Canadian Forest Service Publications

Determination of the compositional change (1999–2006) in the pine forests of British Columbia due to mountain pine beetle infestation. 2009. Robertson, C.; Farmer, C.J.Q.; Nelson, T.A.; Mackenzie, I.K.; Wulder, M.A.; White, J.C. Environmental Monitoring and Assessment 158: 593-608.

Year: 2009

Issued by: Pacific Forestry Centre

Catalog ID: 30011

Language: English

Availability: PDF (request by e-mail)

Available from the Journal's Web site.
DOI: 10.1007/s10661-008-0607-9

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The current mountain pine beetle (Dendroctonus ponderosae Hopkins) outbreak in British Columbia and Alberta is the largest recorded forest pest infestation in Canadian history. We integrate a spatial hierarchy of mountain pine beetle and forest health monitoring data, collected between 1999 and 2006, with provincial forest inventory data, and generate three information products representing 2006 forest conditions in British Columbia: cumulative percentage of pine infested by mountain pine beetle, percentage of pine uninfested, and the change in the percentage of pine on the landscape. All input data were formatted to a standardized spatial representation (1 ha minimum mapping unit), with preference given to the most detailed monitoring data available at a given location for characterizing mountain pine beetle infestation conditions. The presence or absence of mountain pine beetle attack was validated using field data (n?=?2054). The true positive rate for locations of red attack damage over all years was 92%. Classification of attack severity was validated using the Kruskal gamma statistic (??=?0.49). Error between the survey data and field data was explored using spatial autoregressive (SAR) models, which indicated that percentage pine and year of infestation were significant predictors of survey error at a?=?0.05. Through the integration of forest inventory and infestation survey data, the total area of pine infested is estimated to be between 2.89 and 4.14 million hectares. The generated outputs add value to existing monitoring data and provide information to support management and modeling applications.