Forecasting dynamics of a recolonizing wolf population under different management strategies

Species recovery can be influenced by a wide variety of factors, such that predicting the spatiotemporal dynamics of recovering species can be exceedingly difficult. These predictions, however, are valuable for decision makers tasked with managing species and determining their legal status. We applied a spatially explicit projection model to estimate population growth and viability of gray wolves (Canis lupus) from 2021 to 2070 in the state of Washington, USA, where wolves have been naturally recolonizing since the establishment of the first resident pack in 2008. Using this model, we predicted the effects of 12 scenarios relating to management actions (e.g., lethal removals by the state agency, translocation, recreational harvest) and system uncertainties (e.g., immigration from out of state, disease) on the probability of meeting Washington's wolf recovery goals, the probability of extinction, and other metrics related to population status. Population recovery was defined under Washington's Wolf Conservation and Management Plan as four breeding pairs in each of three recovery regions and three additional breeding pairs anywhere in the state. The baseline and two translocation scenarios indicated a high (> 90%) probability of wolf recovery in Washington by 2070, but scenarios related to harvest mortality (removal of 5% of the population every 6 months), increased lethal removals (removal of 8.53% of the population across the state each year), and cessation of immigration from out of state resulted in probabilities of