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Buffel grass and climate change: a framework for projecting invasive species distributions when data are scarce

Martin, Tara G., Murphy, Helen, Liedloff, Adam C., Thomas, Colette, Chadès, Iadine, Cook, Garry D., Fensham, Roderick, McIvor, John and van Klinken, Rieks D. (2015). Buffel grass and climate change: a framework for projecting invasive species distributions when data are scarce. Biological Invasions,17(11):3197-3210.

Document type: Journal Article
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IRMA ID 84376995xPUB269
Title Buffel grass and climate change: a framework for projecting invasive species distributions when data are scarce
Author Martin, Tara G.
Murphy, Helen
Liedloff, Adam C.
Thomas, Colette
Chadès, Iadine
Cook, Garry D.
Fensham, Roderick
McIvor, John
van Klinken, Rieks D.
Journal Name Biological Invasions
Publication Date 2015
Volume Number 17
Issue Number 11
ISSN 1387-3547   (check CDU catalogue  open catalogue search in new window)
Start Page 3197
End Page 3210
Total Pages 14
Place of Publication Netherlands
Publisher Springer Netherlands
HERDC Category C1 - Journal Article (DIISR)
Abstract Invasive species pose a substantial risk to native biodiversity. As distributions of invasive species shift in response to changes in climate so will management priorities and investment. To develop cost-effective invasive species management strategies into the future it is necessary to understand how species distributions are likely to change over time and space. For most species however, few data are available on their current distributions, let alone projected future distributions. We demonstrate the benefits of Bayesian Networks (BNs) for projecting distributions of invasive species under various climate futures, when empirical data are lacking. Using the introduced pasture species, buffel grass (Cenchrus ciliaris) in Australia as an example, we employ a framework by which expert knowledge and available empirical data are used to build a BN. The framework models the susceptibility and suitability of the Australian continent to buffel grass colonization using three invasion requirements; the introduction of plant propagules to a site, the establishment of new plants at a site, and the persistence of established, reproducing populations. Our results highlight the potential for buffel grass management to become increasingly important in the southern part of the continent, whereas in the north conditions are projected to become less suitable. With respect to biodiversity impacts, our modelling suggests that the risk of buffel grass invasion within Australia’s National Reserve System is likely to increase with climate change as a result of the high number of reserves located in the central and southern portion of the continent. In situations where data are limited, we find BNs to be a flexible and inexpensive tool for incorporating existing process-understanding alongside bioclimatic and edaphic variables for projecting future distributions of species invasions
Keywords BN
Bayesian belief network
Expert judgement
Expert elicitation
Invasive species
Exotic pasture
Cenchrus ciliaris
Species distribution models
DOI http://dx.doi.org/10.1007/s10530-015-0945-9   (check subscription with CDU E-Gateway service for CDU Staff and Students  check subscription with CDU E-Gateway in new window)
 
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