Ecological Indicators最新文献

{"title":"Optimization framework for coupled and coordinated development of ecological environment and urbanization in dual-core urban agglomerations: A case study area of Chengdu-Chongqing","authors":"Huilin Yang ,&nbsp;Huaiyong Shao ,&nbsp;Cunbo Zhang ,&nbsp;Chengkang Zhang ,&nbsp;Wei Su ,&nbsp;Qi Zhao","doi":"10.1016/j.ecolind.2025.113624","DOIUrl":"10.1016/j.ecolind.2025.113624","url":null,"abstract":"<div><div>Urban agglomerations, as emerging competitive geographical units in the era of globalization, grapple with the challenge of reconciling rapid urbanization and ecological dynamics, thereby influencing regional sustainability. This predicament is particularly pronounced in dual-core urban agglomerations like Chengdu-Chongqing, necessitating a delicate balance in their interplay. Our study establishes an assessment framework for the synergistic development of ecological environments and urbanization in dual-core urban agglomerations. Leveraging Remote Sensing and Geographic Information System (GIS) techniques, we conduct a multiscale analysis of urbanization and ecological environment synergies. Our findings reveal that: 1) Over the past two decades, the ecological quality of Chengdu-Chongqing urban agglomeration has exhibited a fluctuating yet ascending trend, with nighttime light data indicating continuous and rapid urbanization. 2) The synergistic development of the dual-core urban agglomeration unfolds in distinct stages, influenced by cyclical national policies and unforeseen natural disasters during 2005–2015. Scale differences in the degree of coordinated development within urban agglomeration necessitate strategic differentiation. 3) The trajectory of dual-core urban agglomeration development persists, revealing conspicuous intraregional gaps that, if excessively disparate, could compromise sustainable regional development. This study not only offers scientific decision support for the dual-core urban agglomeration’s development but also advances regional ecological civilization, providing developmental insights for analogous urban agglomerations worldwide.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"176 ","pages":"Article 113624"},"PeriodicalIF":7.0,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144105914","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":"Changes of land use and landscape pattern along sea–land gradient in developed coastal region: A case study of Jiangsu Province, China","authors":"Jiahao Zhai ,&nbsp;Lijie Pu ,&nbsp;Lu Qie ,&nbsp;Gaili He ,&nbsp;Xiaoqing Wang ,&nbsp;Rui Zhang ,&nbsp;Ye Yuan ,&nbsp;Rui Zhong ,&nbsp;Yumeng Lu ,&nbsp;Jiayi Xie ,&nbsp;Jiawei Tao ,&nbsp;Sihua Huang","doi":"10.1016/j.ecolind.2025.113635","DOIUrl":"10.1016/j.ecolind.2025.113635","url":null,"abstract":"<div><div>Sea–land gradient zonality is one of the most fundamental geographic features that may have critical impact on changes in land use and landscape pattern. However, specialized sea–land gradient distance analysis remains insufficient. Here, we selected a 60 km stretch along the coastline of Jiangsu Province, China, establishing 12 equidistant (i.e., 5 km) gradient zones, so as to analyze the characteristics of changes in land use and landscape patterns along sea–land gradient. Our results showed that significant differences in the distribution and area changes of land use types across the gradient zones. Cropland increased only within the 0–5 km gradient zone, while decreasing in all other zones, generally showing a greater decrease farther from the sea. The dominant feature of land use transformation in Jiangsu’s coastal area over the past 30 years has been the conversion of cropland to built-up land. Interestingly, the area of land use transfer in the 0–30 km gradient zone shows a decreasing trend, while the area of land use transfer in the 30–60 km gradient zone shows an increasing trend. Overall, proximity to the sea correlates with higher land use dynamics, especially within the 0–5 km gradient zone. Additionally, sea–land gradient significantly affects landscape patterns, leading to increased fragmentation across most gradient zones from 1990 to 2020. This study findings will furnish critical decision-making support for advancing ecological preservation and sustainable land utilization strategies specific to the Jiangsu coastal region, while also serving as a valuable reference for effectively managing analogous coastal areas globally.