Development and improvement of wildfire baseline emissions, return interval departure, and post-fire recovery data and tools for California forest and wildfire management
Principal Investigator: Hugh Safford
Project Partners: N/A
Institution: University of California, Davis
Project Type: General Research
Grant Award: #8GG21818
Amount awarded: $332,000
Award Date: March, 2021
Subproject A - State and federal land and fire management agencies have made multiple policy changes and intergovernmental agreements over the last 12 years committing themselves to greater use of fire as a resource management tool. The 2021 California Wildfire and Forest Resilience Action Plan sets high goals for the growth of prescribed fire in California, including up to 100,000 acres per year by CALFIRE, “significant expansion” of burned acres by the USFS, development of an interagency Training Center, and promotion of increased burning on tribal and private lands. As CARB seeks to square air quality mandates with the need to reduce fuels on huge landscapes, they are in need of robust information on probable pre-Euroamerican settlement (pre-EAS) emissions baselines to permit regulations that appropriately balance short-term vs long-term and local vs. regional considerations. We will use updated pre-EAS fire areas for key vegetation types and subregions of California and emissions modeling from FOFEM (First-Order Fire Effects Model) to generate robust estimates (means and ranges) of fire emissions in California under the pre-EAS baseline. We will use the same protocol detailed in Stephens et al. (2007), upgrading to the most recent version of FOFEM
Subproject B - Since 2011, the California Fire Return Interval Departure (FRID) geodatabase has provided information on current versus pre-EAS fire frequencies on federal lands in the state, as well as some other jurisdictions adjacent to those federal lands. The FRID data layer is used for land and resource planning and assessment, as well as other natural resource applications such as fuels treatment planning, postfire restoration project design, management response to fire, assessing the effects of fire on ecosystems, and general ecological understanding of historic versus current occurrence of fire on the California National Forests and neighboring jurisdictions. We will extend the California FRID geodatabase to all lands in California by (1) adding new PFR (“presettlement fire regime”) types from new types defined in the fire area estimation work outlined above in Subproject A; (2) calculating FRID using the 2011 E-veg map as the base layer and the California F-veg to fill in gaps in E-veg. Output variables will include all of the current variables calculated in FRID; and (3) we will also look into using a PNV map (with hypothesized pre-EAS vegetation distribution) rather than the E-veg/F-veg hybrid map as the base layer. PNV maps could include a modified LANDFIRE BpS coverage, or potentially the 1930’s Wieslander maps for selected California subregions.
Subproject C – The POSCRPT (Postfire Spatial Conifer Regeneration Prediction Tool), developed by researchers from UC and the Forest Service and based on field data from thousands of field plots, combines metrics of seed availability with climatic, topographic, and fire severity data to produce a spatially-explicit predictive model that forescasts where regeneration of non-serotinous conifers is most likely to occur after large wildfires. Specifically, it predicts the probability of observing at least one regenerating conifer of the common species in certain forest types (Douglas-fir, incense-cedar, Jeffrey pine, ponderosa pine, sugar pine, white fir) 5 years after fire at the field plot (60-m2) scale. POSCRPT’s outputs allow forest managers to quickly identify where there is low potential for future conifer regeneration, as well as where natural regeneration is likely to occur without intervention. In these areas, managers can consider management actions that will protect regenerating conifers from high severity fire in the near term. We will improve the POSCRPT tool in a number of ways and to extend its application to red fir and subalpine forests. We also propose to output a summary of reforestation need in California yellow pine, mixed conifer, and allied forest types from the 2020 and 2021 fires.
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