Seminar Announcement

Emerging at the Right Time, Stopping at the Right Place, and Scaling Up the Right Way: Phenology and Differential Motility Describe Patterns of Bark Beetle Outbreak

James Powell, Utah State University, Department of Mathematics and Statistics/Biology

Monday, October 1, 2012

4:00pm, room 223 Weber Building



The mountain pine beetle (MPB, Dendroctonus ponderosae Hopkins), is an aggressive insect
which attacks living host trees (of genus Pinus). Pines have significant defensive mechanisms,
requiring the beetles to attack en masse to successfully colonize. Temperatures directly but
nonlinearly influence the rates at which insects complete development in their various life stages
and therefore the timing (phenology) of their emergence. Since the beetle larvae consume the
phloem underneath the bark each year they exhaust their host, requiring dispersal to new trees.
Adult beetles must colonize during a relatively narrow window of time to take advantage of
warm temperatures for oviposition, but must also attack late enough to make sure that coldhardened
larvae appear during winter freeze. Thus the beetles exist in a precarious niche
depending on carefully synchronized timing and dispersal. Changing temperatures have
broadened that niche across vastly larger regions, leading to tree mortality across more than
thirty million hectares of western North America. Impacts due to MPB have been larger than
fire, challenging researchers to predict risk factors and rates of population growth. However,
statistical models fit to data at a variety of scales have failed to describe MPB outbreaks.
We have developed a mechanistic approach based on differential beetle motility between
forested and unforested habitats and the effects of temperature on MPB phenology. The
resulting PDE model describes MPB aggregation at scales commensurate with changes in host
density. Solutions are complicated and discontinuous, but homogenization results in a
surprisingly simple diffusive PDE suitable for rapid integration over watersheds and regions. In
fact, with a speed-up of over six orders of magnitude, it is feasible to calibrate the model using
Markov Chain Monte Carlo (MCMC) procedures and Aerial Damage Survey (ADS) data from
central Idaho. We determine a distribution of motility and demographic parameters in a
Bayesian framework, and validate the model by comparing with ADS data collected in the
eastern Cascades. This description of MPB behavior captures patterns of observed damage as
well as details of demographic growth rates.