Ecological Indicators最新文献

{"title":"Determining the suitable ecological water level based on the response relationship between landscape connectivity and water level: A case study of Poyang Lake, China","authors":"Cheng Zhang ,&nbsp;Wenbo Chen ,&nbsp;Fangfang Huang","doi":"10.1016/j.ecolind.2025.113562","DOIUrl":"10.1016/j.ecolind.2025.113562","url":null,"abstract":"<div><div>Water level is an important indicator of hydrological regime of lake, and its spatio-temporal variation has a profound impact on habitat quality and biodiversity conservation. How to determine the suitable ecological water level has long been a hot issue in ecohydrology research. Taking Poyang Lake as a case and from the perspective of habitat, this study firstly used the range of variability approach (RVA) to analyze the natural water level regime of the lake. Then, the probability of connectivity (PC) was applied to analyze the dynamics of grassland connectivity and water connectivity after identifying the distribution pattern of grassland and water body at different water levels. Finally, the natural water level regime was corrected to the suitable ecological water level based on the response relationship between grassland connectivity, water connectivity and water level. The results showed as follows: (1) The annual variation of water level in Poyang Lake showed a significant unimodal distribution, with high water level in flood season from April to September and low water level in dry season from October to March of the following year. The annual water level can reach the highest of 22.63 m in July and the lowest of 7.12 m in February from 2000 to 2020. (2) The grassland and water body constitute the main habitats of Poyang Lake wetland. Under the disturbance of hydrological process, they presented the unique dynamic tradeoff relationships of “One shrinks while the other expands” and “One is fragmented while the other is connected”, respectively. With the increase of water level, grassland connectivity decreased dramatically while water connectivity increased progressively. (3) The annual demand for suitable ecological water level is 14.82–15.65 m. In the wet season, the threshold of suitable ecological water is 14.82–16.96 m, while it is 11.75–14.82 m in the dry season. The threshold of monthly suitable ecological water level from January to December is successively as follows: 9.89–14.82, 9.99–14.82, 12.12–14.82, 13.29–14.82, 14.82–15.69, 14.82–14.86, 14.82–16.12, 14.82–15.13, 14.82–16.46, 14.65–14.82, 12.38–14.82 and 10.31–14.82 m. This thesis proposes a new perspective and innovative approach for determining the suitable ecological water level of lakes, which can better guide hydrological regulation, habitat management and biodiversity conservation in lake areas.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"175 ","pages":"Article 113562"},"PeriodicalIF":7.0,"publicationDate":"2025-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144071535","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An XGBoost-SHAP framework for identifying key drivers of urban flooding and developing targeted mitigation strategies","authors":"Xiaoping Fu ,&nbsp;Mo Wang ,&nbsp;Dongqing Zhang ,&nbsp;Furong Chen ,&nbsp;Xiaotao Peng ,&nbsp;Lie Wang ,&nbsp;Soon Keat Tan","doi":"10.1016/j.ecolind.2025.113579","DOIUrl":"10.1016/j.ecolind.2025.113579","url":null,"abstract":"<div><div>Urban flooding is a multifaceted and severe issue, exacerbated by global climate change and urban expansion. Hence, it is imperative to investigate effective strategies for mitigating the urban flooding risk. This research proposes an innovative framework to recognize the driving factors and evaluate the impact of land cover changes on urban flooding, using a machine learning simulation model in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA). The results indicated that approximately 19.8% of the investigated areas are exposed to high-risk, predominantly in the densely populated urban center of the GBA. In terms of identifying driving factors, impervious surface percentage (ISP) and fractional vegetation cover (FVC) are the primary driving factors of urban flooding. Converting impervious surface (IS) into green space (GS), the areas exposed at medium- and high-risk of flooding in the urban–rural fringe were significantly reduced, while no significant alterations were observed in the areas at very high-risk induced by urban flooding in the central city. By contrast, converting GS into IS significantly increased the areas exposed to very high-risk in the central city. In addition, we proposed optimization strategies for effectively mitigating urban flooding, based on the distribution and regional characteristics of flooding in the central city, rural–urban fringe and rural areas, respectively. This study provides urban planners and designers with valuable insights into how land cover management and green infrastructure can be leveraged to address urban flooding, thus offering practical guidance for sustainable urban development in rapidly urbanizing regions.