Pub Date : 2025-02-01DOI: 10.1016/j.ecolind.2025.113171
Ruifeng Zhu , Zexin He , Shunhong Huang , Huading Shi , Xiaolin Liu , Junke Wang , Jinbin Liu , Anfu Liu , Li Li
The vegetation in Huayuan County was seriously damaged during the mining process. Using remote sensing data, the vegetation coverage in the Huayuan County lead–zinc mining area was analysed to explore the temporal trends and driving factors of the FVC. As calculated from remote sensing data, the average FVC decreased rapidly from 0.74 to 0.36 from 2000--2008, with no significant change from 2009 to -2018, and gradually recovered from 0.36 to 0.5 from 2019--2024. Two typical mining areas were selected for research. After artificial reclamation, the damaged vegetation can be restored, whereas the vegetation in the naturally restored mining area is difficult to restore. The cluster map of the mining area is obtained via the Moran index, which reveals that artificial reclamation has an obvious effect on vegetation restoration. The destruction of vegetation in mining areas is affected primarily by human activities, while human activities are affected primarily by changes in policy; thus, policy factors are the main factors driving changes in vegetation in mining areas, whereas natural factors have a small influence on changes in the FVC in mining areas. This study provides a theoretical basis for vegetation restoration in other mining areas and promotes sustainable development.
{"title":"Spatial and temporal changes in vegetation coverage in Huayuan County and the influence of Chinese policies on vegetation coverage","authors":"Ruifeng Zhu , Zexin He , Shunhong Huang , Huading Shi , Xiaolin Liu , Junke Wang , Jinbin Liu , Anfu Liu , Li Li","doi":"10.1016/j.ecolind.2025.113171","DOIUrl":"10.1016/j.ecolind.2025.113171","url":null,"abstract":"<div><div>The vegetation in Huayuan County was seriously damaged during the mining process. Using remote sensing data, the vegetation coverage in the Huayuan County lead–zinc mining area was analysed to explore the temporal trends and driving factors of the FVC. As calculated from remote sensing data, the average FVC decreased rapidly from 0.74 to 0.36 from 2000--2008, with no significant change from 2009 to -2018, and gradually recovered from 0.36 to 0.5 from 2019--2024. Two typical mining areas were selected for research. After artificial reclamation, the damaged vegetation can be restored, whereas the vegetation in the naturally restored mining area is difficult to restore. The cluster map of the mining area is obtained via the Moran index, which reveals that artificial reclamation has an obvious effect on vegetation restoration. The destruction of vegetation in mining areas is affected primarily by human activities, while human activities are affected primarily by changes in policy; thus, policy factors are the main factors driving changes in vegetation in mining areas, whereas natural factors have a small influence on changes in the FVC in mining areas. This study provides a theoretical basis for vegetation restoration in other mining areas and promotes sustainable development.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"171 ","pages":"Article 113171"},"PeriodicalIF":7.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143334162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-01DOI: 10.1016/j.ecolind.2025.113187
Xiaoqi Li , Jiaojiao Zhu , Xinyi Lyu , Yiyun Sun , Chuandong Tan , Bin Zhang , Paolo Tarolli , Qichi Yang
The Miaoling mountainous region, a typical karst landscape in Southwest China, is rich in biological resources and possesses an indigenous cultural heritage. However, ecological degradation and the encroachment of external cultures present significant threats to these areas, creating dual challenges to their biological and cultural integrity. To effectively protect the bio-cultural features in the Miaoling region, this study proposes a strategy for establishing a conservation framework based on the evaluation of bio-cultural diversity for protection. First, the four indicators of biodiversity and five indicators of cultural diversity were used to assess the value of bio-cultural diversity. Next, the Zonation model was integrated to identify priority zones. Finally, using these priority zones, a ’source − corridor − network’ strategy was developed. The results have revealed that nearly half of the region exhibits a lack of coordination between bio-cultural diversity. The priority conservation zones for bio-cultural diversity, which cover a total area of 2,286.76 km2, are located within small watershed and agroforestry ecosystems, displaying a fragmented distribution. Also, the conservation network encompasses 29 primary corridors, 76 secondary corridors, and 25 nodes. Based on that, a multi-stakeholder adaptive management framework has been proposed, emphasizing policy and financial support, community participation, and collaboration to integrate ecological protection with sustainable development. This study highlights the potential of bio-cultural diversity assessments in identifying priority zones and guiding strategic conservation planning in the karst mountainous regions.
