UV), Visible–Near Infrared (Vis–NIR), and portable X‐ray fluorescence (pXRF) spectral data—individually and in combination—for predicting soil heavy metal concentrations using 110 farmland samples from Chabuqiaer Xibo Autonomous County. Seven preprocessing methods were employed to optimize spectral data quality, in conjunction with principal component analysis (PCA) for feature dimension reduction. Three fusion strategies and four machine learning models were employed for modeling and prediction. The results showed that the Parallel Concatenation Fusion of Multi‐Sensor Data Based on Self‐Attention Mechanism (PCFMS‐SAM) fusion strategy performed best in modeling the three heavy metal elements, with the best model for As being Random Forests (RF) ( <jats:italic>R</jats:italic> <jats:sup>2</jats:sup> = 0.92), for Cd being VPPSO‐SVM ( <jats:italic>R</jats:italic> <jats:sup>2</jats:sup> = 0.79), and for Pb being RF‐XGB ( <jats:italic>R</jats:italic> <jats:sup>2</jats:sup> = 0.84). The consistency correlation coefficients (LCCC) of all optimal models were above 0.8, reflecting a strong alignment between model outputs and observed values. The integration of multi‐source spectral data resulted in a considerable improvement in prediction accuracy over single‐sensor models, underscoring its potential for rapid assessment of soil heavy metals.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"93 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146146034","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}
Lin Yang, Runze Wang, Xinran Zhang, Rui Wang, Shengli Guo
Microorganisms are instrumental in the genesis of microbial necromass carbon (MNC). However, the depth‐specific microbial regulatory mechanisms (e.g., diversity, life‐history strategies, keystone taxa) modulating MNC accumulation across soil profiles under long‐term agricultural management with distinct root distributions remain to be explicitly addressed, especially within the ecologically fragile Loess Plateau. To fill this gap, we investigated amino sugars and microbial community characteristics in the topsoil (0–20 cm, widely recognized as an active layer) and subsoil (140–200 cm, representative of the region's stable layer) of three long‐term cropping systems with distinct root distribution depths. Our core discovery reveals a clear shift in microbial drivers regulating MNC across the soil profile: MNC accumulation is bacteria‐dominated in topsoil but fungi‐dominated in subsoil. Specifically, topsoil MNC was primarily regulated by bacterial α‐diversity, community composition, and bacterial r ‐strategists (which were negatively correlated with MNC), whereas subsoil MNC was dominated by fungal α‐diversity and fungal K‐strategists. Keystone taxa also exhibited depth‐specific effects: bacterial keystone taxa strongly modulated topsoil MNC, while fungal keystone taxa had a more significant correlation with subsoil MNC. Quantitatively, subsoil MNC content ranged from 62.2% to 74.5% lower than that of the topsoil, and its contribution to soil organic carbon ranged from 26.3% to 44.7% lower ( p < 0.01). These findings provide actionable insights for sustainable land management on the Loess Plateau: optimizing subsoil fungal community characteristics can enhance MNC accumulation, supporting land degradation mitigation and improved soil carbon sequestration.
{"title":"Subsoil Microbial Necromass Carbon Predominantly Influenced by Fungal Community Characteristics in Rainfed Cropping System on Loess Plateau","authors":"Lin Yang, Runze Wang, Xinran Zhang, Rui Wang, Shengli Guo","doi":"10.1002/ldr.70482","DOIUrl":"https://doi.org/10.1002/ldr.70482","url":null,"abstract":"Microorganisms are instrumental in the genesis of microbial necromass carbon (MNC). However, the depth‐specific microbial regulatory mechanisms (e.g., diversity, life‐history strategies, keystone taxa) modulating MNC accumulation across soil profiles under long‐term agricultural management with distinct root distributions remain to be explicitly addressed, especially within the ecologically fragile Loess Plateau. To fill this gap, we investigated amino sugars and microbial community characteristics in the topsoil (0–20 cm, widely recognized as an active layer) and subsoil (140–200 cm, representative of the region's stable layer) of three long‐term cropping systems with distinct root distribution depths. Our core