Canadian Forest Service Publications
Calculating the risk of mountain pine beetle attack: a comparison of distance- and density-based estimates of beetle pressure. 2006. Wulder, M.A.; White, J.C.; Dymond, C.C.; Nelson, T.A.; Boots, B.; Shore, T.L. Journal of Environmental Informatics 8(2): 58-69.
Issued by: Pacific Forestry Centre
Catalog ID: 26701
Availability: PDF (download)
An established model for risk rating of Pinus contorta stands for potential mortality caused by mountain pine beetle (Dendroctonus ponderosae) combines information on stand susceptibility and beetle pressure. Susceptibility is determined using attributes in the forest inventory data, while beetle pressure is calculated based on the size and distance to existing infestation locations (distance-based model). An alternate model for calculating beetle pressure is presented in this paper, which uses Voronoi polygons to incorporate size and distance, while emphasizing the density of existing infestation locations (density-based model), in combination with empirical knowledge of beetle dispersal and forest inventory data. Survey data of existing beetle damage were collected using a helicopter mounted global positioning system (GPS) at a study site in central British Columbia, Canada in 1999, 2000, and 2001. These data facilitated the estimation of beetle pressure, and the comparison of risk ratings to actual attack locations. Using the distance-based model, 18% and 27% of areas identified as having a risk rating of greater than 50 in 1999 and 2000 were actually found to be attacked by beetles in surveys conducted in 2000 and 2001. Conversely, 39% and 49% of areas identified as having risk greater than 50 in 1999 and 2000 with the density-based model were attacked in 2000 and 2001. The results suggest that the density-based model of beetle pressure produced risk ratings that had a greater correspondence with actual infestation occurrence than risk ratings generated from the distance-based model. Using data that is typically collected to monitor beetle populations, novel methods of spatial processing may be applied in a transparent manner, generating results that incorporate knowledge of mountain pine beetle dynamics under certain population conditions, into calculations of the risk of mountain pine beetle attack.