{"title":"An integrative conservation and management strategy based on biological and cultural diversity assessment: A case study of Miaoling mountainous region, China","authors":"Xiaoqi Li , Jiaojiao Zhu , Xinyi Lyu , Yiyun Sun , Chuandong Tan , Bin Zhang , Paolo Tarolli , Qichi Yang","doi":"10.1016/j.ecolind.2025.113187","DOIUrl":"10.1016/j.ecolind.2025.113187","url":null,"abstract":"<div><div>The Miaoling mountainous region, a typical karst landscape in Southwest China, is rich in biological resources and possesses an indigenous cultural heritage. However, ecological degradation and the encroachment of external cultures present significant threats to these areas, creating dual challenges to their biological and cultural integrity. To effectively protect the bio-cultural features in the Miaoling region, this study proposes a strategy for establishing a conservation framework based on the evaluation of bio-cultural diversity for protection. First, the four indicators of biodiversity and five indicators of cultural diversity were used to assess the value of bio-cultural diversity. Next, the Zonation model was integrated to identify priority zones. Finally, using these priority zones, a ’source − corridor − network’ strategy was developed. The results have revealed that nearly half of the region exhibits a lack of coordination between bio-cultural diversity. The priority conservation zones for bio-cultural diversity, which cover a total area of 2,286.76 km<sup>2</sup>, are located within small watershed and agroforestry ecosystems, displaying a fragmented distribution. Also, the conservation network encompasses 29 primary corridors, 76 secondary corridors, and 25 nodes. Based on that, a multi-stakeholder adaptive management framework has been proposed, emphasizing policy and financial support, community participation, and collaboration to integrate ecological protection with sustainable development. This study highlights the potential of bio-cultural diversity assessments in identifying priority zones and guiding strategic conservation planning in the karst mountainous regions.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"171 ","pages":"Article 113187"},"PeriodicalIF":7.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143350188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-01DOI: 10.1016/j.ecolind.2025.113203
S. Janzen , J. Balzer , Y. Walz , Z. Sebesvari
Ecosystem-based disaster risk reduction (Eco-DRR) are nature-based solutions increasingly taken up to contribute to reducing disaster risks. The implementation of Eco-DRR improves an ecosystem and its ecosystem services provision so as to reduce all or select components of disaster risk. Since ecosystems are interconnected, the benefits of an Eco-DRR measure may go well beyond the actual implementation site. Yet, Eco-DRR is generally evaluated at the level of the measure itself, missing out to capture the full range of risk-reducing ecosystem services and benefits, which may cascade across the landscape. This paper coins the term “cascading benefits” emerging from Eco-DRR and conceptualises the holistic evaluation of Eco-DRR considering cascading benefits to advance evaluation of Eco-DRR at the landscape level. First, the paper presents the results of a literature review designed to understand how Eco-DRR is evaluated to date and whether and how their cascading benefits are considered in the evaluation. The review identified 51 relevant papers, that allowed extracting 93 Eco-DRR evaluation criteria; none of which capture cascading benefits of Eco-DRR. Next, these 93 criteria were assessed for their potential applicability to evaluate cascading benefits, based on an additional, targeted literature review and 7 expert interviews. As a result, 23 criteria were identified for evaluating cascading benefits, providing an entry point for more holistic Eco-DRR evaluation in the future.