discovery reveals a clear shift in microbial drivers regulating MNC across the soil profile: MNC accumulation is bacteria‐dominated in topsoil but fungi‐dominated in subsoil. Specifically, topsoil MNC was primarily regulated by bacterial α‐diversity, community composition, and bacterial <jats:italic>r</jats:italic> ‐strategists (which were negatively correlated with MNC), whereas subsoil MNC was dominated by fungal α‐diversity and fungal K‐strategists. Keystone taxa also exhibited depth‐specific effects: bacterial keystone taxa strongly modulated topsoil MNC, while fungal keystone taxa had a more significant correlation with subsoil MNC. Quantitatively, subsoil MNC content ranged from 62.2% to 74.5% lower than that of the topsoil, and its contribution to soil organic carbon ranged from 26.3% to 44.7% lower ( <jats:italic>p</jats:italic> < 0.01). These findings provide actionable insights for sustainable land management on the Loess Plateau: optimizing subsoil fungal community characteristics can enhance MNC accumulation, supporting land degradation mitigation and improved soil carbon sequestration.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"110 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146134159","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}
Jianwei Mao, Cun Chang, Shuai Wu, Igboeli Emeka Edwin, Yonghui Wang, Wei Yan, Jian Liu, Yonglong Han, Xiaofei Ma
Under the “carbon peaking and carbon neutrality” goals, the extent to which land use restructuring shapes regional carbon storage (CS) in inland river basins remains insufficiently quantified. Using the Tarim River Basin as a case study, we integrated multiple datasets at 1 km resolution for five time points from 2000 to 2023, and coupled the InVEST carbon model, PLUS scenario simulations, and GeoDetector analysis within a “pattern‐process‐projection” framework (PLUS accuracy: 94.31%). From 2000 to 2023, cropland expanded by 1.69 × 10 4 km 2 and construction land nearly doubled, whereas grassland and forestland decreased by 0.89 × 10 4 km 2 and 0.15 × 10 4 km 2 , respectively, accompanied by intermittent shrinkage of water bodies. CS across the basin increased slightly from 56.53 × 10 8 t to 56.83 × 10 8 t, indicating overall stability, but with clear spatial contrasts: gains occurred along oasis margins and riparian corridors, while losses emerged in transitional zones converted to cropland and construction land. GeoDetector identified fractional vegetation cover, soil erosion, and soil type as dominant drivers ( q > 0.25). Interactions related to fractional vegetation cover (FVC) strengthened after 2010, whereas GDP and population density exerted weaker effects. By 2030, the ecological protection scenario yielded the highest CS (57.10 × 10 8 t), the economic development scenario showed limited gains (+0.08 × 10 8 t), and the natural development scenario approached net neutrality. By integrating multi source data, scenario constraints, and interaction informed driver diagnostics, this study delineates carbon sensitive corridors that are highly accessible and quantifies the carbon benefits of controlling fragmentation, stabilizing cropland density, and optimizing water allocation. The findings provide scientific guidance for land use planning and coordinated water and carbon governance in arid regions.
{"title":"Dynamic Changes and Driving Factors of Ecosystem Carbon Storage in Inland River Basins Under Land Use Change","authors":"Jianwei Mao, Cun Chang, Shuai Wu, Igboeli Emeka Edwin, Yonghui Wang, Wei Yan, Jian Liu, Yonglong Han, Xiaofei Ma","doi":"10.1002/ldr.70475","DOIUrl":"https://doi.org/10.1002/ldr.70475","url":null,"abstract":"Under the “carbon peaking and carbon neutrality” goals, the extent to which land use restructuring shapes regional carbon storage (CS) in inland river basins remains insufficiently quantified. Using the Tarim River Basin as a case study, we integrated multiple datasets at 1 km resolution for five time points from 2000 to 2023, and coupled the InVEST carbon model, PLUS scenario simulations, and GeoDetector analysis within a “pattern‐process‐projection” framework (PLUS accuracy: 94.31%). From 2000 to 2023, cropland expanded by 1.69 × 10 <jats:sup>4</jats:sup> km <jats:sup>2</jats:sup> and construction land nearly doubled, whereas grassland and forestland decreased by 0.89 × 10 <jats:sup>4</jats:sup> km <jats:sup>2</jats:sup> and 