Development of a western hemlock looper Lambdina fiscellaria lugubrosa hazard rating system for interior British Columbia using discriminant function analysis and logistic regression

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dc.contributor.authorBorecky, Neilen_US
dc.date.accessioned2024-08-13T00:05:38Z
dc.date.available2024-08-13T00:05:38Z
dc.date.copyright2003en_US
dc.date.issued2003
dc.degree.departmentDepartment of Biology
dc.degree.levelMaster of Science M.Sc.en
dc.description.abstractThe western hemlock looper (WHL ), Lambdina fiscellaria lugubrosa Hulst, is a major defoliator in British Columbia. The purpose of this thesis is to characterize the susceptibility of forest stands to defoliation by the investigative use of discriminant function analysis and logistic regression techniques upon forest stand and climatic variables. The ability to detect susceptibility of forests to WHL attacks is, at present, scale dependent. Predictions at an inter-watershed scale were far stronger than within watersheds, at the stand-level scale. Defoliated watersheds tend to be, on average, 1.8 ° C cooler and 2 cm precipitation/month wetter than undefoliated watersheds within the same biogeoclimatic sub-zones. Watershed-scale hazard rating using average minimum monthly temperature climate data is an accurate predictor of susceptibility 84-85% of the time. A weak stand-level signature can be identified using age, site-index and species composition with canonical discriminant function analysis (CDA). However, the overlap in CDA-score distribution is very high. This study suggests that outbreaks have some underlying small-scale controlling effects, climate being the obvious one, however at a stand-level, outbreaks tend to be more stochastic in nature, owing to the homogeneity of forest stands within defoliated areas.
dc.format.extent169 pages
dc.identifier.urihttps://hdl.handle.net/1828/17052
dc.rightsAvailable to the World Wide Weben_US
dc.titleDevelopment of a western hemlock looper Lambdina fiscellaria lugubrosa hazard rating system for interior British Columbia using discriminant function analysis and logistic regressionen_US
dc.typeThesisen_US

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