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Applying ecological thresholds to inform conservation and restoration efforts for stream fishes

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Zenodo2026-06-24 更新2026-05-26 收录
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Understanding stream fish responses to landscape stressors is fundamental to designing management strategies to conserve and restore fluvial ecosystems. Landscape stressors, including agricultural, pasture, and urban land use, often elicit threshold responses in stream fishes, causing rapid declines in abundance with comparatively small increases in stressor intensity. However, the use of thresholds to inform conservation and restoration decision-making remains limited, particularly when targeting entire stream fish assemblages at continental spatial extents. Here, we apply known threshold values to characterize the vulnerability of stream fishes across approximately 1.73 million stream reaches in the United States and Europe. We develop a decision-support framework that integrates threshold status indices with network catchment summaries of protected area coverage to prioritize (a) conservation actions in poorly protected catchments approaching land use thresholds, and (b) restoration actions in catchments that have exceeded thresholds despite high protected area coverage. Our findings highlight the vulnerability of stream fishes to landscape stressors across two continents and demonstrate how integrating threshold-based vulnerability assessments with protected area summaries can support management decision-making and help address the freshwater biodiversity crisis. We provide the complete spatial dataset produced by applying this decision-support framework in 19 Freshwater Ecoregions of the World (FEOW) across the United States and Europe, using the thresholds reported in Table 1. The dataset consists of two vector files in the GPKG format, which include separate layers for each FEOW. These layers may be reproduced using the decision-support framework function ("dsf_function.R") by supplying "eu.catchment.vector.gpkg" or "us.catchment.vector.gpkg" as inputs and specifying an abbreviated FEOW name.

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Zenodo
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2026-05-21
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