0.15 × 10 <jats:sup>4</jats:sup> km <jats:sup>2</jats:sup> , respectively, accompanied by intermittent shrinkage of water bodies. CS across the basin increased slightly from 56.53 × 10 <jats:sup>8</jats:sup> t to 56.83 × 10 <jats:sup>8</jats:sup> t, indicating overall stability, but with clear spatial contrasts: gains occurred along oasis margins and riparian corridors, while losses emerged in transitional zones converted to cropland and construction land. GeoDetector identified fractional vegetation cover, soil erosion, and soil type as dominant drivers ( <jats:italic>q</jats:italic> > 0.25). Interactions related to fractional vegetation cover (FVC) strengthened after 2010, whereas GDP and population density exerted weaker effects. By 2030, the ecological protection scenario yielded the highest CS (57.10 × 10 <jats:sup>8</jats:sup> t), the economic development scenario showed limited gains (+0.08 × 10 <jats:sup>8</jats:sup> t), and the natural development scenario approached net neutrality. By integrating multi source data, scenario constraints, and interaction informed driver diagnostics, this study delineates carbon sensitive corridors that are highly accessible and quantifies the carbon benefits of controlling fragmentation, stabilizing cropland density, and optimizing water allocation. The findings provide scientific guidance for land use planning and coordinated water and carbon governance in arid regions.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"159 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146129422","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}
Fatemeh Bagheri, Javad Mirzaei, Mehdi Heydari, Mostafa Moradi
Afforestation plays a crucial role in rehabilitating degraded ecosystems and improving soil and environmental conditions in arid and semi-arid regions. Although many studies have shown that afforestation improves soil properties, the combined effects of slope, aspect, and microtopography on soil biochemical responses remain poorly understood. Furthermore, environmental characteristics, particularly aspect and slope percentage in mountainous forest ecosystems, play a key role in determining the extent of its impact. This study investigated the impact of afforestation using the wild almond (Amygdalus scoparia Spach) on the physical, chemical, and biological properties of soil across different aspects, slopes, and canopy positions. To conduct this research, a total of 72 soil samples were collected in spring from northern and eastern aspects in two slope classes (less than 10% and more than 40%) and three positions (Under canopy upslope [UCU], Under canopy downslope [UCD], and control). The physical, chemical, and biological soil properties were then measured in the laboratory using standard methods. The results showed that saturated point (SP) (39.48 ver. 36.39), sand (25.33 ver. 23.50), clay (32.44 ver. 28.72), organic matter (OM) (2.2 ver. 1.93), and total nitrogen (N) (0.1 ver. 0.09) were higher in the northern aspect than in the eastern aspect, while the BD (1.18 ver. 1.08) was higher in the northern aspect than in the eastern aspect. On slopes of less than 10%, the soil had higher amounts of pH (7.31 ver. 7.24), SP (37.93 ver. 35.99), OM (2.06 ver. 2.16), and N (0.1 ver. 0.07), phosphorus (P) (283 ver. 199) and potassium (K) (287 ver. 193). The highest levels of the urease enzyme (μgρ NH4 Nml-5dwt 2 h− 1 8) were observed on slopes with less than a 10% incline and at the UCD (8.26). The lowest levels were observed on slopes with an incline above 40% and in the control position (μgρ NH4 Nml-5dwt 2 h−1 2). Additionally, enzyme activity was higher in the northern aspect than in the eastern aspect (i.e., phosphatase activity = 901.39). These results indicate that afforestation positively impacts quality-related indicators, including soil respiration, porosity, urease and phosphatase enzymes, and OM and nutrients in the soil. Generally, soil is more fertile on slopes of less than 10%, on northern slopes, and on UCD. This research aims to restore this valuable ecosystem and ensure the region's sustainability, which can lead to improved soil quality and increased ecosystem sustainability. Future restoration efforts in semi-arid mountains should prioritize planting A. scoparia on northern and downslope positions to enhance soil moisture, fertility, organic carbon, and ecosystem recovery efficiency.