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"175 ","pages":"Article 113579"},"PeriodicalIF":7.0,"publicationDate":"2025-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144071532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Soil salinization in drylands: Measure, monitor, and manage","authors":"Jingzhe Wang ,&nbsp;Jianli Ding ,&nbsp;Yankun Wang ,&nbsp;Xiangyu Ge ,&nbsp;Ivan Lizaga ,&nbsp;Xiangyue Chen","doi":"10.1016/j.ecolind.2025.113608","DOIUrl":"10.1016/j.ecolind.2025.113608","url":null,"abstract":"<div><div>Soil salinization poses a critical threat to global agricultural productivity, ecosystem resilience, and regional resource sustainability. Primary and secondary salinization processes—driven by natural and anthropogenic factors—are intensifying under climate change and unsustainable land-use practices, jeopardizing food security and soil health in drylands. This viewpoint article synthesizes global research on the mechanisms governing soil salinization in drylands, evaluates spatial–temporal drivers of salt accumulation, and critically assesses advances in measuring, monitoring, and managing strategies. Emerging technologies are highlighted, including accurate monitoring using multi-source data fusion, advanced modeling techniques and multiscale full-cycle soil salinity simulation through digital twin technology, and integrated approaches combining hydraulic engineering, chemistry, biology, ecology, and nature-based solutions (NBS) to address soil salinization. Salinization management is a global priority for achieving SDG2. Integrating Earth’s Critical Zone framework reveals salinization’s cascading impacts on agroecosystems, urging synergistic adoption of nature-based solutions and precision agriculture. We emphasize sensor-driven soil health monitoring, salt-tolerant crop breeding, and policy frameworks that incentivize circular resource systems. Shifting from soil amelioration to salt-tolerant germplasm innovation, supported by multidisciplinary synergies, represents a strategically crucial pathway for transforming saline-alkali soils into climate-resilient agricultural assets, thereby securing national food security.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"175 ","pages":"Article 113608"},"PeriodicalIF":7.0,"publicationDate":"2025-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144071533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Climatic seasonality shapes insect community composition on the Mongolian Plateau","authors":"Kuanyan Tang ,&nbsp;Mian Gul Hilal ,&nbsp;Hongru Yue ,&nbsp;Xiaolong Ding ,&nbsp;Yifang Xing ,&nbsp;Jinming Zhao ,&nbsp;Yang Liu ,&nbsp;Hao Liu ,&nbsp;Zilong He ,&nbsp;Kejian Lin ,&nbsp;Ning Wang","doi":"10.1016/j.ecolind.2025.113595","DOIUrl":"10.1016/j.ecolind.2025.113595","url":null,"abstract":"<div><div>Insects, as key components of steppe ecosystems, play an essential role in maintaining biodiversity. However, while climate change is recognized as a major factor in steppe degradation and biodiversity decline, the specific mechanisms by which climatic seasonality impacts insect community structure and composition remain poorly understood. To explore this, we conducted a field survey of insect communities across 66 sample plots on the Mongolian Plateau, analyzing climate variables (e.g., annual precipitation, temperature), vegetation status (NDVI), and soil characteristics. Our results indicated that climate, particularly seasonal shifts in precipitation and temperature, were primary factors shaping insect communities. Specifically, precipitation – annual, wettest quarter and warmest quarter – significantly influenced insect abundance and community composition, while temperature seasonality and isothermality were the key drivers of diversity Margalef index. Meanwhile, vegetation status, represented by the NDVI, emerged as a critical factor for overall insect diversity. Moreover, our findings suggested that climate, vegetation, and soil factors collectively influence species richness, providing important insights for steppe biodiversity conservation. Understanding these relationships is essential for developing adaptive conservation strategies under changing climatic conditions.