Ecological Indicators最新文献

{"title":"Ecological risk assessment and source identification of heavy metals in the sediments of the Danjiang River Basin: A quantitative method combining multivariate analysis and the APCS-MLR model","authors":"Zhiming Cao ,&nbsp;Hui Qian ,&nbsp;Yanyan Gao ,&nbsp;Kang Li ,&nbsp;Yixin Liu ,&nbsp;Xiaoxin Shi ,&nbsp;Siqi Li ,&nbsp;Weijie Zhao ,&nbsp;Shuhan Yang ,&nbsp;Panpan Tian ,&nbsp;Puxia Wu ,&nbsp;Yandong Ma","doi":"10.1016/j.ecolind.2025.113518","DOIUrl":"10.1016/j.ecolind.2025.113518","url":null,"abstract":"<div><div>The heavy metal content in river sediment is a sensitive indicator of pollution in aquatic ecosystems and plays a key role in understanding the risks, characteristics, and sources of heavy metal pollution in a region. This study combined traditional assessment methods with the Nemerow integrated risk index (NIRI), which is improved based on the potential ecological risk index (RI) and the Nemerow integrated pollution index (NIPI), to evaluate the pollution level of sediment in the Danjiang River. Based on principal component analysis (PCA), the absolute principal component score-multiple linear regression (APCS-MLR) model was employed to analyze the contribution of pollution sources. The study results showed that the average concentrations of most heavy metals exceeded their corresponding background values, and the distribution of heavy metal content was significantly influenced by human activities. The degree of pollution varied among the sampling sites, and the results of NIRI on the spatial distribution and severity of contamination are generally consistent with other assessment indicators, providing a more detailed and comprehensive delineation. The results of the multivariate statistical analysis indicate that Cu, Zn, Pb, and As mainly originated from natural sources, Cd and Ni primarily came from mixed sources such as agriculture and mining, while Cr was mainly associated with industrial activities. The APCS-MLR model results further confirm with high confidence that the sources of heavy metals in the sediments of the study area are complex, predominantly influenced by natural processes such as weathering and erosion. As the water source for the Middle Route of the South-to-North Water Diversion Project, the safety of the Danjiang River’s aquatic ecosystem is crucial for the health of nearly 100 million people in China. These findings provide an important foundation for Danjiang River water resource protection and offer a reference for ecological security and pollution prevention in other rivers.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"175 ","pages":"Article 113518"},"PeriodicalIF":7.0,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143869609","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":"Multivariate geostatistical methods for analysing the contribution of urban lakes and neighbouring greenery to mitigating PM2.5 under stressor indicators","authors":"Han Liu ,&nbsp;Wenyu An ,&nbsp;Arkadiusz Przybysz ,&nbsp;Dingyi Hao ,&nbsp;Yimei Sun ,&nbsp;Junze Song ,&nbsp;Jiayi Sui ,&nbsp;Jiahan Sun ,&nbsp;Chunyang Zhu","doi":"10.1016/j.ecolind.2025.113489","DOIUrl":"10.1016/j.ecolind.2025.113489","url":null,"abstract":"<div><div>Maintaining the ecological integrity and functionality of ecosystems is one of the major challenges faced in the sustainable management of natural capital. Urban areas play a key role in this setting, providing multiple ecosystem services for a rapidly growing urban population worldwide while under constant pressure from several interacting natural and anthropogenic stressors. This paper targets the critical knowledge gap concerning how different stressor indicators – traffic (TD), building density (BD), building height (BH), percentage of impervious surface (PLAND_I) and land surface temperature (LST) – and their interactions affect the removal of particulate matter (PM_2.5) by urban blue-green infrastructure at multiple spatial scales. With spatial ranges varying with the area of blue-green infrastructure, the results showed that within the small-scale spatial range (90–450 m) the stressors LST, TD, PLAND_I and their interactions had a significant impact on PM_2.5; in the mesoscale spatial range (240–600 m), the stressors LST, TD, BH, PLAND_I, BD and their interactions had a strong impact on PM_2.5; while in the large-scale spatial range (390–1200 m), stressors of TD, PLAND_I, LST, BH and their interactions had a significant impact on PM_2.5. Additionally, several spatial structures of PM_2.5-stressor interactions were found, especially with larger lakes (exceeding 67.6 ha), which were dominated by negative correlations, which is singularity attributed to their greater capacity for PM_2.5 accumulation and microclimatic regulation and may mitigate the influence of stress factors. Importantly, this study confirmed that interactive stressors contributed more to the