Understanding the spatial dynamics and interactions of hydrological ecosystem services (HES) is critical for sustainable watershed management under increasing land use pressure and climate variability. This study evaluates five key HES indicators—freshwater provision, green water scarcity, green water vulnerability, flood regulation, and erosion regulation—in the Zhuoshui River Basin, Taiwan, using the SWAT model for the period 2002–2020. Spatial autocorrelation (global and local Moran's I) was employed to identify clustering patterns of high and low HES performance. The results reveal pronounced spatial disparities: downstream areas experience higher green-water stress, especially during the wet season, whereas forested upstream regions provide stronger regulatory functions. Urban and agricultural zones exhibit reduced freshwater provision. Spearman's correlation analysis indicates trade-offs between freshwater provision and regulatory services in intensively managed landscapes, along with strong synergies among green-water-related indicators. ANOVA with Scheffé post hoc tests further confirms that land-use type significantly influences HES performance. Overall, the findings advance spatially explicit HES assessment and offer a decision-support framework to guide ecological restoration, land-use zoning, and climate-adaptation planning at the subbasin scale.
{"title":"Analyzing the spatial intercorrelations of hydrological ecosystem services of different land use/land cover at the catchment scale","authors":"Yung-Chieh Wang , Li-Chi Chiang , Zi-Rong Yu , Pin-Chih Shih","doi":"10.1016/j.ecolind.2026.114628","DOIUrl":"10.1016/j.ecolind.2026.114628","url":null,"abstract":"<div><div>Understanding the spatial dynamics and interactions of hydrological ecosystem services (HES) is critical for sustainable watershed management under increasing land use pressure and climate variability. This study evaluates five key HES indicators—freshwater provision, green water scarcity, green water vulnerability, flood regulation, and erosion regulation—in the Zhuoshui River Basin, Taiwan, using the SWAT model for the period 2002–2020. Spatial autocorrelation (global and local Moran's I) was employed to identify clustering patterns of high and low HES performance. The results reveal pronounced spatial disparities: downstream areas experience higher green-water stress, especially during the wet season, whereas forested upstream regions provide stronger regulatory functions. Urban and agricultural zones exhibit reduced freshwater provision. Spearman's correlation analysis indicates trade-offs between freshwater provision and regulatory services in intensively managed landscapes, along with strong synergies among green-water-related indicators. ANOVA with Scheffé post hoc tests further confirms that land-use type significantly influences HES performance. Overall, the findings advance spatially explicit HES assessment and offer a decision-support framework to guide ecological restoration, land-use zoning, and climate-adaptation planning at the subbasin scale.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"183 ","pages":"Article 114628"},"PeriodicalIF":7.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146074661","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}
Pub Date : 2026-02-01DOI: 10.1016/j.ecolind.2026.114605
Kristian Rubiano , Dennis Castillo Figueroa , Nicolás Bernal Guatibonza , Nicola Clerici
Deforestation is a major environmental threat in Colombia, particularly in the Andean region, which harbors exceptional biodiversity and provides critical ecosystem services. This study assessed the projected deforestation in Colombian Andean forests under two scenarios—Business as Usual -BAU- and Governance -GOV- for the 2018–2030 and 2030–2050 periods, using spatially explicit models. Forest types were classified based on national ecosystem maps, and changes were estimated for the Andes, and within National Natural Parks. Under the BAU scenario, deforestation is widespread, especially in Basal and Fragmented forests, which by 2050 show declines of up to 8 % and 5.4 %, respectively. In contrast, Andean and Sub-Andean forests exhibit lower losses, though still notable over time. The GOV scenario projects significantly lower deforestation rates across all forest types and periods, with total losses remaining below 0.5 %. Within protected areas, forest loss is limited (<0.8 %) under all scenarios, but higher under BAU, particularly in Catatumbo Barí and Cordillera de los Picachos parks. These findings highlight contrasting futures for Andean forests depending on governance pathways. While the BAU scenario reflects continued deforestation despite protection efforts, the GOV scenario underscores the positive impact of improved institutional frameworks and land-use policies. This study emphasizes the urgent need to strengthen governance and enforcement mechanisms, even within protected areas, to safeguard Colombian biodiversity and ecosystem services. Our projections offer a valuable tool for anticipating deforestation risks and inform adaptive, regionally tailored conservation strategies in one of South America's most ecologically important regions.