{"title":"Are we missing out in evaluating ecosystem-based disaster risk reduction measures? A review and way forward considering cascading benefits","authors":"S. Janzen , J. Balzer , Y. Walz , Z. Sebesvari","doi":"10.1016/j.ecolind.2025.113203","DOIUrl":"10.1016/j.ecolind.2025.113203","url":null,"abstract":"<div><div>Ecosystem-based disaster risk reduction (Eco-DRR) are nature-based solutions increasingly taken up to contribute to reducing disaster risks. The implementation of Eco-DRR improves an ecosystem and its ecosystem services provision so as to reduce all or select components of disaster risk. Since ecosystems are interconnected, the benefits of an Eco-DRR measure may go well beyond the actual implementation site. Yet, Eco-DRR is generally evaluated at the level of the measure itself, missing out to capture the full range of risk-reducing ecosystem services and benefits, which may cascade across the landscape. This paper coins the term “cascading benefits” emerging from Eco-DRR and conceptualises the holistic evaluation of Eco-DRR considering cascading benefits to advance evaluation of Eco-DRR at the landscape level. First, the paper presents the results of a literature review designed to understand how Eco-DRR is evaluated to date and whether and how their cascading benefits are considered in the evaluation. The review identified 51 relevant papers, that allowed extracting 93 Eco-DRR evaluation criteria; none of which capture cascading benefits of Eco-DRR. Next, these 93 criteria were assessed for their potential applicability to evaluate cascading benefits, based on an additional, targeted literature review and 7 expert interviews. As a result, 23 criteria were identified for evaluating cascading benefits, providing an entry point for more holistic Eco-DRR evaluation in the future.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"171 ","pages":"Article 113203"},"PeriodicalIF":7.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143402066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-01DOI: 10.1016/j.ecolind.2025.113213
Dace Kirsteina , Marie A.E. Mueller , Ross S. Purves
Parks are open spaces planned and designed for leisure and recreation and together with other green spaces they have great value for people, especially in urban areas. To understand the spatial distribution of parks and green spaces, and what types of parks work best and for whom, we need to identify, describe, and categorise parks holistically. To do so, we used open data, including OpenStreetMap and Light Detection and Ranging (LiDAR) data, to measure six characteristics, identified from the literature as being important for well-being, in 1,638 parks in London: size, trail and pathway density, water cover, buildings and other anthropogenic features, horizontal vegetation coverage, and vertical vegetation structure. We used multi-dimensional clustering analysis to group five types of parks with similar characteristics. The clusters differed in the number of parks they included, their characteristics, and their spatial distribution across London. Linking our classification to an index of multiple deprivation reveals that provision of parks is uneven, and that relatively more deprived places have less provision of parks with factors often associated with wellbeing (in particular, larger parks containing water bodies). Furthermore, when we linked the 30 top-ranked parks in social media to our typology, we found that most of the top-ranked parks (34%) belonged to a small cluster of very large parks with a lot of water area. This cluster only made up 4% of all London parks.
{"title":"Characterising London parks and gardens using open data","authors":"Dace Kirsteina , Marie A.E. Mueller , Ross S. Purves","doi":"10.1016/j.ecolind.2025.113213","DOIUrl":"10.1016/j.ecolind.2025.113213","url":null,"abstract":"<div><div>Parks are open spaces planned and designed for leisure and recreation and together with other green spaces they have great value for people, especially in urban areas. To understand the spatial distribution of parks and green spaces, and what types of parks work best and for whom, we need to identify, describe, and categorise parks holistically. To do so, we used open data, including OpenStreetMap and Light Detection and Ranging (LiDAR) data, to measure six characteristics, identified from the literature as being important for well-being, in 1,638 parks in London: size, trail and pathway density, water cover, buildings and other anthropogenic features, horizontal vegetation coverage, and vertical vegetation structure. We used multi-dimensional clustering analysis to group five types of parks with similar characteristics. The clusters differed in the number of parks they included, their characteristics, and their spatial distribution across London. Linking our classification to an index of multiple deprivation reveals that provision of parks is uneven, and that relatively more deprived places have less provision of parks with factors often associated with wellbeing (in particular, larger parks containing water bodies). Furthermore, when we linked the 30 top-ranked parks in social media to our typology, we found that most of the top-ranked parks (34%) belonged to a small cluster of very large parks with a lot of water area. This cluster only made up 4% of all London parks.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"171 ","pages":"Article 113213"},"PeriodicalIF":7.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143394357","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-01DOI: 10.1016/j.ecolind.2025.113228
Jiangheng Qiu , Feng Liu , Decai Wang , Kun Yan , Junhui Guo , Weijie Huang , Yongkang Feng
Digital soil mapping based on the soil-landscape model can predict soil information using readily available environmental covariates such as topography and vegetation. However, its application in low-relief areas where topographic factors are relatively uniform and vegetation conditions are similar, is challenging. Meanwhile, geostatistical models often have better performance in low relief areas compared to topographically complex areas. Therefore, we hypothesized that the method of combining geostatistical modeling with soil-landscape modelling can achieve higher prediction accuracy. We comprehensively selected multiple environmental covariates suitable for the study area and compared four models: Inverse Distance Weighting (IDW), Ordinary Kriging (OK), Random Forest (RF), and Random Forest Regression Kriging (RF-RK). These models were used to predict six soil properties (clay, silt, and sand contents, pH, cation exchange capacity, and soil organic matter content) in the study area and evaluate their prediction accuracies. The results were as follows: (1) When the spatial autocorrelation of soil property data was weak, the RF model, which does not consider spatial autocorrelation, yielded more accurate predictions for clay content and soil pH, with R2 of 0.62 and 0.30, and a NRMSE of 0.46 and 0.08, respectively. (2) When the spatial autocorrelation was strong, the RF-RK model, which accounts for both the soil-environment relationship and spatial autocorrelation, provided more accurate results for sand and silt contents, cation exchange capacity, and soil organic matter content. The RF-RK model achieved R2 values of 0.81, 0.82, 0.79, and 0.69, and NRMSE values of 0.14, 0.09, 0.14, and 0.26, respectively. (3) Soil type and distance from the Yangtze River were the most important environmental variables explaining the spatial distribution of soil properties. The spatial heterogeneity of soil type and the geographical influence of the Yangtze River explained soil property variations better than other variables. This study highlights the potential of the integrated modeling approach for digital soil mapping in low relief areas. High-precision spatial maps of key soil attributes in the study area can provide critical data support for land planning and sustainable agricultural development.