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"175 ","pages":"Article 113595"},"PeriodicalIF":7.0,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144067974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diversity patterns and trait-specific variations in soil nematode communities associated with Solidago invasion","authors":"Zsolt Tóth ,&nbsp;Kristóf Korponai","doi":"10.1016/j.ecolind.2025.113598","DOIUrl":"10.1016/j.ecolind.2025.113598","url":null,"abstract":"<div><div>Plant invasions substantially alter both aboveground and belowground communities. Invasive species modify habitats, directly and indirectly affecting soil biota and functions. Soil nematodes, the most diverse and abundant faunal groups in the soil food web, play a crucial role in shaping plant-soil feedback mechanisms.</div><div>Using a DNA metabarcoding approach, we conducted the first in-depth analysis to examine the relationship between nematode assemblages and the dominance of the aggressive exotic species, Canadian goldenrod (<em>Solidago canadensis</em>), by comparing invaded and uninvaded (control) plot pairs in a protected urban meadow over two consecutive growing seasons.</div><div>In <em>Solidago</em> stands, nematode taxonomic diversity declined, particularly at the ASV level, with herbivores and fungivores contributing most to this decline. In contrast, bacterivore genus richness was higher in invaded soils compared to control soils. Although overall functional diversity declined, herbivorous nematodes were functionally more diverse in invaded soils. Community composition differed significantly between invaded and uninvaded soils, with influences from soil moisture and season. Bacterivore frequency (mainly enrichment opportunists) was higher, while herbivore frequency (particularly facultative endoparasites) was lower in invaded soils. These changes led to a simplification of network structure, reducing herbivore connections and increasing the roles of bacterivores and predator-omnivores.</div><div>Our results suggest that the invasion strategy of <em>S. canadensis</em> relies mainly on two key plant-soil feedback mechanisms: (1) release from herbivory pressure, and (2) enhanced nutrient acquisition or supply via bacterial pathways. By integrating taxonomic, trait-based, and network approaches, this study highlights how plant invasions can reshape belowground biodiversity and alter ecosystem functioning.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"175 ","pages":"Article 113598"},"PeriodicalIF":7.0,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144071530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of priority areas for ecological restoration based on ecological security patterns and ecological risks: A case study of the Hefei Metropolitan Area","authors":"Xiaonan Niu ,&nbsp;Jing Zhang ,&nbsp;Shangxiao Wang ,&nbsp;Leli Zong ,&nbsp;Mo Zhou ,&nbsp;Ming Zhang","doi":"10.1016/j.ecolind.2025.113590","DOIUrl":"10.1016/j.ecolind.2025.113590","url":null,"abstract":"<div><div>Intensifying human activities have triggered significant ecological degradation, necessitating innovative approaches to ecosystem restoration. This study introduces a novel integrated methodology combining Ecological Security Patterns (ESP) and Ecological Risk Assessment (ERA) to identify priority ecological restoration areas in the Hefei Metropolitan Area. By synthesizing these complementary approaches, we overcome the limitations of individual methods and establish a comprehensive framework for prioritizing ecological restoration. We construct a complex ecological network comprising 36 source areas spanning 8313.96 km² and 92 interconnected ecological corridors extending 24,489.17 km. We have identified 73 ecological restoration nodes and 19 key restoration areas covering 544.45 km², predominantly located at critical ecological junctions. The study categorizes restoration zones into five distinct types: river and lake wetland restoration, mine environment remediation, urban ecological landscape reconstruction, ecological corridor connectivity restoration, and soil and water conservation improvement. Combining ESP with ERA allows for the identification of regions most vulnerable to ecological damage while preserving key ecological functions and networks. Through the identification of urban ecological conflict zones, this study provides a strategic framework for enhancing ecosystem resilience and promoting sustainable urban development. This research is significant because of its potential to address the urgent need for effective ecological restoration strategies in rapidly urbanizing regions, offering a systematic approach to balance ecological preservation with urban development.