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UBC Theses and Dissertations

Using airborne laser scanning to identify fine scale movement patterns of grizzly bears in west-central Alberta Prehn, Brandon

Abstract

Grizzly bears utilize large home ranges and move through many stages of forest succession. Research to date has confirmed bears display preference for habitats along forest edges, as well as certain landcover classes. However, the effect of fine-scale patterns and changes in forest structure on bear movement and habitat selection is less well understood. To date, habitat selection studies of grizzly bears have thoroughly examined the effects of various habitat characteristics such as anthropogenic disturbance, food availability, topographic variables, and plant communities, though there is more opportunity to leverage advanced remote sensing, three-dimensional data to refine and enhance our understanding. To address this, I processed Airborne Laser Scanning data in the Yellowhead region of Alberta to characterize forest structure and used resource selection functions to determine whether ALS-derived descriptions of habitat could effectively model habitat selection by bears. I found: 1) ALS, when combined with a topographic index, provides enough structural information and context to reliably describe habitat selection. 2) Canopy cover and vegetation height both influence selection as a function of distance from the forest edge. 3) Outside a forest stand, cover > 2 m increases the probability of selection, while inside forested stands, higher canopy cover is negatively related to selection. My final model cross-validation demonstrated selective use of forest edge habitat. Selective use of forest edges implies that the shape and spatial arrangement of forest cut blocks and associated retention patches left during harvesting operations may be optimized to minimize human-bear encounters and associated human-caused mortality of grizzly bears, in accordance with the “emulating natural disturbance” forest management philosophy.

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Attribution-NonCommercial-NoDerivatives 4.0 International