{"title":"Mapping key soil properties in low relief areas using integrated machine learning and geostatistics","authors":"Jiangheng Qiu , Feng Liu , Decai Wang , Kun Yan , Junhui Guo , Weijie Huang , Yongkang Feng","doi":"10.1016/j.ecolind.2025.113228","DOIUrl":"10.1016/j.ecolind.2025.113228","url":null,"abstract":"<div><div>Digital soil mapping based on the soil-landscape model can predict soil information using readily available environmental covariates such as topography and vegetation. However, its application in low-relief areas where topographic factors are relatively uniform and vegetation conditions are similar, is challenging. Meanwhile, geostatistical models often have better performance in low relief areas compared to topographically complex areas. Therefore, we hypothesized that the method of combining geostatistical modeling with soil-landscape modelling can achieve higher prediction accuracy. We comprehensively selected multiple environmental covariates suitable for the study area and compared four models: Inverse Distance Weighting (IDW), Ordinary Kriging (OK), Random Forest (RF), and Random Forest Regression Kriging (RF-RK). These models were used to predict six soil properties (clay, silt, and sand contents, pH, cation exchange capacity, and soil organic matter content) in the study area and evaluate their prediction accuracies. The results were as follows: (1) When the spatial autocorrelation of soil property data was weak, the RF model, which does not consider spatial autocorrelation, yielded more accurate predictions for clay content and soil pH, with R<sup>2</sup> of 0.62 and 0.30, and a NRMSE of 0.46 and 0.08, respectively. (2) When the spatial autocorrelation was strong, the RF-RK model, which accounts for both the soil-environment relationship and spatial autocorrelation, provided more accurate results for sand and silt contents, cation exchange capacity, and soil organic matter content. The RF-RK model achieved R<sup>2</sup> values of 0.81, 0.82, 0.79, and 0.69, and NRMSE values of 0.14, 0.09, 0.14, and 0.26, respectively. (3) Soil type and distance from the Yangtze River were the most important environmental variables explaining the spatial distribution of soil properties. The spatial heterogeneity of soil type and the geographical influence of the Yangtze River explained soil property variations better than other variables. This study highlights the potential of the integrated modeling approach for digital soil mapping in low relief areas. High-precision spatial maps of key soil attributes in the study area can provide critical data support for land planning and sustainable agricultural development.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"171 ","pages":"Article 113228"},"PeriodicalIF":7.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143394359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rivers are among the most altered and impacted freshwater ecosystems on Earth, so that collective efforts should be fuelled by professionals and societies to implement their biomonitoring and conservation. Citizen science is recognized as a powerful approach but its application in river biomonitoring is still scarce, especially in Italy. This study was aimed at developing and validating a citizen science biomonitoring approach for river ecosystems based on the analysis of benthic macroinvertebrate communities. By using a calibration dataset composed of 932 sampling events performed by professionals, a simplified macroinvertebrate community was first obtained by selecting only 36 representative taxa. Four different, but routinely applied, metrics were calculated on both the simplified and calibration communities and showed strong and significant correlations. Thresholds for the four selected metrics were statistically derived and offered a good agreement in discriminating not-impacted and impacted conditions according to the official methodology. The performance of the proposed approach was validated on ten independent sampling campaigns with citizen science volunteers and compared to benchmark sites. Since 33 out of 36 taxa were recorded at least once, results showed that the simplified macroinvertebrate community was effective and representative. The ecological status assessment and the selected metrics were generally comparable to the values of the benchmark sites, despite some differences being observed depending on the metric. This study represents one of the first efforts in the direction of developing a citizen science macroinvertebrate-based methodology for river biomonitoring in Italy and it supports the adoption of a multi-metric approach.