{"title":"Soil Rehabilitation in Degraded Oak Forest Stands Through Afforestation With Amygdalus scoparia","authors":"Fatemeh Bagheri, Javad Mirzaei, Mehdi Heydari, Mostafa Moradi","doi":"10.1002/ldr.70441","DOIUrl":"https://doi.org/10.1002/ldr.70441","url":null,"abstract":"Afforestation plays a crucial role in rehabilitating degraded ecosystems and improving soil and environmental conditions in arid and semi-arid regions. Although many studies have shown that afforestation improves soil properties, the combined effects of slope, aspect, and microtopography on soil biochemical responses remain poorly understood. Furthermore, environmental characteristics, particularly aspect and slope percentage in mountainous forest ecosystems, play a key role in determining the extent of its impact. This study investigated the impact of afforestation using the wild almond (<i>Amygdalus scoparia</i> Spach) on the physical, chemical, and biological properties of soil across different aspects, slopes, and canopy positions. To conduct this research, a total of 72 soil samples were collected in spring from northern and eastern aspects in two slope classes (less than 10% and more than 40%) and three positions (Under canopy upslope [UCU], Under canopy downslope [UCD], and control). The physical, chemical, and biological soil properties were then measured in the laboratory using standard methods. The results showed that saturated point (SP) (39.48 ver. 36.39), sand (25.33 ver. 23.50), clay (32.44 ver. 28.72), organic matter (OM) (2.2 ver. 1.93), and total nitrogen (N) (0.1 ver. 0.09) were higher in the northern aspect than in the eastern aspect, while the BD (1.18 ver. 1.08) was higher in the northern aspect than in the eastern aspect. On slopes of less than 10%, the soil had higher amounts of pH (7.31 ver. 7.24), SP (37.93 ver. 35.99), OM (2.06 ver. 2.16), and N (0.1 ver. 0.07), phosphorus (P) (283 ver. 199) and potassium (K) (287 ver. 193). The highest levels of the urease enzyme (μgρ NH4 Nml-5dwt 2 h<sup>− 1</sup> 8) were observed on slopes with less than a 10% incline and at the UCD (8.26). The lowest levels were observed on slopes with an incline above 40% and in the control position (μgρ NH4 Nml-5dwt 2 h<sup>−1</sup> 2). Additionally, enzyme activity was higher in the northern aspect than in the eastern aspect (i.e., phosphatase activity = 901.39). These results indicate that afforestation positively impacts quality-related indicators, including soil respiration, porosity, urease and phosphatase enzymes, and OM and nutrients in the soil. Generally, soil is more fertile on slopes of less than 10%, on northern slopes, and on UCD. This research aims to restore this valuable ecosystem and ensure the region's sustainability, which can lead to improved soil quality and increased ecosystem sustainability. Future restoration efforts in semi-arid mountains should prioritize planting <i>A. scoparia</i> on northern and downslope positions to enhance soil moisture, fertility, organic carbon, and ecosystem recovery efficiency.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"9 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146134152","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}
Guannan Chen, Zhenhuang Yang, Grzegorz Mentel, Paweł Jamróz, Dariusz Zarzecki
Due to severe climate challenges, global economies are transitioning to green energy, specifically, the solar thermal and wind energy to attain the COP28 targets and sustainable development goals (SDGs). To fulfill energy demand, countries are investing in these sources, yet their role in the global greenhouse gas (GHG) emissions is not clearly examined. The objective of this research is to examine the linear and nonlinear implications of solar thermal and wind energy on global GHG emissions. Employing the extended STIRPAT model, this study further considers the role of forest land management, economic growth, foreign trade, and urbanization over the period 1990Q1–2021Q4. The autoregressive distributed lag model has been used to address the mixed integration order variables. The empirical results indicate that both linear and nonlinear solar thermal, forest land resources, and wind energy significantly reduce GHG emissions in the short- and long-run. The influence of nonlinear solar and wind energy is stronger than their linear terms. Additionally, the forest areas are significantly correlated with the decreased emissions level. On the other hand, the environmental Kuznets curve hypothesis is valid as economic growth boosts emissions in the short run while diminishing it in the long run. In contrast, the results reveal that urbanization and international trade are the leading drivers of global GHG emissions. Based on the findings, this study recommends promoting renewable energy investment, forest conservation incentives, and carbon-border adjustments.
{"title":"From Growth to Green: The Complex Interplay of Renewables, Forest Land Management and Trade on GHG Emissions","authors":"Guannan Chen, Zhenhuang Yang, Grzegorz Mentel, Paweł Jamróz, Dariusz Zarzecki","doi":"10.1002/ldr.70431","DOIUrl":"https://doi.org/10.1002/ldr.70431","url":null,"abstract":"Due to severe climate challenges, global economies are transitioning to green energy, specifically, the solar thermal and wind energy to attain the COP28 targets and sustainable development goals (SDGs). To fulfill energy demand, countries are investing in these sources, yet their role in the global greenhouse gas (GHG) emissions is not clearly examined. The objective of this research is to examine the linear and nonlinear implications of solar thermal and wind energy on global GHG emissions. Employing the extended STIRPAT model, this study further considers the role of forest land management, economic growth, foreign trade, and urbanization over the period 1990Q1–2021Q4. The autoregressive distributed lag model has been used to address the mixed integration order variables. The empirical results indicate that both linear and nonlinear solar thermal, forest land resources, and wind energy significantly reduce GHG emissions in the short- and long-run. The influence of nonlinear solar and wind energy is stronger than their linear terms. Additionally, the forest areas are significantly correlated with the decreased emissions level. On the other hand, the environmental Kuznets curve hypothesis is valid as economic growth boosts emissions in the short run while diminishing it in the long run. In contrast, the results reveal that urbanization and international trade are the leading drivers of global GHG emissions. Based on the findings, this study recommends promoting renewable energy investment, forest conservation incentives, and carbon-border adjustments.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"91 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146134157","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}
