Multi-scale dynamic maps for the management of invading and established wildlife populations: brushtail possums in New Zealand
J. D. Shepherd A C , S. Gillingham A , T. Heuer A , M. C. Barron B , A. E. Byrom B and R. P. Pech BA Landcare Research, Private Bag 11052, Palmerston North 4442, New Zealand.
B Landcare Research, PO Box 69040, Lincoln 7640, New Zealand.
C Corresponding author. Email: shepherdj@landcareresearch.co.nz
Wildlife Research 45(4) 336-343 https://doi.org/10.1071/WR17135
Submitted: 27 September 2017 Accepted: 11 April 2018 Published: 18 July 2018
Abstract
Context: The abundance and distribution of mammalian species often change in response to environmental variability, losses or gains in suitable habitat and, in the case of pest species, control programs. Consequently, conventional distribution maps rapidly become out of date and fail to provide useful information for wildlife managers. For invasive brushtail possum populations in New Zealand, the main causes of change are control programs by central and local government agencies, and post-control recovery through recolonisation and in situ recruitment. Managers need to know current, and likely future, possum population levels relative to control targets to help assess success at preventing the spread of disease or for protecting indigenous species. Information on the outcomes of government-funded possum control needs to be readily available to members of the general public interested in issues such as conservation, disease management and animal welfare.
Aims: To produce dynamic, scalable maps of the current and predicted future distribution and abundance of possums in New Zealand, taking into account changes due to control, and to use recent visualisation technology to make this information accessible to managers and the general public for assessing control strategies at multiple spatial scales.
Methods: We updated an existing individual-based spatial model of possum population dynamics, extending it to represent all individuals in a national population of up to 40 million. In addition, we created a prototype interface for interactive web-based presentation of the model’s predictions.
Key results: The improved capability of the new model for assessing possum management at local-to-national scales provided for real-time, mapped updates and forecasts of the distribution and abundance of possums in New Zealand. The versatility of this platform was illustrated using scenarios for current and emerging issues in New Zealand. These are hypothetical incursions of possums, reinvasion of large areas cleared of possums, and impacts on animal welfare of national-scale management of possums as vectors of bovine tuberculosis (TB).
Conclusions: The new individual-based spatial model for possum populations in New Zealand demonstrated the utility of combining models of wildlife population dynamics with high-speed computing capability to provide up-to-date, easily accessible information on a species’ distribution and abundance. Applications include predictions for future changes in response to incursions, reinvasion and large-scale possum control. Similar models can be used for other species for which there are suitable demographic data, typically pest species, harvested species or species with a high conservation value.
Implications: Models such as the spatial model for possums in New Zealand can provide platforms for (1) real-time visualisation of wildlife distribution and abundance, (2) reporting and assessing progress towards achieving management goals at multiple scales, (3) use as a decision-support tool to scope potential changes in wildlife populations or simulate the outcomes of alternative management strategies, and (4) making information about pest control publicly available.
Additional keywords: animal ethics, invasion, pest management, population modelling, range expansion, reinvasion.
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