Theoretical Ecology

, Volume 1, Issue 3, pp 163–177

Connecting host physiology to host resistance in the conifer-bark beetle system

Original Paper


Host defenses can generate Allee effects in pathogen populations when the ability of the pathogen to overwhelm the defense system is density-dependent. The host–pathogen interaction between conifer hosts and bark beetles is a good example of such a system. If the density of attacking beetles on a host tree is lower than a critical threshold, the host repels the attack and kills the beetles. If attack densities are above the threshold, then beetles kill the host tree and successfully reproduce. While the threshold has been found to correlate strongly with host growth, an explicit link between host physiology and host defense has not been established. In this article, we revisit published models for conifer-bark beetle interactions and demonstrate that the stability of the steady states is not consistent with empirical observations. Based on these results, we develop a new model that explicitly describes host damage caused by the pathogen and use the physiological characteristics of the host to relate host growth to defense. We parameterize the model for mountain pine beetles and compare model predictions with independent data on the threshold for successful attack. The agreement between model prediction and the observed threshold suggests the new model is an effective description of the host–pathogen interaction. As a result of the link between the host–pathogen interaction and the emergent Allee effect, our model can be used to better understand how the characteristics of different bark beetle and host species influence host–pathogen dynamics in this system.


Host–pathogen models Attack threshold Allee effect Bark beetles Resin defenses Mountain pine beetles Carbon budget model 

Copyright information

© Springer Science+Business Media B.V. 2008

Authors and Affiliations

  1. 1.Department of Biological SciencesUniversity of AlbertaEdmontonCanada
  2. 2.Department of Mathematical and Statistical SciencesUniversity of AlbertaEdmontonCanada
  3. 3.Department of BiologyQueen’s UniversityKingstonCanada

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