Ecological Indicators生态指标
Ecological Indicators(英文缩写 ECOL INDIC),ISSN 1470-160X,eISSN 1872-7034,中文译名:生态指标 是一本学术期刊。本页汇总该期刊的最新影响因子、分区信息以及最新收录于 PubMed 的文献,帮助您快速了解期刊全貌。
发文量统计区间：2025-09-27 至 2026-09-27，按本站收录文献的发表日期统计。
期刊介绍
历年影响因子趋势
| JCR 数据年份 | 影响因子 | JCR 分区 |
|---|---|---|
| 2021 | 6.263 | Q1 |
| 2022 | 6.900 | Q1 |
| 2023 | 7.000 | Q1 |
| 2024 | 7.400 | Q1 |
| 2025 | 8.700 | Q1 |
Ecological Indicators 最新收录文献
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1. Identifying algal indicators for streamflow duration assessment methods in forested headwater streams.
PMID:日期:2026-08-01Streamflow duration assessment methods (SDAMs) are rapid tools for reach-scale streamflow duration classification. SDAMs use single-visit indicator data as surrogates because direct measurement of long-term flow duration is resource intensive. Algae (diatoms and soft-bodied algae) are potentially strong indicators of streamflow-duration class (SDC) because of geographical ubiquity and biodiversity across moisture gradients. Algal cover and algal assemblage data (presence/absence, density, and biovolume) at species- and genus-levels were analyzed from 508 samples across 22 ephemeral, 37 intermittent, and 51 perennial reaches distributed along 31 forested headwater streams within 4 ecoregions in the contiguous United States. Random forest models using species- and genus-level datasets to predict SDCs had classification accuracy ranging from 69.5% - 88.4%, with accuracy being highest for density, intermediate for presence/absence, lowest for biovolume data. Species-level models had 0.6% - 5.9% higher accuracy for density and presence/absence datasets than genus-level models. Based on their median ranks of minimum node depth among random forest models, season (wet vs dry) was a more important factor than habitat sampled (erosional vs depositional) when distinguishing ephemeral, intermittent and perennial but habitat was more important when distinguishing ephemeral from non-ephemeral reaches. Algal cover index (categorical visual-tactile assessment) was the most important indicator of SDC. Except for the red alga, , the identified indicator taxa were diatoms. Our findings support epilithic algal cover as an SDAM indicator for forested headwater streams. Until taxonomic tools are available for field identifications, algal cover index and abundance of soft-bodied algae and live diatoms may be candidate indicators for regional SDAMs.
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2. Site selection algorithms for optimal ecological monitoring design.
PMID:日期:2025-09-01Comprehensive monitoring of biodiversity to direct conservation action is foundational to addressing the ongoing biodiversity crisis. As integrative monitoring programs increasingly come online in response to multilateral biodiversity agreements, establishing best practices for optimal design is critical. Appropriately selecting monitoring locations is fundamental for producing robust biodiversity data. Despite extensive development of algorithms to systematically select sites, practical discussions of which algorithm is optimal for different monitoring settings is largely absent from the literature. Here, we benchmark the performance of four common selection algorithms, outline the characteristics of the suite of algorithms suitable for ecological monitoring design, and offer recommendations for their best use under different constraints on network design. While all algorithms outperformed simple random samples, performance differences were negligible between algorithms. We recommend instead that practitioners choose algorithms based on feature availability, which varies greatly between algorithms.
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3. Tower-to-global upscaling of terrestrial carbon fluxes driven by MODIS-LAI, Sentinel-3-LAI and ERA5-Land data.
