Abstract
Expanding urban white-tailed deer populations are causing concerns for wildlife professionals and residents. I used distance sampling to estimate deer population density and abundance in the eastside communities of Syracuse, New York. I estimated a population size of between 93 - 159 deer (mean: 121) for 28.9 square kilometers of the study area. I classified high resolution orthoimagery and identified patches of cover with deer behavior thresholds and an animal-centric delineation algorithm. I predicted deer abundance from binomial mixture models and a suite of landscape covariates. Model weight of evidence supported variables corresponding to cover, food, and water constituents on the landscape. Deer population density predicted from abundance modeling was 73% higher than the distance sampling estimate indicating a substantial bias. Because assumptions associated with distance sampling and mixture modeling were reasonably met, low encounter rates with deer during sunrise surveys are the probable cause of the observed discrepancy.