School of BioSciences - Research Publications

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    Integrated perspective on translating biophysical to economic impacts of climate change
    Piontek, F ; Drouet, L ; Emmerling, J ; Kompas, T ; Mejean, A ; Otto, C ; Rising, JS ; Soergel, B ; Taconet, N ; Tavoni, M (NATURE PORTFOLIO, 2021-07)
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    Early Decision Indicators for Foot-and-Mouth Disease Outbreaks in Non-Endemic Countries
    Garner, MG ; East, IJ ; Stevenson, M ; Sanson, RL ; Rawdon, TG ; Bradhurst, RA ; Roche, SE ; Van Ha, P ; Kompas, T (Frontiers Media, 2016)
    This Research Topic presents valuable studies presenting different aspects and implementations of mathematical modeling for disease spread and control in the veterinary field.
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    Optimal surveillance against foot-and-mouth disease: the case of bulk milk testing in Australia
    Kompas, T ; Pham, VH ; Hoa, TMN ; East, I ; Roche, S ; Garner, G (WILEY, 2017-10)
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    Optimal surveillance against bioinvasions: a sample average approximation method applied to an agent-based spread model
    Hoa-Thi-Minh, N ; Pham, VH ; Kompas, T (WILEY, 2021-12)
    Trade-offs exist between the point of early detection and the future cost of controlling any invasive species. Finding optimal levels of early detection, with post-border active surveillance, where time, space and randomness are explicitly considered, is computationally challenging. We use a stochastic programming model to find the optimal level of surveillance and predict damages, easing the computational challenge by combining a sample average approximation (SAA) approach and parallel processing techniques. The model is applied to the case of Asian Papaya Fruit Fly (PFF), a highly destructive pest, in Queensland, Australia. To capture the non-linearity in PFF spread, we use an agent-based model (ABM), which is calibrated to a highly detailed land-use raster map (50 m × 50 m) and weather-related data, validated against a historical outbreak. The combination of SAA and ABM sets our work apart from the existing literature. Indeed, despite its increasing popularity as a powerful analytical tool, given its granularity and capability to model the system of interest adequately, the complexity of ABM limits its application in optimizing frameworks due to considerable uncertainty about solution quality. In this light, the use of SAA ensures quality in the optimal solution (with a measured optimality gap) while still being able to handle large-scale decision-making problems. With this combination, our application suggests that the optimal (economic) trap grid size for PFF in Queensland is ˜0.7 km, much smaller than the currently implemented level of 5 km. Although the current policy implies a much lower surveillance cost per year, compared with the $2.08 million under our optimal policy, the expected total cost of an outbreak is $23.92 million, much higher than the optimal policy of roughly $7.74 million.
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    Equilibrium Modeling for Environmental Science: Exploring the Nexus of Economic Systems and Environmental Change
    Cantele, M ; Bal, P ; Kompas, T ; Hadjikakou, M ; Wintle, B (AMER GEOPHYSICAL UNION, 2021-09)
    Abstract Equilibrium models (EMs) are frequently employed to examine the potential impacts of economic, energy, and trade policies as well as form the foundation of most integrated assessment models. Despite their central role coupling economic and environmental systems, environmental scientists are largely unfamiliar with the structure and methodology underpinning EMs, which serves as a barrier to interdisciplinary collaboration and model improvement. In this study we systematically extract data from 10 years of published EMs with a focus on how these models have been extended beyond their economic origins to encompass environmentally relevant sectors of interest. The results indicate that there is far greater spatial coverage of high income countries compared to low income countries, with notable gaps in Central America, Africa, the Middle East, and Central Asia. We also find a high degree of aggregation within production inputs and sectoral outputs, particularly within the context of global socioeconomic scenarios. For example, we were unable to identify a single temporally dynamic study that distinguished between products arising from managed versus natural forest, or pastures relative to natural grasslands. Due to the necessary breadth and associated knowledge gaps within a model of the entire global economy, we see considerable potential for cross‐disciplinary innovation as natural scientists gain familiarity into the role these models play in bridging the nexus between socioeconomic systems and environmental change.
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    Approaches for estimating benefits and costs of interventions in plant biosecurity across invasion phases
    Welsh, MJ ; Turner, JA ; Epanchin-Niell, RS ; Monge, JJ ; Soliman, T ; Robinson, AP ; Kean, JM ; Phillips, C ; Stringer, LD ; Vereijssen, J ; Liebhold, AM ; Kompas, T ; Ormsby, M ; Brockerhoff, EG (WILEY, 2021-07)
    Nonnative plant pests cause billions of dollars in damages. It is critical to prevent or reduce these losses by intervening at various stages of the invasion process, including pathway risk management (to prevent pest arrival), surveillance and eradication (to counter establishment), and management of established pests (to limit damages). Quantifying benefits and costs of these interventions is important to justify and prioritize investments and to inform biosecurity policy. However, approaches for these estimations differ in (1) the assumed relationship between supply, demand, and prices, and (2) the ability to assess different types of direct and indirect costs at invasion stages, for a given arrival or establishment probability. Here we review economic approaches available to estimate benefits and costs of biosecurity interventions to inform the appropriate selection of approaches. In doing so, we complement previous studies and reviews on estimates of damages from invasive species by considering the influence of economic and methodological assumptions. Cost accounting is suitable for rapid decisions, specific impacts, and simple methodological assumptions but fails to account for feedbacks, such as market adjustments, and may overestimate long-term economic impacts. Partial equilibrium models consider changes in consumer and producer surplus due to pest impacts or interventions and can account for feedbacks in affected sectors but require specialized economic models, comprehensive data sets, and estimates of commodity supply and demand curves. More intensive computable general equilibrium models can account for feedbacks across entire economies, including capital and labor, and linkages among these. The two major considerations in choosing an approach are (1) the goals of the analysis (e.g., consideration of a single pest or intervention with a limited range of impacts vs. multiple interventions, pests or sectors), and (2) the resources available for analysis such as knowledge, budget and time.
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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 Global MetaUniversity to Lead by Design to a Sustainable Well-Being Future
    Costanza, R ; Kubiszewski, I ; Kompas, T ; Sutton, PC (Frontiers, 2021-05-07)
    The COVID19 pandemic has revealed deep, ingrained problems with higher education, but also opportunities for positive transformation. In the post-COVID world, education at all levels has the chance to become: (1) universally available at low cost; (2) focused on developing competencies, (3) empowering fulfilling lives, not merely job training; and (4) engaged with communities to solve real-world problems. Achieving this will require overcoming the mass production model of higher education by utilizing the full potential of the Internet in creative ways balanced with face-to-face solutions-based integrated learning, research, and outreach agenda. Building a global collaborative consortium of universities and other educational institutions can move this agenda forward. We describe how this “MetaUniversity” could be structured and how it would serve to advance this agenda and lead the way to a sustainable well-being future for humanity and the rest of nature.