Citation

Penman TD, Cirulis B, Marcot BG. J. Environ. Manage. 2020; 270: e110735.

Copyright

(Copyright © 2020, Elsevier Publishing)

DOI

10.1016/j.jenvman.2020.110735

PMID

32721285

Abstract

Environmental decision-making requires an understanding of complex interacting systems across scales of space and time. A range of statistical methods, evaluation frameworks and modeling approaches have been applied for conducting structured environmental decision-making under uncertainty. Bayesian Decision Networks (BDNs) are a useful construct for addressing uncertainties in environmental decision-making. In this paper, we apply a BDN to decisions regarding fire management to evaluate the general efficacy and utility of the approach in resource and environmental decision-making. The study was undertaken in south-eastern Australia to examine decisions about prescribed burning rates and locations based on treatment and impact costs. Least-cost solutions were identified but are unlikely to be socially acceptable or practical within existing resources; however, the statistical approach allowed for the identification of alternative, more practical solutions. BDNs provided a transparent and effective method for a multi-criteria decision analysis of environmental management problems.

Language: en

Keywords

Monitoring; Risk; Fires; Decision Making; South Australia; Uncertainty; Bayesian network; Bayes Theorem; Decision modeling; Integrated modeling; Prescribed fire; Wildfires