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"175 ","pages":"Article 113590"},"PeriodicalIF":7.0,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144071531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring lake ecological water levels via the Lake Ecological Comprehensive Evaluation Index (LECEI) approach in conjunction with terrestrial and aquatic environments","authors":"Weifeng Yue ,&nbsp;Changming Cao ,&nbsp;Qingqing Fang ,&nbsp;Guoqiang Wang ,&nbsp;Ziyi Zan ,&nbsp;Kun Wang ,&nbsp;Tingxi Liu","doi":"10.1016/j.ecolind.2025.113582","DOIUrl":"10.1016/j.ecolind.2025.113582","url":null,"abstract":"<div><div>Determining ecological water levels crucially lies in elucidating the relationship between water levels and ecological environmental quality, which are essential for the sustainable development of lake ecosystems. However, the response of lake environmental quality to water level fluctuations remains incompletely understood. This study employed forward and inverse modelling of remote sensing data at large spatiotemporal scales to propose a novel comprehensive evaluation framework, the Lake Ecological Comprehensive Evaluation Index (LECEI), which characterises lake environmental quality by integrating the terrestrial (lakeshore zones that are assessed using the remote sensing ecological index, RSEI) and aquatic (water bodies that are assessed using lake water quality indicators, LWQIs) indicators. The upper limit, lower limit, and optimal ecological water levels were subsequently quantitatively determined on the basis of the nonlinear relationship between the water level and the LECEI. This study revealed correlation coefficients between the LECEI and water levels ranging from 0.77 to 0.79 for Wuliangsuhai Lake from 1990 to 2017. Additionally, the upper and lower ecological water levels were determined to be 1018.77 m and 1019.23 m, respectively, by an analysis of the probability density distribution of the LECEI in conjunction with its nonlinear relationship with the water level. Furthermore, this study examined the relationship between the LECEI and water level elevation and identified 1019.13 m as the optimal ecological water level for maintaining lake environmental quality, indicating an inflection point from a slow to a significant increase in the LECEI. By employing this novel comprehensive evaluation framework, this study successfully determined the ecological water levels of the lake, thereby supporting the maintenance of health and sustainable development of lake ecosystems.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"175 ","pages":"Article 113582"},"PeriodicalIF":7.0,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144067978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning classification and driver analysis of diel variability in dissolved oxygen in Taihu Lake","authors":"Tingting Luo ,&nbsp;Yehui Zhang","doi":"10.1016/j.ecolind.2025.113593","DOIUrl":"10.1016/j.ecolind.2025.113593","url":null,"abstract":"<div><div>Dissolved oxygen (DO) plays a crucial role in aquatic ecosystems, yet its diel variations are influenced by complex environmental interactions. This study analyzed high-frequency DO data from Sanshandao Island in Taihu Lake (2020–2022) to classify diel DO variation patterns and identify key drivers. Using K-means clustering, we identified three distinct types: Type I (warm, humid, rainy, moderate DO fluctuations, late DO peaks, influenced by photosynthesis and precipitation), Type II (warm, dry, high radiation, largest diel DO amplitude, early peaks, photosynthesis-dominated), and Type III (cold-season conditions, high DO levels, minimal diel fluctuations, temperature-driven). Photosynthetically active radiation (PAR) and precipitation were major regulators of diel DO dynamics. PAR strongly influenced DO variations in Type II, while precipitation played a key role in distinguishing Type I from Type II by affecting vertical mixing. To enhance interpretability and predictive accuracy, XGBoost regression models were trained separately for each type, with SHAP analysis quantifying the contributions of individual drivers. The classification-based modeling approach improved performance significantly (R2 increased from 0.73 to &gt; 0.8 in Type I and III). This study presents an integrated framework combining unsupervised clustering and interpretable machine learning to uncover the mechanisms of diel DO variation. The results underscore the need to account for DO pattern heterogeneity in prediction and management and offer new tools for developing targeted water quality strategies in eutrophic lake systems.