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| Created: | Jul 25, 2023 at 12:32 a.m. | |
| Last updated: | Sep 30, 2024 at 12:27 a.m. | |
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| Sharing Status: | Public |
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Abstract
Aquatic habitat suitability models are increasingly coupled with water management models to estimate environmental effects of water management. Many types of habitat models exist, but there are no standard methods to compare predictive performance of habitat model types for use with water management models. In this study, we compared three common aquatic habitat model types: a hydraulic-habitat model, a habitat threshold model, and a geospatial model. Each of the models predicted native Bonneville Cutthroat Trout distribution in the Bear River Watershed (Utah, Idaho, and Wyoming, USA) at a monthly timestep. We compared the differences in predictive performance among models by validating 1) environmental predictors of the models with field observations from summer 2022, using the coefficient of determination (R²), Nash–Sutcliffe efficiency (NSE) index, and percent bias (PBIAS) and 2) habitat suitability estimates generated by each model with fish presence data and three accuracy metrics developed for this study. Validation of environmental predictors revealed observed conditions were not well represented by any of the three models—a function of either outdated, incorrect, or over-generalized input data. Validation of habitat suitability predictions using Bonneville Cutthroat Trout presence data showed the habitat threshold model most accurately classified fish presence observations in suitable habitat, but suitable habitat was likely overpredicted. While more precise habitat modeling methods may be useful to support generalized habitat estimates for native fish, overall, simple models, like the habitat threshold model, are promising for incorporating ecological objectives into water management models.
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This resource was created using funding from the following sources:
| Agency Name | Award Title | Award Number |
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| National Science Foundation | CAREER: Robust aquatic habitat representation for water resources decision-making | Award # 1653452 |
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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