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Ullrika Sahlin. Foto.

Ullrika Sahlin

Universitetslektor

Ullrika Sahlin. Foto.

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

Författare

  • Ullrika Sahlin
  • Matthias C.M. Troffaes
  • Lennart Edsman

Summary, in English

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.

Avdelning/ar

  • Beräkningsvetenskap för hälsa och miljö
  • Centrum för miljö- och klimatvetenskap (CEC)
  • BECC: Biodiversity and Ecosystem services in a Changing Climate

Publiceringsår

2021

Språk

Engelska

Sidor

2140-2153

Publikation/Tidskrift/Serie

Risk Analysis

Volym

41

Issue

11

Dokumenttyp

Artikel i tidskrift

Förlag

John Wiley & Sons Inc.

Ämne

  • Computer Science
  • Environmental Sciences
  • Probability Theory and Statistics

Nyckelord

  • Bayesian
  • decision theory
  • invasive species
  • subjective probability
  • utility

Status

Published

Forskningsgrupp

  • Computational Science for Health and Environment

ISBN/ISSN/Övrigt

  • ISSN: 0272-4332