Ecological Indicators最新文献

{"title":"Assessment of urban flood resilience and obstacle factors identification: A case study of three major urban agglomerations in China","authors":"Yi Xiao ,&nbsp;Xi Rao ,&nbsp;Ming Chang ,&nbsp;Liang Chen ,&nbsp;Huan Huang","doi":"10.1016/j.ecolind.2025.113659","DOIUrl":"10.1016/j.ecolind.2025.113659","url":null,"abstract":"<div><div>Urban flooding has emerged as a structural challenge that hinders the resilient transformation of cities in the context of intensifying global climate change and frequent extreme weather events. However, comprehensive and systematic comparative analyses at the urban agglomeration scale are relatively scarce. To address this gap, this study developed a multidimensional evaluation framework (EEISI) that integrates economic, ecological, infrastructural, social, and institutional resilience. Based on the CRITIC-TOPSIS weighted evaluation model and the Coupling Coordination Degree (CCD) model, this study measures urban flood resilience and the interactions among resilience subsystems in China’s three major urban agglomerations. Furthermore, this study employs the Standard Deviational Ellipse (SDE) model to explore their spatial–temporal evolution patterns and identify key constraints to resilience enhancement through an obstacle degree model. Key findings indicate: (1) UFR exhibits phased fluctuations with an upward trend, yet significant developmental disparities persist between core and peripheral cities, with the Pearl River Delta demonstrates systemic advantages through subsystem optimization; (2) Subsystem coordination has gradually improved but remains at a primary coordination level, reflecting imperfect cross-system governance mechanisms; (3) Structural fiscal allocation imbalances and fragmented institutional supply constitute the primary obstacles, manifested in constraints such as governmental governance capacity, municipal maintenance funding, and the adequacy of the social security system; This study enriches and refines the existing research indicator system, providing theoretical references for flood resilience capacity building and the practice of resilient city development in urban agglomerations.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"176 ","pages":"Article 113659"},"PeriodicalIF":7.0,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144154787","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 new method of three-dimensional green volume retrieval and its applications in urban greenery evaluation","authors":"Zehu Hong ,&nbsp;Yun Liu ,&nbsp;Weiheng Xu ,&nbsp;Leiguang Wang ,&nbsp;Ning Lu ,&nbsp;Guanglong Ou ,&nbsp;Weili Kou","doi":"10.1016/j.ecolind.2025.113629","DOIUrl":"10.1016/j.ecolind.2025.113629","url":null,"abstract":"<div><div>Urban greening benefits plays a crucial role in promoting public health and aligns with regional development strategies. Three-Dimensional Green Volume (3DGV) has emerged as a precise metric for evaluating greening benefits, yet its large-scale application remains limited. This study developed a satellite-derived 3DGV retrieval model using multi-source remote sensing data to assess urban greenery in central Yunnan, China. Field measurements were collected to establish UAV-derived 3DGV retrieval models, integrating Canopy Height Model (CHM), Leaf Area Index (LAI), and Fractional Vegetation Cover (FVC) from RGB images. We established a power regression model in large scale retrieval linking these UAV-derived parameters to Sentinel-1 and Sentinel-2 images, achieving strong performance (R² = 0.72; RMSE = 139.71 m³/pixel; AE = 120.69 m³/pixel; MAE = 10.54 %). Spatial analysis was used to revealed the distribution of retrieved 3DGV, and it showed a pronounced west-to-east gradient (Moran’s I = 0.772) and an obviously increase trend from 2018 to 2022. This study demonstrated that Sentinel-1 and Sentinel-2 images enable accurate large-scale 3DGV mapping and reveal 3DGV dynamics to evaluate the greening benefits, providing a feasible and effectiveness approach for sustainable urban greenery evaluation and ecological management.