Understanding implications of forest management practices with respect to occurrence and severity of wildfires, evaluating post fire recovery and resiliency and improving tools (i.e. Fire Behaviour Predictor)
Project Reference Number: 2020-01a
Project Status: Active
Led by: Dr. Phil Burton (UNBC), Dr.Sam Coggins (BVRC Research Associate)
Funder: BC Wildfire Service, Canadian Forest Service
Efficacy of current fuel management activities is being evaluated with the goal of developing guidance for linking stand management activities (e.g., harvesting, prescribed burning) to improved wildfire risk reduction outcomes. The specific goal is to determine if, and to what degree, any particular age class, composition, or treatment history of managed forest stands proved significantly resistance to crown fire in recent central BC wildfires. We are determining if, and to what degree, forest stands dominated by trembling aspen, black cottonwood, or paper birch experienced reduced burn severity compared to other forest types.
A literature review and preliminary analysis of data was done (i.e., Burton and Boxwell report). Reconnaissance and fire team calibration occurred in summer 2020. The team completed 4 weeks for field work related to forest type and burn severity. They sampled 154 plots distributed in conifer leading moderate burn, conifer leading high burn severity, aspen leading moderate severity, aspen leading high burn severity, and unburned sites. Early results suggest broadleaf leading stands burned less than expected and show the presence of 25-year-old pine plantations that have been skipped by fires.
A UBC graduate student, Brent Murray, is using remotely sensed imagery to examine forest resilience and burn severity following wildfire. Burn severity will be estimated using different methods. The burn severity indices generated will be used to examine vegetation regrowth, verify the extent of post-fire forest mortality, and assess whether forest vegetation has returned to a pre-burn or is in an alternative state. Linkages between different modeling tools will be determined and tools analyzed for applicability in filling key data gaps in BC.
We are providing data and statistical relationships to enhance existing Fire Behaviour Prediction (FBP) models by incorporating burn severity information extracted from retrospective landscape analysis of recent Central BC wildfires.