GAM model. Thus, overlooking interactive stressors may lead to an overestimation of PM removal by urban blue-green infrastructure. Regarding the spatial interactions of stressors-PM at multiple scales, spatial range conditions can change the properties of the blue-green infrastructure that determine the effective PM accumulation and identify the crucial stressor indices. A framework was developed to address the stressors’ mode of action and the extent to which the combined stressors affect PM mitigation. It allows the scientific community and relevant stakeholders to evaluate which stressors and their interactions in relation to PM removal share a common spatial pattern, and to assess independently the spatial covariation between stressors and PM removal at different spatial scales. It also demonstrates the possibility of using these stressor indicators as potential predictors of the impacts of land-use intensity on PM mitigation.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"174 ","pages":"Article 113489"},"PeriodicalIF":7.0,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143863718","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":"Climate controls the global distribution of soil organic and inorganic carbon","authors":"Yiheng Huang,&nbsp;Fangli Wei","doi":"10.1016/j.ecolind.2025.113514","DOIUrl":"10.1016/j.ecolind.2025.113514","url":null,"abstract":"<div><div>Soil organic carbon (SOC) and inorganic carbon (SIC) are key components of soil carbon, each playing a distinct role in soil health, carbon cycling, and climate regulation. However, their relative distributions across the global lands remains understudied. Here through analysing two data-driven global estimates of SOC and SIC, we found distinct distributions of SIC and SOC along vertical soil depths, among different land covers, soil orders and climate zones. While the density of SOC is higher in top soils, there are more SIC in deep soils. Vegetation shifts the relative distribution of SIC vs. SOC, with the ratio between SIC and SOC (<span><math><mrow><msub><mi>log</mi><mn>10</mn></msub><mfrac><mrow><mi>SIC</mi></mrow><mrow><mi>SOC</mi></mrow></mfrac></mrow></math></span>) decreasing progressively from bare soils, cropland, grassland to forest. Climate plays a major role in shaping <span><math><mrow><msub><mi>log</mi><mn>10</mn></msub><mfrac><mrow><mi>SIC</mi></mrow><mrow><mi>SOC</mi></mrow></mfrac></mrow></math></span>, accounting for 66 % of variations in top soil (0–0.3 m), 65 % in mid soil (0.3–1 m), and 74 % in deep soil (1–2 m). Higher temperature favours the preservation of SIC compared to SOC, as revealed by the positive relationship between <span><math><mrow><msub><mi>log</mi><mn>10</mn></msub><mfrac><mrow><mi>SIC</mi></mrow><mrow><mi>SOC</mi></mrow></mfrac></mrow></math></span> and MAT. The close link between key climate variables and the distribution of SIC vs. SOC indicates that future climate change is highly likely to alter the composition of soil carbon. Our finding provides support for differentiated soil carbon preservation strategies under different environment.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"175 ","pages":"Article 113514"},"PeriodicalIF":7.0,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143870534","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":"Synergistic security relationships and risk measurement of water resources-social economy-ecological environment in Beijing-Tianjin-Hebei region","authors":"Yue Xu ,&nbsp;Li Yang ,&nbsp;Keyu Sun ,&nbsp;Junqi Zhu","doi":"10.1016/j.ecolind.2025.113512","DOIUrl":"10.1016/j.ecolind.2025.113512","url":null,"abstract":"<div><div>China’s productivity progress has promoted good socio-economic functioning, but has brought serious negative impacts on natural resources and eco-environment. Promoting synergistic security of water resources (W), social economy (S) and ecological environment (E) provides technical support for promoting regional economic growth, social progress and ecological harmony. This study constructed an index system based on stability (S), coordination (C) and resilience (R). Then the entropy weight-CRITIC method, coupled coordination degree model, and obstacle degree model were used to comprehensively evaluate the level of synergistic security of WSE-SCR in the Beijing-Tianjin-Hebei (BTH) region. Finally, the two-dimensional and three-dimensional joint risk probability distributions of different provincial regions were explored by combining the Copula function. The results showed that the level of synergistic security in the BTH region increased from 2006 to 2022, and the multi-year average value was within the security range, specifically Beijing (0.69) &gt; Hebei (0.66) &gt; Tianjin (0.65). The key factors affecting the WSE-SCR are per capita water resources (S1), per capita water consumption (S3), proportion of secondary industry (S5), ecological water use ratio (C4), and investment in infrastructure construction (R8). In terms of two-dimensional joint risk probability, the C-R of Beijing and the S-R of Tianjin and Hebei had the highest probability of security risk, which were 0.5598, 0.5308 and 0.5488, respectively. The three-dimensional joint risk probability of the S-C-R of Beijing, Tianjin and Hebei (S ≤ 0.6, C ≤ 0.6, and R ≤ 0.6) were greater than 30 %, which were 0.389, 0.341 and 0.352, and increased with the increase of single dimension risk. This study can provide scientific information for advancing the synergistic security and sustainable improvement of WSE in arid zones.