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"176 ","pages":"Article 113635"},"PeriodicalIF":7.0,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144105835","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":"Advancing sustainable development in large lake basins: A static–dynamic integrated management framework for ecosystem service supply–demand matching","authors":"Suwen Xiong,&nbsp;Fan Yang","doi":"10.1016/j.ecolind.2025.113611","DOIUrl":"10.1016/j.ecolind.2025.113611","url":null,"abstract":"<div><div>Rising human activity has intensified pressure on ecological resources, disrupting the ecosystem service supply–demand (ESSD) balance. Compared to other ecological habitats, large lake basins contain sensitive water–land interlaced systems, posing significant challenges for multiscale sustainable management. This study uses the Dongting Lake Basin as a case to examine six ecosystem services (ESs): water yield (WY), food production (FP), carbon sequestration (CS), soil retention (SR), habitat quality (HQ), and leisure entertainment (LE). Integrating spatial autocorrelation analysis and ecosystem service supply–demand ratio (ESSDR), we identified the spatiotemporal mismatch patterns of ecosystem service supply (ESS) and ecosystem service demand (ESD). Subsequently, we developed a sustainable management framework based on the static mean ESSDR and dynamic change rate indices. Results show that from 2000 to 2020, FP, CS, HQ, and LE supplies declined, whereas WY and SR supplies increased. CS, SR, LE, and HQ demand rose, whereas WY and FP demand decreased. ESS–ESD’s clustering relationships were dominated by H–L and L–H mismatch zones. The ESSD mismatch degree has intensified over time. ES surplus zones (SI) were mainly in forested areas at sub-basin edges, whereas ES deficit zones (SII) overlapped with northern croplands and eastern construction areas. Dynamic evolution analysis indicated sustainable zones (S) clustering in northern sub-basins, whereas unsustainable zones (US) dominated the Southern Xiangjiang Basin. ESS–ESD management zones exhibited marked heterogeneity across sub-basins. SII-US zones in the Northern Xiangjiang River Basin should restrict excessive urbanization. SII-S zones in the Dongting Lake Ring Area should promote sustainable agriculture. SI-S zones in the Lishui, Zishui, and Northern Yuanjiang River Basins can expand eco-economic projects. SI-US zones in the Southern Yuanjiang and Xiangjiang River Basins must advance green industry upgrades. The static–dynamic ESSD management framework offers transferable technical guidance for sustainable governance in other lake basins.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"176 ","pages":"Article 113611"},"PeriodicalIF":7.0,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144105984","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":"Unraveling the impact of national strategy on urban blue-green space and growth dynamics: A spatiotemporal analysis in Beijing-Tianjin-Hebei (BTH) region","authors":"Lifan Zhang ,&nbsp;Yanling Zhao ,&nbsp;Tingting He ,&nbsp;He Ren ,&nbsp;Huanyu Chang ,&nbsp;Zixiang Dou ,&nbsp;Shaoqing Wang ,&nbsp;Zhibin Li","doi":"10.1016/j.ecolind.2025.113627","DOIUrl":"10.1016/j.ecolind.2025.113627","url":null,"abstract":"<div><div>Urban blue-green spaces (UBGS) play a vital role in providing ecological services and enhancing human well-being in high-density cities. In this study, the spatiotemporal dynamics and drivers of UBGS in the Beijing-Tianjin-Hebei (BTH) region, a key economic and ecological hub in China, were examined using Landsat satellite data from 2010 to 2023 to analyze UBGS changes within urban areas. Subsequently, the relationship between UBGS changes and economic and population growth were assessed. Our results reveal a general increase in Urban Green Spaces (UGS) and Urban Blue Spaces (UBS) across BTH cities, with significant UGS quality improvements, especially in Beijing, Shijiazhuang, and Tianjin. Here, over 25% of the area experienced a significant increase in NDVI (Normalized Difference Vegetation Index) values, reflecting improved vegetation health. Landscape pattern analysis indicated UGS became more contiguous, with increased connectivity and structural integrity, as the aggregation index rose by 6.7% and the largest patch index by 239.2%. The BTH Coordinated Development strategy has helped reduce population pressures, supporting economic and environmental balance. Our findings offer valuable insights into sustainable urban development and UBGS conservation, relevant for urbanizing regions worldwide.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"176 ","pages":"Article 113627"},"PeriodicalIF":7.0,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144098924","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":"Urbanization’s Role in shrinking greenness Gradients: Core area vegetation Growth and convergence of Rural-Urban Green coverage in 766 Chinese cities using seven indicators","authors":"Qikang Zhong,&nbsp;Zhe Li","doi":"10.1016/j.ecolind.2025.113628","DOIUrl":"10.1016/j.ecolind.2025.113628","url":null,"abstract":"<div><div>Urbanization significantly alters vegetation greenness, yet the spatial and temporal dynamics of this change, especially in core urban areas versus rural zones, remain underexplored. This study evaluates the impact of urbanization