Detecting the phenology of important vegetative grizzly bear foods using remote sensing and analysing their relationship to grizzly bear habitat selection

Understanding patterns in vegetation phenology under increasing anthropogenic pressures, and within a changing climate, is essential for determining the availability of key plant-food resources, which drive habitat selection of wildlife. In creating a fine scale phenology product to monitor daily phenology trends, this thesis determines how variations in availability of key plant-food species is affecting daily habitat selection of grizzly bears (Ursus arctos), across years, within the Yellowhead Bear Management Area, Alberta, Canada. Dynamic Time Warping is used to combine Landsat satellite data and Moderate Resolution Image Spectroradiometer (MODIS) imagery, to quantify daily changes in vegetation at a 30 m resolution, from 2000-2018. This approach, entitled DRIVE, was validated against the start and end of season dates (SOS and EOS respectively) derived from time-lapse imagery obtained from ground cameras. Results showed correlations of r = 0.73 at SOS and r = 0.85 at EOS with a mean absolute error of 7.17 and 10.76 days at SOS and EOS respectively. Analysis of the DRIVE product also indicated that SOS is advancing at a maximum rate of 0.78 days per year from 2000-2018. A set of new methods were then developed to create daily vegetative food species availability layers from 2000-2017. Annual species distribution models (SDMs) were created using maximum entropy modelling. SDMs were combined with DRIVE outputs to create daily plant-food availability layers for eight food species. Food availability layers were combined with environmental variables and grizzly bear GPS collar data to create resource selection functions modelling daily and seasonal selection. Results determined that in the dry spring, selection for roots was stronger and occurred earlier than in the average/wet years, in the wet summer the length of selection increased for forbs and in the dry fall, the period of selection for berries was longer than in the wet year. Through this research, I found that variations in phenology driven by climate and anthropogenic processes, has the potential to affect grizzly bear habitat selection into the future. The datasets and approaches developed here will provide resource managers with an important tool for use in grizzly bear habitat management and population recovery.Forestry, Faculty ofGraduat