@article {9449,
	title = {Parasitoids and dipteran predators exploit volatiles from microbial symbionts to locate bark beetles},
	journal = {Environmental Entomology},
	volume = {37},
	number = {1},
	year = {2008},
	month = {February},
	pages = {150-161},
	type = {Article},
	abstract = {Host location by parasitoids and dipteran predators of bark beetles is poorly understood. Unlike coleopteran predators that locate prey by orienting to prey pheromones, wasps and flies often attack life stages not present until after pheromone production ceases. Bark beetles have important microbial symbionts, which could provide sources of cues. We tested host trees, trees colonized by beetles and symbionts, and trees colonized by symbionts alone for attractiveness to hymenopteran parasitoids and dipteran predators. Field studies were conducted with Ips pini in Montana. Three pteromalid wasps were predominant. All were associated with the second and third instars of L pini. Heydenia unica was more attracted to logs colonized by either I. pini or the fungus Ophiostoma ips than logs alone or blank controls (screen with no log). Rhopalicus pulchripennis was more attracted to logs colonized by L pini than logs alone or blank controls. Dibrachys cavus was attracted to logs but did not distinguish whether or not they were colonized. Two dolichopodid predators were predominant. A Medetera species was more attracted to colonized than uncolonized logs and more attracted to logs than blank controls. It was also more attracted to logs colonized with the yeast Pichia scolyti than uncolonized logs, but attraction was less consistent. An unidentified dolichopodid was more attracted to logs colonized with L pini, O. ips, and the bacteria Burkholderia sp., than to uncolonized logs, It was also attracted to uncolonized logs. Its responses were less consistent and pronounced than H. unica. These results suggest some parasitoids and dipteran predators exploit microbial symbionts of bark beetles to locate hosts. Overall, specialists showed strong attraction to fungal cues, whereas generalists were more attracted by plant volatiles. These results also show how microbial symbionts can have conflicting effects on host fitness},
	keywords = {Ips pini},
	isbn = {0046-225X},
	author = {Boone, Celia K. and Six, Diana L. and Zheng, Yanbing and Raffa, Kenneth F.}
}
@article {9113,
	title = {Movement of outbreak populations of mountain pine beetle: influences of spatiotemporal patterns and climate},
	journal = {Ecography},
	volume = {31},
	number = {3},
	year = {2008},
	month = {June},
	pages = {348-358},
	type = {Article},
	abstract = {Insect outbreaks exert landscape-level influences, yet quantifying the relative contributions of various exogenous and endogenous factors that contribute to their pattern and spread remains elusive. We examine an outbreak of mountain pine beetle covering an 800 thousand ha area on the Chilcotin Plateau of British Columbia, Canada, during the 1970s and early 1980s. We present a model that incorporates the spatial and temporal arrangements of outbreaking insect populations, as well as various climatic factors that influence insect development. Onsets of eruptions of mountain pine beetle demonstrated landscape-level synchrony. On average, the presence of outbreaking populations was highly correlated with outbreaking populations within the nearest 18 km the same year and local populations within 6 km in the previous two years. After incorporating these spatial and temporal dependencies, we found that increasing temperatures contributed to explaining outbreak probabilities during this 15 yr outbreak. During collapse years, landscape-level synchrony declined while local synchrony values remained high, suggesting that in some areas host depletion was contributing to population decline. Model forecasts of outbreak propensity one year in advance at a 12 by 12 km scale provided 80\% accuracy over the landscape, and never underestimated the occurrence of locally outbreaking populations. This model provides a flexible approach for linking temperature and insect population dynamics to spatial spread, and complements existing decision support tools for resource managers.},
	keywords = {Dendroctonus ponderosae},
	isbn = {0906-7590},
	author = {Aukema, Brian H. and Carroll, Allan L. and Zheng, Yanbing and Zhu, Jun and Raffa, Kenneth F. and Moore, R. Dan and Stahl, Kerstin and Taylor, Stephen W.}
}
@article {5964,
	title = {Autologistic regression analysis of spatial-temporal binary data via Monte Carlo maximum likelihood},
	journal = {Journal of Agricultural Biological and Environmental Statistics},
	volume = {13},
	number = {1},
	year = {2008},
	month = {March},
	pages = {84-98},
	type = {Article},
	abstract = {This article considers logistic regression analysis of binary data that are measured on a spatial lattice and repeatedly over discrete time points. We propose a spatial-temporal autologistic regression model and draw statistical inference via maximum likelihood. Due to an unknown normalizing constant in the likelihood function, we use Monte Carlo to obtain maximum likelihood estimates of the model parameters and predictive distributions at future time points. We also use path sampling to estimate the unknown normalizing constant and approximate an information criterion for model assessment. The methodology is illustrated by the analysis of a dataset of mountain pine beetle outbreaks in western Canada.},
	keywords = {Dendroctonus ponderosae},
	isbn = {1085-7117},
	author = {Zhu, Jun and Zheng, Yanbing and Carroll, Allan L. and Aukema, Brian H.}
}