{"title":"The future of Colombian Andean forests under different deforestation scenarios","authors":"Kristian Rubiano , Dennis Castillo Figueroa , Nicolás Bernal Guatibonza , Nicola Clerici","doi":"10.1016/j.ecolind.2026.114605","DOIUrl":"10.1016/j.ecolind.2026.114605","url":null,"abstract":"<div><div>Deforestation is a major environmental threat in Colombia, particularly in the Andean region, which harbors exceptional biodiversity and provides critical ecosystem services. This study assessed the projected deforestation in Colombian Andean forests under two scenarios—Business as Usual -BAU- and Governance -GOV- for the 2018–2030 and 2030–2050 periods, using spatially explicit models. Forest types were classified based on national ecosystem maps, and changes were estimated for the Andes, and within National Natural Parks. Under the BAU scenario, deforestation is widespread, especially in Basal and Fragmented forests, which by 2050 show declines of up to 8 % and 5.4 %, respectively. In contrast, Andean and Sub-Andean forests exhibit lower losses, though still notable over time. The GOV scenario projects significantly lower deforestation rates across all forest types and periods, with total losses remaining below 0.5 %. Within protected areas, forest loss is limited (<0.8 %) under all scenarios, but higher under BAU, particularly in Catatumbo Barí and Cordillera de los Picachos parks. These findings highlight contrasting futures for Andean forests depending on governance pathways. While the BAU scenario reflects continued deforestation despite protection efforts, the GOV scenario underscores the positive impact of improved institutional frameworks and land-use policies. This study emphasizes the urgent need to strengthen governance and enforcement mechanisms, even within protected areas, to safeguard Colombian biodiversity and ecosystem services. Our projections offer a valuable tool for anticipating deforestation risks and inform adaptive, regionally tailored conservation strategies in one of South America's most ecologically important regions.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"183 ","pages":"Article 114605"},"PeriodicalIF":7.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146074658","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}
Pub Date : 2026-02-01DOI: 10.1016/j.ecolind.2026.114647
Zixuan Yang , Jie Xiang , Sheng Li , Hong Qian , Bin Dong
Forests act as critical carbon sink ecosystems, with their carbon sequestration capacity influenced by multiple factors. However, the long-term relationship between forest spatial morphological patterns and carbon storage remains insufficiently explored. This study focuses on Jinhua City, Zhejiang Province, using multi-source data from 2002 to 2020, including morphological spatial pattern analysis (MSPA) metrics, climatic factors, land use types, and socioeconomic data. By employing MSPA and an explainable machine learning (ML) framework, we investigated the relationships between forest carbon storage and key influencing factors. The results indicate that: (1) Incorporating MSPA factors significantly enhances the predictive accuracy of vegetation carbon storage models. (2) NDVI, MSPA factors, and SSD (sunshine duration) are the most critical determinants of carbon storage levels, exhibiting pronounced nonlinear relationships with forest vegetation carbon storage. Specifically, NDVI, D_CORE (density of core), and SSD show the most significant positive contributions, whereas D_ISLET (density of islet), D_BRANCH (density of branch), and D_LOOP (density of loop) exhibit relatively lower and negative correlations. (3) Certain key influencing factors display threshold effects and optimal intervals. In Jinhua City, the significantly higher carbon sequestration benefits are associated with NDVI values ranging from 0.63 to 0.73, D_CORE between 63% and 89%, and SSD of 1482 h, providing actionable guidance for spatial planning. This study provides new insights into forest carbon management in Jinhua, suggesting that optimizing landscape ecological spatial patterns should be prioritized in ecological conservation efforts. Additionally, differentiated strategies should be developed for distinct regions to support sustainable forest management in alignment with China's dual carbon goals.
