Aquatic Gap Analysis Project (AGAP) Aquatic Species Distribution Modeling on the National Hydrography Dataset Plus Version 2.1
August 2, 2022
This USGS data release contains products that resulted from aquatic species distribution modeling in the United States on the National Hydrography Dataset Plus Version 2.1. Source data, supporting code and model results are documented in this data release. The file species_model_list.csv provides a list of most recent models for each combination of species, habitat, and region.
Citation Information
Publication Year | 2022 |
---|---|
Title | Aquatic Gap Analysis Project (AGAP) Aquatic Species Distribution Modeling on the National Hydrography Dataset Plus Version 2.1 |
DOI | 10.5066/P94XM9XV |
Authors | Daniel J Wieferich, Alexa McKerrow, Arthur Cooper, Hao Yu, Jared A. Ross, Dana M. Infante |
Product Type | Data Release |
Record Source | USGS Asset Identifier Service (AIS) |
USGS Organization | Science Analytics and Synthesis Program |
Rights | This work is marked with CC0 1.0 Universal |
Related
Developing fluvial fish species distribution models across the conterminous United States—A framework for management and conservation
This report explains the steps and specific methods used to predict fluvial fish occurrences in their native ranges for the conterminous United States. In this study, boosted regression tree models predict distributions of 271 ecologically important fluvial fish species using relations between fish presence/absence and 22 natural and anthropogenic landscape variables. Models developed for the fres
Authors
Hao Yu, Arthur R. Cooper, Jared Ross, Alexa McKerrow, Daniel J. Wieferich, Dana M. Infante
Related
Developing fluvial fish species distribution models across the conterminous United States—A framework for management and conservation
This report explains the steps and specific methods used to predict fluvial fish occurrences in their native ranges for the conterminous United States. In this study, boosted regression tree models predict distributions of 271 ecologically important fluvial fish species using relations between fish presence/absence and 22 natural and anthropogenic landscape variables. Models developed for the fres
Authors
Hao Yu, Arthur R. Cooper, Jared Ross, Alexa McKerrow, Daniel J. Wieferich, Dana M. Infante