With the implementation of various ecological restoration and regional development policies, both urbanization and soil conservation in the Loess Plateau (LP) have advanced substantially, but conflicts between development and the ecological environment are becoming increasingly prominent. Soil conservation is a key regulating ecosystem service, and understanding its interaction and coupling mechanism with urbanization is crucial for achieving sustainable urban development. This study used multi-source remote sensing data and evaluated soil erosion and conservation status over the past 30 years based on the revised universal soil loss equation (RUSLE) model. In addition, the coupling coordination degree model (CCDM) was employed to investigate the spatiotemporal characteristics and reveal the mechanism of the coupling coordinate degree (CCD) between soil conservation rate (SCR) and urbanization index (UBZ). Results indicate that: (1) soil erosion intensity (SE) has been well controlled in the Loess Plateau in recent decades, and the SCR has an obvious upward trend, but there is a risk of soil erosion worsening in the urban agglomeration area; (2) the coupling coordination degree between UBZ and SCR has improved significantly in the research period, but it is still concentrated in the southeast of the Loess Plateau and around the provincial capital cities; (3) there is a very significant logarithmic function fitting relationship between UBZ and CCD. At present, UBZ is the main factor leading CCD, and cities need to pay attention to controlling SE to maintain the stable growth rate of CCD when they develop to a certain period. This study pioneers the integration of multi-source remote sensing data with the RUSLE-CCDM framework to quantify a logarithmic relationship between urbanization and soil conservation coupling in the LP, proposing a phased constraint-incentive-restoration governance strategy aligned with environmental thresholds.
{"title":"Coupling Coordinated Development of Urbanization and Soil Conservation Ratio in the Loess Plateau Region of China","authors":"Xun Zhang, Zhaoliang Gao, Huazhu Zheng, Claudio O. Delang, Hongming He, Shaobo Long, Yongcai Lou","doi":"10.1002/ldr.70477","DOIUrl":"https://doi.org/10.1002/ldr.70477","url":null,"abstract":"With the implementation of various ecological restoration and regional development policies, both urbanization and soil conservation in the Loess Plateau (LP) have advanced substantially, but conflicts between development and the ecological environment are becoming increasingly prominent. Soil conservation is a key regulating ecosystem service, and understanding its interaction and coupling mechanism with urbanization is crucial for achieving sustainable urban development. This study used multi-source remote sensing data and evaluated soil erosion and conservation status over the past 30 years based on the revised universal soil loss equation (RUSLE) model. In addition, the coupling coordination degree model (CCDM) was employed to investigate the spatiotemporal characteristics and reveal the mechanism of the coupling coordinate degree (CCD) between soil conservation rate (SCR) and urbanization index (UBZ). Results indicate that: (1) soil erosion intensity (SE) has been well controlled in the Loess Plateau in recent decades, and the SCR has an obvious upward trend, but there is a risk of soil erosion worsening in the urban agglomeration area; (2) the coupling coordination degree between UBZ and SCR has improved significantly in the research period, but it is still concentrated in the southeast of the Loess Plateau and around the provincial capital cities; (3) there is a very significant logarithmic function fitting relationship between UBZ and CCD. At present, UBZ is the main factor leading CCD, and cities need to pay attention to controlling SE to maintain the stable growth rate of CCD when they develop to a certain period. This study pioneers the integration of multi-source remote sensing data with the RUSLE-CCDM framework to quantify a logarithmic relationship between urbanization and soil conservation coupling in the LP, proposing a phased constraint-incentive-restoration governance strategy aligned with environmental thresholds.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"159 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146115734","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}
Balancing ecosystem-service supply and demand is central to understanding both the natural and social dimensions of ecosystem services and to enhancing human well-beings. Concurrently, collaborative efforts are underway to improve multiple ecosystem services, including the promotion of carbon neutrality and water purification (WP) within basin regions. Here, we quantified the WP and carbon sequestration (CS) of the Three Gorges Reservoir Area (TGRA) and explored the driving mechanism of two ecosystem services from the perspective of supply and demand. The results reveal that CS and WP of TGRA have generally achieved a balance between supply and demand over the past 30 years. WP-supply showed a significant decline (−6.25 × 102 t/year), while CS-supply exhibited steady growth (20.27 × 104 tC/year). WP-demand experienced a slight reduction (−8.42 × 102 t/year), whereas CS-demand increased sharply (73.7 × 104 tC/year). Spatial analysis indicated that both CS and WP supply–demand reachability peaked in regions exceeding 1000 m in elevation and 25° in slope. WP exhibited strong spatial clustering, with high–high agglomerations predominantly located in the central Yangtze and southwestern areas, and low–low clusters concentrated in northern and southern zones. However, CS exhibited distinct spatial variation, featuring high–low zones in the east and low–high zones in the southwest. Climate factors significantly enhanced WP-supply (0.41) and WP-demand (0.54) but inhibited both CS-supply (−0.11) and CS-demand (−0.05). Socioeconomic factors are positively related to CS-demand (0.94) while negatively impacting CS-supply (−0.38). Soil factors exerted a positive influence on CS-supply (0.35) but a negative effect on WP-supply (−0.37). Moreover, management strategies in the TGRA should integrate spatially targeted measures for WP to address local supply–demand gaps, along with a spatially regulated regional “cap and trade” mechanism to sustain CS surplus. Supported by vegetation restoration and coordinated water–carbon governance, this approach can strengthen WP–CS synergies.