{"title":"Unveiling critical morphological contributions in Forest vegetation carbon storage: An MSPA and explainable machine learning analysis of Jinhua City, China","authors":"Zixuan Yang , Jie Xiang , Sheng Li , Hong Qian , Bin Dong","doi":"10.1016/j.ecolind.2026.114647","DOIUrl":"10.1016/j.ecolind.2026.114647","url":null,"abstract":"<div><div>Forests act as critical carbon sink ecosystems, with their carbon sequestration capacity influenced by multiple factors. However, the long-term relationship between forest spatial morphological patterns and carbon storage remains insufficiently explored. This study focuses on Jinhua City, Zhejiang Province, using multi-source data from 2002 to 2020, including morphological spatial pattern analysis (MSPA) metrics, climatic factors, land use types, and socioeconomic data. By employing MSPA and an explainable machine learning (ML) framework, we investigated the relationships between forest carbon storage and key influencing factors. The results indicate that: (1) Incorporating MSPA factors significantly enhances the predictive accuracy of vegetation carbon storage models. (2) NDVI, MSPA factors, and SSD (sunshine duration) are the most critical determinants of carbon storage levels, exhibiting pronounced nonlinear relationships with forest vegetation carbon storage. Specifically, NDVI, D_CORE (density of core), and SSD show the most significant positive contributions, whereas D_ISLET (density of islet), D_BRANCH (density of branch), and D_LOOP (density of loop) exhibit relatively lower and negative correlations. (3) Certain key influencing factors display threshold effects and optimal intervals. In Jinhua City, the significantly higher carbon sequestration benefits are associated with NDVI values ranging from 0.63 to 0.73, D_CORE between 63% and 89%, and SSD of 1482 h, providing actionable guidance for spatial planning. This study provides new insights into forest carbon management in Jinhua, suggesting that optimizing landscape ecological spatial patterns should be prioritized in ecological conservation efforts. Additionally, differentiated strategies should be developed for distinct regions to support sustainable forest management in alignment with China's dual carbon goals.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"183 ","pages":"Article 114647"},"PeriodicalIF":7.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146074665","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}
Pub Date : 2026-02-01DOI: 10.1016/j.ecolind.2026.114659
José Riofrío , Nicholas C. Coops , Muhammad Waseem Ashiq , Alexis Achim
Understanding species composition shifts in boreal mixedwoods forests is essential for anticipating forest succession pathways under changing disturbance regimes. Species composition transitions in boreal forests reflect complex successional processes influenced by interactions between disturbance regimes, structural dynamics, and species traits. In this study, we integrated satellite-derived annual species composition data with airborne laser scanning (ALS) structural metrics, spatially explicit mortality estimates and disturbance history to investigate composition transitions across ∼288,000 ha of the Romeo Mallette Forest, Ontario. We focused on mid to late successional stages, identifying 27 species composition transitions and modeling their likelihood using extreme gradient boosting (XGBoost). From 2005 to 2018, 5% of the analyzed stands (∼42,000 ha) predominantly transitioned from hardwood to coniferous or mixed compositions. Transition probabilities were strongly associated with ALS-derived gap metrics, mortality rates, and cumulative years of spruce budworm and Forest Tent Caterpillar defoliation, while traditional site factors had limited predictive value. Notably, the number of years affected by spruce budworm defoliation significantly increased the likelihood of transition in stands dominated by more susceptible species. The results advance our understanding of mid-late succession pathways and support the integration of remote sensing time series into forest monitoring frameworks, improving inventory accuracy, and guiding adaptive management under evolving disturbance regimes.
{"title":"Linking species composition shifts from satellite time series to disturbance regimes and Lidar-derived structural and mortality indicators in boreal mixedwoods","authors":"José Riofrío , Nicholas C. Coops , Muhammad Waseem Ashiq , Alexis Achim","doi":"10.1016/j.ecolind.2026.114659","DOIUrl":"10.1016/j.ecolind.2026.114659","url":null,"abstract":"<div><div>Understanding species composition shifts in boreal mixedwoods forests is essential for anticipating forest succession pathways under changing disturbance regimes. Species composition transitions in boreal forests reflect complex successional processes influenced by interactions between disturbance regimes, structural dynamics, and species traits. In this study, we integrated satellite-derived annual species composition data with airborne laser scanning (ALS) structural metrics, spatially explicit mortality estimates and disturbance history to investigate composition transitions across ∼288,000 ha of the Romeo Mallette Forest, Ontario. We focused on mid to late successional stages, identifying 27 species composition transitions and modeling their likelihood using extreme gradient boosting (XGBoost). From 2005 to 2018, 5% of the analyzed stands (∼42,000 ha) predominantly transitioned from hardwood to coniferous or mixed compositions. Transition probabilities were strongly associated with ALS-derived gap metrics, mortality rates, and cumulative years of spruce budworm and Forest Tent Caterpillar defoliation, while traditional site factors had limited predictive value. Notably, the number of years affected by spruce budworm defoliation significantly increased the likelihood of transition in stands dominated by more susceptible species. The results advance our understanding of mid-late succession pathways and support the integration of remote sensing time series into forest monitoring frameworks, improving inventory accuracy, and guiding adaptive management under evolving disturbance regimes.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"183 ","pages":"Article 114659"},"PeriodicalIF":7.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146074746","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}
Pub Date : 2026-02-01DOI: 10.1016/j.ecolind.2026.114654
M. Allison Stegner , Jayne Belnap , Tara B.B. Bishop , Anna C. Knight , Travis W. Nauman , Michael C. Duniway
Public lands are challenged by a range of pressures—changing climate, increasing visitation, resource extraction—and their effects can span spatial scales, often crossing land management jurisdictional boundaries. Research approaches which explicitly span jurisdictions can support strategies to contend with regional pressures. We assess management-relevant drivers of change—aridification, livestock grazing, invasive species, surface disturbance, and fire—across a patchwork of land management units and agencies on the Colorado Plateau, focusing on southeastern Utah, USA. We use vulnerability analysis, first evaluating exposure to drivers across the landscape, then quantifying sensitivity to each driver across different land types, defined by mapped Ecological Site Groups, a system for classifying landscapes according to physical factors including climate, soils, and topographic setting. We address the questions: 1) how are drivers spatially distributed across the study region; and, 2) based on exposure and sensitivity, are certain land types more vulnerable to these drivers? We find that the study region has high exposure and sensitivity—and thus high vulnerability—to aridification and grazing, but low exposure and vulnerability to other drivers. Although more sensitive land types were not generally more exposed, identifying which areas are most sensitive can guide adaptive measures, like where new uses or disturbances would be least harmful and which areas could be prioritized for restoration. The method we demonstrate is a flexible tool for assessing landscape-scale impacts, is built on nationally available datasets, and can be tailored to different datasets and sensitivity metrics.