PMID:日期:2025-08-01Recent efforts in upscaling terrestrial carbon fluxes (TCFs) from eddy covariance (EC) flux towers have gained momentum with machine learning, capturing complex relationships between TCFs and their driving variables. We applied Gaussian process regression (GPR) models to upscale TCF products from tower-to-global scale and studied the predictive capacity of climate variables and leaf area index (LAI) across biomes (2004-2023). The developed GPR models (EC-GPR-TCFs) were trained with FLUXNET data, including gross primary productivity, ecosystem respiration, and net ecosystem exchange. LAI field measurements were combined with climate variables observed at EC towers, including soil variables at varying depths. Upscaling was realized in Google Earth Engine at varying spatial resolutions from 300 m to 5 km, employing the EC-GPR-TCFs models with the MCD15A3H-LAI product from MODIS, the S3-TOA-GPR-LAI product derived from Sentinel-3 (S3) and ERA5-Land climate data. Tower data availability for training and validating the model is reduced when combining multiple variables and measurements, a challenge addressed by the EC-GPR-TCFs models. Bidecadal temporal correlation analysis (2004-2023) between TCFs and predictor variables highlighted three key variables for estimating TCFs: LAI, shortwave incoming solar radiation (SW), and latent heat flux (LE), with the strongest correlations in forests of temperate and cold climates. Multi-year (2019-2023) intercomparison of EC-GPR-TCFs estimations against EC towers data for validation revealed consistent results with and generally around 0.6 and below 3 μmol m s, respectively. At the global scale, decadal (2010-2020) intercomparison against four benchmark TCF products (LPJ-GUESS, MOD17A2H, FLUXCOM, and SCOPE-GPR-TCFs) resulted in varying fits with corresponding median and values in the ranges 0.7-0.85; 1.97-4.36 μmol m s for GPP and 0.81-0.85; 2.20-3.38 μmol m s for RECO. Our analysis offers a deeper understanding of how climate predictors influence TCFs across biomes, providing a new perspective on TCF upscaling methodologies.
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4. Charting a course for freshwater biomonitoring: The grand challenges identified by the global scientific community.
PMID:日期:2025-07-01The past 50 years have seen biomonitoring emerge as an essential means of generating the knowledge needed to inform protection and restoration of freshwater ecosystems. Despite the successes of biomonitoring, most freshwater ecosystems remain unmonitored. Moreover, degradation of freshwaters continues at a rapid rate with new threats and novel stressors emerging that are difficult to assess using existing techniques. New technologies and techniques have been developed to improve biomonitoring, but application has been slow and integration with existing approaches is often problematic. Clearly, freshwater biomonitoring faces many important challenges that must be addressed to meet management needs of the coming decades. We identify Grand Challenges facing freshwater biomonitoring with the aim of encouraging research and practice to address these challenges. We asked 256 biomonitoring scientists from around the globe to identify what they considered the most important challenges. From their submissions we established five Grand Challenges and 18 associated subchallenges. For each Grand Challenge, we outline the current state of biomonitoring practice and suggest promising pathways and approaches to address them. By identifying and describing these challenges, we strive to position freshwater biomonitoring to take advantage of emerging opportunities and enhance its capacity to meet current and future management needs.
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5. Unveiling two millennia of ecosystem changes in the Azores through elementome trajectory analysis.
PMID:日期:2025-07-01The elemental composition of ecosystems responds to environmental perturbations such as land-use change, offering valuable insights into the impacts of global change. This study applies trajectory analysis to two millennia of elemental composition (elementome), including carbon (C), nitrogen (N), and other geochemical elements records from five lakes in the Azores archipelago. By integrating multivariate elemental data, we aim to reconstruct past environmental shifts and understand long-term ecosystem dynamics in response to anthropogenic and non-anthropogenic impacts. We quantified elementome trajectory analysis metrics, such as elemental turnover, trajectory directionality, and trajectory speed, as ecological indicators to quantify the magnitude and graduality of island ecosystem disturbances. We also tracked elemental shifts over time using CONISS analysis and compared these shifts with previously published environmental reconstructions from the same lakes. Additionally, we analyzed and compared trajectory shapes across the lakes to identify patterns and differences. Our results indicate that the elementome trajectories primarily reflected changes in erosion rates, in-lake biological activity, and catchment dynamics, characterized by distinct patterns of climate variability, wildfires, and agropastoral activities. Trajectory shapes revealed different patterns across shallow and deeper lakes. Our findings demonstrate the utility of Elementome Trajectory Analysis for disentangling the complex interplay between natural and anthropogenic drivers of ecosystem change in island environments, providing a powerful new tool for paleoecological reconstructions and for monitoring changes at a catchment level.
