Abstract

Determining how resource availability changes daily, seasonally and annually, and how wildlife react to these changes, is valuable for managing wildlife. For vegetative resources phenological information can be used to determine availability and model the distribution of available resources. This study develops a set of annually varying species distribution models using maximum entropy modeling for eight grizzly bear key plant-food species using 1635 food occurrences collected between 2001 and 2017. Seasonal availability (phenology) of plant-food species were then estimated daily at a 30 m resolution for the period 2000–2017 using ground data collected at 15 sites in 2015 and 2018 combined with newly created fine scale phenology product DRIVE (Daily Remote Inference of Vegetation). These food availability layers were then used to develop resource selection functions with grizzly bear GPS collar data to describe daily and seasonal habitat selection and to compared how this changes over a three-year period based on changes in mean annual precipitation. Results demonstrated that grizzly bears selected areas where key plant-food species were available and that habitat selection varied between wet and dry years dependant on season and species. In dry spring conditions, selection for root species was stronger and occurred earlier than for an average and wet year. In the wet summer, length of selection for forb species increased, while strength of selection for wet and dry years was species dependant. In the fall, strength of selection for berry species between wet and dry years was species dependant, but overall selection for berry species was prolonged in the dry fall year. This research aids in predicting how inter-annual differences in climate affect grizzly bear habitat selection and provides insights to managers regarding how changes in management practices that encourage growth of understory vegetation could be used to maximize food resources regionally for grizzly bears and other wildlife.

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