Non-Destructive Fuel Volume Measurements Can Estimate Fine-Scale Biomass across Surface Fuel Types in a Frequently Burned Ecosystem

Abstract

Measuring wildland fuels is at the core of fire science, but many established field methods are not useful for ecosystems characterized by complex surface vegetation. A recently developed sub-meter 3D method applied to southeastern U.S. longleaf pine (Pinus palustris) communities captures critical heterogeneity, but similar to any destructive sampling measurement, it relies on separate plots for calculating loading and consumption. In this study, we investigated how bulk density differed by 10-cm height increments among three dominant fuel types, tested predictions of consumption based on fuel type, height, and volume, and compared this with other field measurements. The bulk density changed with height for the herbaceous and woody litter fuels (p < 0.001), but live woody litter was consistent across heights (p > 0.05). Our models predicted mass well based on volume and height for herbaceous (RSE = 0.00911) and woody litter (RSE = 0.0123), while only volume was used for live woody (R2 = 0.44). These were used to estimate consumption based on our volume-mass predictions, linked pre- and post-fire plots by fuel type, and showed similar results for herbaceous and woody litter when compared to paired plots. This study illustrates an important non-destructive alternative to calculating mass and estimating fuel consumption across vertical volume distributions at fine scales.

A Comparison of Four Spatial Interpolation Methods for Modeling Fine-Scale Surface Fuel Load in a Mixed Conifer Forest with Complex Terrain

“…Though several studies (e.g., 61) have used repeated measures of relatively coarse-scale (<900 m 2 ) remote sensing data to develop fuel maps, there have been fewer studies that have utilized repeated measures to develop fine-scale fuel maps. At these finer scales, several studies have shown the promise of terrestrial and aerial LiDAR and uncrewed aerial system (UAS) structures for motion approaches for capturing forest structure parameters for mapping fuels and for capturing vegetative structural changes (e.g., [68][69][70][71][72][73]), but we are unaware of any studies that have utilized long-term repeated remote sensing measures for fuels mapping. With these three-dimensional remote sensing techniques providing spatially explicit estimates of individual trees, these data could provide a better correlation of how a forest structure impacts the input of fuels and microclimatic influences on fuel decomposition to improve surface fuel mapping.…”

Vegetation’s influence on fire behavior goes beyond just being fuel

“…Fires restart the competitive process in the understory community, often creating a diverse plant community (Loudermilk et al 2019;Glitzenstein et al 2003). The variation in groundcover community and interaction with leaf and woody debris create distinct fine-scale vegetation structure characteristics that interact to drive heterogeneity in fire spread and consumption (Loudermilk et al 2012;Hiers et al 2021). Non-native invasive grass understories can also influence fire spread, driving novel vegetation recovery trajectories post-fire (Franklin et al 2006;Strand et al 2019).…”

Terrestrial Laser Scan Metrics Predict Surface Vegetation Biomass and Consumption in a Frequently Burned Southeastern U.S. Ecosystem

“…The spatial variation in biomass at scales relevant to surface fire is the most difficult aspect to capture because of the complexity of composition and distribution within and across stands, even within the same ecosystem and timespan since the last burn event [6,15,18]. In southeastern U.S. ecosystems, where production and turnover rates are high [19,20], repeated burning provides a continuum of fine surface fuels and living vegetation that enable a broad range of fire behavior throughout the year [21,22].…”