Smith, Bradley2020-08-252020-08-252020-01https://hdl.handle.net/11299/215032University of Minnesota M.S. thesis. January 2020. Major: Conservation Biology. Advisor: Glenn DelGiudice. 1 computer file (PDF); xiii, 143 pages.Advances in technology enhance our ability to understand wildlife-habitat relationships. The Minnesota Department of Natural Resources’ new statewide white-tailed deer (Odocoileus virginianus) management plan aims to enhance its ability to maintain regional deer numbers near population goals. Habitat management is acknowledged as a key component to achieving the plan’s objectives. Informed habitat management prescriptions, based on an improved understanding of optimal size, shape, and arrangement of forest stands and foraging sites, and edge relationships, will contribute to a more successful integration of long-term forest and deer habitat management strategies. The objectives of my study were to establish the feasibility of combining cutting-edge Global positioning system (GPS) collar, remote sensing, and Geographic Information System technologies to 1) classify and inventory available habitat on deer winter ranges and 2) characterize how deer use habitat at the stand level to facilitate an improved understanding of their habitat requirements in northern Minnesota. During winter 2017–2018, 20 adult female deer were captured and fitted with GPS collars on 2 study areas (10/site) in northcentral (Inguadona Lake [IN]) and northeastern (Elephant Lake [EL]) Minnesota, with an additional 40 collars (20/site) deployed during winter 2018–2019. Prior to the deployment of GPS collars on free-ranging deer, I conducted stationary tests to evaluate the location-fix-success and spatial accuracy of 48 collars placed in 4 different cover types. The overall mean location error of the GPS collars was 5.7 m (± 0.15, range = 0–189), with errors in dense conifer (10.3 ± 0.52, range = 0–189 m) being greater than in hardwood stands (6.2 ± 0.22, range = 0–91 m), browse patches (3.2 ± 0.08, range = 0–26 m), and openings (3.2 ± 0.08, range = 0–32 m). With incorporation into the collars of quick fix pseudoranging (QFP) programming, I recovered 100% of the location-fixes during the stationary tests and from 30 collars deployed on free-ranging deer. Spatially, dense conifer stands accounted for 21% and 9%, and moderately dense conifer stands for 4% and 10% of the EL and IN sites, respectively. The proportion of forage openings was 9% on both sites. The mean size (area) of available dense conifer stands was similar on both study sites (6.7, 95% CI = 4.94–8.54 ha vs 6.0, 95% CI = 4.68–7.23 ha). Available forest stands were generally circular, providing a larger core area and less edge, with a mean edge:area ratio <400 m/ha. Deer use of cover types was highly variable among individuals. Mean individual use of dense conifer stands was 23% (range = 0–79%) and 9% (range = 0–29%), and mean use of forage openings was 13% (range = 0–42%) and 24% (range = 0–70%) at the EL and IN sites, respectively. To better understand deer use at the stand level and the arrangement of cover types, I measured the distance from each location-fix to the nearest dense conifer stand and forage opening. While using forage openings, deer were a mean of 177 m (± 7, range = 0–833) and 195 m (± 4, range = 0–882) from dense conifer stands at EL and IN. Likewise, individuals using dense conifer stands were a mean of 241 m (± 6, range =0–777) and 147 m (± 8, range =0–1,030) from forage openings at the respective sites. The use of an integrated technological approach is essential to a more thorough understanding of seasonal habitat requirements of deer. The ability to retrieve 100% of location-fixes with high spatial accuracy will allow us to confidently assess winter habitat use by white-tailed deer as winter progresses and assist managers in formulating prescriptions that effectively integrate forest and habitat management strategies and activities.enGISGPSOdocoileus virginianusQFPremote sensingWhite-tailed deerThesis or Dissertation