on vegetation greenness across 766 cities in China from 2000 to 2022, using seven distinct indicators, including three newly proposed ones. Satellite-based vegetation indices, Enhanced Vegetation Index (EVI) and Normalized Difference Vegetation Index (NDVI), are used to quantify shifts in vegetation coverage, focusing on the greenness gradients from urban cores to rural areas. The results reveal a shrinking greenness gradient due to urbanization, with significant increases in vegetation coverage in urban core areas. Specifically, ΔVI (urban VI minus rural VI) decreased by 9.6 % (p &lt; 0.05), indicating a convergence of vegetation greenness between urban and rural areas. Meanwhile, the proportion of urban VI relative to rural VI (PVI) showed no significant trend across cities (p &gt; 0.05), but exhibited a notable increase of 15.3 % in urban core areas, suggesting a positive urbanization impact on greenness in these regions. Spatial trends showed that 73.5 % of urban areas exhibited increasing EVI values, compared to 90.6 % in rural areas. The percentage increase in EVI during the study period was 34.0 % in urban core areas, compared to 20.9 % in urban areas and 21.4 % in rural zones. This study’s novel use of seven distinct indicators offers a comprehensive evaluation of urbanization’s impact on vegetation greenness, providing valuable insights for sustainable urban planning and environmental management.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"176 ","pages":"Article 113628"},"PeriodicalIF":7.0,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144105836","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 the monthly contribution of drivers on European summer wildfires with explainable artificial intelligence (XAI)","authors":"Hanyu Li ,&nbsp;Stenka Vulova ,&nbsp;Alby Duarte Rocha ,&nbsp;Birgit Kleinschmit","doi":"10.1016/j.ecolind.2025.113605","DOIUrl":"10.1016/j.ecolind.2025.113605","url":null,"abstract":"<div><div>As climate change continues, wildfires are becoming more frequent, posing significant challenges to both society and ecosystems. The time-lagged effects of wildfire drivers make them difficult to quantify, and a comprehensive understanding of how preceding weather and vegetation conditions influence wildfire risk across Europe is still lacking. In this study, we focus on summer wildfires in European forests, shrubs, and herbaceous vegetation areas from 2014 to 2023. Using the long short-term memory (LSTM) method, we developed a reliable model with an Area Under the ROC Curve of 0.928, incorporating 18 indicators related to burned areas, meteorology, vegetation, topography, and human activity. We then used SHapley Additive exPlanations (SHAP), an Explainable Artificial Intelligence method, to interpret the model and obtain the contribution of drivers in the 11 months preceding wildfire events. The results indicate that the four main contributors are the condition indices of Land Surface Temperature, Solar Radiation, and Soil Moisture, along with NDVI. Wildfire severity in summertime is most strongly tied to current-season drivers, with the winter-to-spring transition as the next key period. Wildfire risk in the Mediterranean is the highest among biogeographic regions, with the relatively high contribution of drivers to August wildfires emerging as early as spring. For wildfires caused by the cumulative effects, early monitoring of SHAP values can provide effective warnings. Our study provides a new method for quantitative analysis of the time-lag effects of wildfire drivers, which will help to better understand the mechanisms of wildfire occurrence and enhance prevention and mitigation.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"176 ","pages":"Article 113605"},"PeriodicalIF":7.0,"publicationDate":"2025-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144098923","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":"Health risk assessment of heavy metals based on source analysis and Monte Carlo in the Lijiang River Basin, China","authors":"Wanjun Zhang ,&nbsp;Cunlin Xin ,&nbsp;Wenyue Du ,&nbsp;Shi Yu","doi":"10.1016/j.ecolind.2025.113620","DOIUrl":"10.1016/j.ecolind.2025.113620","url":null,"abstract":"<div><div>This study investigates the hydrochemical characteristics of surface water in the Lijiang River Basin with complex pollution sources, focusing on tracing the origins and health risks of heavy metals and hydrochemical components. Systematic analysis of 120 surface water samples revealed that the water chemistry predominantly follows the HCO₃-Ca·Mg type, demonstrating the dominant influence of carbonate rock weathering in the basin. Source analysis using the Positive Matrix Factorization (PMF) model indicated dual contamination drivers from natural geological processes and anthropogenic activities, with industrial and agricultural inputs being the most significant contributors. The Comprehensive Environmental