Evaluating forest resilience and carbon recovery using a chronosequence of co-located pre-, active-, and post-wildfire measurements in California mixed-conifer forests
Principal Investigator: Jessica Miesel, Ph.D.
Project Partners: Matthew Dickinson, Ph.D.; Eric Knapp, Ph.D.; Alicia Reiner; Carol Ewell
Institution: Michigan State University
Project Type: General Research
Grant Award: #8GG19804; 8GG21824
Amount awarded: $453,078
Award Date: September 2019; March 2021
Contemporary fires in California increasingly exceed historical norms, raising concern about potential shifts toward novel disturbance regimes that threaten ecosystem health and productivity. Extreme fires can push ecosystems towards ecological tipping points, into alternative stable states that may support diminished ecosystem functions and loss of ecosystem services such as carbon sequestration. This occurs when forests lack resilience to high-severity fire, leading to ecosystem state changes from forested to non-forest cover. Increased fire emissions coupled with subsequent loss of C sequestration potential contributes to positive feedback loops between fire and climate, as climate extremes (e.g., longer and/or hotter droughts) further increase wildfire occurrence, size, and severity.
Although increases in carbon emissions are expected to occur with increases in fire severity, two major gaps in knowledge of fire impacts on forest C recovery remain. First, data documenting changes in forest structure and composition between pre- and post-wildfire measurements remain critically lacking, because of the unpredictability in where and when wildfires will actually occur. This contrasts with more more readily available data from prescribed burns, which are typically conducted under low-risk conditions. Second, knowledge of how the timescale of forest recovery is influenced by prefire conditions and how it differs across gradients of burn severity is also limited by the same lack of data. The lack of data is a problem because fire and forest planning, management, and modeling depend on knowledge representative of wildfire conditions. A globally unique monitoring initiative by the USDA Forest Service Fire Behavior Assessment Team (FBAT) has generated 15 years of co-located before-, during-, and after-fire data on forest composition, structure, & biomass from active wildfire incidents, primarily in California. The FBAT’s original objective was to provide data-driven reports to inform local forest and fire management decisions, but the accumulated data and field plots have outstanding potential to advance knowledge about how pre-fire conditions and burn severity influence forest recovery and resilience.
Led by Dr. Jessica Miesel from Michigan State University, this project leverages the unique FBAT data and re-measures the network of field plots to evaluate how forest vegetation and carbon recover, across a chronosequence of time since fire. The information provided by this project will improve the ability to predict forest recovery after fire and will help identify how forest management can improve forest resilience.
For more information on this project please visit:
Jessica Miesel, PhD (PI) email@example.com
CAL FIRE Forest Health Research Program