Predicting the spread of all invasive forest pests in the United States

Ecol Lett. 2017 Apr;20(4):426-435. doi: 10.1111/ele.12741. Epub 2017 Feb 8.

Abstract

We tested whether a general spread model could capture macroecological patterns across all damaging invasive forest pests in the United States. We showed that a common constant dispersal kernel model, simulated from the discovery date, explained 67.94% of the variation in range size across all pests, and had 68.00% locational accuracy between predicted and observed locational distributions. Further, by making dispersal a function of forest area and human population density, variation explained increased to 75.60%, with 74.30% accuracy. These results indicated that a single general dispersal kernel model was sufficient to predict the majority of variation in extent and locational distribution across pest species and that proxies of propagule pressure and habitat invasibility - well-studied predictors of establishment - should also be applied to the dispersal stage. This model provides a key element to forecast novel invaders and to extend pathway-level risk analyses to include spread.

Keywords: Dispersal kernel; habitat invasibility; macroecology; propagule pressure; spatially explicit.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animal Distribution
  • Animals
  • Computer Simulation*
  • Conservation of Natural Resources*
  • Forests*
  • Fungi / physiology*
  • Insecta / physiology*
  • Introduced Species*
  • Mites / physiology*
  • Models, Biological
  • Population Dynamics
  • United States

Associated data

  • Dryad/10.5061/dryad.75265