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Predictive modelling to aid the regional-scale management of a vertebrate pest

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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 European 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 parameterising 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.

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Acknowledgments

We thank the eleven experts who gave us their valuable time to attend the 2-day workshop and participate in the modelling exercise. We thank Luis Laredo and Pierre Audois for help with the spatial modelling and map creation. We would also like to thank Brian Cooke and Darren Kriticos for the CLIMEX parameters for use in the model. We thank the internal CSIRO reviewers (Peter Durr and Hazel Parry) and external reviewers for their critical insights on the manuscript. We thank the Queensland Murray Darling Committee, especially Darren Marshall and Vanessa MacDonald, for encouragement and financial and administrative support provided in this study and the associated workshop.

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  1. Water for Healthy Country Flagship and Biosecurity Flagship, CSIRO Ecosystem Sciences, GPO Box 2583, Brisbane, QLD, 4001, Australia

    Justine V. Murray & Rieks D. van Klinken

  2. Queensland Murray Darling Committee, PO Box 6232, Toowoomba West, QLD, 4350, Australia

    David McK. Berman

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  1. Justine V. Murray
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Correspondence to Justine V. Murray.

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Murray, J.V., Berman, D.M. & van Klinken, R.D. Predictive modelling to aid the regional-scale management of a vertebrate pest. Biol Invasions 16, 2403–2425 (2014). https://doi.org/10.1007/s10530-014-0673-6

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