Pronghorn (Antilocapra americana) response to wind energy development on winter range in south-central, Wyoming

In order to understand the potential impacts of wind energy development to pronghorn (Antilocapra americana) on winter range, I evaluated the response of a wintering pronghorn population to the Dunlap Ranch wind energy facility over 3 winters in south-central Wyoming, USA. My objectives were to 1) evaluate displacement of pronghorn in relation to wind energy infrastructure components to identify changes in movement rates influenced by vicinity to wind energy development, 2) develop a resource selection function (RSF) for pronghorn exposed to wind energy at the population level to gain insights into winter resource selection on this landscape, 3) apply the overall best fit population level model to individuals with home ranges that overlapped wind energy to isolate potential avoidance behavior relative to each individual within its own home range, and 4) to identify environmental and anthropogenic predictor variables (inclusive of wind energy) influencing pronghorn mortality risk on winter range. In addition, I modeled resource selection and estimated survival for a neighboring population of pronghorn near Walcott Junction, Wyoming.;Dunlap Ranch was developed for wind energy production in 2010 and was located approximately 11.8 km north of Medicine Bow, in Carbon County, Wyoming. I obtained location data from 47 female pronghorn equipped with GPS-transmitters at Dunlap Ranch. I modeled frequency of use as a continuous response variable to predict pronghorn resource selection across the Dunlap Ranch both at the population and individual levels. I estimated survival for pronghorn using the Kaplan-Meier product limit estimator. Finally, I modeled mortality risk for pronghorn at Dunlap Ranch using the Cox proportional hazards model inclusive of cumulative, weekly, and monthly temporal scales.;At the population level, pronghorn at the Dunlap Ranch selected for areas closer to wind energy facilities and with lower slopes, standard deviation in snow depth, and density of fences. At the individual level, coefficients for distance to nearest wind energy facility did not differ from zero (P > 0.05) across all 3 winters, indicating no effect of wind energy development on pronghorn resource selection on winter range in my study area. In addition, pronghorn daily net displacement did not increase closer to wind energy development (r2 = 0.001-0.012) during each winter. Twenty-four pronghorn from the Dunlap Ranch study area died with the majority of deaths (n = 13 or 54.2% of deaths) occurring in winter 2010-2011.;Overall, I did not detect an influence of wind energy development on pronghorn movement behavior, resource selection, or mortality risk at the Dunlap Ranch. Most avoidance behaviors documented in ungulate populations are associated with human presence and increased traffic. Lower traffic rates observed within the Dunlap Ranch paired with less overall length of access roads and less habitat developed than in oil and gas fields may explain why avoidance and increased movement rates were not observed in pronghorn. My results are valuable in providing guidance for wildlife managers considering future wind energy development on pronghorn winter range. For example, identifying sagebrush as influential for pronghorn winter mortality risk should lead to greater conservation of sagebrush stands in areas where development and pronghorn winter range coincide. My results also illustrate that fence densities and variability in snow depth are important contributors to habitat selection by wintering pronghorn in south-central Wyoming and must be considered when implementing further modifications (energy and other human developments) to these harsh environmental landscapes to minimize impacts to pronghorn. Regardless, caution must be taken when generalizing these results across pronghorn populations. Although pronghorn were not impacted negatively by wind energy on the Dunlap Ranch, my results cannot be directly applied to populations exposed to wind energy development at larger scales and on other seasonal ranges where traffic levels and environmental conditions may differ. (Abstract shortened by UMI.).