{"title":"Bridging science and society: Developing a citizen science biomonitoring approach for river ecosystems in Italy","authors":"Samuele Roccatello , Alessandro Lagrotteria , Chiara Andrà , Alberto Doretto","doi":"10.1016/j.ecolind.2025.113199","DOIUrl":"10.1016/j.ecolind.2025.113199","url":null,"abstract":"<div><div>Rivers are among the most altered and impacted freshwater ecosystems on Earth, so that collective efforts should be fuelled by professionals and societies to implement their biomonitoring and conservation. Citizen science is recognized as a powerful approach but its application in river biomonitoring is still scarce, especially in Italy. This study was aimed at developing and validating a citizen science biomonitoring approach for river ecosystems based on the analysis of benthic macroinvertebrate communities. By using a calibration dataset composed of 932 sampling events performed by professionals, a simplified macroinvertebrate community was first obtained by selecting only 36 representative taxa. Four different, but routinely applied, metrics were calculated on both the simplified and calibration communities and showed strong and significant correlations. Thresholds for the four selected metrics were statistically derived and offered a good agreement in discriminating not-impacted and impacted conditions according to the official methodology. The performance of the proposed approach was validated on ten independent sampling campaigns with citizen science volunteers and compared to benchmark sites. Since 33 out of 36 taxa were recorded at least once, results showed that the simplified macroinvertebrate community was effective and representative. The ecological status assessment and the selected metrics were generally comparable to the values of the benchmark sites, despite some differences being observed depending on the metric. This study represents one of the first efforts in the direction of developing a citizen science macroinvertebrate-based methodology for river biomonitoring in Italy and it supports the adoption of a multi-metric approach.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"171 ","pages":"Article 113199"},"PeriodicalIF":7.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143388041","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-01DOI: 10.1016/j.ecolind.2025.113202
Xu Luo , Yingzhong Xie , Cui Han , Yaxin Zhao , Ying Zhao , Jianping Li
Diverse plant species are crucial for the sustenance of soil health and the facilitation of nutrient cycling by reconstructing the soil microbial communities and improving extracellular enzyme activities (EEAs). However, it is unclear whether the effect of plant species combination on the interaction between soil microbial communities and EEAs contributes to the improvement of soil quality. Therefore, we selected three dominant and seven subdominant plant species from the northern Yanchi desert steppe of Ningxia to assess plant species richness (monoculture and 4-, 6-, 8-, and 10-species mixtures). We found the following: (1) The number of ASVs of soil bacteria and fungi in monoculture was generally higher than that in mixed communities. Although the microbial abundance varied among plant species richness levels, the core microbial communities were the same. EEAs in monoculture were higher than species mixtures, but EEAs did not show a consistent trend with the increase of species richness. (2) Phylogenetic Investigation of Communities by Reconstruction of Unobserved States predicted 5 primary functions, encompassing 25 secondary functions dominated by bacterial metabolism, and 5 primary functions, encompassing 29 secondary functions dominated by fungal biosynthesis. (3) The Mantel test results demonstrated a strong correlation between soil carbon (C), nitrogen (N), and phosphorus (P) acquisition enzyme activities and the functional cellular processes of bacteria. (4) Structural equation modeling revealed that plant species richness directly negatively affected soil C, N, and P-acquiring enzyme activities. However, the functional activities of bacterial and fungal communities positively influenced soil organic carbon (SOC), total nitrogen (TN), and total phosphorus (TP) by indirectly regulating EEAs. The final model explained 69% of the SOC, 61% of the soil TN, and 25% of the soil TP. This study aimed to provide valuable data to support theoretical frameworks for conserving grassland biodiversity and maintaining soil health.
