We derive a system of nonlinear partial differential equations describing the phenomenon of mountain pine beetles attacking lodgepole pine en masse. A methodology for projecting the behavior of these partial differential equations onto purely local ordinary differential equations is discussed and im
Mathematical Elements of Attack Risk Analysis for Mountain Pine Beetles
β Scribed by JAMES POWELL; BRUCE KENNEDY; PETER WHITE; BARBARA BENTZ; JESSE LOGAN; DAVID ROBERTS
- Publisher
- Elsevier Science
- Year
- 2000
- Tongue
- English
- Weight
- 452 KB
- Volume
- 204
- Category
- Article
- ISSN
- 0022-5193
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β¦ Synopsis
Three di!erent mathematical approaches are combined to develop a spatial framework in which risk of mountain pine beetle (MPB) attack on individual hosts may be assessed. A density-based partial di!erential equation model describes the dispersal and focusing behavior of MPB. A local projection onto a system of ordinary di!erential equations predicts the consequences of the density equations at individual hosts. The bifurcation diagram of these equations provides a natural division into categories of risk for each host. A stem-competition model links host vigor to stand age and demographics. Coupled together, these models illuminate spatial risk structures which may also shed light on the role of climatic variables in population outbreaks. Preliminary results suggest that stand microclimate has much greater in#uence on risk of attack than host vigor and stand age.
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The dynamic interaction between mountain pine beetles (MPB) and hosts (generally lodgepole pine) is reviewed briefly. In particular, successful "switching" from initial foci of attack to nearby hosts which may be higher-quality resources is a potentially critical element initiating the transition fr
Mountain pine beetle (Dendroctonus ponderosae Hopkins) is the most destructive insect infesting mature pine forests in North America and has devastated millions of hectares of forest in western Canada. Past studies have demonstrated the use of multispectral imagery for remote identification and mapp