A guide to eliciting and using expert knowledge in Bayesian ecological models

Kuhnert, Petra M.; Martin, Tara G.; Griffiths, Shane P.

doi:10.1111/j.1461-0248.2010.01477.x

Cited by 361 publications

(339 citation statements)

References 51 publications

(85 reference statements)

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“…Although our optimization tool can accommodate differences in parameters across a network, such information is often not available. In the absence of explicit information, expert elicitation can be used and these qualitative values can be incorporated into our framework (44).…”

Section: Discussionmentioning

confidence: 99%

General rules for managing and surveying networks of pests, diseases, and endangered species

Chadès

Martin

Nicol

et al. 2011

Proc. Natl. Acad. Sci. U.S.A.

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193

223

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The efficient management of diseases, pests, or endangered species is an important global issue faced by agencies constrained by limited resources. The management challenge is even greater when organisms are difficult to detect. We show how to prioritize management and survey effort across time and space for networks of susceptible-infected-susceptible subpopulations. We present simple and robust rules of thumb for protecting desirable, or eradicating undesirable, subpopulations connected in typical network patterns (motifs). We further demonstrate that these rules can be generalized to larger networks when motifs are combined in more complex formations. Results show that the best location to manage or survey a pest or a disease on a network is also the best location to protect or survey an endangered species. The optimal starting point in a network is the fastest motif to manage, where line, star, island, and cluster motifs range from fast to slow. Managing the most connected node at the right time and maintaining the same management direction provide advantages over previously recommended outside-in strategies. When a species or disease is not detected and our belief in persistence decreases, our results recommend shifting resources toward management or surveillance of the most connected nodes. Our analytic approximation provides guidance on how long we should manage or survey networks for hard-to-detect organisms. Our rules take into account management success, dispersal, economic cost, and imperfect detection and offer managers a practical basis for managing networks relevant to many significant environmental, biosecurity, and human health issues.conservation planning | decision theory | metapopulation | optimization | Markov decision process I nfectious diseases, invasive pests, and other threats to species persistence have profound impacts on human health, agriculture, and biodiversity (1-3). Many threatened or invasive species are difficult to detect and their presence in an area can be uncertain due to the imperfect nature of most detection methods (4, 5). Even large charismatic mammals such as the Sumatran tiger (Panthera tigris sumatrae) or the Sumatran rhinoceros (Dicerorrhinus sumatrensis) can be surprisingly hard to detect. It is possible that some areas are being managed while the invasive pests, diseases, or threatened species have already disappeared. It is also likely that managers, in the absence of sighting, might stop managing too early and give up too soon on a species or disease (6, 7). Managers need to know when to stop managing or surveying for species in areas of particular interest.At present the epidemiology, ecology, and conservation literature provides little guidance on how to approach such a problem. The problem of how to allocate management and surveillance effort has been studied for a single cryptic population (8-10). For example, Regan et al. (8) determined when to stop monitoring an invasive plant with a long-lived seed bank. Chadès et al. (9) determined when to stop managing ...

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Section: Discussionmentioning

confidence: 99%

General rules for managing and surveying networks of pests, diseases, and endangered species

Chadès

Martin

Nicol

et al. 2011

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

193

223

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“…Given the international context of decommissioning, cultural backgrounds and language uncertainty are likely to be major sources of bias (Kuhnert et al, 2010).…”

Section: Research Requirementsmentioning

confidence: 99%

“…Expert opinion is increasingly being used in environmental decision-making where empirical data are either uncertain or unavailable (Kuhnert et al, 2010;Martin et al, 2012). Expert opinion has already been applied to a wide range of environmental problems, including spatial distribution modeling of declining species (Murray et al, 2009), assessment of climate change impacts (Morgan et al, 2001), and forestry management (Crome et al, 1996).…”

Section: Expert Opinion For Performance Evaluationsmentioning

confidence: 99%

A multi-criteria decision approach to decommissioning of offshore oil and gas infrastructure

