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Prior and Posterior Linear Pooling for Combining Expert Opinions: Uses and Impact on Bayesian Networks-The Case of the Wayfinding Model. ENTROPY 2018; 20:e20030209. [PMID: 33265300 PMCID: PMC7512724 DOI: 10.3390/e20030209] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/15/2017] [Revised: 03/17/2018] [Accepted: 03/18/2018] [Indexed: 11/16/2022]
Abstract
The use of expert knowledge to quantify a Bayesian Network (BN) is necessary when data is not available. This however raises questions regarding how opinions from multiple experts can be used in a BN. Linear pooling is a popular method for combining probability assessments from multiple experts. In particular, Prior Linear Pooling (PrLP), which pools opinions and then places them into the BN, is a common method. This paper considers this approach and an alternative pooling method, Posterior Linear Pooling (PoLP). The PoLP method constructs a BN for each expert, and then pools the resulting probabilities at the nodes of interest. The advantages and disadvantages of these two methods are identified and compared and the methods are applied to an existing BN, the Wayfinding Bayesian Network Model, to investigate the behavior of different groups of people and how these different methods may be able to capture such differences. The paper focusses on six nodes Human Factors, Environmental Factors, Wayfinding, Communication, Visual Elements of Communication and Navigation Pathway, and three subgroups Gender (Female, Male), Travel Experience (Experienced, Inexperienced), and Travel Purpose (Business, Personal), and finds that different behaviors can indeed be captured by the different methods.
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Wu PPY, Mengersen K, McMahon K, Kendrick GA, Chartrand K, York PH, Rasheed MA, Caley MJ. Timing anthropogenic stressors to mitigate their impact on marine ecosystem resilience. Nat Commun 2017; 8:1263. [PMID: 29093493 PMCID: PMC5665875 DOI: 10.1038/s41467-017-01306-9] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2016] [Accepted: 09/08/2017] [Indexed: 11/09/2022] Open
Abstract
Better mitigation of anthropogenic stressors on marine ecosystems is urgently needed to address increasing biodiversity losses worldwide. We explore opportunities for stressor mitigation using whole-of-systems modelling of ecological resilience, accounting for complex interactions between stressors, their timing and duration, background environmental conditions and biological processes. We then search for ecological windows, times when stressors minimally impact ecological resilience, defined here as risk, recovery and resistance. We show for 28 globally distributed seagrass meadows that stressor scheduling that exploits ecological windows for dredging campaigns can achieve up to a fourfold reduction in recovery time and 35% reduction in extinction risk. Although the timing and length of windows vary among sites to some degree, global trends indicate favourable windows in autumn and winter. Our results demonstrate that resilience is dynamic with respect to space, time and stressors, varying most strongly with: (i) the life history of the seagrass genus and (ii) the duration and timing of the impacting stress.
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Affiliation(s)
- Paul Pao-Yen Wu
- Australian Research Council Centre of Excellence in Mathematical and Statistical Frontiers, University of Melbourne, Melbourne, VIC, 3010, Australia.
- School of Mathematical Sciences, Queensland University of Technology, GPO Box 2434, 2 George Street, Brisbane, QLD, 4001, Australia.
| | - Kerrie Mengersen
- Australian Research Council Centre of Excellence in Mathematical and Statistical Frontiers, University of Melbourne, Melbourne, VIC, 3010, Australia
- School of Mathematical Sciences, Queensland University of Technology, GPO Box 2434, 2 George Street, Brisbane, QLD, 4001, Australia
| | - Kathryn McMahon
- School of Sciences and Centre for Marine Ecosystems Research, Edith Cowan University, 270 Joondalup Drive, Joondalup, WA, 6027, Australia
- WAMSI Headquarters, M095, University of Western Australia, 35 Stirling Highway, Crawley, WA, 6009, Australia
| | - Gary A Kendrick
- WAMSI Headquarters, M095, University of Western Australia, 35 Stirling Highway, Crawley, WA, 6009, Australia
- UWA Oceans Institute and School of Biological Sciences, University of Western Australia, 35 Stirling Highway, Crawley, WA, 6009, Australia
| | - Kathryn Chartrand
- Centre for Tropical Water & Aquatic Ecosystem Research, James Cook University, PO Box 6811, 14-88 McGregor Road, Cairns, QLD, 4870, Australia
| | - Paul H York
- Centre for Tropical Water & Aquatic Ecosystem Research, James Cook University, PO Box 6811, 14-88 McGregor Road, Cairns, QLD, 4870, Australia
| | - Michael A Rasheed
- Centre for Tropical Water & Aquatic Ecosystem Research, James Cook University, PO Box 6811, 14-88 McGregor Road, Cairns, QLD, 4870, Australia
| | - M Julian Caley
- Australian Research Council Centre of Excellence in Mathematical and Statistical Frontiers, University of Melbourne, Melbourne, VIC, 3010, Australia
- School of Mathematical Sciences, Queensland University of Technology, GPO Box 2434, 2 George Street, Brisbane, QLD, 4001, Australia
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