{"title":"Coupling Water Purification and Carbon Sequestration at Various Spatial Scales From Supply and Demand Perspective","authors":"Jing Cheng, Mingyang Ding, Zhenya Zhu, Xinping Luo, Xin Huang, Chunbo Huang","doi":"10.1002/ldr.70434","DOIUrl":"https://doi.org/10.1002/ldr.70434","url":null,"abstract":"Balancing ecosystem-service supply and demand is central to understanding both the natural and social dimensions of ecosystem services and to enhancing human well-beings. Concurrently, collaborative efforts are underway to improve multiple ecosystem services, including the promotion of carbon neutrality and water purification (WP) within basin regions. Here, we quantified the WP and carbon sequestration (CS) of the Three Gorges Reservoir Area (TGRA) and explored the driving mechanism of two ecosystem services from the perspective of supply and demand. The results reveal that CS and WP of TGRA have generally achieved a balance between supply and demand over the past 30 years. WP-supply showed a significant decline (−6.25 × 10<sup>2</sup> t/year), while CS-supply exhibited steady growth (20.27 × 10<sup>4</sup> tC/year). WP-demand experienced a slight reduction (−8.42 × 10<sup>2</sup> t/year), whereas CS-demand increased sharply (73.7 × 10<sup>4</sup> tC/year). Spatial analysis indicated that both CS and WP supply–demand reachability peaked in regions exceeding 1000 m in elevation and 25° in slope. WP exhibited strong spatial clustering, with high–high agglomerations predominantly located in the central Yangtze and southwestern areas, and low–low clusters concentrated in northern and southern zones. However, CS exhibited distinct spatial variation, featuring high–low zones in the east and low–high zones in the southwest. Climate factors significantly enhanced WP-supply (0.41) and WP-demand (0.54) but inhibited both CS-supply (−0.11) and CS-demand (−0.05). Socioeconomic factors are positively related to CS-demand (0.94) while negatively impacting CS-supply (−0.38). Soil factors exerted a positive influence on CS-supply (0.35) but a negative effect on WP-supply (−0.37). Moreover, management strategies in the TGRA should integrate spatially targeted measures for WP to address local supply–demand gaps, along with a spatially regulated regional “cap and trade” mechanism to sustain CS surplus. Supported by vegetation restoration and coordinated water–carbon governance, this approach can strengthen WP–CS synergies.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"47 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146129252","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}
As the hinterland of the Qinghai-Tibet Plateau, the Sanjiangyuan region possesses pivotal ecological and strategic value, with its soil quality serving as a cornerstone for regional and global ecological balance. However, under the coupled stressors of climate warming and intensifying anthropogenic activities, the accumulation of soil potentially toxic elements (PTEs) has accelerated markedly, posing a substantial environmental threat to this fragile ecosystem. To unravel the driving mechanisms governing soil PTE contamination, this study focused on the alpine grasslands of Sanjiangyuan, analyzing the concentrations of five priority PTEs (Pb, Cd, Cr, As, and Hg). Employing an integrated framework that couples spatial interpolation, correlation analysis, and Positive Matrix Factorization (PMF), we systematically disentangled how elevation, climatic factors, soil physicochemical properties, and