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"176 ","pages":"Article 113629"},"PeriodicalIF":7.0,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144154558","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":"Tree density has been underestimated in the mountainous regions of Northeast China","authors":"Yunkun Song ,&nbsp;Wenqiang Xie ,&nbsp;Fang Wu ,&nbsp;Xuefeng Cui ,&nbsp;Xiaodong Yan ,&nbsp;Shuaifeng Song ,&nbsp;Jun Ren ,&nbsp;Hui Bai ,&nbsp;Yu Zhang ,&nbsp;Wei Pang ,&nbsp;Yueying Xiao ,&nbsp;Wang Zhan","doi":"10.1016/j.ecolind.2025.113655","DOIUrl":"10.1016/j.ecolind.2025.113655","url":null,"abstract":"<div><div>Previous attempts to quantify tree density have often underestimated the numbers of trees in mountainous regions with complex terrain. We surveyed trees with a diameter at breast height (DBH) of ≥10 cm across 1,926 plots. By utilizing recursive feature elimination (RFE), we identified six key variables for our <em>meta</em>-learner in the stacking process, including the soil silt content, soil clay content, elevation, Normalized Difference Vegetation Index (NDVI), precipitation in the wettest month, and precipitation in the coldest quarter, all of which were found to influence tree density. We developed a stacking ensemble learning algorithm, which ultimately generated a tree density map with a spatial resolution of 30 m for the mountainous regions of Northeast China. The estimated tree count is approximately 27.497 billion. Compared to global tree density datasets, our approach increased R² to 0.454, while root<!--> <!-->mean<!--> <!-->square<!--> <!-->error (RMSE) and bias improved by 47.90 % and 74.52 %, respectively. This approach can increase the accuracy of local tree density simulations, which is crucial for the precise modeling of the forest carbon sequestration potential, the development of targeted forest conservation strategies, and the implementation of effective carbon management practices.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"176 ","pages":"Article 113655"},"PeriodicalIF":7.0,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144154557","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":"Increases in forest carbon stocks of up to 32% by 2100 across the subalpine forests of the Tibetan Plateau","authors":"Ting Li ,&nbsp;Qi Wang ,&nbsp;Huan Wang ,&nbsp;Jicheng Wang ,&nbsp;Xiaorui Li ,&nbsp;Zhanmang Liao ,&nbsp;Peng Luo ,&nbsp;Changhong Lai ,&nbsp;Yang Liu ,&nbsp;Yi Jian","doi":"10.1016/j.ecolind.2025.113675","DOIUrl":"10.1016/j.ecolind.2025.113675","url":null,"abstract":"<div><div>Forest carbon stocks dynamics, influenced by forest migration, growth, and mortality under climate change, remain insufficiently understood, particularly regarding their extent, timing, and geographic distribution. We studied data from 1,248 forest plots on the Tibetan Plateau to understand how forest carbon dynamics respond to climate and forest age and to predict future changes under different climate scenarios. Our findings suggest that forest carbon stocks in the eastern mountains of the Tibetan Plateau could increase by up to 32 % by 2100, reaching saturation as growth fluxes declines over time. However, growth fluxes offset the increase in mortality fluxes, which mitigates carbon losses. We also predicted that the carbon stocks distribution center will shift northwestward by 0.23 km/year and upslope by 0.25 m/year. The distribution of growth and mortality fluxes varies geographically. Regions with higher forest growth fluxes, particularly along the southern and northern edges and in transition zones, will experience faster precipitation migration. In contrast, areas on the northwestern edge and at lower altitudes, where temperature migration is faster, face elevated forest mortality risks. These results highlight the need for ecological compensation to mitigate increased mortality-related carbon and ensure sustainable forest management.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"176 ","pages":"Article 113675"},"PeriodicalIF":7.0,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144154559","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":"Maintaining rockfall protection in mountain forests under climate change: optimizing management for sustainable stem size distributions","authors":"Ulrike Hiltner ,&nbsp;Jonas Glatthorn ,&nbsp;Timothy Thrippleton ,&nbsp;Harald Bugmann","doi":"10.1016/j.ecolind.2025.113634","DOIUrl":"10.1016/j.ecolind.2025.113634","url":null,"abstract":"<div><div>Climate change threatens the long-term effectiveness of mountain forests, which provide crucial protection against rockfall. Maintaining this protection function requires a sustainable stem size distribution, yet how to adapt forest management for this purpose remains unclear. This study uses a simulation-based optimization approach, integrating the dynamic forest model ForClim with the Simulated Annealing optimization algorithm, to identify adaptive management strategies for Swiss forests. We first established sustainable stem size distributions for managed protection forests