Developing Fluvial Fish Species Distribution Models Across the Conterminous United States—A Scientific Framework to Support Management and Conservation

Scientific Investigations Report 2023-5088
Science Analytics and Synthesis Program
Prepared in cooperation with Department of Fisheries and Wildlife, Michigan State University
By: , and 



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 freshwater portions of the ranges for species represented 28 families. Cyprinidae was the family with the most species (87 of 271) modeled for this study, followed by Percidae (34) and Ictaluridae (17). Model predictive performance was evaluated using four metrics: area under the receiver operating characteristic curve, sensitivity, specificity, and True Skill Statistic, which are all from tenfold cross-validation results. The relative importance of the predictor variables in the boosted regression tree models was calculated and ranked for each species. The three strongest natural predictors of fish distributions were network catchment area, the mean annual air temperature of the local catchment, and the maximum elevation of the local catchment, while the three strongest anthropogenic predictors were downstream main stem dam density, distance to downstream main stem dam, and the percentage of pasture/hay land use area within network catchment boundaries. Study results showed 61 fish species were sensitive to climate variables, and 40 fish species were sensitive to anthropogenic stressors. The models developed in this study can be used to derive critical information regarding habitat protection priorities, anthropogenic threats, and potential effects of climate change on habitat suitability, aiding in efforts to conserve fluvial fishes now and into the future.

Suggested Citation

Yu, H., Cooper, A.R., Ross, J., McKerrow, A., Wieferich, D.J., and Infante, D.M., 2023, Developing fluvial fish species distribution models across the conterminous United States—A framework for management and conservation: U.S. Geological Survey Scientific Investigations Report 2023–5088, 41 p.,

ISSN: 2328-0328 (online)

Study Area

Table of Contents

  • Acknowledgments
  • Abstract
  • Introduction
  • Materials and Methods
  • Results
  • Discussion
  • Summary
  • Data Access
  • References Cited
  • Appendix 1. Fluvial Fish for Which Insufficient Occurrence Data Were Available to Support Species Distribution Modeling
Publication type Report
Publication Subtype USGS Numbered Series
Title Developing fluvial fish species distribution models across the conterminous United States—A framework for management and conservation
Series title Scientific Investigations Report
Series number 2023-5088
DOI 10.3133/sir20235088
Year Published 2023
Language English
Publisher U.S. Geological Survey
Publisher location Reston VA
Contributing office(s) Science Analytics and Synthesis
Description Report: vii, 41 p.; Data Release
Country United States
Other Geospatial Conterminous United States
Online Only (Y/N) Y
Google Analytic Metrics Metrics page
Additional publication details