{"title":"Vulnerability of different Colorado plateau land types to drivers of change","authors":"M. Allison Stegner , Jayne Belnap , Tara B.B. Bishop , Anna C. Knight , Travis W. Nauman , Michael C. Duniway","doi":"10.1016/j.ecolind.2026.114654","DOIUrl":"10.1016/j.ecolind.2026.114654","url":null,"abstract":"<div><div>Public lands are challenged by a range of pressures—changing climate, increasing visitation, resource extraction—and their effects can span spatial scales, often crossing land management jurisdictional boundaries. Research approaches which explicitly span jurisdictions can support strategies to contend with regional pressures. We assess management-relevant drivers of change—aridification, livestock grazing, invasive species, surface disturbance, and fire—across a patchwork of land management units and agencies on the Colorado Plateau, focusing on southeastern Utah, USA. We use vulnerability analysis, first evaluating exposure to drivers across the landscape, then quantifying sensitivity to each driver across different land types, defined by mapped Ecological Site Groups, a system for classifying landscapes according to physical factors including climate, soils, and topographic setting. We address the questions: 1) how are drivers spatially distributed across the study region; and, 2) based on exposure and sensitivity, are certain land types more vulnerable to these drivers? We find that the study region has high exposure and sensitivity—and thus high vulnerability—to aridification and grazing, but low exposure and vulnerability to other drivers. Although more sensitive land types were not generally more exposed, identifying which areas are most sensitive can guide adaptive measures, like where new uses or disturbances would be least harmful and which areas could be prioritized for restoration. The method we demonstrate is a flexible tool for assessing landscape-scale impacts, is built on nationally available datasets, and can be tailored to different datasets and sensitivity metrics.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"183 ","pages":"Article 114654"},"PeriodicalIF":7.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146074588","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}
Pub Date : 2026-02-01DOI: 10.1016/j.ecolind.2026.114629
Fabienne Horneman , Alice Stocco , Paolo Comandini , Alberto Barausse , Nuno Caiola , Agustín Sánchez-Arcilla , Vicente Gracia , Richard Marijnissen , Sara Pino Cobacho , Luciana Villa Castrillón , Joanna Staneva , Elitsa Hineva , Nataliya Andreeva , Massimiliano Marino , Rosaria Ester Musumeci , Julien Dalle , Mathis Cognat , Olivier Boutron , Morgane Jolivet , Avi Uzan , Silvia Torresan
Ecosystems along river-to-sea continuums face urgent challenges that demand swift restoration interventions, often exceeding the data availability, collection and testing capacity. This makes expert- and consensus-based approaches vital for guiding decisions, particularly in data-scarce coastal regions. With the aim to provide practical guidance for assessing the applicability of different restoration techniques, this study involved a group of 23 experts from various European and Mediterranean regions to evaluate 49 restoration techniques tested recently in nine sites, representing diverse coastal ecosystems. Through a Delphi-based expert elicitation, a series of gray, hybrid, and green restoration techniques was assessed in terms of their structural and functional performance. Additionally, the assessment of the pressures affecting the regions allowed exploring the restoration techniques' resilience to both natural and anthropogenic pressures and impacts. Results from the data collected so far suggest that, while green restoration techniques are environmentally friendly and significantly support natural processes, their limited scale of influence makes them vulnerable when pressures are strong or widespread on the ecosystem. This often leads to opting for hybrid or engineering-based solutions for restoration, as they provide a more robust structure and longevity albeit with reduced capacity to foster natural processes. This result underscores a critical dilemma: while green and/or integrated solutions can help mitigate human-induced impacts and digital tools may support decision-making, restoration efforts alone may sometimes be insufficient if the underlying anthropogenic pressures on human-dominated coastal ecosystems remain unaddressed. Subsequently, the identified techniques and their performance evaluated under current and future conditions have been compiled into an open-source, interactive digital tool, designed to assist decision-makers and practitioners in selecting the most suitable restoration strategies by leveraging the knowledge acquired through ongoing experiences in coastal restoration. This digital platform not only facilitates access to information but also enables the integration of new data on emerging techniques, making it a dynamic and evolving resource for coastal restoration management.