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6. Ecological condition of mountain lakes in the conterminous United States and vulnerability to human development.
PMID:日期:2025-04-01Mountain lakes provide cultural, aesthetic, and recreational services across the globe. Despite their recognized importance, there is no consistent definition of a mountain lake, which hampers describing them individually as well as in aggregate. Additionally, it makes it difficult to study and manage this unique population. We develop a rules-based approach for classifying mountain lakes according to the topography of the area draining directly to the lake. We apply the approach to the data from the United States National Lakes Assessment, for which the population is defined as lakes that are at least 1 ha in surface area and at least 1 m deep in the conterminous US (CONUS). Leveraging this national assessment allows for evaluating the condition of mountain lakes relative to all lakes in the CONUS. There are an estimated 12,353 (95 % C.I. 10,529-14,177) mountain lakes that account for 6.4 % of the lake population in the CONUS. Mountain lakes are in better condition than non-mountain lakes for 11 of 12 physical, chemical, and biological indicators (acid neutralizing capacity was the one exception). Approximately 25 % of mountain lakes are classified as eutrophic or hypereutrophic, and nearly 50 % are in fair or poor condition with respect to riparian vegetation and lakeshore disturbance. Mountain lake watersheds have lower proportions of developed land cover (mean ± 95 % CI: 0.8 ± 0.1 %) compared to non-mountain lakes (6.7 ± 0.3 %); however, developed land cover is more concentrated closer to the lakeshore for mountain lakes compared to non-mountain lakes. Coupled with characteristics such as high runoff, low hydraulic conductivity, and shallow bedrock depths, mountain lakes may be more susceptible to the adverse effects of human development and climate change compared to non-mountain lakes. These findings underscore the need for targeted monitoring, conservation, and management strategies to protect these valuable and sensitive lake environments.
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7. A social-ecological-technological vulnerability approach for assessing urban hydrological risks.
PMID:日期:2025-04-01In the context of urban population growth and climate change, and ever greater number of people are anticipated to face severe risks associated with extreme climate events; major ones are due to stormwater-related hazards. This study offers novel understanding of the complex nature of water-related risks in urban geographies by employing a Social-Ecological-Technological Systems (SETS) framework to assess vulnerabilities. Hydrology-informed urban risk index was developed, quantifying seventeen indicators from historical and modeled data on sewer overflow and flood events. The spatially explicit SETS-based approach identifies high-risk communities and hotspots where multiple vulnerabilities intersect and can serve as a valuable tool for guiding policy and decision-making to support more resilient urban futures. Our findings reveal that social vulnerability plays a critical role in determining the overall risk (R = 0.4), with the greatest impacts imposed on socially vulnerable communities. However, insights from the ecological (R = 0.2) and technological (R = 0.1) domains provide essential guidance for future risk reduction strategies-such as upgrading outdated sewer infrastructure and exploring green space potential for run-off mitigation. The framework proposed is generalizable to other cities facing similar environmental challenges, highlighting its potential as a foundational tool for policymaking to reduce risks associated with extreme climate events.
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8. Striving for consistency in a national lake assessment: defining reference status and littoral macroinvertebrate condition in lakes across the conterminous United States.
PMID:日期:2025-01-01Benthic macroinvertebrates are widely used for assessing lotic ecosystems, however, their use in assessing lake condition has been more limited-especially at large, continental extents. We used data collected during the U.S. EPA's National Lake Assessment between 2007-2022 to develop and validate a national macroinvertebrate multi-metric index (MMI) of lake condition across the conterminous U.S. As part of that process, we identified least-disturbed ecoregional reference lakes by filtering all sampled lakes by using specific physical, chemical, and disturbance variables to remove disturbed lakes. To account for natural variability, different criteria values were used for each of the nine national ecoregions. This allowed for a regionally explicit and reproducible definitions of lake reference condition for current and future analyses. Because of insufficient reference lake numbers in some of the nine ecoregions, macroinvertebrate MMI development was done independently for each of five aggregate national ecoregions. All 126 candidate macroinvertebrate metrics were screened for reproducibility, responsiveness, and redundancy to identify the best metric in each of six group types: composition, diversity, feeding group, habit, richness, and pollution tolerance for each ecoregion. The six chosen metrics were summed to calculate the MMI. Condition benchmarks (good/fair/poor) for assessing biological condition were defined for each ecoregion based on reference lake MMI percentiles. Using these five MMIs with the 2022 survey data, an estimated 44% of the lakes were in good condition, whereas 27% were in poor condition. Our MMIs offer managers valuable tools for assessing lakes at large ecoregional and continental extents.
