Prevent, search or destroy? a partially observable model for invasive species management

Rout, Tracy M., Moore, Joslin L. and Mccarthy, Michael A. (2014) Prevent, search or destroy? a partially observable model for invasive species management. Journal of Applied Ecology, 51 3: 804-813. doi:10.1111/1365-2664.12234

Author Rout, Tracy M.
Moore, Joslin L.
Mccarthy, Michael A.
Title Prevent, search or destroy? a partially observable model for invasive species management
Journal name Journal of Applied Ecology   Check publisher's open access policy
ISSN 1365-2664
Publication date 2014-06-01
Year available 2014
Sub-type Article (original research)
DOI 10.1111/1365-2664.12234
Open Access Status
Volume 51
Issue 3
Start page 804
End page 813
Total pages 10
Place of publication Oxford, United Kingdom
Publisher Wiley-Blackwell Publishing
Language eng
Formatted abstract

1. The extensive impact of invasive species has motivated a growing field of research combining ecological and economic models to find cost-effective management strategies. Ecological systems are rarely perfectly observable, meaning decision-makers are usually uncertain about the current extent of an infestation and even whether an invasive species is present or absent. We show how to account for this uncertainty when providing decision support for invasive species management.
2. We constructed the first partially observable model to analyse the trade-off between all three facets of invasive species management: quarantine, surveillance and control. We use a partially observable Markov decision process (POMDP) to determine how to allocate resources between these actions when the extent of an invasion is uncertain. We use a case study of potential black rat Rattus rattus invasion on Barrow Island, Western Australia.
3. Our model shows it is often better to manage based on an uncertain belief in species presence than to spend money trying to confirm the presence or absence through surveillance. While it was never optimal to invest solely in surveillance to reduce uncertainty, it was often optimal to combine surveillance with quarantine or control. These mixed strategies, where multiple actions are implemented simultaneously, were more often optimal than for similar decision models where the extent of the infestation is known, suggesting an element of risk spreading.
4. Optimal investments in each action were driven by their estimated efficacy, and the difference in the estimated impact of a localized and widespread invasion. For example, in our case study, it was often optimal to invest solely in control due to the low estimated efficacy of quarantine and the relatively small impact of a localized incursion.
5. Synthesis and applications. Our analysis shows that the cost of reducing uncertainty through surveillance is not always accompanied by an improvement in management outcomes. By carefully analysing the benefits of surveillance prior to implementation of invasive species management strategies, managers can avoid wasting resources and improve management outcomes.
Keyword Control
Markov decision process
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2015 Collection
School of Biological Sciences Publications
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Citation counts: TR Web of Science Citation Count  Cited 12 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 16 times in Scopus Article | Citations
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