in four elevation zones − lower montane to subalpine − under historical climate, leading to a so-called target profile. These represent a novel indicator enabling foresters to tailor silvicultural interventions towards improving rockfall protection. Subsequently, we assessed climate change impacts on these distributions. Our simulations show that climate change will alter stem size distributions, particularly at higher elevations where a reduction of soil water availability will hinder regeneration and growth. This leads to fewer trees, especially smaller ones. We developed optimized management regimes to counteract this effect, recommending specific adjustments depending on elevation zone and management type, such as less frequent and less intensive harvesting with larger minimum removal DBH in higher-elevation mountain forest plentering, and adjustments to target DBH and harvest intensity in lower-elevation plentering. This study demonstrates that adapting silvicultural interventions can preserve the desired forest structure under climate change, without fundamental regime shifts. These findings provide practical guidance for forest managers, enabling them to proactively respond to climate change impacts and ensure the long-term functionality of rockfall protection across elevation zones.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"176 ","pages":"Article 113634"},"PeriodicalIF":7.0,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144137843","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":"Optimal time-window for assessing soil salinity via Sentinel-2 multitemporal synthetic data in the arid agricultural regions of China","authors":"Ju Xiong ,&nbsp;Xiangyu Ge ,&nbsp;Jianli Ding ,&nbsp;Jinjie Wang ,&nbsp;Zipeng Zhang ,&nbsp;Chuanmei Zhu ,&nbsp;Lijing Han ,&nbsp;Jingzhe Wang","doi":"10.1016/j.ecolind.2025.113642","DOIUrl":"10.1016/j.ecolind.2025.113642","url":null,"abstract":"<div><div>Soil salinity is a critical issue affecting agricultural productivity in arid regions. Remote sensing is an effective tool for assessing and monitoring soil salinity to enable precision soil care. However, obtaining bare-soil information from agriculturally active regions remains challenging. Therefore, this study aimd to identify the optimal temporal window for assessing soil salinity. We developed three different time-synthesis strategies based on Sentinel-2 time-series images (1-month synthetic, 2-month synthetic, and seasonal synthetic image) through median and mean syntheses. We constructed estimation models (including random forest (RF) and gradient tree boosting (GTB)) using band and spectral indices information from synthetic images in the Google Earth Engine (GEE) platform. Additionally, we compared the results of different modeling strategies and assessed the uncertainty in soil salinity mapping. The results showed the optimal time-window for assessing soil salinization was the images synthesized in summer (June-August) (R²: 0.41–0.45), which was approximately 36.51% higher than that during the bare soil period (March-April). Assessment models constructed from summer synthetic imagery had a low uncertainty in soil salinity mapping. The median-based synthesis approach was the most effective, compared to the mean-based synthesis approach with an R² of 0.45 (RF validation mean). The six spectral indices including EVI, GYEX, TBI, GARI, NDSI, and NDVI proved more important in the estimation model than the original Sentinel-2 bands. Moreover, the red band (band 4) and short-wave infrared band (band 12) in the summer synthetic spectra exhibited the strongest correlation with soil salinity, with Pearson correlation coefficient of 0.56 for both. Our findings indicate that summer was the optimal period for assessing soil salinization in the arid agricultural regions of China. This study employs temporal synthesis techniques to accurately identify the specific “period” most closely correlated with ground-measured soil salinity (optimal time-window), offering a practical and efficient alternative strategy for precise salinization inversion in regions where remote-sensing data are scarce.