Predictive modelling to aid the regional-scale management of a vertebrate pest
Article
Article Title | Predictive modelling to aid the regional-scale management of a vertebrate pest |
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ERA Journal ID | 3212 |
Article Category | Article |
Authors | Murray, Justine V. (Author), Berman, David McK. (Author) and van Klinken, Rieks D. (Author) |
Journal Title | Biological Invasions |
Journal Citation | 16 (11), pp. 2403-2425 |
Number of Pages | 22 |
Year | 2014 |
Publisher | Springer |
Place of Publication | Netherlands |
ISSN | 1387-3547 |
1573-1464 | |
Digital Object Identifier (DOI) | https://doi.org/10.1007/s10530-014-0673-6 |
Web Address (URL) | https://link.springer.com/article/10.1007%2Fs10530-014-0673-6 |
Abstract | Extensive resources are allocated to managing vertebrate pests, yet spatial understanding of pest threats, and how they respond to management, is limited at the regional scale where much decision- making is undertaken. We provide regional-scale spatial models and management guidance for Euro- pean rabbits (Oryctolagus cuniculus) in a 260,791 km2 region in Australia by determining habitat suitability, habitat susceptibility and the effects of the primary rabbit management options (barrier fence, shooting and baiting and warren ripping) or changing predation or disease control levels. A participatory modelling approach was used to develop a Bayesian network which captured the main drivers of suitability and spread, which in turn was linked spatially to develop high resolution risk maps. Policy-makers, rabbit managers and technical experts were responsible for defining the questions the model needed to address, and for subsequently developing and the model. Habitat suitability was determined by conditions required for warren-building and by above-ground requirements, such as food and harbour, and habitat susceptibility by the distance from current distributions, habitat suitability, and the costs of traversing habitats of different quality. At least one-third of the region had a high probability of being highly suitable (support high rabbit densities), with the model supported by validation. Habitat susceptibility was largely restricted by the current known rabbit distribution. Warren ripping was the most effective control option as warrens were considered essential for rabbit persistence. The anticipated increase in disease resistance was predicted to increase the probability of moderately suitable habitat becoming highly suitable, but not increase the at-risk area. We demonstrate that it is possible to build spatial models to guide regional-level management of vertebrate pests which use the best available knowledge and capture fine spatial-scale processes. |
Keywords | European rabbit, Bayesian networks, habitat suitability, susceptibility, warren ripping, predators, disease, cost-distance |
ANZSRC Field of Research 2020 | 410404. Environmental management |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | Commonwealth Scientific and Industrial Research Organisation (CSIRO), Australia |
Queensland Murray Darling Committee, Australia | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q4vy5/predictive-modelling-to-aid-the-regional-scale-management-of-a-vertebrate-pest
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