Canadian Forest Service Publications
Spatial distribution of mountain pine beetle outbreaks in relation to climate and stand characteristics: a dendroecological analysis. 2007. Campbell, E.; Alfaro, R.I.; Hawkes, B.C. Journal of Integrative Plant Biology 49(2): 168-178.
Issued by: Pacific Forestry Centre
Catalog ID: 26732
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Principal components analysis, followed by K-means cluster analysis, was used to detect variations in the timing and magnitude of Pinus contorta Dougl. ex Loud. growth releases attributed to mountain pine beetle outbreaks in 31 stands of central British Columbia. Four major growth release patterns were identified from 1970 to 2000. Variations in the timing of growth releases among clustered stands corresponded well to aerial survey data indicating the timing of beetle outbreaks in the study area. Redundancy analysis was used to determine how variations in the timing and magnitude of growth releases attributed to beetle outbreaks changed with variations in climate or stand conditions over the study area. The first RDA axis, which accounted for 39% of the variations in growth patterns among stands, was significantly (P <0.05) correlated with gradients in the percentage of pine in stands killed by mountain pine beetle, summer aridity, variation in summer precipitation, distance from initial infestation site, average pine age, and maximum August temperatures. The second RDA axis explained 6% of the variations and was significantly correlated with gradients in the beetle climate suitability index, extreme cold month temperatures, and site index. Comparisons of growth release patterns with aerial survey data and redundancy analyses indicated that dendrochronological techniques are useful for identifying mountain pine beetle outbreaks in central British Columbia, particularly among stands that had a density high enough to produce a growth release signal. Provided future studies account for interannual weather fluctuations, identification of growth increases due to stand thinning caused by beetle outbreaks will be useful for reconstructing the history of beetle outbreaks over much longer time periods.