4.7 Article

Is invasion history a useful tool for predicting the impacts of the world's worst aquatic invasive species?

Journal

ECOLOGICAL APPLICATIONS
Volume 21, Issue 1, Pages 189-202

Publisher

ECOLOGICAL SOC AMER
DOI: 10.1890/09-1452.1

Keywords

common carp; Cyprinus carpio; impact; invasive species; meta-analysis; predictive model; risk assessment

Funding

  1. Natural Sciences and Engineering Research Council of Canada
  2. Le Fonds Quebecois de la Recherche sur la Nature et les Technologies

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The ecological impact stemming from a biological invasion is the most poorly understood aspect of the invasion process. While forecasting methods are generally lacking, a potential means of predicting future impacts is to examine the effects caused by a nonindigenous species (NIS) at previously invaded locations, i.e., its invasion history. However, given the context dependence of impact and the scarcity of data, it is uncertain whether invasion history can in fact be used to forecast the effects of most introduced species. Using a sample of 19 aquatic NIS listed with the IUCN's 100 World's Worst Alien Invasive Species, we reviewed the literature to determine (1) the amount of information currently available concerning their ecological impacts, (2) if the effects reported to be caused by each NIS are consistent across multiple studies, and (3) whether their invasion histories provide sufficient quantitative information to assess and forecast the severity of their impacts on recipient environments. As a case study, we conducted a meta-analysis and developed models that relate the severity of the impacts of a well-documented invader, common carp (Cyprinus carpio), to two potential predictor variables: biomass and time since introduction. We then tested whether models developed from one set of observations can predict the severity of impacts reported at other sites. Models incorporating biomass and pre-impact conditions explained 91% of the variation in carp impact severity at new locations (i.e., those not used to build the models). For most other NIS, limited availability of comparable quantitative data currently prevents the development of similar empirical models for predicting the severity of future impact. Nonetheless, invasion history can often be used to develop informative predictions concerning the type and direction of impacts to be expected at novel recipient sites.

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