Science Inventory

Causal Bayesian networks in assessments of wildfire risks: Opportunities for ecological risk assessment and management


Carriger, J., M. Thompson, AND M. Barron. Causal Bayesian networks in assessments of wildfire risks: Opportunities for ecological risk assessment and management. Integrated Environmental Assessment and Management. Allen Press, Inc., Lawrence, KS, 17(6):1168-1178, (2021).


The purpose of the research was to explore the application of Bayesian networks in the assessment of the ecological risks and impacts of wildfires. The research addresses wildfires, which are increasing across the globe and have devastating effects on human health, infrastructure, and ecological systems and presents an approach that will facilitate the assessment of wildfire impacts and risks. The impact of the work is that adoption of the Bayesian approach will facilitate understanding and modeling causal linkages between fire and ecological impacts that will ultimately improve wildfire assessment and decision making in optimizing protection of ecological resources.


Wildfire risks and losses have increased over the last 100 years, associated with population expansion, land use and management practices, and global climate change, with more than 30% of the global land surface experiencing significant fire frequency. While there have been extensive efforts at modeling the probability and severity of wildfires, there have been fewer efforts to examine causal linkages from wildfires to impacts on ecological receptors and critical habitats. Bayesian networks are effective tools for graphing and evaluating causal knowledge and uncertainties in complex assessments related to wildfires. Here we explore the possibilities for using Bayesian networks for assessing wildfire impacts to ecological systems through levels of causal representation and scenario examination with multi-disciplinary experts and stakeholders. Ultimately, BNs may facilitate understanding the factors contributing to fire susceptibility and resilience, and the prediction and assessment of wildfire risks to and impacts on fire-affected ecosystems.

Record Details:

Product Published Date:11/01/2021
Record Last Revised:05/15/2023
OMB Category:Other
Record ID: 357083