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"175 ","pages":"Article 113512"},"PeriodicalIF":7.0,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143869608","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":"Analysis of the spatio-temporal characteristics and driving forces of greenness in mega urban agglomerations in China","authors":"Shaoyu Wang ,&nbsp;Dongmei Yan ,&nbsp;Yayang Lu ,&nbsp;Wanrong Wu ,&nbsp;Ying Sun ,&nbsp;Zhe Zhang","doi":"10.1016/j.ecolind.2025.113472","DOIUrl":"10.1016/j.ecolind.2025.113472","url":null,"abstract":"<div><div>Timely monitoring of greenness dynamics in urban agglomerations and analyzing their driving factors are important for sustainable development. However, current research on vegetation greenness at the scale of urban agglomerations remains limited. This study examines the greenness dynamics and its driving factors in China’s four major urban agglomerations Beijing–Tianjin–Hebei (BTH), Yangtze River Delta (YRD), Pearl River Delta (PRD), Chengdu–Chongqing (CC) at a 30-meter spatial resolution over a long period (2000–2023). The use of an innovative integrated approach, combining the Gap Filling and Savitzky–Golay filtering (GF-SG) method, pixel dichotomy model, spatiotemporal dynamic analysis and geographical detector, provides a more comprehensive understanding of greenness dynamics in urban agglomerations. The results indicate several key points: 1.The proportion of areas where vegetation greenness increased (27.69 %, 14.10 %, 31.56 %, 23.09 %) is consistently larger than the proportion of areas where greenness decreased (4.3 %, 6.78 %, 5.11 %, 1.62 %) within BTH, YRD, PRD, CC. Greenness is dramatically increasing in all urban centers, but significantly decreasing at the edges of urban expansion; 2. Land cover conversions emerged as the dominant driver of greenness changes (the highest Q-value is 0.5743), which indicates that land cover conversions play a greater role than natural factors. 3. The expansion of urban land and ecological land restoration explain the main reasons for the decrease and increase in greenness. Meanwhile, there are differences in the primary land cover conversions corresponding to the greenness changes among the four urban agglomerations. These findings not only contribute to understanding urban greenness dynamics but also offer a new perspective on the role of land cover conversions in shaping vegetation patterns.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"174 ","pages":"Article 113472"},"PeriodicalIF":7.0,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143858821","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":"Eutrophication promoted the change of macrophyte community from R strategy to C strategy in Lake Taihu","authors":"Qiduo Yang ,&nbsp;Yanhui Liu ,&nbsp;Hanhan Zhang ,&nbsp;Qingya Gong ,&nbsp;Ke Geng ,&nbsp;Yaling Su ,&nbsp;Kuanyi Li ,&nbsp;Chunlei Yue ,&nbsp;Baohua Guan","doi":"10.1016/j.ecolind.2025.113484","DOIUrl":"10.1016/j.ecolind.2025.113484","url":null,"abstract":"<div><div>Functional traits effectively reflect plants’ ecological strategies in response to environmental changes. This study investigated how lake eutrophication influences macrophyte communities ecological strategies by analyzing leaf functional traits along the eastern littoral zone of Lake Taihu. Using Grime’s CSR framework (C: competitive; S: stress-tolerant; R: ruderal), we compared strategies among different macrophyte life forms (submerged, floating-leaved, and emergent) across a eutrophicaiton gradient. The study sites exhibited varying degrees of eutrophication (from mesotrophication to heavy eutrophication), with significant differences in nutrient contents and light availability. The macrophyte community was predominantly characterized by C and R strategies, with dominance shifting from R to C as eutrophication increased. Different life forms showed distinct responses: Submerged macrophyte transitioned from R to C strategies, floating-leaved macrophytes decreased C strategies proportion with increased S strategies while emergent macrophytes remained stable. Environmental factorss influenced community strategies indirectly through macrophyte traits, with C and S strategies negatively correlation with underwater light availability but positively with nutrient levels. while R strategy showed opposite correlations.This study revealed that reduced underwater light availability, rather than increased nutrient levels,was the primary driver of changes in macrophyte ecological strategies under eutrophication.