Water Quality Index (CEWQI) ranged from 36.14 to 79.62, suggesting that the overall water quality in the study area is good. High-quality water is generally located in the upper and middle reaches of the basin, while the downstream water quality is comparatively poorer. Major pollutants identified include Cd, Fe, Mn, Cu, Al, Hg, and NO₃⁻, based on entropy weight coefficients and standard limits. Monte Carlo risk assessments indicate that Al poses non-carcinogenic risks to both adults and children, whereas Cd presents non-carcinogenic risks specifically to children and significant carcinogenic risks to all populations. Source analysis demonstrated that non-carcinogenic risks predominantly originate from agricultural non-point source pollution, whereas carcinogenic risks correlate closely with endogenous sediment release. These findings provide scientific foundations for targeted water pollution management in river basins, strengthening agricultural surface source control and sediment management is important for safeguarding the health of the population and promoting sustainable regional development.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"176 ","pages":"Article 113620"},"PeriodicalIF":7.0,"publicationDate":"2025-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144090564","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":"A study on land use change simulation based on PLUS model and the U-net structure: A case study of Jilin Province","authors":"Jiafu Liu,&nbsp;Xiangli Kong,&nbsp;Yue Zhu,&nbsp;Baihao Zhang","doi":"10.1016/j.ecolind.2025.113619","DOIUrl":"10.1016/j.ecolind.2025.113619","url":null,"abstract":"<div><div>Deep learning and spatial models are typical paradigms for land cover change simulation, each exhibiting certain differences in representing land use change mechanisms. This study investigates land use changes in Jilin Province from 2000 to 2020, independently constructing land cover change simulation frameworks using the PLUS model and U-Net neural network, and simulates land use for the year 2030. The simulation differences were quantified through spatial consistency analysis. By comparing the performance of the two methods in land use change prediction, this study reveals the divergent characteristics of the two approaches in capturing complex transformation patterns. The findings indicate that: 1) Cross-validation based on actual 2020 land use data shows that the overall Kappa index for the PLUS model and U-Net neural network are 0.802 and 0.810, respectively, with spatial consistency values of 87.88 % and 88.99 %, and the MSE value for U-Net is 0.43. These results demonstrate that both models possess reliable simulation performance. 2) The two methods exhibit significant differences in predictive performance. The U-Net model, which utilizes convolutional neural networks to extract multi-scale spatial features and addresses the class imbalance issue with the OHEM-Dice composite function, significantly enhances the prediction accuracy of nonlinear dynamics. It is more sensitive to short-term land use changes, but its generalization ability is constrained by sample size and balance. The PLUS model, on the other hand, is more suited for long-term trend prediction and shows significant advantages in simulating land types with fewer pixels, particularly maintaining high stability even under conditions of missing data or sample imbalance. 3) In terms of land use transformation patterns, the PLUS model primarily predicts unidirectional transformations. Arable land transitions to construction land and forest land by 326.73 km² and 301.82 km², respectively, while wetland transitions to forest land by 0.28 km², reflecting an orderly transformation driven by policies. Conversely, the U-Net model predicts more complex bidirectional flow features, with arable land transitioning to construction land and forest land by 396.43 km² and 498.06 km², respectively, and significant bidirectional transformations between arable land and grassland. This suggests that deep learning can capture nonlinear coupling processes of “human decisions-ecological responses” that traditional models struggle to quantify, providing a new approach for land sustainability assessment.