{"title":"Nature-based adaptation in human dominated coastal ecosystems","authors":"Fabienne Horneman , Alice Stocco , Paolo Comandini , Alberto Barausse , Nuno Caiola , Agustín Sánchez-Arcilla , Vicente Gracia , Richard Marijnissen , Sara Pino Cobacho , Luciana Villa Castrillón , Joanna Staneva , Elitsa Hineva , Nataliya Andreeva , Massimiliano Marino , Rosaria Ester Musumeci , Julien Dalle , Mathis Cognat , Olivier Boutron , Morgane Jolivet , Avi Uzan , Silvia Torresan","doi":"10.1016/j.ecolind.2026.114629","DOIUrl":"10.1016/j.ecolind.2026.114629","url":null,"abstract":"<div><div>Ecosystems along river-to-sea continuums face urgent challenges that demand swift restoration interventions, often exceeding the data availability, collection and testing capacity. This makes expert- and consensus-based approaches vital for guiding decisions, particularly in data-scarce coastal regions. With the aim to provide practical guidance for assessing the applicability of different restoration techniques, this study involved a group of 23 experts from various European and Mediterranean regions to evaluate 49 restoration techniques tested recently in nine sites, representing diverse coastal ecosystems. Through a Delphi-based expert elicitation, a series of gray, hybrid, and green restoration techniques was assessed in terms of their structural and functional performance. Additionally, the assessment of the pressures affecting the regions allowed exploring the restoration techniques' resilience to both natural and anthropogenic pressures and impacts. Results from the data collected so far suggest that, while green restoration techniques are environmentally friendly and significantly support natural processes, their limited scale of influence makes them vulnerable when pressures are strong or widespread on the ecosystem. This often leads to opting for hybrid or engineering-based solutions for restoration, as they provide a more robust structure and longevity albeit with reduced capacity to foster natural processes. This result underscores a critical dilemma: while green and/or integrated solutions can help mitigate human-induced impacts and digital tools may support decision-making, restoration efforts alone may sometimes be insufficient if the underlying anthropogenic pressures on human-dominated coastal ecosystems remain unaddressed. Subsequently, the identified techniques and their performance evaluated under current and future conditions have been compiled into an open-source, interactive digital tool, designed to assist decision-makers and practitioners in selecting the most suitable restoration strategies by leveraging the knowledge acquired through ongoing experiences in coastal restoration. This digital platform not only facilitates access to information but also enables the integration of new data on emerging techniques, making it a dynamic and evolving resource for coastal restoration management.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"183 ","pages":"Article 114629"},"PeriodicalIF":7.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146074589","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}
Pub Date : 2026-02-01DOI: 10.1016/j.ecolind.2026.114652
Jacob O. Iteba , Gideon L. Kuluo , Sharon I. Lubembe , Kelvin O. Moenga , Suzanne R. Jacobs , Lutz Breuer , Frank O. Masese
Afromontane headwater streams are highly vulnerable to land use changes and face growing threats from population growth and agricultural intensification. This study assessed how land use affects macroinvertebrate assemblages and their functional traits in the Sondu-Miriu River basin, western Kenya, through intensive sampling campaigns under wet and dry conditions. Water quality changes mirrored a disturbance gradient with good water quality conditions being noted in minimally disturbed natural forest and moderately disturbed streams (characterized by tree and tea plantations and smallholder tea) compared to highly disturbed smallholder agriculture streams under both flow conditions. This change in environmental conditions was reflected in macroinvertebrate species richness and diversity, which were significantly higher at natural forest and the moderately disturbed tree and tea plantations and smallholder tea streams than in highly disturbed smallholder agriculture streams. Environmental filtering was evident in the different land use types, where nutrient enrichment (nitrates and total phosphorous), turbidity and oxygen depletion were key drivers of macroinvertebrate assemblage and trait distributions. Pollution-tolerant taxa (e.g., oligochaetes) and traits (small body size, spiracular respiration, collector-gatherer feeding) dominated smallholder agriculture streams, while sensitive taxa (e.g., Afrocaenis sp.) and traits (large body size and gill respiration) were more abundant in natural forest streams. Collectively, our results underscore the value of integrating trait-based measures with traditional taxonomic metrics to evaluate how tropical stream ecosystems are influenced by changes in land use and seasonality.