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"176 ","pages":"Article 113642"},"PeriodicalIF":7.0,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144137844","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":"Spatio-temporal variation and influencing factors of carbon emissions from land use change in Xilingol region of Inner Mongolia, China","authors":"Anting Du ,&nbsp;Siqin Tong ,&nbsp;Jinyuan Ren ,&nbsp;Gang Bao ,&nbsp;Xiaojun Huang ,&nbsp;Yuhai Bao ,&nbsp;Dorjsuren Altantuya ,&nbsp;Chunlan Li","doi":"10.1016/j.ecolind.2025.113633","DOIUrl":"10.1016/j.ecolind.2025.113633","url":null,"abstract":"<div><div>Land use carbon emissions (LUCE) play a critical role in sustainable regional development. As a key coal production base and ecological barrier in northern China, the Xilingol League faces pressing challenges in balancing LUCE with sustainability objectives. However, substantial knowledge gaps remain regarding spatiotemporal dynamics and driving mechanisms of LUCE in mining-grassland transition zones. This study integrated multi-temporal remote sensing data (1990–2020, 30 m resolution) with socioeconomic statistics and applied the Hasse Diagram Technique (HDT) to analyze carbon emission drivers in this ecologically fragile region. The results yielded three key findings: (1) built-up areas expanded by 2.4 times, becoming the dominant carbon source, while the high- and moderate-coverage grasslands declined significantly; (2) LUCE exhibited the distinct spatiotemporal patterns, remaining stable and low from 1990 to 2000 but increasing rapidly from 2000 to 2020, with the spatial distribution demonstrating the “east-high, west-low; south-high, and north-low” pattern and the emissions consistently concentrated in or near Xilinhot City; and (3) the influence of drivers shifted over time, with the biological disturbances becoming increasingly prominent, while the impacts of urbanization, industrialization, and economic factors declined after 2000. This study offers practical insights into LUCE dynamics in the Xilingol League and provides scientific support for the development of regional carbon reduction and ecological conservation policies.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"176 ","pages":"Article 113633"},"PeriodicalIF":7.0,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144137842","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":"Actual evapotranspiration dominated net primary productivity loss caused by concurrent droughts","authors":"Zice Ma ,&nbsp;Donghua Chen ,&nbsp;Peng Sun ,&nbsp;Yufeng Liu ,&nbsp;Lizao Ye","doi":"10.1016/j.ecolind.2025.113645","DOIUrl":"10.1016/j.ecolind.2025.113645","url":null,"abstract":"<div><div>Drought profoundly affects terrestrial ecosystem (TE) carbon cycling, but the impact of concurrent droughts (CDs) remains poorly understood. Using Net Primary Productivity (NPP), Standardized Precipitation Evapotranspiration Index (SPEI), Standardized Soil Moisture Index (SSMI), and Standardized Concurrent Drought Index (SCDI) (1982–2022), we analyzed trends and quantified drought impacts on global NPP loss. Our study further quantified the effects of three drought categories on global NPP loss. The findings suggest that NPP has generally decreased across the southern hemisphere, particularly in subtropical Evergreen Broadleaf Forest (EBF) ecosystems (−3.14 gC m⁻² yr⁻¹). Zones exhibiting a noticeable decline in NPP often correspond with a decrease in both SPEI and SSMI, leading to an upward trend where 32.4 % of TE experience CDs. Further analysis revealed that CDs have dominated NPP changes in approximately 48.5 % of the global ecosystem. This contributes to an average NPP loss of approximately 15.03 gC m⁻² yr⁻¹ in global TE. Random Forest experiments identified ET as the dominant hydrothermic factor of NPP loss under CDs, particularly in forest ecosystems where the importance scores range from 23.0 % to 37.0 %. Our findings underscore the significance of ET anomalies in NPP loss resulting from CDs, providing scientific evidence for addressing ecological risks under climate change.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"176 ","pages":"Article 113645"},"PeriodicalIF":7.0,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144137845","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 dynamics in a 450-year-old natural landslide-dammed valley farmland: Insights into precipitation responses","authors":"Zhao Jin ,&nbsp;Huifeng Wu ,&nbsp;Hao Han ,&nbsp;Yunchong Fu ,&nbsp;Jing Zhang ,&nbsp;Guofan Cao ,&nbsp;Keyan Xu","doi":"10.1016/j.ecolind.2025.113661","DOIUrl":"10.1016/j.ecolind.2025.113661","url":null,"abstract":"<div><div>Tens of thousands of sediment check dams have historically played vital ecological functions in China’s Loess Plateau, and dammed valley farmland has been a significant agricultural resource for centuries. However, newly created valley farmlands under the “Gully Land Consolidation” project often face lower arable quality and frequent soil salinization compared to their