Northern range limit mountain pine beetle (Dendroctonus ponderosae) outbreak dynamics and climate interactions in mixed sub-boreal pine forests of British Columbia.

Insect outbreaks are some of the most destructive processes of forest change with long-term economic and ecological effects that can be severe. For native insects that have co-evolved with their host forests it is important to develop and implement management strategies that are consistent with the basic ecology of the ecosystem being affected. This requires a sound ecological understanding of the disturbance regime and its function, which can only be gained through long-term stand histories appropriate to the scale of the process. This is becoming increasingly important in light of changing climate conditions which have already influenced disturbance regimes and the spatial distribution of insect ranges with unknown consequences. The objectives of this study were to develop a long-term record of mountain pine beetle (MPB) outbreaks near the northern limit of the species' range and to examine the interacting factors driving that disturbance regime. Using a combination of dendrochronological methods to reconstruct stand and outbreak history together with long-term local and large-scale climate data, I developed an integrated model of outbreak dynamics for north-central BC where little is known about the role of MPB in forest stand dynamics or the influence of climate on outbreak development. Using a 200-year outbreak reconstruction I determined that host susceptibility and mortality patterns had distinctly different characteristics than those described further south. Climate was more important than forest structure in determining outbreak frequency and severity, and persistent warm temperature anomalies, including the large-scale climate patterns driving these trends, were the most important direct climate drivers of outbreak development. Over short time scales, host stress preceded outbreaks, but long-term periods of vigorous tree growth were also important for outbreaks to develop. Differences between this study and others suggest that outbreak risk management and predictive models must consider regio