{"title":"Land use influence on macroinvertebrate assemblages and trait-based functional composition in Afromontane headwater streams","authors":"Jacob O. Iteba , Gideon L. Kuluo , Sharon I. Lubembe , Kelvin O. Moenga , Suzanne R. Jacobs , Lutz Breuer , Frank O. Masese","doi":"10.1016/j.ecolind.2026.114652","DOIUrl":"10.1016/j.ecolind.2026.114652","url":null,"abstract":"<div><div>Afromontane headwater streams are highly vulnerable to land use changes and face growing threats from population growth and agricultural intensification. This study assessed how land use affects macroinvertebrate assemblages and their functional traits in the Sondu-Miriu River basin, western Kenya, through intensive sampling campaigns under wet and dry conditions. Water quality changes mirrored a disturbance gradient with good water quality conditions being noted in minimally disturbed natural forest and moderately disturbed streams (characterized by tree and tea plantations and smallholder tea) compared to highly disturbed smallholder agriculture streams under both flow conditions. This change in environmental conditions was reflected in macroinvertebrate species richness and diversity, which were significantly higher at natural forest and the moderately disturbed tree and tea plantations and smallholder tea streams than in highly disturbed smallholder agriculture streams. Environmental filtering was evident in the different land use types, where nutrient enrichment (nitrates and total phosphorous), turbidity and oxygen depletion were key drivers of macroinvertebrate assemblage and trait distributions. Pollution-tolerant taxa (e.g., oligochaetes) and traits (small body size, spiracular respiration, collector-gatherer feeding) dominated smallholder agriculture streams, while sensitive taxa (e.g., <em>Afrocaenis</em> sp.) and traits (large body size and gill respiration) were more abundant in natural forest streams. Collectively, our results underscore the value of integrating trait-based measures with traditional taxonomic metrics to evaluate how tropical stream ecosystems are influenced by changes in land use and seasonality.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"183 ","pages":"Article 114652"},"PeriodicalIF":7.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146074662","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}
Pub Date : 2026-02-01DOI: 10.1016/j.ecolind.2026.114658
Shengjun Yan , Xuan Wang , Rui Yan , Zhenmei Liao , Changan Liu , Daoyan Xu , Guoxiang Liao
The spatial distribution of plant communities is often explained by the joint effects of environmental filtering and dispersal limitation. However, the relative importance of these two processes in shaping plant β-diversity patterns (which characterize environmental gradients and ecological processes) in coastal wetlands remains insufficiently explored, and it is still unclear how anthropogenic disturbances influence such patterns. In this study, we examined the β-diversity patterns of plant communities along 10 parallel transects spanning a human-impacted zone (with constructed embankments) and a natural coastal wetland zone within the coastal wetlands of the Yellow River Delta. Differences in plant communities between the two zones were assessed by principal coordinates analysis. β-diversity was partitioned using a distance matrix-based variation partitioning analysis, and the generalized dissimilarity model (GDM) was applied to identify its main drivers. Plant community composition differed significantly between the two zones (PERMANOVA, R2 = 0.18, p < 0.01). The overall β-diversity was predominantly composed of the turnover component, which accounted for 60.59% and 55.84% of the total dissimilarity in the natural and human-impacted zones, respectively. Accordingly, the process shaping this dominant component shifted from environmental filtering in the natural zone to dispersal limitation in the human-impacted zone. The GDM analyses showed that, in the natural coastal wetland zone, β-diversity was primarily driven by environmental factors, particularly salinity (54.73%; p = 0.02) and elevation (30.23%; p = 0.04), whereas in the human-impacted zone, spatial distance (54.26%; p = 0.04) was the main driver. Our results demonstrate that anthropogenic disturbances reconfigure the dominant assembly processes, shifting plant community β-diversity from environmental filtering to dispersal limitation. These findings have implications for the conservation of coastal wetlands; that is, conservation efforts should target areas with intact vegetation communities spanning from the sea to the land.