{"title":"Plant species richness increases the relationship between soil microbial and extracellular enzyme activities and enhances soil fertility","authors":"Xu Luo , Yingzhong Xie , Cui Han , Yaxin Zhao , Ying Zhao , Jianping Li","doi":"10.1016/j.ecolind.2025.113202","DOIUrl":"10.1016/j.ecolind.2025.113202","url":null,"abstract":"<div><div>Diverse plant species are crucial for the sustenance of soil health and the facilitation of nutrient cycling by reconstructing the soil microbial communities and improving extracellular enzyme activities (EEAs). However, it is unclear whether the effect of plant species combination on the interaction between soil microbial communities and EEAs contributes to the improvement of soil quality. Therefore, we selected three dominant and seven subdominant plant species from the northern Yanchi desert steppe of Ningxia to assess plant species richness (monoculture and 4-, 6-, 8-, and 10-species mixtures). We found the following: (1) The number of ASVs of soil bacteria and fungi in monoculture was generally higher than that in mixed communities. Although the microbial abundance varied among plant species richness levels, the core microbial communities were the same. EEAs in monoculture were higher than species mixtures, but EEAs did not show a consistent trend with the increase of species richness. (2) Phylogenetic Investigation of Communities by Reconstruction of Unobserved States predicted 5 primary functions, encompassing 25 secondary functions dominated by bacterial metabolism, and 5 primary functions, encompassing 29 secondary functions dominated by fungal biosynthesis. (3) The Mantel test results demonstrated a strong correlation between soil carbon (C), nitrogen (N), and phosphorus (P) acquisition enzyme activities and the functional cellular processes of bacteria. (4) Structural equation modeling revealed that plant species richness directly negatively affected soil C, N, and P-acquiring enzyme activities. However, the functional activities of bacterial and fungal communities positively influenced soil organic carbon (SOC), total nitrogen (TN), and total phosphorus (TP) by indirectly regulating EEAs. The final model explained 69% of the SOC, 61% of the soil TN, and 25% of the soil TP. This study aimed to provide valuable data to support theoretical frameworks for conserving grassland biodiversity and maintaining soil health.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"171 ","pages":"Article 113202"},"PeriodicalIF":7.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143420004","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-01DOI: 10.1016/j.ecolind.2025.113207
Anne Lyche Solheim, Jan-Erik Thrane, Sophie Mentzel, S. Jannicke Moe
Freshwater biological indicators are essential and required by the EU Water Framework Directive (WFD) to assess ecological impacts of human pressures and measures to restore degraded rivers and lakes. The level of degradation and how this level changes over time can be assessed by using the ecological quality ratio (EQR) for each major group of biological communities. The EQR is measuring the deviation from reference conditions found in pristine waters on a harmonized scale from 1 (undisturbed water bodies) to 0 (fully deteriorated water bodies). EQR values have been reported by many European countries to the European Environment Agency (EEA), for four biological quality elements (BQEs): phytobenthos and benthic invertebrates in rivers, and phytoplankton and macrophytes in lakes. Following internal data processing, normalization, quality checking and publication of the dataset, the EQR data can be used to analyse trends to assess whether biological communities are recovering. Here we report on trend analysis based on consistent time series of normalised EQR values (nEQR) for years 2015–2021 from 2500 rivers and 700 lakes. For each of the BQEs, the time series were grouped according to their initial status (i.e. ecological quality of the BQE in 2015). For the subset of rivers where phytobenthos and benthic invertebrates initially indicated poor or bad status, the overall trends were positive (Sen’s slope S = 0.027 and 0.014, respectively). Correspondingly, positive trends were also found for phytoplankton and macrophytes in lakes with initially poor or bad status (S = 0.009 and 0.014, respectively). Conversely, for water bodies with initial status high or good, negative trends were indicated for all BQEs (S in range −0.027−−0.011), although statistically significant only for phytobenthos and invertebrates. These preliminary results demonstrate the potential of these indicators in assessing effectiveness of European water policies. Nevertheless, longer time series will be needed for more robust assessment of trends in ecological quality of water bodies.
{"title":"Harmonised biological indicators for rivers and lakes: Towards European assessment of temporal trends in ecological quality","authors":"Anne Lyche Solheim, Jan-Erik Thrane, Sophie Mentzel, S. Jannicke Moe","doi":"10.1016/j.ecolind.2025.113207","DOIUrl":"10.1016/j.ecolind.2025.113207","url":null,"abstract":"<div><div>Freshwater biological indicators are essential and required by the EU Water Framework Directive (WFD) to assess ecological impacts of human pressures and measures to restore degraded rivers and lakes. The level of degradation and how this level changes over time can be assessed by using the ecological quality ratio (EQR) for each major group of biological communities. The EQR is measuring the deviation from reference conditions found in pristine waters on a harmonized scale from 1 (undisturbed water bodies) to 0 (fully deteriorated water bodies). EQR values have been reported by many European countries to the European Environment Agency (EEA), for four biological quality elements (BQEs): phytobenthos and benthic invertebrates in rivers, and phytoplankton and macrophytes in lakes. Following internal data processing, normalization,<!