Heterogeneity shapes invasion: host size and environment influence susceptibility to a nonnative pathogen

Ecol Appl. 2006 Feb;16(1):166-75. doi: 10.1890/05-0211.

Abstract

Theoretical study of invasion dynamics has suggested that spatial heterogeneity should strongly influence the rate and extent of spreading organisms. However, empirical support for this prediction is scant, and the importance of understanding heterogeneity for real-world systems has remained ambiguous. This study quantified the influence of host and environmental heterogeneity on the dynamics of a 19-year disease invasion by the exotic and fatal pathogen, Phytophthora lateralis, within a stream population of its host tree, Port Orford cedar (Chamaecyparis lawsoniana). Using dendrochronology, we reconstructed the invasion history along a 1350-m length of infected stream, which serves as the only route of pathogen dispersal. Contrary to theoretical predictions, the temporal progression of the disease invasion was not related to a host's downstream spatial position, but instead was determined by two sources of heterogeneity: host size and proximity to the stream channel. These sources of heterogeneity influenced both the epidemic and endemic dynamics of this pathogen invasion. This analysis provides empirical support for the influence of heterogeneity on the invasion dynamics of a commercially important forest pathogen and highlights the need to incorporate such natural variability into both invasion theory and methods aimed at controlling future spread.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Animals
  • Chamaecyparis / parasitology*
  • Chamaecyparis / physiology
  • Communicable Diseases / epidemiology
  • Communicable Diseases / parasitology
  • Disease Susceptibility* / epidemiology
  • Disease Susceptibility* / parasitology
  • Disease Transmission, Infectious / prevention & control
  • Ecosystem*
  • Endemic Diseases / prevention & control
  • Environmental Monitoring*
  • Epidemiological Monitoring
  • Host-Parasite Interactions
  • Models, Biological
  • Plant Diseases*
  • Population Dynamics
  • Time Factors