White‐tailed deer population dynamics in a multipredator landscape shaped by humans

• Published in: Ecological Applications
• Main Authors: Ganz, Taylor R., Bassing, Sarah B., DeVivo, Melia T., Gardner, Beth, Kertson, Brian N., Satterfield, Lauren C., Shipley, Lisa A., Turnock, Benjamin Y., Walker, Savanah L., Abrahamson, Derek, Wirsing, Aaron J., Prugh, Laura R.
• Other Authors: Washington Department of Fish and Wildlife, WSL, National Science Foundation, Rocky Mountain Elk Foundation
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2024
• Subjects: Canis lupus; Lynx
• Online Access: http://dx.doi.org/10.1002/eap.3003; https://esajournals.onlinelibrary.wiley.com/doi/am-pdf/10.1002/eap.3003; https://esajournals.onlinelibrary.wiley.com/doi/pdf/10.1002/eap.3003

Abstract Large terrestrial mammals increasingly rely on human‐modified landscapes as anthropogenic footprints expand. Land management activities such as timber harvest, agriculture, and roads can influence prey population dynamics by altering forage resources and predation risk via changes in habitat, but these effects are not well understood in regions with diverse and changing predator guilds. In northeastern Washington state, USA, white‐tailed deer ( Odocoileus virginianus ) are vulnerable to multiple carnivores, including recently returned gray wolves ( Canis lupus ), within a highly human‐modified landscape. To understand the factors governing predator–prey dynamics in a human context, we radio‐collared 280 white‐tailed deer, 33 bobcats ( Lynx rufus ), 50 cougars ( Puma concolor ), 28 coyotes ( C. latrans ), and 14 wolves between 2016 and 2021. We first estimated deer vital rates and used a stage‐structured matrix model to estimate their population growth rate. During the study, we observed a stable to declining deer population (lambda = 0.97, 95% confidence interval: 0.88, 1.05), with 74% of Monte Carlo simulations indicating population decrease and 26% of simulations indicating population increase. We then fit Cox proportional hazard models to evaluate how predator exposure, use of human‐modified landscapes, and winter severity influenced deer survival and used these relationships to evaluate impacts on overall population growth. We found that the population growth rate was dually influenced by a negative direct effect of apex predators and a positive effect of timber harvest and agricultural areas. Cougars had a stronger effect on deer population dynamics than wolves, and mesopredators had little influence on the deer population growth rate. Areas of recent timber harvest had 55% more forage biomass than older forests, but horizontal visibility did not differ, suggesting that timber harvest did not influence predation risk. Although proximity to roads did not affect the overall population growth rate, ...