Bullington, Grace A

Quantifying the impacts of environmental conditions on the abundance of wildlife populations is important for making informed management decisions in the face of increasing environmental threats. Managers require robust tools to estimate abundance and density of wildlife rapidly and with precision. Within the context of studying white-tailed deer, I evaluated the use of camera-traps and a recently developed spatial-mark resight model to estimate deer density and evaluate habitat and land use factors influencing deer density. The study was conducted in central Ontario, Canada on approximately 16 km2 of public land including the protected Peterborough Crown Game Preserve. Telemetry locations from 39 radio-collared deer were used and one hundred camera-traps were deployed for a total of 140 days from January 2022 to May 2022. Using telemetry locations and camera-trap photos I built a two-step spatial-mark resight model to estimate deer density. Deer density varied during the study as a portion of the population migrated to wintering areas outside of the study area. Despite fluctuations in precision, estimates improved towards the end of the study as more data became available and deer space use stabilized. The average deer density during the entire study was 3.0 deer/km2 (95% CI= 0.1, 5.8; SD= 1.7; CV= 55%; N= 238 deer). The lowest mean density was 0.2 deer/km2 (95% CI= 0.1, 0.4; SD= 0.1; CV= 50%; N= 15 deer) from February 26th to March 11th and the highest mean density was 4.8 deer/km2 (95% CI= 3.1, 6.2; SD= 0.8; CV= 17%; N= 378 deer) from May 7th to May 20th. When I incorporated spatial covariates into the model to estimate effects on deer density, higher proportions of mixed forest, deciduous forest, and road and trail density all had negative effects on deer density. While models contained some uncertainty, deer density appeared higher in the portion of the study area protected from licensed hunting. This thesis provides a framework for managers to use camera-traps and the spatial-mark resight model to monitor deer populations and link environmental covariates to spatial variation in density. As environmental threats such as habitat loss and infectious diseases increase in severity, monitoring wildlife population numbers will be vital for informed responses to these threats. The two-step spatial-mark resight model with environmental covariates provides managers with a long-term monitoring tool to evaluate management efforts and population health in forested areas.

Author Keywords: camera-trap, chronic wasting disease, landscape ecology, spatial-capture recapture, white-tailed deer, wildlife management