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

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.

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PID https://www.doi.org/10.1371/journal.pone.0068678
PID pmc:PMC3706395
PID pmid:23874718
URL http://dx.plos.org/10.1371/journal.pone.0068678
URL https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3706395/
URL http://europepmc.org/articles/PMC3706395?pdf=render
URL https://doi.org/10.1371/journal.pone.0068678
URL https://paperity.org/p/60627205/are-high-impact-species-predictable-an-analysis-of-naturalised-grasses-in-northern
URL https://academic.microsoft.com/#/detail/2196316583
URL http://eprints.lincoln.ac.uk/id/eprint/39017/
URL http://era.deedi.qld.gov.au/3926/
URL https://dx.plos.org/10.1371/journal.pone.0068678
URL https://espace.library.uq.edu.au/view/UQ:308551
URL https://www.cabdirect.org/cabdirect/abstract/20133308604
URL https://doaj.org/toc/1932-6203
URL http://europepmc.org/articles/PMC3706395
URL http://dx.doi.org/10.1371/journal.pone.0068678
URL https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0068678
URL http://eprints.lincoln.ac.uk/id/eprint/39017/1/Van%20Klinken%20et%20al.%202013.pdf
URL http://era.daf.qld.gov.au/id/eprint/3926/
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Access Right Open Access
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Author Shaun Coutts, 0000-0003-0282-4559
Author Rieks van Klinken, 0000-0002-7578-8977
Contributor van Kleunen, Mark
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Collected From PubMed Central; ORCID; Datacite; UnpayWall; DOAJ-Articles; Crossref; Microsoft Academic Graph; University of Lincoln Institutional Repository
Hosted By Europe PubMed Central; PLoS ONE; University of Lincoln Institutional Repository
Publication Date 2013-07-09
Publisher Public Library of Science
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Country United Kingdom
Format application/pdf
Language English
Resource Type Other literature type; Article
keyword Q
keyword R
keyword keywords.General Biochemistry, Genetics and Molecular Biology
system:type publication
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Source https://science-innovation-policy.openaire.eu/search/publication?articleId=dedup_wf_001::bbac6f44ab3edbcedbfad518137c6e81
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Last Updated 26 December 2020, 05:51 (CET)
Created 26 December 2020, 05:51 (CET)