{"title":"Effects of environmental filtering and dispersal limitation on the β-diversity of coastal wetland plant communities","authors":"Shengjun Yan , Xuan Wang , Rui Yan , Zhenmei Liao , Changan Liu , Daoyan Xu , Guoxiang Liao","doi":"10.1016/j.ecolind.2026.114658","DOIUrl":"10.1016/j.ecolind.2026.114658","url":null,"abstract":"<div><div>The spatial distribution of plant communities is often explained by the joint effects of environmental filtering and dispersal limitation. However, the relative importance of these two processes in shaping plant β-diversity patterns (which characterize environmental gradients and ecological processes) in coastal wetlands remains insufficiently explored, and it is still unclear how anthropogenic disturbances influence such patterns. In this study, we examined the β-diversity patterns of plant communities along 10 parallel transects spanning a human-impacted zone (with constructed embankments) and a natural coastal wetland zone within the coastal wetlands of the Yellow River Delta. Differences in plant communities between the two zones were assessed by principal coordinates analysis. β-diversity was partitioned using a distance matrix-based variation partitioning analysis, and the generalized dissimilarity model (GDM) was applied to identify its main drivers. Plant community composition differed significantly between the two zones (PERMANOVA, R<sup>2</sup> = 0.18, <em>p</em> < 0.01). The overall β-diversity was predominantly composed of the turnover component, which accounted for 60.59% and 55.84% of the total dissimilarity in the natural and human-impacted zones, respectively. Accordingly, the process shaping this dominant component shifted from environmental filtering in the natural zone to dispersal limitation in the human-impacted zone. The GDM analyses showed that, in the natural coastal wetland zone, β-diversity was primarily driven by environmental factors, particularly salinity (54.73%; <em>p</em> = 0.02) and elevation (30.23%; <em>p</em> = 0.04), whereas in the human-impacted zone, spatial distance (54.26%; <em>p</em> = 0.04) was the main driver. Our results demonstrate that anthropogenic disturbances reconfigure the dominant assembly processes, shifting plant community β-diversity from environmental filtering to dispersal limitation. These findings have implications for the conservation of coastal wetlands; that is, conservation efforts should target areas with intact vegetation communities spanning from the sea to the land.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"183 ","pages":"Article 114658"},"PeriodicalIF":7.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146074745","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}
Pub Date : 2026-02-01DOI: 10.1016/j.ecolind.2026.114653
Ilaria Bonfanti , Nicoletta Cannone
The year 2022 in Europe was extreme due to prolonged heatwaves and severe drought. We analyse through high-resolution remote sensing the impacts of the extreme year 2022 on the phenology and the occurrence of early crown discoloration of deciduous forests in northern Italy from the lowlands (Monza) to the Prealps (Cernobbio) and the Alps (Valdidentro).
We analysed plant phenology using the normalized difference vegetation index (NDVI) of 2244 images of Sentinel-2 (period 2017–2023) and identified by General Regression Model the drivers of early crown discoloration in the year 2022. We also computed the biomass production at peak season using NDVI provided by Landsat. Drought intensity was quantified using vapour pressure deficit (VPD) and Standardized Precipitation Evapotranspiration Index (SPEI) from 2004 to 2023.
The extreme year 2022 produced the largest impact at the lowlands, with early crown discoloration occurring 40 days earlier than mean leaf senescence and decrease of biomass production, but high resilience in 2023. Unexpectedly, the year 2022 induced early crown discoloration of 15 days earlier than leaf senescence at the alpine and prealpine sites, with a legacy effect of decreased biomass production in 2023 at the alpine site, suggesting its poor resilience. Early crown discoloration was driven by persistent drought (SPEI) and summer VPD, with relative influence being species and site dependent. The greening of the following year was not affected by the extreme conditions of 2022.
The sensitivity of high elevation deciduous forests to extreme heat and drought suggest to assess their future potential resistance and recovery.
{"title":"High elevation deciduous forests show unexpected sensitivity to extreme heat and drought","authors":"Ilaria Bonfanti , Nicoletta Cannone","doi":"10.1016/j.ecolind.2026.114653","DOIUrl":"10.1016/j.ecolind.2026.114653","url":null,"abstract":"<div><div>The year 2022 in Europe was extreme due to prolonged heatwaves and severe drought. We analyse through high-resolution remote sensing the impacts of the extreme year 2022 on the phenology and the occurrence of early crown discoloration of deciduous forests in northern Italy from the lowlands (Monza) to the Prealps (Cernobbio) and the Alps (Valdidentro).</div><div>We analysed plant phenology using the normalized difference vegetation index (NDVI) of 2244 images of Sentinel-2 (period 2017–2023) and identified by General Regression Model the drivers of early crown discoloration in the year 2022. We also computed the biomass production at peak season using NDVI provided by Landsat. Drought intensity was quantified using vapour pressure deficit (VPD) and Standardized Precipitation Evapotranspiration Index (SPEI) from 2004 to 2023.