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"174 ","pages":"Article 113484"},"PeriodicalIF":7.0,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143863719","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":"How does agricultural resilience in China vary by region?","authors":"Yuzhen Yang ,&nbsp;Pengfei Feng ,&nbsp;Jin Guo","doi":"10.1016/j.ecolind.2025.113513","DOIUrl":"10.1016/j.ecolind.2025.113513","url":null,"abstract":"<div><div>Understanding regional variation in agricultural resilience is crucial for promoting sustainable agricultural practices. However, research on the extent of agricultural resilience and its determinants in different regions of China remains limited. This study utilized data from the China Economic and Social Big Data Research Platform to extract relevant indicators, applied the entropy weight method to calculate indicator weights, and conducted an analysis of regional variations in agricultural resilience and its driving factors across 344 cities in China. The findings reveal a significant increase in agricultural resilience, rising from 0.158 to 0.330, with a consistent upward trend (P &lt; 0.05). The spatial distribution of agricultural resilience demonstrates marked heterogeneity and clustering, with high-resilience areas predominantly concentrated in economically advanced coastal regions, while low-resilience areas are primarily located in less-developed western provinces. Key determinants of agricultural resilience include infrastructure, healthcare, education, technological advancements, and natural environmental factors, but the significance of these factors vary by region. This study underscores the necessity of region-specific strategies to enhance agricultural resilience, and emphasizes the integration of infrastructure development, localized agricultural education, and telemedicine systems to strengthen agricultural resilience. These findings offer insights for fostering resilient agriculture in China and other developing countries.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"174 ","pages":"Article 113513"},"PeriodicalIF":7.0,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143858823","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":"Analyzing climatic and Non-Climatic impacts on Structure, phenology and functions of Western Himalayan forests","authors":"Deep C. Tiwari ,&nbsp;Pooja Negi ,&nbsp;Shinny Thakur ,&nbsp;Suresh K. Rana ,&nbsp;Rajiv Pandey ,&nbsp;I.D. Bhatt ,&nbsp;Sunil Nautiyal","doi":"10.1016/j.ecolind.2025.113511","DOIUrl":"10.1016/j.ecolind.2025.113511","url":null,"abstract":"<div><div>The Himalayan forests are critically threatened by climatic and non-climatic drivers, resulting in significant alterations in the ecological balance. This study attempted to analyze the key ecological features and threats to the west Himalayan Forest ecosystem by systematically analyzing 614 Scopus-indexed articles published over the last three decades. Pine forests exhibit maximum tree densities, ranging from 153 to 1,675 trees/ha, while Banj oak forests demonstrate densities of 250 to 1,500 trees/ha. Moru Oak forests possess maximum aboveground biomass ranging from 500-989 Mg/ha, and maximum carbon stocks of 30–445 Mg/ha. Climate change has facilitated the proliferation of invasive species in the region, threatening native biodiversity. Invasive species like <em>Lantana camara</em> and <em>Ageratina adenophora</em> display broad altitudinal adaptability. The increasing number of fire incidents driven by human activities and climate change is another major threat to forests. Multiple reports of phenological shift such as early flowering and fruiting in <em>Rhododendron arboreum</em> and <em>Myrica esculenta</em>, and upward treeline shifts, are visible impacts of climate change in the region. These impacts highlight the necessity for integrated research to develop effective adaptation strategies and conservation measures in the region. Sustainable management practices based on an in-depth ecological understanding of the forest ecosystem under the prevailing threats will facilitate the conservation and identification of critical ecosystem-based approach (EbA) in the western Himalaya.