Skip to main content

Lund University Publications

LUND UNIVERSITY LIBRARIES

Robust Decision Analysis under Severe Uncertainty and Ambiguous Tradeoffs : An Invasive Species Case Study

Sahlin, Ullrika LU orcid ; Troffaes, Matthias C.M. and Edsman, Lennart (2021) In Risk Analysis 41(11). p.2140-2153
Abstract

Bayesian decision analysis is a useful method for risk management decisions, but is limited in its ability to consider severe uncertainty in knowledge, and value ambiguity in management objectives. We study the use of robust Bayesian decision analysis to handle problems where one or both of these issues arise. The robust Bayesian approach models severe uncertainty through bounds on probability distributions, and value ambiguity through bounds on utility functions. To incorporate data, standard Bayesian updating is applied on the entire set of distributions. To elicit our expert's utility representing the value of different management objectives, we use a modified version of the swing weighting procedure that can cope with severe value... (More)

Bayesian decision analysis is a useful method for risk management decisions, but is limited in its ability to consider severe uncertainty in knowledge, and value ambiguity in management objectives. We study the use of robust Bayesian decision analysis to handle problems where one or both of these issues arise. The robust Bayesian approach models severe uncertainty through bounds on probability distributions, and value ambiguity through bounds on utility functions. To incorporate data, standard Bayesian updating is applied on the entire set of distributions. To elicit our expert's utility representing the value of different management objectives, we use a modified version of the swing weighting procedure that can cope with severe value ambiguity. We demonstrate these methods on an environmental management problem to eradicate an alien invasive marmorkrebs recently discovered in Sweden, which needed a rapid response despite substantial knowledge gaps if the species was still present (i.e., severe uncertainty) and the need for difficult tradeoffs and competing interests (i.e., value ambiguity). We identify that the decision alternatives to drain the system and remove individuals in combination with dredging and sieving with or without a degradable biocide, or increasing pH, are consistently bad under the entire range of probability and utility bounds. This case study shows how robust Bayesian decision analysis provides a transparent methodology for integrating information in risk management problems where little data are available and/or where the tradeoffs are ambiguous.

(Less)
Please use this url to cite or link to this publication:
author
; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Bayesian, decision theory, invasive species, subjective probability, utility
in
Risk Analysis
volume
41
issue
11
pages
2140 - 2153
publisher
John Wiley & Sons Inc.
external identifiers
  • pmid:33951209
  • scopus:85105079850
ISSN
0272-4332
DOI
10.1111/risa.13722
language
English
LU publication?
yes
id
fae85d1f-5690-4078-a62a-aabe00c28018
date added to LUP
2021-05-28 16:58:10
date last changed
2024-07-13 14:06:03
@article{fae85d1f-5690-4078-a62a-aabe00c28018,
  abstract     = {{<p>Bayesian decision analysis is a useful method for risk management decisions, but is limited in its ability to consider severe uncertainty in knowledge, and value ambiguity in management objectives. We study the use of robust Bayesian decision analysis to handle problems where one or both of these issues arise. The robust Bayesian approach models severe uncertainty through bounds on probability distributions, and value ambiguity through bounds on utility functions. To incorporate data, standard Bayesian updating is applied on the entire set of distributions. To elicit our expert's utility representing the value of different management objectives, we use a modified version of the swing weighting procedure that can cope with severe value ambiguity. We demonstrate these methods on an environmental management problem to eradicate an alien invasive marmorkrebs recently discovered in Sweden, which needed a rapid response despite substantial knowledge gaps if the species was still present (i.e., severe uncertainty) and the need for difficult tradeoffs and competing interests (i.e., value ambiguity). We identify that the decision alternatives to drain the system and remove individuals in combination with dredging and sieving with or without a degradable biocide, or increasing pH, are consistently bad under the entire range of probability and utility bounds. This case study shows how robust Bayesian decision analysis provides a transparent methodology for integrating information in risk management problems where little data are available and/or where the tradeoffs are ambiguous.</p>}},
  author       = {{Sahlin, Ullrika and Troffaes, Matthias C.M. and Edsman, Lennart}},
  issn         = {{0272-4332}},
  keywords     = {{Bayesian; decision theory; invasive species; subjective probability; utility}},
  language     = {{eng}},
  number       = {{11}},
  pages        = {{2140--2153}},
  publisher    = {{John Wiley & Sons Inc.}},
  series       = {{Risk Analysis}},
  title        = {{Robust Decision Analysis under Severe Uncertainty and Ambiguous Tradeoffs : An Invasive Species Case Study}},
  url          = {{http://dx.doi.org/10.1111/risa.13722}},
  doi          = {{10.1111/risa.13722}},
  volume       = {{41}},
  year         = {{2021}},
}