natural counterparts. To draw insights from natural dammed valley farmland, we selected the 450-year-old Huangtuwa natural landslide-dammed valley farmland (NLDF) for high-frequency, long-term monitoring and analysis of soil water content and precipitation during 2019–2020 and used the HYDRUS-1D model to assess its water storage capabilities. The results indicate that the soils from 0–100 cm can be clearly categorized into three groups: the rapid response layer (0–40 cm), which reacts quickly to rainfall; the water transport and emergency reservoir layer (∼60 cm), characterized by lower water content that fluctuates rapidly during extreme rainfall, functioning as both a reservoir and drainage pathway; and the stable water supply layer (∼100 cm), with the most stable water content (16.6 %, SD: 1.2 %), crucial for fertility and cultivation. Based on HYDRUS-1D model calculations, the soil water storage of NLDF remained stable under low precipitation but showed a sharp rise and decline when precipitation exceeded 9.8 mm. We employed a random forest model to assess the factors influencing the soil layers’ response rates to rainfall and their soil moisture expansion potential during extreme rainfall events. The results emphasized that soil total nitrogen, organic carbon, and pH were more influential than physical properties, highlighting the significant interaction between soil moisture and nutrients and the potential important influence of vegetation on water movement in NLDF. Overall, NLDF’s sustained arability is attributed to its multi-dimensional, synergistic ecological layout. New dammed valley farmland should replicate NLDF’s structure by pre-establishing vertical soil layer distribution during landform reshaping and adopting a synergistic ecological layout that integrates vegetation, soil, and precipitation.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"176 ","pages":"Article 113661"},"PeriodicalIF":7.0,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144154550","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":"Species distribution model performance improves when habitat characterizations are centered on detected individuals instead of observers","authors":"Fang-Yu Shen ,&nbsp;Fiona Victoria Stanley Jothiraj ,&nbsp;Rebecca A. Hutchinson ,&nbsp;Tyler A. Hallman ,&nbsp;Jenna R. Curtis ,&nbsp;W. Douglas Robinson","doi":"10.1016/j.ecolind.2025.113546","DOIUrl":"10.1016/j.ecolind.2025.113546","url":null,"abstract":"<div><div>Species distribution models (SDMs) link species occurrence to environmental characteristics to predict suitable habitats beyond known occurrences. The conventional procedure to fit SDMs for individual organisms detected at some distance away from observers is to characterize species’ associated habitat based on observer’s survey location. However, each surveyed individual may be detected in habitats distinct from those where observers are located. Here, we compared environmental variables centered on the observer and individual bird locations and the consequent effects on SDMs performance. We utilized remote sensing data on observer- and bird-locations to characterize habitat at three radii (pixel radius: 30-m; fixed radius: 100-m; species-specific effective detection radius). We trained Poisson boosted regression tree models for 105 bird species from structured professional surveys. We evaluated models’ predictability with Kendall’s rank correlation coefficient and used linear mixed-effect models to measure the effect of characterization locations and radii. Models based on bird locations exhibited a median increase of 22.9% in predictive performance, demonstrating higher Kendall’s rank correlation coefficients than those based on observer locations, leading to more reliable prediction maps. SDMs of habitat specialists and generalists performed better when habitat characterization was centered on bird instead of surveyor locations. A higher percentage of habitat specialists (72%) than generalists (55%) showed better model performance in bird-location than in observer-location models. Across radii, fixed radius generally performed better than species-specific effective and pixel radii. Our findings emphasize the importance of prioritizing habitat characterizations based on detected individuals’ locations to enhance model performance and improve species distribution predictions.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"176 ","pages":"Article 113546"},"PeriodicalIF":7.0,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144138320","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}