Abstract
Species moved by human activities beyond the limits of their native geographic ranges into areas in which they do not naturally occur (termed aliens) can cause a broad range of significant changes to recipient ecosystems; however, their impacts vary greatly across species and the ecosystems into which they are introduced. There is therefore a critical need for a standardised method to evaluate, compare, and eventually predict the magnitudes of these different impacts. Here, we propose a straightforward system for classifying alien species according to the magnitude of their environmental impacts, based on the mechanisms of impact used to code species in the International Union for Conservation of Nature (IUCN) Global Invasive Species Database, which are presented here for the first time. The classification system uses five semi-quantitative scenarios describing impacts under each mechanism to assign species to different levels of impact-ranging from Minimal to Massive-with assignment corresponding to the highest level of deleterious impact associated with any of the mechanisms. The scheme also includes categories for species that are Not Evaluated, have No Alien Population, or are Data Deficient, and a method for assigning uncertainty to all the classifications. We show how this classification system is applicable at different levels of ecological complexity and different spatial and temporal scales, and embraces existing impact metrics. In fact, the scheme is analogous to the already widely adopted and accepted Red List approach to categorising extinction risk, and so could conceivably be readily integrated with existing practices and policies in many regions.
Publication types
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Research Support, Non-U.S. Gov't
MeSH terms
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Animal Distribution / physiology*
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Animals
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Biodiversity
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Environment*
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Extinction, Biological
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Food Chain
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Herbivory / physiology
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Human Activities / trends
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Humans
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Introduced Species / statistics & numerical data*
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Plant Dispersal / physiology*
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Plants / microbiology
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Plants / parasitology
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Plants / virology
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Population Dynamics / trends
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Predatory Behavior / physiology
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Soil / chemistry
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Species Specificity
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Uncertainty
Grants and funding
The sDiv workshop that led to the sImpact working group was funded by the German Research Foundation DFG (FZT 118). JP, PP, and ZM acknowledge the support from long-term research development project no. RVO 67985939 (Academy of Sciences of the Czech Republic), Centre of Excellence PLADIAS no. 14-36079G, and grant no. P504/11/1028 (Czech Science Foundation), and institutional resources of the Ministry of Education, Youth and Sports of the Czech Republic. PP acknowledges the support by the Praemium Academiae award from the Academy of Sciences of the Czech Republic. JMJ acknowledges support from the ERA-Net BiodivERsA (project FFII), with the national funder German Research Foundation DFG (JE 288/7-1). SK acknowledges financial support from the Swiss National Science Foundation, the DST-NRF Centre of Excellence for Invasion Biology, and the Drakenstein Trust. DMR and JRUW acknowledge support from the DST-NRF Centre of Excellence for Invasion Biology and the National Research Foundation (grants 85417 and 86894, respectively). AS acknowledges financial support of the German Academic Exchange Service (DAAD). MV acknowledges support from the Severo Ochoa Program for Centres of Excellence in R+D+I (SEV-2012-0262). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.