Application of multiple‐population viability analysis to evaluate species recovery alternatives
2020
Neville, Helen M. | Leasure, Douglas R. | Dauwalter, Daniel C. | Dunham, Jason B. | Bjork, Robin | Fesenmyer, Kurt A. | Chelgren, Nathan D. | Peacock, Mary M. | Luce, Charles H. | Isaak, Dan | Carranza, Lee Ann | Sjoberg, Jon | Wenger, Seth J.
Population viability analysis (PVA) is a powerful conservation tool, but it remains impractical for many species, particularly species with multiple, broadly distributed populations for which collecting suitable data can be challenging. A recently developed method of multiple‐population viability analysis (MPVA), however, addresses many limitations of traditional PVA. We built on previous development of MPVA for Lahontan cutthroat trout (LCT) (Oncorhynchus clarkii henshawi), a species listed under the U.S. Endangered Species Act, that is distributed broadly across habitat fragments in the Great Basin (U.S.A.). We simulated potential management scenarios and assessed their effects on population sizes and extinction risks in 211 streams, where LCT exist or may be reintroduced. Conservation populations (those managed for recovery) tended to have lower extinction risks than nonconservation populations (mean = 19.8% vs. 52.7%), but not always. Active management or reprioritization may be warranted in some cases. Eliminating non‐native trout had a strong positive effect on overall carrying capacities for LCT populations but often did not translate into lower extinction risks unless simulations also reduced associated stochasticity (to the mean for populations without non‐native trout). Sixty fish or 5–10 fish/km was the minimum reintroduction number and density, respectively, that provided near‐maximum reintroduction success. This modeling framework provided crucial insights and empirical justification for conservation planning and specific adaptive management actions for this threatened species. More broadly, MPVA is applicable to a wide range of species exhibiting geographic rarity and limited availability of abundance data and greatly extends the potential use of empirical PVA for conservation assessment and planning.
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