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

Martin, Tara G., Murphy, Helen, Liedloff, Adam, Thomas, Colette, Chadès, Iadine, Cook, Garry, Fensham, Rod, 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). pp. 3197-3210.

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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.

Item ID: 40784
Item Type: Article (Refereed Research - C1)
Keywords: BN, Bayesian belief network, expert judgement, expert elicitation, invasive species, exotic pasture, Cenchrus ciliaris, species distribution models
ISSN: 1573-1464
Funders: Department of Environment, Water, Heritage and the Arts
Date Deposited: 13 Oct 2015 23:15
FoR Codes: 05 ENVIRONMENTAL SCIENCES > 0502 Environmental Science and Management > 050205 Environmental Management @ 30%
05 ENVIRONMENTAL SCIENCES > 0502 Environmental Science and Management > 050211 Wildlife and Habitat Management @ 30%
05 ENVIRONMENTAL SCIENCES > 0501 Ecological Applications > 050101 Ecological Impacts of Climate Change @ 40%
SEO Codes: 96 ENVIRONMENT > 9603 Climate and Climate Change > 960399 Climate and Climate Change not elsewhere classified @ 50%
96 ENVIRONMENT > 9604 Control of Pests, Diseases and Exotic Species > 960410 Control of Pests, Diseases and Exotic Species in Sparseland, Permanent Grassland and Arid Zone Environments @ 50%
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