Species distribution models and model performance evaluations of twenty-four fishes native to Pacific Northwest US
April 17, 2025
This data release provides spatial data for species distribution models developed for 24 stream fishes native to the Pacific Northwest, USA and associated model evaluation metrics used to determine the best supported model. These models support a larger analysis for understanding native stream fish vulnerability in the region, specifically population viability analyses built to determine species extinction risk. The models were developed using the Maximum Entropy (MaxEnt) machine learning approach. This approach is best suited for the presence only occurrence data available for our analyses. The point occurrences representing presences in the models were previously collated for the Pacific Northwest Rarity and Climate Sensitivity Index (Moore et al., 2025). The environmental predictors used to develop the models were chosen based on a combination of biological relevance to the included species and being uncorrelated with other selected predictors. Models were predicted across two possible extents for each species, the extent of the species' IUCN range polygon if available or the extent of a convex hull of occurrence records used to build the model.
Citation Information
Publication Year | 2025 |
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Title | Species distribution models and model performance evaluations of twenty-four fishes native to Pacific Northwest US |
DOI | 10.5066/P13QTXJG |
Authors | Chloe E Moore, Meryl Mims, Jason Dunham, Joseph R Benjamin, Kristin L Jaeger, Patricia Haggerty |
Product Type | Data Release |
Record Source | USGS Asset Identifier Service (AIS) |
USGS Organization | Forest and Rangeland Ecosystem Science Center (FRESC) Headquarters |
Rights | This work is marked with CC0 1.0 Universal |
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Jason B Dunham
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Joseph R Benjamin
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Jason B Dunham
Supervisory Research Ecologist
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Joseph R Benjamin
Research Biologist
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Phone