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"176 ","pages":"Article 113619"},"PeriodicalIF":7.0,"publicationDate":"2025-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144090563","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":"Impacts of human footprint on habitat quality and permafrost environment in Northeast China","authors":"Jianjun Tang ,&nbsp;Xiaoying Jin ,&nbsp;Haowei Mu ,&nbsp;Sizhong Yang ,&nbsp;Ruixia He ,&nbsp;Xiaoying Li ,&nbsp;Wenhui Wang ,&nbsp;Shuai Huang ,&nbsp;Jiaxing Zu ,&nbsp;Hongwei Wang ,&nbsp;Zuwang Li ,&nbsp;Lin Yang ,&nbsp;Shanzhen Li ,&nbsp;Yanlin Shi ,&nbsp;Suiqiao Yang ,&nbsp;Raul-D. Serban ,&nbsp;Mihaela Șerban ,&nbsp;Alexander Fedorov ,&nbsp;Leonid Gagarin ,&nbsp;Ze Zhang ,&nbsp;Huijun Jin","doi":"10.1016/j.ecolind.2025.113587","DOIUrl":"10.1016/j.ecolind.2025.113587","url":null,"abstract":"<div><div>In Northeast China, intensified human footprints have greatly altered ecosystem service functions, leading to biodiversity decline, habitat fragmentation, and permafrost warming and thaw. For regional ecological security, it is crucial to conduct a detailed investigation of how human footprints affect the ecological environment and ground temperatures over the long-term. This study examines spatiotemporal characteristics of human footprints, habitat quality (HQ), and permafrost distribution in Northeast China using human footprint data, the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model, and GeoDetector model. The following results were obtained. (1) Between 2000 and 2020, human footprint of Northeast China experienced four growth stages with an overall growth rate of 54.2 %, with the most rapid growth between 2010 and 2015. Built environment and nighttime lights (NTL) significantly contributed to human footprint, while cropland had a relatively low contribution at only 1.3 %. (2) In Northeast China, total HQ decreased by 14.5 %, although high habitat degradation level increased by 2.5 %. The areal extent of high-level HQ patches declined by 12.2 % with rising human footprint index, and the proportion of low- and lower-quality habitats increased significantly. (3) Between 2000 and 2018, mean annual ground temperature in Northeast China increased by 0.15 °C, reflecting significant permafrost degradation and an average annual increase rate of 0.063 °C. During this period, permafrost area decreased by 0.9 × 10⁵ km², and the southern limit of latitudinal permafrost also shifted northward. (4) Waterways and roads are the main drivers of rising ground temperatures, with waterways having the highest q-value (0.56). The interactions between paired impacting factors also indicate that the highest q-value (0.71) for the intersections of waterways and roads. These research results may contribute to a better understanding of the relationships among human footprint, ecological environment, and ground temperatures in Northeast China, and help provide a basis for ecological conservation.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"175 ","pages":"Article 113587"},"PeriodicalIF":7.0,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144084557","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":"Metaweb approach to unravel food web structures: Exploring environmental changes and biotic interactions in Korean stream ecosystems","authors":"Da-Yeong Lee ,&nbsp;Sagar Adhurya ,&nbsp;Dae-Seong Lee ,&nbsp;Young-Seuk Park","doi":"10.1016/j.ecolind.2025.113599","DOIUrl":"10.1016/j.ecolind.2025.113599","url":null,"abstract":"<div><div>Understanding food webs is crucial for grasping ecosystem functions and energy flows. However, the inherent complexity and variability of food web structures pose significant challenges to community ecology. The concept of a metaweb is key to overcoming these challenges. Metawebs enable the construction of food webs using biomonitoring data, and provide a comprehensive analysis of ecosystem interactions. Using network theory and food web metrics, we (1) applied metaweb approaches to construct and compare local food webs across multiple study sites, offering a holistic perspective on regional ecosystem dynamics; (2) examined the impacts of environmental changes on food web structures to identify patterns indicative of ecosystem status; and (3) evaluated the influence of habitat heterogeneity on food web configuration. Local food webs were constructed using the KF-metaweb and biomonitoring data from Korean streams, and food web structure metrics were subsequently calculated. Hierarchical cluster analysis of 255 local food webs, based on similarities in food web metrics, revealed five distinct clusters. Non-metric multidimensional scaling illustrated the relationships among food web metrics, environmental variables, and biological indices. The structural patterns of local food webs are associated with water quality, land use type, temperature, and stream magnitude. The responses of food web structures to environmental factors varied both in general trends and across clusters, highlighting the role of habitat heterogeneity in shaping food web responses. Certain food web metrics exhibit limited explanatory power regarding ecosystem status. This study provides a basis for future research by enabling cross-site comparisons using a metaweb framework, thereby advancing our understanding of ecological interactions and ecosystem dynamics.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"175 ","pages":"Article 113599"},"PeriodicalIF":7.0,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144084639","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}