Mountain Pine Beetle and Lodgepole pine:
Temporal Dynamics of Fuels and Fire Behavior in South-Central Oregon

Bark beetles have caused mortality over millions of acres during the past 30 or so years. Recently, the mountain pine beetle (Dendroctonus ponderosae) (MPB) has caused extensive lodgepole pine mortality in the western US. Several waves of MPB have occurred over the past 30 years in central and south-central Oregon which peaked at over 1,000,000 acres in 1986. Currently, over 400,000 acres are being impacted in the area. This extensive mortality from bark beetles, and especially the MPB, has raised questions about the potential for catastrophic fire following widespread mortality. Although there is a major concern about fire behavior following widespread tree mortality caused by bark beetles, recent literature has suggested that there is a lack of specific data concerning how MPB caused mortality influences temporal and spatial aspects of fuels and potential fire behavior.

Specifically for the lodgepole pine forests of south central Oregon, on the Deschutes and Fremont-Winema National Forests, we will address the following:

   1. How do fuel profiles (ground, surface, ladder and crown fuels) in lodgepole pine forests change over time in response to MPB epidemics in south-central Oregon?

   2. What are the effects of MPB epidemics on future fire behavior in lodgepole pine forests of south-central Oregon and how does fire behavior change over time following the epidemics?

We propose a retrospective approach to understanding post-MPB-epidemic fuels for the lodgepole pine type on the Deschutes and Fremont-Winema National Forests in order to reconstruct stand development and ground, surface, ladder, and crown fuels. By selecting stands with different time since MPB epidemic (i.e, developing a chronosequence) these reconstructions will be used to detect temporal changes in stand development and ground, surface, ladder, and crown fuels. To model and estimate the temporal and spatial change in potential fire behavior we will use standard fuel models or, if necessary, custom fuels models from our collected data, in conjunction with the fire behavior algorithms in BehavePlus v 4.0.0, FlamMap, and FARSITE.

Link to pdf of FULL proposal


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