--> <!-->quality checking and publication of the dataset, the EQR data can be used to analyse trends to assess whether biological communities are recovering. Here we report on trend analysis based on consistent time series of normalised EQR values (nEQR) for years 2015–2021 from 2500 rivers and 700 lakes. For each of the BQEs, the time series were grouped according to their initial status (i.e. ecological quality of the BQE in 2015). For the subset of rivers where phytobenthos and benthic invertebrates initially indicated poor or bad status, the overall trends were positive (Sen’s slope <em>S</em> = 0.027 and 0.014, respectively). Correspondingly, positive trends were also found for phytoplankton and macrophytes in lakes with initially poor or bad status (<em>S</em> = 0.009 and 0.014, respectively). Conversely, for water bodies with initial status high or good, negative trends were indicated for all BQEs (<em>S</em> in range −0.027−−0.011), although statistically significant only for phytobenthos and invertebrates. These preliminary results demonstrate the potential of these indicators in assessing effectiveness of European water policies. Nevertheless, longer time series will be needed for more robust assessment of trends in ecological quality of water bodies.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"171 ","pages":"Article 113207"},"PeriodicalIF":7.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143420007","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-01DOI: 10.1016/j.ecolind.2025.113115
Aurelio D. Herraiz , Pablo Salazar-Zarzosa , Cristina Acosta-Muñoz , Rocío Hernández-Clemente , Rafael Villar
Land surface phenology is influenced by a complex interplay of various abiotic factors, including climatic, edaphic, and topographic conditions, along with biotic factors such as competition or species composition. It is particularly important to recognize the varied phenological responses of forest species to aridity, which reflect their different adaptations to climate change. Traditional field measurements may not effectively capture these phenological changes across extensive regions. Thus, this study aims to analyse the key phenological indicators of the ten most common Mediterranean forest species using remote sensing data. Specifically, we will investigate how aridity affects these indicators in areas like Southern Spain, where aridity levels are expected to rise, and we will track their changes over time. To achieve this, we processed the maximum monthly Normalized Difference Vegetation Index (NDVI) data from 1994 to 2021, obtained from Landsat 05 and 07 satellites for 2,358 plots of the Spanish National Forest Inventory in Andalucia (Southern Spain). Evergreen species showed the Start Of Season (SOS) in autumn with maximums NDVI in winter (December-February) and the End Of Season (EOS) in late spring with minimums NDVI in summer (June-August), indicating the important effect of precipitation on the physiological response of Mediterranean vegetation. Over the 28-year analysis period, a general positive trend in NDVI (greening) and its associated phenological metrics was observed for most species. However, aridity impacts surface phenology differently among Mediterranean species, notably shortening the growth season of Scots pine and causing significant seasonal phenology shifts in Cork oak, Stone pine, and Aleppo pine. These findings suggest that time-series Landsat data enhances our understanding of forest dynamics and aridity’s effects on vegetation. Remote sensing of forest species’ responses to aridity is crucial for resilience studies and species management in global change scenarios.
{"title":"Aridity-induced phenological shifts and greening trends in Mediterranean forest species: Insights from 28 years of Landsat data in southern Spain","authors":"Aurelio D. Herraiz , Pablo Salazar-Zarzosa , Cristina Acosta-Muñoz , Rocío Hernández-Clemente , Rafael Villar","doi":"10.1016/j.ecolind.2025.113115","DOIUrl":"10.1016/j.ecolind.2025.113115","url":null,"abstract":"<div><div>Land surface phenology is influenced by a complex interplay of various abiotic factors, including climatic, edaphic, and topographic conditions, along with biotic factors such as competition or species composition. It is particularly important to recognize the varied phenological responses of forest species to aridity, which reflect their different adaptations to climate change. Traditional field measurements may not effectively capture these phenological changes across extensive regions. Thus, this study aims to analyse the key phenological indicators of the ten most common Mediterranean forest species using remote sensing data. Specifically, we will investigate how aridity affects these indicators in areas like Southern Spain, where aridity levels are expected to rise, and we will track their changes over time. To achieve this, we processed the maximum monthly Normalized Difference Vegetation Index (NDVI) data from 1994 to 2021, obtained from Landsat 05 and 07 satellites for 2,358 plots of the Spanish National Forest Inventory in Andalucia (Southern Spain). Evergreen species showed the Start Of Season (SOS) in autumn with maximums NDVI in winter (December-February) and the End Of Season (EOS) in late spring with minimums NDVI in summer (June-August), indicating the important effect of precipitation on the physiological response of Mediterranean vegetation. Over the 28-year analysis period, a general positive trend in NDVI (greening) and its associated phenological metrics was observed for most species. However, aridity impacts surface phenology differently among Mediterranean species, notably shortening the growth season of Scots pine and causing significant seasonal phenology shifts in Cork oak, Stone pine, and Aleppo pine. These findings suggest that time-series Landsat data enhances our understanding of forest dynamics and aridity’s effects on vegetation. Remote sensing of forest species’ responses to aridity is crucial for resilience studies and species management in global change scenarios.