Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/107341
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Type: Journal article
Title: Predicting the risk of biological invasions using environmental similarity and transport network connectedness
Author: Cope, R.
Ross, J.
Wittmann, T.
Watts, M.
Cassey, P.
Citation: Risk Analysis, 2017; OnlinePubl:1-19
Publisher: Wiley
Issue Date: 2017
ISSN: 0272-4332
1539-6924
Statement of
Responsibility: 
Robert C. Cope, Joshua V. Ross, Talia A. Wittmann, Michael J. Watts, and Phillip Cassey
Abstract: Understanding the risk of biological invasions associated with particular transport pathways and source regions is critical for implementing effective biosecurity management. This may require both a model for physical connectedness between regions, and a measure of environmental similarity, so as to quantify the potential for a species to be transported from a given region and to survive at a destination region. We present an analysis of integrated biosecurity risk into Australia, based on flights and shipping data from each global geopolitical region, and an adaptation of the "range bagging" method to determine environmental matching between regions. Here, we describe global patterns of environmental matching and highlight those regions with many physical connections. We classify patterns of global invasion risk (high to low) into Australian states and territories. We validate our analysis by comparison with global presence data for 844 phytophagous insect pest species, and produce a list of high-risk species not previously known to be present in Australia. We determined that, of the insect pest species used for validation, the species most likely to be present in Australia were those also present in geopolitical regions with high transport connectivity to Australia, and those regions that were geographically close, and had similar environments.
Keywords: Australia; biological invasions; biosecurity; climate similarity; flights; shipping
Description: First published: 10 August 2017
Rights: © 2017 Society for Risk Analysis
RMID: 0030074159
DOI: 10.1111/risa.12870
Grant ID: http://purl.org/au-research/grants/arc/DP140102319
http://purl.org/au-research/grants/arc/FT0991420
http://purl.org/au-research/grants/arc/FT130100254
Appears in Collections:Mathematical Sciences publications

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