ECO-CBET: Collaborative Research: Effect of surface-fuel attributes and forest-thinning patterns on wildfire, carbon storage, and advancing forest restoration

2318717 (Cobian). In recent years, high-severity wildfires have severely damaged forested mountain watersheds that store carbon, supply western-states’ water, and provide many co-benefits. While periodic low- to medium-severity wildfires are a natural part of western U.S. forests, too much of the area is burning at high severity owing to excessive fuel loads and a warming climate. Therefore, a critical goal of forest management is often the introduction of practices designed to reduce the risk of high severity fires. These practices, known collectively as forest restoration, involve thinning and removing or masticating the less-fire-resistant, smaller trees, while leaving larger, more widely spaced trees. A common restoration approach is applying mechanical thinning followed by mastication which changes the forest-canopy structure and surface-fuel loading and characteristics. While it is known that changing the arrangement and density of trees and other vegetation through mastication affects fire behavior, there is a lack a quantitative understanding of how attributes of masticated fuels affect subsequent fire severity. The goal of this project is to develop metrics of the impact of fuel treatments on fire behavior across a range of spatial and temporal scales. This project will contribute to improved understanding of how surface-fuel attributes, resulting from management decisions, influence fire behavior and severity and thus forest biomass carbon storage.

Mechanical thinning followed by mastication changes the forest-canopy structure and surface-fuel loading and characteristics. While these changes can impact fire behavior significantly, their sensitivities to the type and degree of mastication are not well understood. The three main goals of the study are: (1) To establish the importance of heterogeneous and multiscale surface-fuel loadings and attributes, following mechanical fuel treatments, on the temperature, flame length, and spread of fire as these fuels burn; (2) To develop and assess predictive tools for wildfire severity and spread in the forest given these different fuel attributes, under contrasting micro-meteorological conditions; and (3) To demonstrate carbon-storage and related benefits from different fuel treatments designed to reduce the occurrence and impacts of high-severity wildfires. The study will use bench-scale combustion experiments, field measurements involving controlled burns in thinned and masticated stands in a mixed-conifer forest, and modeling of wildland fire and carbon storage. Results from experiments, modeling, and assessment of field-scale control burns will be used to identify key drivers of fire severity in ground fuels following thinning. Primary contributions of the study will be improved understanding of how surface-fuel attributes, resulting from management decisions, influence fire behavior and severity and thus forest biomass carbon storage. Results will improve modeling of flame length, fire spread and carbon balance and storage in the litter, mineral soil, and deeper regolith. This research will engage decision maker and stakeholder partnerships with organizations that are advancing landscape restoration, providing much-needed improvements in projection of how their investments may affect wildfire severity.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Award Number: 2621749
Principal Investigator: Jeanette Cobian
Funds Obligated: $799,430
State: CA