</div><div>The extreme year 2022 produced the largest impact at the lowlands, with early crown discoloration occurring 40 days earlier than mean leaf senescence and decrease of biomass production, but high resilience in 2023. Unexpectedly, the year 2022 induced early crown discoloration of 15 days earlier than leaf senescence at the alpine and prealpine sites, with a legacy effect of decreased biomass production in 2023 at the alpine site, suggesting its poor resilience. Early crown discoloration was driven by persistent drought (SPEI) and summer VPD, with relative influence being species and site dependent. The greening of the following year was not affected by the extreme conditions of 2022.</div><div>The sensitivity of high elevation deciduous forests to extreme heat and drought suggest to assess their future potential resistance and recovery.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"183 ","pages":"Article 114653"},"PeriodicalIF":7.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146074664","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}
Pub Date : 2026-02-01DOI: 10.1016/j.ecolind.2026.114665
Fang Gui , Shoutao Zhu , Jiayi Tang , Jinlong Huang , Xiaolu Zhou , Peng Li , Zelin Liu , Cicheng Zhang , Ziying Zou , Tong Li , Changhui Peng
PM2.5 poses a significant threat to public health and ecological stability, particularly in rapidly urbanizing China. Although vegetation is recognized as an effective nature-based solution for air pollution mitigation, the combined effects of vegetation type, amount, and spatial configuration at the national scale remain poorly understood. This study systematically evaluates the impacts of vegetation types, spatial configurations, and greenness levels on PM2.5 concentrations across China. The relationships and spatial heterogeneity between PM2.5 and vegetation landscape metrics (including Class Area (CA) and Fragmentation Index (Fra) of forests, shrublands, and grasslands, as well as the Normalized Difference Vegetation Index (NDVI)) were quantified using Pearson correlation analysis, multivariate linear regression controlling for meteorological and anthropogenic factors, and machine learning models. Results indicate that vegetation landscape metrics explain more than 25% of the spatial variation in PM2.5. Pronounced spatial heterogeneity was observed: PM2.5 exhibited significant negative correlations with NDVI in 91.23% of the study area (p < 0.05), while positive correlations occurred in limited arid inland basins and high-mountain border regions. Forest CA and Fra were generally negatively correlated with PM2.5 in the eastern-western transitional zones, whereas Forest Fra tended to aggravate pollution in densely forested eastern China. In contrast, shrubland and grassland CA and Fra showed positive correlations with PM2.5 in over 50% of the regions, particularly in ecologically fragile areas dominated by vegetation degradation and wind-blown dust. These findings demonstrate that vegetation effects on PM2.5 are highly area-dependent and context-specific, providing important implications for regionally differentiated landscape planning and air quality management in China.
{"title":"Impact of vegetation landscape on PM2.5 and spatial heterogeneity in China","authors":"Fang Gui , Shoutao Zhu , Jiayi Tang , Jinlong Huang , Xiaolu Zhou , Peng Li , Zelin Liu , Cicheng Zhang , Ziying Zou , Tong Li , Changhui Peng","doi":"10.1016/j.ecolind.2026.114665","DOIUrl":"10.1016/j.ecolind.2026.114665","url":null,"abstract":"<div><div>PM<sub>2.5</sub> poses a significant threat to public health and ecological stability, particularly in rapidly urbanizing China. Although vegetation is recognized as an effective nature-based solution for air pollution mitigation, the combined effects of vegetation type, amount, and spatial configuration at the national scale remain poorly understood. This study systematically evaluates the impacts of vegetation types, spatial configurations, and greenness levels on PM<sub>2.5</sub> concentrations across China. The relationships and spatial heterogeneity between PM<sub>2.5</sub> and vegetation landscape metrics (including Class Area (CA) and Fragmentation Index (Fra) of forests, shrublands, and grasslands, as well as the Normalized Difference Vegetation Index (NDVI)) were quantified using Pearson correlation analysis, multivariate linear regression controlling for meteorological and anthropogenic factors, and machine learning models. Results indicate that vegetation landscape metrics explain more than 25% of the spatial variation in PM<sub>2.5</sub>. Pronounced spatial heterogeneity was observed: PM<sub>2.5</sub> exhibited significant negative correlations with NDVI in 91.23% of the study area (<em>p</em> < 0.05), while positive correlations occurred in limited arid inland basins and high-mountain border regions. Forest CA and Fra were generally negatively correlated with PM<sub>2.5</sub> in the eastern-western transitional zones, whereas Forest Fra tended to aggravate pollution in densely forested eastern China. In contrast, shrubland and grassland CA and Fra showed positive correlations with PM<sub>2.5</sub> in over 50% of the regions, particularly in ecologically fragile areas dominated by vegetation degradation and wind-blown dust. These findings demonstrate that vegetation effects on PM<sub>2.5</sub> are highly area-dependent and context-specific, providing important implications for regionally differentiated landscape planning and air quality management in China.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"183 ","pages":"Article 114665"},"PeriodicalIF":7.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146074715","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}
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