Linking Resource Selection to Population Dynamics of Mule Deer

PhD Dissertation, Mark Hurley (2010-2016)

Ecologists aim to understand and predict the effect of management actions on population dynamics of animals, a difficult task in highly variable environments. Mule deer (Odocoileus hemionus) occupy such variable environments and display volatile population dynamics, providing a challenging management scenario. I first investigated the ecological drivers of overwinter juvenile survival, the most variable life stage in this ungulate. I tested for both direct and indirect effects of spring and fall phenology on winter survival of 2,315 mule deer fawns from 1998 – 2011 across a wide range of environmental conditions in Idaho, USA. I showed that early winter precipitation and direct and indirect effects of spring and especially fall plant productivity (NDVI) accounted for 45% of observed variation in overwinter survival. I next developed predictive models of overwinter survival for 2,529 fawns within 11 Population Management Units in Idaho, 2003 – 2013. I used Bayesian hierarchical survival models to estimate survival from remotely-sensed measures of summer NDVI and winter snow conditions (MODIS snow and SNODAS). The multi-scale analysis produced well performing models, predicting out-of-sample data with a validation R2 of 0.66. Next, I asked how predation risk and deer density influences neonatal fawn survival. I developed a spatial coyote predation risk model and tested the effect on fawn mortality. I then regressed both total fawn mortality and coyote-caused mortality on mule deer density to test the predation-risk hypothesis that coyote predation risk increased as deer density increased as low predation risk habitats were filled, forcing maternal females to use high predation risk habitats. Fawn mortality did not increase with density, but coyote predation increased with increasing deer density, confirming density-dependence in fawn mortality was driven by coyote behavior, not density per se. Finally, I used integrated population models (IPM) to collate the previous findings into a model that simultaneously estimates all mule deer vital rates to test ecological questions concerning population drivers. I tested whether density-dependence or environmental stochasticity (weather) drives mule deer population dynamics. The vital rate most influenced by density was recruitment, yet across most populations, weather was the predominant force affecting mule deer dynamics. These IPM’s will provide managers with a means to estimate population dynamics with precision and flexibility.