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9. Improved thermal preferences and a stressor index derived from modeled stream temperatures and regional taxonomic standards for freshwater macroinvertebrates of the Pacific Northwest, USA.
PMID:日期:2024-03-11Benthic macroinvertebrate taxa vary in their sensitivities to water quality and habitat conditions, contributing to their extensive use as ecological indicators. As climate change and landscape alteration increasingly impact stream temperatures, interest is growing in expanding our knowledge of how macroinvertebrates are affected by current and future thermal conditions. Using samples from 3501 sites, we evaluated relationships between macroinvertebrate taxa and modeled stream temperatures across Oregon and Washington, in the U.S. Pacific Northwest. We used Maximum Weekly Maximum Temperature (MWMT) values from the NorWeST temperature dataset, which is the same metric used for numeric water temperature standards in Oregon and Washington. MWMT captures peak thermal stress, when cold-water adapted aquatic biota are closest to their upper physiological limits. For each macroinvertebrate taxon, we characterized relationships between MWMT and their distributions with three measures: 1) central thermal tendency, based on weighted average (WA) optima calculations and relative abundance data; 2) lower and upper thermal limits, based on the 10th and 90th percentiles of taxon occurrence, using presence data; and 3) thermal sensitivity curve shape, based on Generalized Additive Model (GAM) plots. We assigned 521 taxa, from species to phyla, to seven thermal preference categories, ranging from cold and warm stenotherms (narrow range) to eurythermal (wide range). Thermal sensitivity and variability within each taxonomic group were identified for establishing taxonomic targets for regional monitoring programs. We also developed the Macroinvertebrate Thermal Tolerance Index (MTTI) to represent the assemblage-level response to available thermal habitats, using WA optima and relative abundances for 324 taxa. The MTTI model had a strong relationship with modeled temperatures (R = 0.68) and a root-mean-square-error of 2.5 °C. Our work builds on previous regional and national efforts to identify thermal indicator taxa by using modeled stream network temperatures and a thermal metric that corresponds directly to regional water temperature standards. Both the taxa thermal preferences and the MTTI can be used to help identify causes of biological impairment, prioritize restoration and protection actions, and monitor assemblage-wide changes in thermal tolerance over time.
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10. Methods for a composite ecological suitability measure to inform cumulative restoration assessments in Gulf of Mexico estuaries.
PMID:日期:2023-10-01Ecosystem management requires a systematic, holistic approach that considers ecological and social outcomes. Effective restoration practices promote a balance of ecological and social goals by addressing ecological integrity, efficiently maximizing benefits while minimizing investment, and encompassing collaborative stakeholder engagement. Socio-ecological assessments can inform adaptive management and be utilized to prioritize restoration activities and monitor restoration effectiveness. In estuarine systems, socio-ecological assessments should evaluate the ability of habitats to support both ecologically and locally important species. The composite measure presented utilizes a combination of ecological and social measures to characterize ecological suitability for individual and multiple Gulf of Mexico estuarine species. The ecological suitability value (ES) for a given spatial unit is based on a suite of biophysical measures of the quality and extent of suitable habitat for each species, the species' trophic importance in a food web context, and the importance of each species in relation to stakeholder values and benefits. ES values for individual spatial units can be aggregated to estimate the distribution of ecological suitability at the estuarine scale. The ES values are calculated using examples for each step in the process. The information provided by ecological suitability characterizations can support restoration prioritization decisions for Gulf of Mexico estuaries and can provide a baseline measure to gauge restoration effectiveness over time to inform cumulative restoration assessments.