Predicting persistence of Rio Grande Cutthroat Trout populations in an uncertain future

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Predicting persistence of Rio Grande Cutthroat Trout populations in an uncertain future


The Rio Grande Cutthroat Trout Oncorhynchus clarkii virginalis (RGCT) occupies just 12% of its ancestral range. As the southernmost subspecies of Cutthroat Trout, we expect a warming climate to bring additional stressors to RGCT populations, such as increased stream temperatures, reduced streamflows, and increased incidence of wildfire. We developed a Bayesian network (BN) model using site-specific data, empirical research, and expert knowledge to estimate the probability of persistence for each of the 121 remaining RGCT conservation populations and to rank the severity of the threats they face. These inputs quantified the genetic risks (e.g., inbreeding risk and hybridization risk), population demographics (disease risk, habitat suitability, and survival), and probability of stochastic disturbances (stream drying risk and wildfire risk) in an uncertain future. We also created stream temperature and base flow discharge models coupled with regionally downscaled climate projections to predict future abiotic conditions at short-term (2040s) and long-term (2080s) time horizons. In the absence of active management, we predicted a decrease in the average probability of population persistence from 0.53 (current) to 0.31 (2040s) and 0.26 (2080s). Only 11% of these populations were predicted to have a greater than 75% chance of persisting to the 2080s. Threat of invasion by nonnative trout had the strongest effect on population persistence. Of the 78 populations that are already invaded or lacking complete barriers, 60% were estimated to be extirpated by 2080 and the remainder averaged only a 10% chance of persistence. In contrast, the effects of increased stream temperatures were predicted to affect the future persistence of only 9% of the 121 RGCT populations remaining, as most have been restricted to high-elevation habitats that are cold enough to buffer against some stream warming. Our BN model provides a framework for evaluating threats and will be useful to guide management actions that are likely to provide the most benefit for long-term conservation.

Bibliographic Citation


Zeigler, Matthew P.
Rogers, Kevin B.
Roberts, James J.
Todd, Andrew S.
Fausch, Kurt D.


Rio Grande Cutthroat Trout
Oncorhynchus clarkii virginalis
Bayesian network model


30 pages

Date Created








Is Part Of

North American Journal of Fisheries Management



Zeigler, Matthew P. et al., “Predicting persistence of Rio Grande Cutthroat Trout populations in an uncertain future,” CPW Digital Collections, accessed February 27, 2024,