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"174 ","pages":"Article 113511"},"PeriodicalIF":7.0,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143858822","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":"Accuracy and applicability assessment of vegetation types of the land cover products produced in China","authors":"Caixia Li ,&nbsp;Lingting Lei ,&nbsp;Xiang Jia ,&nbsp;Xiaoyan Xiong ,&nbsp;Xiaoli Zhang","doi":"10.1016/j.ecolind.2025.113506","DOIUrl":"10.1016/j.ecolind.2025.113506","url":null,"abstract":"<div><div>Highly accurate land use/land cover (LULC) information is crucial for monitoring current environmental changes. The existing LULC products generated based on Landsat, MODIS, Sentinel, and other remote sensing images have obvious differences in classification accuracy, spatial and temporal resolution, the applicability, and the stability of the time series products in different regions. The accuracy and applicability assessment of LULC products in China is predominantly concerned with the comparative analysis of area and spatial distribution characteristics of single temporal data, while the assessment of vegetation types in the spatial and temporal dimensions is seldom involved, resulting in the applications of these products in forest resource monitoring and ecological value evaluation at national and regional scales remaining unclear. Therefore, we analyzed the applicability of three land cover products produced by Chinese institutions, including 35 issues of CLCD, 3 issues of GlobeLand30 and 10 issues of GLC_FCS30D, in terms of temporal stability and spatial consistency, and developed a spatial accuracy assessment method to realize the spatial accuracy mapping of different land cover products using the multiscale geographically weighted regression model (MGWR). The results show that with respect to temporal stability, the CLCD product has high stability in forests and grasslands and is suitable for monitoring long-term changes; the GLC_FCS30D product has obvious advantages in the stability of shrubland types and local feature recognition; the vegetation type stability of the GlobeLand30 product reaches more than 0.85, but is limited by the short time series data. With respect to spatial consistency, the GLC_FCS30D product shows better overall spatial consistency than the CLCD and GlobeLand30 products, the fineness of vegetation type delineation is correlated with the level of spatial consistency, and there are obvious geographic differences in spatial expression between different products. The three products have different levels of ambiguity in distinguishing the boundaries of forests, shrublands and grasslands. The CLCD product has the highest overall spatial accuracy, with local spatial accuracy variations in the north, southeast, and southwest in China, and users who are concerned about these regions should be aware of the differences between the products. This study provides a reasonable basis for Chinese users to make appropriate selections of land cover products or to integrate different products according to application scenarios.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"174 ","pages":"Article 113506"},"PeriodicalIF":7.0,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143858820","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":"How do exergy-based indicators respond to physical habitat changes?","authors":"Marden Seabra Linares ,&nbsp;Diego Rodrigues Macedo ,&nbsp;Gilberto Nepomuceno Salvador ,&nbsp;Carlos Bernardo Mascarenhas Alves ,&nbsp;Paulo Santos Pompeu ,&nbsp;Marcos Callisto","doi":"10.1016/j.ecolind.2025.113499","DOIUrl":"10.1016/j.ecolind.2025.113499","url":null,"abstract":"<div><div>Eco-exergy and specific eco-exergy are thermodynamic indicators widely used in recent decades to monitor the ecological status of aquatic ecosystems. However, there is still a gap in the knowledge of how these indicators respond to variations in stream physical habitat resulting from natural variation or anthropogenic disturbances. Our objective was to determine what instream physical habitat metrics are related to the variation of eco-exergy and specific eco-exergy from benthic macroinvertebrates and fish assemblages in southeastern Brazil. For benthic macroinvertebrate assemblages, eco-exergy positively correlated with Catchment Disturbance Index scores, whereas specific eco-exergy was positively correlated with Mean Depth. For fish assemblages, eco-exergy was positively correlated with Mean Dead Wood Fish Cover. In contrast, specific eco-exergy was positively correlated with Local Disturbance Index scores and was negatively associated with Mean Depth, Mean Percentage of Riffle, and Mean Undergrowth Proportion. Our results show that exergy-based indicators respond well to natural and human changes in various aspects of instream physical habitat. Whereas their capacity to respond directly to anthropogenic disturbances differ by the assemblage used to calculate eco-exergy and specific eco-exergy, both indices may be useful tools for environmental managers and decision-makers to respond to multiple aspects of lotic ecosystem physical habitat conditions.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"174 ","pages":"Article 113499"},"PeriodicalIF":7.0,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143858818","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}