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Steven I Higgins1, David M Richardson2

  • 1Department of Botany, University of Otago, Dunedin 9054, New Zealand; and steven.higgins@otago.ac.nz.

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Predicting invasive species is challenging. This study links species distribution models with introduction data, finding that broader environmental tolerance increases invasion risk, though specific traits are context-dependent.

Keywords:
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Area of Science:

  • Ecology
  • Invasive Species Biology
  • Biogeography

Background:

  • Invasive species pose significant economic and ecological threats globally.
  • Predicting which introduced species will become invasive remains a major challenge for ecologists.
  • Unintentional introductions offer valuable insights into invasion dynamics.

Purpose of the Study:

  • To develop a predictive model for species invasion risk.
  • To link physiological niche breadth with invasive success.
  • To understand the context-specific nature of traits defining invasive species.

Main Methods:

  • Utilized a physiologically based species distribution model.
  • Integrated data on the invasive success of 749 Australian acacia and eucalypt species introduced worldwide.
  • Validated the model against an independent dataset of introduced species occurrences.

Main Results:

  • The model achieved 92% accuracy in predicting species occurrences outside Australia.
  • Invasiveness was positively correlated with physiological niche volume projected across geographic space.
  • Species with broader environmental tolerance showed higher invasive potential.

Conclusions:

  • Broader physiological tolerance is a key predictor of invasive success.
  • The traits conferring invasiveness are context-specific, explaining previous research inconsistencies.
  • This approach reconciles predictive modeling with the need to manage invasive species.