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"171 ","pages":"Article 113115"},"PeriodicalIF":7.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143334110","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Wetlands are among the most important and productive ecosystems, offering both ecological and socioeconomic benefits. It is essential to understand the ecosystem services (ESs) offered by wetlands for their efficient conservation and sustainable use. Ethiopia has a lot of wetland resources, but little is known about their ESs. Therefore, the purpose of this study was to assess the ESs provided by six (Geray, Gudera, Infranze, Kurt_Bahir, Wonjeta and Zindib) wetlands in the upper Abbay River basin, Ethiopia.The data were collected from 377 household heads through face-to-face interviews using 4-point Likert-type scale question items. Rapid assessment of wetland ecosystem service (RAWES) approach was applied to triangulate the data collected through cross-sectional household survey. Descriptive statistics was applied to analyze household survey and the RAWES data. Kruskal-Wallis test was used to analyze the differences among the ESs provided by the wetlands whereas; Mann-Whitney U test was used to analyze the difference between the mean score of survey and RAWES data. The findings of both the RAWES and the survey data revealed that the wetlands provide various provisioning services; particularly water for livestock, other domestic purposes and irrigation crop production, livestock fodder and seedling raising. The importance of all the wetlands in delivering these provisioning services was not similar. As confirmed by Kruskal-Wallis test, the differences among the six wetlands were statistically significant (p < 0.05). Infranze wetland was found to be the most important wetland whereas Zindib wetland was the least. The importance of the wetlands in providing regulating, cultural and supporting services was recognized by significant number of respondent; although most of them rated the delivery of these ESs as ‘low’. The views of participants of RAWES on the contribution of the wetlands to regulating, cultural and supporting services, however, were different from the respondents’ views. Mann-Whitney U test confirmed that the differences are statistically significant. This indicated that the respondents had low understanding towards these ESs of the wetlands may be due to their low educational level. Therefore, increasing the society’s awareness towards the non-material benefits of the wetlands is crucial for their sustainable utilization.
{"title":"Ecosystem services of wetlands in the upper Abbay River basin, Ethiopia","authors":"Getachew Fentaw , Getachew Beneberu , Ayalew Wondie , Belachew Getnet Eneyew","doi":"10.1016/j.ecolind.2025.113142","DOIUrl":"10.1016/j.ecolind.2025.113142","url":null,"abstract":"<div><div>Wetlands are among the most important and productive ecosystems, offering both ecological and socioeconomic benefits. It is essential to understand the ecosystem services (ESs) offered by wetlands for their efficient conservation and sustainable use. Ethiopia has a lot of wetland resources, but little is known about their ESs. Therefore, the purpose of this study was to assess the ESs provided by six (Geray, Gudera, Infranze, Kurt_Bahir, Wonjeta and Zindib) wetlands in the upper Abbay River basin, Ethiopia.The data were collected from 377 household heads through face-to-face interviews using 4-point Likert-type scale question items. Rapid assessment of wetland ecosystem service (RAWES) approach was applied to triangulate the data collected through cross-sectional household survey. Descriptive statistics was applied to analyze household survey and the RAWES data. Kruskal-Wallis test was used to analyze the differences among the ESs provided by the wetlands whereas; Mann-Whitney <em>U</em> test was used to analyze the difference between the mean score of survey and RAWES data. The findings of both the RAWES and the survey data revealed that the wetlands provide various provisioning services; particularly water for livestock, other domestic purposes and irrigation crop production, livestock fodder and seedling raising. The importance of all the wetlands in delivering these provisioning services was not similar. As confirmed by Kruskal-Wallis test, the differences among the six wetlands were statistically significant (p < 0.05). Infranze wetland was found to be the most important wetland whereas Zindib wetland was the least. The importance of the wetlands in providing regulating, cultural and supporting services was recognized by significant number of respondent; although most of them rated the delivery of these ESs as ‘low’. The views of participants of RAWES on the contribution of the wetlands to regulating, cultural and supporting services, however, were different from the respondents’ views. Mann-Whitney <em>U</em> test confirmed that the differences are statistically significant. This indicated that the respondents had low understanding towards these ESs of the wetlands may be due to their low educational level. Therefore, increasing the society’s awareness towards the non-material benefits of the wetlands is crucial for their sustainable utilization.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"171 ","pages":"Article 113142"},"PeriodicalIF":7.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143359167","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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