Are high-impact species predictable? An analysis of naturalised grasses in Northern Australia

van Klinken, Rieks D., Panetta, F. Dane and Coutts, Shaun R. (2013) Are high-impact species predictable? An analysis of naturalised grasses in Northern Australia. PLoS ONE, 8 7: e68678.1-e68678.10. doi:10.1371/journal.pone.0068678


Author van Klinken, Rieks D.
Panetta, F. Dane
Coutts, Shaun R.
Title Are high-impact species predictable? An analysis of naturalised grasses in Northern Australia
Journal name PLoS ONE   Check publisher's open access policy
ISSN 1932-6203
Publication date 2013-07
Year available 2013
Sub-type Article (original research)
DOI 10.1371/journal.pone.0068678
Open Access Status DOI
Volume 8
Issue 7
Start page e68678.1
End page e68678.10
Total pages 11
Place of publication San Francisco, CA United States
Publisher Public Library of Science
Collection year 2014
Language eng
Formatted abstract
Predicting which species are likely to cause serious impacts in the future is crucial for targeting management efforts, but the characteristics of such species remain largely unconfirmed. We use data and expert opinion on tropical and subtropical grasses naturalised in Australia since European settlement to identify naturalised and high-impact species and subsequently to test whether high-impact species are predictable. High-impact species for the three main affected sectors (environment, pastoral and agriculture) were determined by assessing evidence against pre-defined criteria. Twenty-one of the 155 naturalised species (14%) were classified as high-impact, including four that affected more than one sector. High-impact species were more likely to have faster spread rates (regions invaded per decade) and to be semi-aquatic. Spread rate was best explained by whether species had been actively spread (as pasture), and time since naturalisation, but may not be explanatory as it was tightly correlated with range size and incidence rate. Giving more weight to minimising the chance of overlooking high-impact species, a priority for biosecurity, meant a wider range of predictors was required to identify high-impact species, and the predictive power of the models was reduced. By-sector analysis of predictors of high impact species was limited by their relative rarity, but showed sector differences, including to the universal predictors (spread rate and habitat) and life history. Furthermore, species causing high impact to agriculture have changed in the past 10 years with changes in farming practice, highlighting the importance of context in determining impact. A rationale for invasion ecology is to improve the prediction and response to future threats. Although our study identifies some universal predictors, it suggests improved prediction will require a far greater emphasis on impact rather than invasiveness, and will need to account for the individual circumstances of affected sectors and the relative rarity of high-impact species.
Keyword Biological Invasions
Plant Introductions
Fire Cycle
Invasiveness
Consequences
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2014 Collection
School of Biological Sciences Publications
 
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