Fowler

Macreadie

Jones

et al. 2014

Ocean & Coastal Management

149

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Article (refereed) -postprintFowler, A.M.; Macreadie, P.I.; Jones, D.O.B.; Booth, D.J.. 2014 A multi-criteria decision approach to decommissioning of offshore oil and gas infrastructure. Ocean & Coastal Management, 87. 20-29. 10.1016/j.ocecoaman.2013 Contact NOC NORA team at publications@noc.soton.ac.ukThe NERC and NOC trademarks and logos ('the Trademarks') are registered trademarks of NERC in the UK and other countries, and may not be used without the prior written consent of the Trademark owner.A multi-criteria decision approach to decommissioning of offshore oil and gas infrastructure AbstractThousands of the world's offshore oil and gas structures are approaching obsolescence and will require decommissioning within the next decade. Many nations have blanket regulations requiring obsolete structures to be removed, yet this option is unlikely to yield optimal environmental, societal and economic outcomes in all situations. We propose that nations adopt a flexible approach that allows decommissioning options to be selected from the full range of alternatives (including 'rigs-to-reefs' options) on a case-by-case basis. We outline a method of multi-criteria decision analysis (Multi-criteria Approval, MA) for evaluating and comparing alternative decommissioning options across key selection criteria, including environmental, financial, socioeconomic, and health and safety considerations. The MA approach structures the decision problem, forces explicit consideration of trade-offs and directly involves stakeholder groups in the decision process. We identify major decommissioning options and provide a generic list of selection criteria required for inclusion in the MA decision process. To deal with knowledge gaps concerning environmental impacts of decommissioning, we suggest that expert opinion feed into the MA approach until sufficient data become available. We conducted a limited trial of the MA decision approach to demonstrate its application to a complex and controversial decommissioning scenario; Platform Grace in southern California. The approach indicated, for this example, that the option 'leave in place intact' would likely provide best environmental outcomes in the event of future decommissioning. In summary, the MA approach will allow the environmental, social, and economic impacts of decommissioning decisions to be assessed simultaneously in a transparent manner.

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“…Elicitation of expert judgment is particularly useful where decisions are time-sensitive and management or policy cannot wait for improved scientific knowledge (Knol et al, 2010). (Knol et al, 2010;Kuhnert et al, 2010) Figure 8 presents a structured process for eliciting expert judgment. In the first step, a clear articulation of the research question(s) will inform the design and implementation of the study as well as the larger structure of the modeling process.…”

Section: Fire Effects Analysis and Incorporation Of Expert Judgmentmentioning

confidence: 99%

“…Expert systems are commonly used in natural resource management decision-making (González et al, 2007;Hirsch et al, 2004;Kaloudis et al, 2005;Vadrevu et al, 2010), and rely on the unique expertise and judgment of professionals as a proxy for empirical data. Increasingly in a variety of natural resource management applications researchers and practitioners are adopting structured approaches for eliciting and using expert knowledge (Kuhnert et al, 2010;Martin et al, 2009). Elicitation of expert judgment is particularly useful where decisions are time-sensitive and management or policy cannot wait for improved scientific knowledge (Knol et al, 2010).…”

Section: Fire Effects Analysis and Incorporation Of Expert Judgmentmentioning

confidence: 99%

The Science and Opportunity of Wildfire Risk Assessment

Thompson¹,

Ager²,

Finney³

et al. 2012

Novel Approaches and Their Applications in Risk Assessment

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A guide to eliciting and using expert knowledge in Bayesian ecological models

Cited by 361 publications

References 51 publications

General rules for managing and surveying networks of pests, diseases, and endangered species

General rules for managing and surveying networks of pests, diseases, and endangered species

A multi-criteria decision approach to decommissioning of offshore oil and gas infrastructure

The Science and Opportunity of Wildfire Risk Assessment

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