anthropogenic disturbances shape the spatial distribution patterns and variability of soil PTEs. Results indicated that: (1) Soil PTE concentrations exhibited a unimodal distribution along the elevational gradient, peaking at intermediate altitudes, and showed significant positive correlations with mean annual precipitation (MAP) and vegetation cover (<i>p</i> < 0.05). Spatially, concentrations displayed a distinct decreasing gradient from the southern region toward the eastern and northwestern sectors. Notably, the southern region was characterized by the highest contaminant loads (Pb: 16.47 ± 3.82, Cd: 0.10 ± 0.02, Cr: 52.78 ± 7.56, As: 14.45 ± 2.35, Hg: 0.041 ± 0.004 mg kg<sup>−1</sup>), whereas the northwestern region presented the lowest values (Pb: 8.41 ± 1.10, Cd: 0.04 ± 0.002, Cr: 30.47 ± 3.48, As: 11.89 ± 1.97, Hg: 0.017 ± 0.001 mg kg<sup>−1</sup>). (2) Reflecting its lithogenic origin, Cr exhibited significantly stronger correlations with key edaphic properties—including soil water content (SWC), pH, organic/inorganic carbon (SOC, SIC), total nitrogen (TN), and soil total phosphorus (STP)—compared to other PTEs. Notably, these associations were more robust in the subsurface layer (10–20 cm) than in the surface layer (0–10 cm). (3) Within the 0–20 cm soil profile, concentrations of PTEs exhibited a significant decline with increasing distance from anthropogenic disturbances. Pb showed the highest sensitivity to this spatial gradient, evidenced by a feature importance score of 30.05%. While this distance effect attenuated notably with soil depth, sharp concentration gradients were observed in the surface layer: Pb dropped from 12.45 ± 3.49 to 4.21 ± 0.82 mg kg<sup>−1</sup>, Cd from 0.071 ± 0.015 to 0.023 ± 0.001 mg kg<sup>−1</sup>, Cr from 53.97 ± 8.79 to 23.43 ± 4.22 mg kg<sup>−1</sup>, As from 13.21 ± 2.56 to 9.36 ± 1.64 mg kg<sup>−1</sup>, and Hg from 0.039 ± 0.002 to 0.013 ± 0.003 mg kg<sup>−1</sup>. (4) The PMF model identified four distinct source factors contributing to soil PTE accumulation. Traffic emissions and fossil fuel combustion (ac
三江源地区是青藏高原腹地，土壤质量是区域乃至全球生态平衡的基石，具有重要的生态和战略价值。然而，在气候变暖和人类活动加剧的双重压力下，土壤潜在有毒元素（pte）的积累明显加快，对这一脆弱的生态系统构成了重大的环境威胁。为了揭示土壤PTE污染的驱动机制，本研究以三江源高寒草原为研究对象，分析了5种优先PTE （Pb、Cd、Cr、As和Hg）的浓度。采用空间插值、相关分析和正矩阵分解（PMF）相结合的综合框架，系统地揭示了海拔、气候因子、土壤理化性质和人为干扰对土壤pte空间分布格局和变异的影响。结果表明：(1)土壤PTE浓度沿海拔梯度呈单峰分布，在中海拔处达到峰值，与年平均降水量（MAP）和植被覆盖度呈显著正相关（p < 0.05）。从空间上看，从南部向东部和西北部呈明显的递减趋势。值得注意的是，南部地区的污染物负荷最高（Pb: 16.47±3.82,Cd: 0.10±0.02,Cr: 52.78±7.56,As: 14.45±2.35,Hg: 0.041±0.004 mg kg - 1），而西北部地区的污染物负荷最低（Pb: 8.41±1.10,Cd: 0.04±0.002,Cr: 30.47±3.48,As: 11.89±1.97,Hg: 0.017±0.001 mg kg - 1）。(2) Cr与土壤水分（SWC）、pH、有机/无机碳（SOC， SIC）、全氮（TN）、土壤全磷（STP）等关键土壤性质的相关性显著强于其他pte，反映了其成岩成因。值得注意的是，这些关联在亚表层（10-20 cm）比在表层（0-10 cm）更为强烈。(3)在0 ~ 20 cm土壤剖面上，pte浓度随距离人为干扰的增加而显著降低。Pb对该空间梯度的敏感性最高，特征重要性得分为30.05%。虽然这种距离效应随着土壤深度的增加而明显减弱，但在表层中发现了明显的浓度梯度：Pb从12.45±3.49 mg kg - 1下降到4.21±0.82 mg kg - 1， Cd从0.071±0.015 mg kg - 1下降到0.023±0.001 mg kg - 1， Cr从53.97±8.79 mg kg - 1下降到23.43±4.22 mg kg - 1， As从13.21±2.56 mg kg - 1下降到9.36±1.64 mg kg - 1， Hg从0.039±0.002 mg kg - 1下降到0.013±0.003 mg kg - 1。(4) PMF模型识别出4种不同的土壤PTE积累源因子。交通排放和化石燃料燃烧（占总变化的32.1%）是Pb和as的主要驱动因素。相比之下，Hg主要受混合人为源控制（28.6%），Cr主要受自然成土过程控制（23.5%）。此外，镉主要来源于工农业活动（15.8%）。空间上，三江源地区土壤PTE污染受外部环境因子（高程、MAP、年平均温度、人为干扰）和内部生态系统因子（植被和土壤性质）的复杂相互作用调节。驱动机制表现出明显的垂直分层：表层土壤PTE积累受植被和土壤因子的耦合驱动，而底土变化主要受土壤性质的制约。值得注意的是，人为影响的特征是地表富集，并随着土壤深度的增加而迅速减弱。因此，管理战略应优先考虑南部地区严格的缓解干预措施，而东部和西北部地区则侧重于预防性保护。
