%0 Research article
%T Improvement of low level bark beetle damage estimates with adaptive cluster sampling
%A Coggins, Sam B.
%A Coops, Nicholas C.
%A Wulder, Michael A.
%D 2010
%J Silva Fennica
%V 44
%N 2
%R doi:10.14214/sf.456
%U https://silvafennica.fi/article/456
%X Detection of low level infestation in forest stands is of principle  importance to determine effective control strategies before the attack  spread to large areas. Of particular concern is the ongoing mountain  pine beetle, Dendroctonus ponderosae (Hopkins) epidemic, which has  caused approximately 14 million hectares of damage to lodgepole pine  (Pinus contorta Dougl. ex. Loud var. latifolia Engl.) forests in western  Canada. At the stand level attacked trees are often difficult to locate  and can remain undetected until the infestation has become established  beyond a small number of trees. As such, methods are required to detect  and characterise low levels of attack prior to infestation expansion, to  inform management, and to aid mitigation activities. In this paper, an  adaptive cluster sampling approach was applied to very fine-scale (20  cm) digital aerial imagery to locate mountain pine beetle damaged trees  at the leading edge of the current infestation. Results indicated a mean  number of 7.36 infested trees per hectare with a variance of 18.34. In  contrast a non-adaptive approach estimated the mean number of infested  trees in the same area to be 61.56 infested trees per hectare with a  variance of 41.43. Using a relative efficiency estimator the adaptive  cluster sampling approach was found to be over two times more efficient  when compared to the non-adaptive approach.