A GIS-based risk rating of forest insect outbreaks using aerial overview surveys and the local Moran's I statistic
Dates
Year
2013
Citation
Bone, Christopher, Wulder, Michael A., White, Joanne C., Robertson, Colin, and Nelson, Trisalyn A., 2013, A GIS-based risk rating of forest insect outbreaks using aerial overview surveys and the local Moran's I statistic: Applied Geography, v. 40, no. 0, p. 161-170.
Summary
The objective of this study is to provide an approach for assessing the short-term risk of mountain pine beetle Dendroctonus ponderosae Hopkins (Coleoptera: Scolytidae) attack over large forested areas based on the spatial-temporal behavior of beetle spread. This is accomplished by integrating GIS, aerial overview surveys, and local indicators of spatial association (LISA) in order to measure the spatial relationships of mountain pine beetle impacts from one year to the next. Specifically, we implement a LISA method called the bivariate local Moran's Ii to estimate the risk of mountain pine beetle attack across the pine distribution of British Columbia, Canada. The bivariate local Moran's Ii provides a means for classifying locations [...]
Summary
The objective of this study is to provide an approach for assessing the short-term risk of mountain pine beetle Dendroctonus ponderosae Hopkins (Coleoptera: Scolytidae) attack over large forested areas based on the spatial-temporal behavior of beetle spread. This is accomplished by integrating GIS, aerial overview surveys, and local indicators of spatial association (LISA) in order to measure the spatial relationships of mountain pine beetle impacts from one year to the next. Specifically, we implement a LISA method called the bivariate local Moran's Ii to estimate the risk of mountain pine beetle attack across the pine distribution of British Columbia, Canada. The bivariate local Moran's Ii provides a means for classifying locations into separate qualitative risk categories that describe insect population dynamics from one year to the next, revealing where mountain pine beetle populations are most likely to increase, stay constant, or decline. The accuracy of the model's prediction of qualitative risk was higher in initial years and lower in later years of the study, ranging from 91% in 2002 to 72% in 2006. The risk rating can be continually updated by utilizing annual overview surveys, thus ensuring that risk prediction remains relatively high in the short-term. Such information can equip forest managers with the ability to allocate mitigation resources for responding to insect epidemics over very large areas.
