title: A case study of bats and white-nose syndrome demonstrating how to model population viability with evolutionary effects.
abstract: Ecological factors generally affect population viability on rapid time scales. Traditional population viability analyses (PVA) therefore focus on alleviating ecological pressures, discounting potential evolutionary impacts on individual phenotypes. Recent studies of evolutionary rescue (ER) focus on cases in which severe, environmentally induced population bottlenecks trigger a rapid evolutionary response that can potentially reverse demographic threats. ER models have focused on shifting genetics and resulting population recovery, but no one has explored how to incorporate those findings into PVA. We integrated ER into PVA to identify the critical decision interval for evolutionary rescue (DIER) under which targeted conservation action should be applied to buffer populations undergoing ER against extinction from stochastic events and to determine the most appropriate vital rate to target to promote population recovery. We applied this model to little brown bats (Myotis lucifugus) affected by white-nose syndrome (WNS), a fungal disease causing massive declines in several North American bat populations. Under the ER scenario, the model predicted that the DIER period for little brown bats was within 11 years of initial WNS emergence, after which they stabilized at a positive growth rate (λ = 1.05). By comparing our model results with population trajectories of multiple infected hibernacula across the WNS range, we concluded that ER is a potential explanation of observed little brown bat population trajectories across multiple hibernacula within the affected range. Our approach provides a tool that can be used by all managers to provide testable hypotheses regarding the occurrence of ER in declining populations, suggest empirical studies to better parameterize the population genetics and conservation-relevant vital rates, and identify the DIER period during which management strategies will be most effective for species conservation.
authors: Department of Ecology, Evolution and Natural Resources, Rutgers, The State University of New Jersey, 14 College Farm Road, New Brunswick, NJ, 08901, U.S.A.|Rutgers Cooperative Extension, New Jersey Agricultural Experiment Station, Rutgers, The State University of New Jersey, 88 Lipman Drive, New Brunswick, NJ, 08901, U.S.A.
authors: Brooke
authors: B
authors: Maslo
authors: Department of Ecology, Evolution and Natural Resources, Rutgers, The State University of New Jersey, 14 College Farm Road, New Brunswick, NJ, 08901, U.S.A.|The Center for Discrete Mathematics and Theoretical Computer Science (DIMACS), Rutgers, The State University of New Jersey, 96 Frelinghuysen Road, Piscataway, NJ, 08854, U.S.A.
authors: Nina H
authors: NH
authors: Fefferman
mesh_terms: D000818:Animals; D001203:Ascomycota / Q000502:physiology*; D005075:Biological Evolution; D002685:Chiroptera / Q000502:physiology; D003247:Conservation of Natural Resources / Q000379:methods*; D003710:Demography; D008954:Models, Biological; D009181:Mycoses / Q000453:epidemiology* / Q000382:microbiology
keywords: Pseudogymnoascus destructans; demografía evolutiva; evolución rápida; evolutionary demography; genética de poblaciones; novel pathogen; patógeno novedoso; population genetics; rapid evolution