Sells, S.N., and Costello, C.M., 2023, Grizzly Bear Space Use in the US Northern Rocky Mountains (ver. 3.0, July 2024): U.S. Geological Survey data release, https://doi.org/10.5066/P91EWUO8.
Understanding habitat selection is challenging but key for species of conservation concern, including grizzly bears (Ursus arctos). Over the past century, persecution and habitat loss led to near extirpation of grizzly bears throughout most of their range in the continental United States. Given threats facing the remnant populations, grizzly bears in the continental U.S. were listed as Threatened under the Endangered Species Act in 1975. Six recovery zones, located in different ecosystems, were established in the 1990s and populations slowly increased in four of these areas. Recent numbers included >1,000 individuals each in the NCDE and GYE, >44 individuals on the U.S. side of the SE, and >50 individuals in the CYE. However, no resident grizzly bears are known to occupy the NCE or BE. Sells et al. (2022) developed an approach for understanding and predicting habitat use over multiple stages that test hypotheses of animal behavior, use newly gained knowledge to mechanistically simulate individual movements, translate results to predictive habitat maps, and test their predictive power across a large spatiotemporal scale. Grizzly bears in the NCDE served as our primary study system. Mechanistically modeling grizzly bear movements demonstrated that grizzly bears have highly individualistic spatial behaviors. Some individuals avoided whereas others preferred areas of vegetation green-up, terrain ruggedness, forest edge, riparian areas, building densities, and secure habitat. Such individualism supported the need for an individual-based modeling approach to understand and predict grizzly bear behavior. External validation using >375,000 GPS locations for 262 individuals over nearly 2 decades demonstrated mean Spearman rank scores of >0.90 across seasons and years, and overall scores of 1.0. The top 5 classes of our predictive habitat maps contained 73.5% of female fixes and 83.6% of male fixes, and the top class (comprising 10% of mapped area) contained 25.6% and 41.7% of female and male fixes, respectively. Sells et al. (2023) evaluated transferability of Sells et al. (2022)’s iSSFs by applying them within the nearby SE, CYE, and GYE. We simulated 100 replicates of 5,000 steps for each iSSF in each ecosystem, summarized relative use into 10 equal-area classes for each sex, and overlaid GPS locations from bears in the SE, CYE, and GYE on resulting maps. Spearman rank correlations between numbers of locations and class rank were ≥0.96 within each study area, indicating models were highly predictive of grizzly bear space use in these nearby populations. Assessment of models using smaller subsets of data in space and time demonstrated generally high predictive accuracy for females. Although generally high across space and time, predictive accuracy for males was low within some watersheds and in summer within the SE and CYE, potentially due to seasonal effects, vegetation, and food assemblage differences. Altogether, these results demonstrated high transferability of our models to landscapes in the Northern Rocky Mountains, suggesting they may be used to evaluate habitat suitability and connectivity throughout the region to benefit conservation planning.
