Canadian Forest Service Publications

Incorporating Present and Future Climatic Suitability into Decision Support Tools to Predict Geographic Spread of the Mountain Pine Beetle. 2008. Shore, T.L.; Riel, W.G.; Fall, A. Natural Resources Canada, Canadian Forest Service, Pacific Forestry Centre, Victoria, BC. Mountain Pine Beetle Working Paper 2008-10. 22 p.

Year: 2008

Issued by: Pacific Forestry Centre

Catalog ID: 28990

Language: English

Series: Mountain Pine Beetle Working Paper (PFC - Victoria)

Availability: Order paper copy (free), PDF (download)

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The main goal of this project was to adapt existing mountain pine beetle (MPB) decision-support tools to incorporate climatic suitability information to refine the spatial characterization of present climate and to support assessments of future climate. These tools include susceptibility and risk rating systems, the MPBSim stand-scale MPB population model, the landscape-scale SELES-MPB population model, and graph-based connectivity methods. We made significant advances on all of these, resulting in a suite of tools with increased capabilities and generality. During the course of this project, we also provided decisions support in the specific areas of study, in particular Dawson Creek and central-western Alberta.

The basis of the climatic suitability was the work of A. Carroll et al. (2004) which produced estimates of MPB climatic suitability in five classes across western Canada, for historical, existing and future climates. Future climate information was derived from global circulation models such as the CGCM model. They input general climate information into the BioSim tool, in conjunction with topography and other variables relevant to downscaling for MPB, to produce the MPB climatic suitability maps. We used these maps to create an adaptation of the MPB susceptibility and risk rating system that replaced the coarser location factor (based on latitude, longitude and elevation) with MPB climatic suitability. It is important to note that the MPB climatic suitability refers only to climatic conditions relevant for MPB survival and reproduction, while the susceptibility rating system incorporates pine host information.

We also modified MPBSim, a stand-scale population model, to utilize the MPB climatic suitability information. In previous applications, MPBSim was adapted to local conditions via a calibration process using local weather information. In some senses, this calibration process resulted in a reasonably precise adjustment to local conditions. However, it was also fairly labour intensive and didn't account as well for spatial variability. Our approach here was to use climatic suitability to both increase spatial precision as well as produce outputs that can be readily adapted to different stand and landscapes.

The SELES-MPB landscape-scale population model scales MPBSim dynamics to broad spatial areas. We modified this tool to utilize the revised MPBSim output. This supports more rapid adaptation to other landscapes, as well as allows examination of potential effects of future climate. Our Dawson Creek analysis indicated that beetle management in the Dawson Creek area could significantly affect the spread and impact of the beetle outbreak over the next 10 years, provided that high levels of fell and burn and survey efforts are maintained. Estimated impacts are significantly affected by external pressure from the main outbreak, as estimated using the provincial-scale BCMPB projection. If mountain pine beetle populations can be held low until the main outbreak subsides (which will likely occur within the next five years due to availability of hosts), management should be able to curtail major losses in the Dawson Creek area.

In areas with new or no current MPB attack, especially in areas within the expanding range, there is relatively high uncertainty of how the MPB may spread, such as in central-western Alberta. We developed graph-based connectivity methods to assess the spatial pattern of high susceptibility hosts across broad regions, under historic, existing or future climates. This information has been useful to help prioritize and rank stands for treatment in areas of imminent or future risk, and to identify areas for which treatment has no benefit.