Niche differentiation and fine-scale projections for Argentine ants based on remotely sensed data

Núria Roura-Pascual, Andrew V. Suarez, Kristina McNyset, Crisanto Gómez, Pere Pons, Yoshifumi Touyama, Alexander L. Wild, Ferran Gascon, A. Townsend Peterson

Research output: Contribution to journalArticlepeer-review

Abstract

Modeling ecological niches of species is a promising approach for predicting the geographic potential of invasive species in new environments. Argentine ants (Linepithema humile) rank among the most successful invasive species: native to South America, they have invaded broad areas worldwide. Despite their widespread success, little is known about what makes an area susceptible - or not - to invasion. Here, we use a genetic algorithm approach to ecological niche modeling based on high-resolution remote-sensing data to examine the roles of niche similarity and difference in predicting invasions by this species. Our comparisons support a picture of general conservatism of the species' ecological characteristics, in spite of distinct geographic and community contexts.

Original languageEnglish (US)
Pages (from-to)1832-1841
Number of pages10
JournalEcological Applications
Volume16
Issue number5
DOIs
StatePublished - Oct 2006

Keywords

  • Biological invasions
  • Ecological differentiation
  • Ecological niche
  • Genetic Algorithm for Rule-set Prediction (GARP)
  • Iberian Peninsula
  • Invasive spread
  • Japan
  • Linepithema humile
  • Moderate resolution imaging spectroradiometer (MODIS)
  • North America

ASJC Scopus subject areas

  • Ecology

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