{"title":"Spatial Distribution and Key Driving Factors of Soil Potentially Toxic Elements in Sanjiangyuan Alpine Grasslands—A Dual-Factor Perspective of Natural and Anthropogenic Drivers","authors":"Yukun Zhang, Dongdong Chen, Qi Li, Fuquan He, Li Zhang, Liang Zhao","doi":"10.1002/ldr.70476","DOIUrl":"https://doi.org/10.1002/ldr.70476","url":null,"abstract":"As the hinterland of the Qinghai-Tibet Plateau, the Sanjiangyuan region possesses pivotal ecological and strategic value, with its soil quality serving as a cornerstone for regional and global ecological balance. However, under the coupled stressors of climate warming and intensifying anthropogenic activities, the accumulation of soil potentially toxic elements (PTEs) has accelerated markedly, posing a substantial environmental threat to this fragile ecosystem. To unravel the driving mechanisms governing soil PTE contamination, this study focused on the alpine grasslands of Sanjiangyuan, analyzing the concentrations of five priority PTEs (Pb, Cd, Cr, As, and Hg). Employing an integrated framework that couples spatial interpolation, correlation analysis, and Positive Matrix Factorization (PMF), we systematically disentangled how elevation, climatic factors, soil physicochemical properties, and anthropogenic disturbances shape the spatial distribution patterns and variability of soil PTEs. Results indicated that: (1) Soil PTE concentrations exhibited a unimodal distribution along the elevational gradient, peaking at intermediate altitudes, and showed significant positive correlations with mean annual precipitation (MAP) and vegetation cover (<i>p</i> < 0.05). Spatially, concentrations displayed a distinct decreasing gradient from the southern region toward the eastern and northwestern sectors. Notably, the southern region was characterized by the highest contaminant loads (Pb: 16.47 ± 3.82, Cd: 0.10 ± 0.02, Cr: 52.78 ± 7.56, As: 14.45 ± 2.35, Hg: 0.041 ± 0.004 mg kg<sup>−1</sup>), whereas the northwestern region presented the lowest values (Pb: 8.41 ± 1.10, Cd: 0.04 ± 0.002, Cr: 30.47 ± 3.48, As: 11.89 ± 1.97, Hg: 0.017 ± 0.001 mg kg<sup>−1</sup>). (2) Reflecting its lithogenic origin, Cr exhibited significantly stronger correlations with key edaphic properties—including soil water content (SWC), pH, organic/inorganic carbon (SOC, SIC), total nitrogen (TN), and soil total phosphorus (STP)—compared to other PTEs. Notably, these associations were more robust in the subsurface layer (10–20 cm) than in the surface layer (0–10 cm). (3) Within the 0–20 cm soil profile, concentrations of PTEs exhibited a significant decline with increasing distance from anthropogenic disturbances. Pb showed the highest sensitivity to this spatial gradient, evidenced by a feature importance score of 30.05%. While this distance effect attenuated notably with soil depth, sharp concentration gradients were observed in the surface layer: Pb dropped from 12.45 ± 3.49 to 4.21 ± 0.82 mg kg<sup>−1</sup>, Cd from 0.071 ± 0.015 to 0.023 ± 0.001 mg kg<sup>−1</sup>, Cr from 53.97 ± 8.79 to 23.43 ± 4.22 mg kg<sup>−1</sup>, As from 13.21 ± 2.56 to 9.36 ± 1.64 mg kg<sup>−1</sup>, and Hg from 0.039 ± 0.002 to 0.013 ± 0.003 mg kg<sup>−1</sup>. (4) The PMF model identified four distinct source factors contributing to soil PTE accumulation. Traffic emissions and fossil fuel combustion (ac","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"89 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146116137","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}
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