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"175 ","pages":"Article 113593"},"PeriodicalIF":7.0,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143948752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Soil water balance in response to rainfall variability over a dammed valley farmland in the Chinese Loess Plateau","authors":"Han Zheng ,&nbsp;Jintao Bai ,&nbsp;Panpan Niu ,&nbsp;Tao Peng ,&nbsp;Zhao Jin ,&nbsp;Han Bao ,&nbsp;Syeda Alveena Fatima Naqvi ,&nbsp;Yijing Guan","doi":"10.1016/j.ecolind.2025.113594","DOIUrl":"10.1016/j.ecolind.2025.113594","url":null,"abstract":"<div><div>The dammed valley farmlands created by a mega land consolidation project are crucial in combating land degradation and sustaining food security in the Chinese Loess Plateau. Understanding the response of soil water balance to rainfall variability is essential for the effective water resources management in water scarcity regions facing global climate change. Based on continuous <em>in situ</em> 3-m soil water profile beneath a dammed valley maize farmland, the Hydrus-1D model was calibrated and then employed to simulate the soil water movement and water budgets during two maize growing seasons with contrasting hydrological conditions in 2019 (drought year) and 2020 (normal year). Results showed that the Hydrus-1D model could accurately depict the soil water dynamics at different depths during the two growing seasons. The simulated soil water storage changes (Δ<em>S</em>) and actual evapotranspiration (ET) also showed good agreement with the Δ<em>S</em> from soil water monitoring data and ET from eddy covariance method, respectively. The simulated data indicated that the maximum infiltration depth of rainfall (<em>P</em>) was 100 cm and 150 cm in 2019 and 2020, respectively. The soil water recharge from groundwater by capillary rise varied significantly with crop phenology and water availability, but with close sums during the two growing seasons (45.24 mm and 34.15 mm). ET dominated the soil water consumption for both years, with the ratio of ET to <em>P</em> of 0.98 and 0.73 during the growing seasons of 2019 and 2020, respectively. The simulated Δ<em>S</em> was pronouncedly lower in the drought year (51.79 mm) compared with the normal year (147.53 mm), representing 16.5 % and 30.3 % of the total growing-season <em>P</em>, respectively. The simulated deep drainage was 20.18 mm in 2020, but this value was reduced to zero in 2019. This research could deepen our understanding on the impacts of rainfall variability on soil water balance in the water-limited agricultural regions.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"175 ","pages":"Article 113594"},"PeriodicalIF":7.0,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144067971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatial effects of human activities on multi-subsurface soil organic carbon during the last 20 years in Shaanxi Province, China","authors":"Yujie Zhou ,&nbsp;Yiheng Zhang ,&nbsp;Wanying Li","doi":"10.1016/j.ecolind.2025.113603","DOIUrl":"10.1016/j.ecolind.2025.113603","url":null,"abstract":"<div><div>Soil organic carbon (SOC), as a crucial carbon reservoir and a key component of ecosystems, plays an essential role in mitigating global climate warming driven by carbon emissions from human activities. In this study, we developed the Human Activity Intensity (HAI) index, which integrates factors such as population density and land use/land cover, establishing a spatial linkage between surface and subsurface SOC data at multiple depths. Additionally, we investigated the influence of surface ecological conditions, represented by the Remote Sensing-based Ecological Index (RSEI) on SOC. Our analysis elucidates the differential impacts of human activities and ecological conditions on SOC across distinct soil layers, underscoring the pivotal role of SOC as a fundamental ecological variable. Results from the Geographically Weighted Regression (GWR) model showed that the primary negative impacts (GWR regression coefficient &lt; 0) of HAI on RSEI were concentrated in the central region of Shaanxi Province, with relatively minor positive effects. In contrast, significant positive impacts (GWR regression coefficient &gt; 0) were predominantly observed in the northern part of Yulin City. Furthermore, we found that the spatial effects of HAI on surface SOC were more pronounced than those on multi-subsurface SOC layers. GWR model results indicated a gradual decline in the spatial effects with increasing soil depth, stabilizing at approximately 60 cm. The spatial distribution of surface vegetation conditions and land use/cover was found to significantly influence the spatial patterns of both surface and subsurface SOC across multiple soil layers. Collectively, our findings offer valuable macro-scale insights into the spatial relationships between human activities and SOC, extending the analysis into a multidimensional environmental context.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"175 ","pages":"Article 113603"},"PeriodicalIF":7.0,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144067967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}