School of BioSciences - Research Publications

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    Reconstructing the dynamics of managed populations to estimate the impact of citizen surveillance
    Spring, D ; Le, TP ; Bloom, SA ; Keith, JM ; Kompas, T (ELSEVIER, 2023-01)
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    Budgeting and portfolio allocation for biosecurity measures
    Kompas, T ; Chu, L ; Pham, VH ; Spring, D (WILEY, 2019-07)
    This paper presents a practical model for optimally allocating a budget across different biosecurity threats and measures (e.g. prevention or border quarantine, active surveillance for early detection, and containment and eradication measures) to ensure the highest rate of return. Our portfolio model differs from the common principle, which ranks alternative projects by their benefit cost ratios and picks the one that generates the highest average benefit cost ratio. The model we propose, instead, aims to allocate shares of the budget to the species where it is most cost‐effective, and consequently determine the optimal scale of the control program for each threat under varying budget constraints. The cost‐effectiveness of each block of budget spent on a threat is determined by minimising its expected total cost, including the damages it inflicts, and the control expenditures incurred in preventing or mitigating damages. As an illustration, the model is applied to the optimal allocation of a budget across four of Australia's most dangerous pests and diseases: red imported fire ants; foot‐and‐mouth disease; papaya fruit fly; and orange hawkweed. The model can readily be extended to consider more species and activities, and more complex settings including cases where detailed spatial and temporal information needs to be considered.
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    Look before you treat: increasing the cost effectiveness of eradication programs with aerial surveillance
    Spring, D ; Croft, L ; Kompas, T (SPRINGER, 2017-02)
    Most successful invasive species eradication programs were applied to invasions confined to a small area. Invasions occupying large areas at a low density can potentially be eradicated if individual infestations can be found at affordable cost. The development of low cost aerial surveillance methods allows for larger areas to be monitored but such methods often have lower sensitivity than conventional surveillance methods, making their cost-effectiveness uncertain. Here, we consider the cost-effectiveness of including a new aerial monitoring method in Australia’s largest eradication program, the campaign to eradicate red imported fire ants (Solenopsis invicta). The program previously relied on higher sensitivity ground surveillance and broadcast treatment. The high cost of those methods restricted the total area that could be managed with available resources below the level required to prevent ongoing expansion of the invasion. By increasing the area that can be monitored and thereby improving the targeting of treatment and ground surveillance, we estimate that remote sensing could substantially reduce eradication costs despite the method’s low sensitivity. The development of low cost monitoring methods could potentially lead to substantially improved management of invasive species.
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    A generalised and scalable framework for modelling incursions, surveillance and control of plant and environmental pests
    Bradhurst, R ; Spring, D ; Stanaway, M ; Milner, J ; Kompas, T (Elsevier BV, 2021-05)
    Invasive plant and environmental pests can seriously impact environment, economy, health and amenity. It is challenging to form response policies given the diversity of pest species; complex spatiotemporal interplay between arrival, spread, surveillance, and control; and limited field data when pests are rare/absent. Models can provide useful decision support through the exploration of incursion pathways and comparison of surveillance and control strategies. However, increased use of quantitative models to inform pest management requires adaptable modelling frameworks. The new Australian Priority Pest and Disease modelling framework (APPDIS) allows pest models to be constructed through user configuration choices for a broad range of different pest types. Pest populations may be defined as point incursions, established populations, or estimated mechanistically from environmental criteria. Spread occurs at multiple scales, through either simple mathematical kernels, or more complex spatial pathways, depending on data availability and pest type. Useful experiments can be conducted on general surveillance, specific surveillance, and treatment regimes. Control activities are dynamically resource-constrained and costed for relative comparisons in terms of benefit and cost. A case study on a tramp ant incursion is provided for illustrative purposes.
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    Delimiting a species' geographic range using posterior sampling and computational geometry
    Keith, JM ; Spring, D ; Kompas, T (Nature Publishing Group, 2019-06-20)
    Accurate delimitation of the geographic range of a species is important for control of biological invasions, conservation of threatened species, and understanding species range dynamics under environmental change. However, estimating range boundaries is challenging because monitoring methods are imperfect, the area that might contain individuals is often incompletely surveyed, and species may have patchy distributions. In these circumstances, large areas can be surveyed without finding individuals despite occupancy extending beyond surveyed areas, resulting in underestimation of range limits. We developed a delimitation method that can be applied with imperfect survey data and patchy distributions. The approach is to construct polygons indicative of the geographic range of a species. Each polygon is associated with a specific probability such that each interior point of the polygon has at least that posterior probability of being interior to the true boundary according to a Bayesian model. The method uses the posterior distribution of latent quantities derived from an agent-based Bayesian model and calculates the posterior distribution of the range as a derived quantity from Markov chain Monte Carlo samples. An application of this method described here informed the Australian campaign to eradicate red imported fire ants (Solenopsis invicta).