(1) Department of Geography, University of Victoria, Victoria, BC, V8W 3P5, Canada;(2) Department of Geography and Environmental Studies, Wilfrid Laurier University, Waterloo, ON, N2L 3C5, Canada
Abstract:
Epidemic populations of mountain pine beetle highlight the need to understand landscape scale spatial patterns of infestation.
The observed infestation patterns were explored using a randomization procedure conditioned on the probability of forest risk
to beetle attack. Four randomization algorithms reflecting different representations of the data and beetle processes were
investigated. Local test statistics computed from raster representations of surfaces of kernel density estimates of infestation
intensity were used to identify locations where infestation values were significantly higher than expected by chance (hot
spots). The investigation of landscape characteristics associated with hot spots suggests factors that may contribute to high
observed infestations.