Remotely Sensed Fine-Fuel Changes from Wildfire and Prescribed Fire in a Semi-Arid Grassland

The spread of flammable invasive grasses, woody plant encroachment, and enhanced aridity have interacted in many grasslands globally to increase wildfire activity and risk to valued assets. Annual variation in the abundance and distribution of fine-fuel present challenges to land managers implementing prescribed burns and mitigating wildfire, although methods to produce high-resolution fuel estimates are still under development. To further understand how prescribed fire and wildfire influence fine-fuels in a semi-arid grassland invaded by non-native perennial grasses, we combined high-resolution Sentinel-2A imagery with in situ vegetation data and machine learning to estimate yearly fine-fuel loads from 2015 to 2020. The resulting model of fine-fuel corresponded to field-based validation measurements taken in the first (R2 = 0.52, RMSE = 218 kg/ha) and last year (R2 = 0.63, RMSE = 196 kg/ha) of this 6-year study. Serial prediction of the fine-fuel model allowed for an assessment of the effect of prescribed fire (average reduction of −80 kg/ha 1-year post fire) and wildfire (−260 kg/ha 1-year post fire) on fuel conditions. Post-fire fine-fuel loads were significantly lower than in unburned control areas sampled just outside fire perimeters from 2015 to 2020 across all fires (t = 1.67, p < 0.0001); however, fine-fuel recovery occurred within 3–5 years, depending upon burn and climate conditions. When coupled with detailed fuels data from field measurements, Sentinel-2A imagery provided a means for evaluating grassland fine-fuels at yearly time steps and shows high potential for extended monitoring of dryland fuels. Our approach provides land managers with a systematic analysis of the effects of fire management treatments on fine-fuel conditions and provides an accurate, updateable, and expandable solution for mapping fine-fuels over yearly time steps across drylands throughout the world.

Where there's smoke, there's fuel: predicting Great Basin rangeland wildfire

Wildfires are a growing management concern in western US rangelands, where invasive annual grasses have altered fire regimes and contributed to an increased incidence of catastrophic large wildfires. Fire activity in arid, non-forested regions is thought to be largely controlled by interannual variation in fuel amount, which in turn is controlled by antecedent weather. Thus, long-range forecasting of fire activity in rangelands should be feasible given annual estimates of fuel quantity. Using a 32 yr time series of spatial data, we employ machine learning algorithms to predict the relative probability of large (>400 ha) wildfire in the Great Basin based on fine-scale annual and 16-day estimates of cover and production of vegetation functional groups, weather, and multitemporal scale drought indices. We evaluate the predictive utility of these models with a leave-one-year-out cross-validation, building spatial forecasts of fire probability for each year that we compare against actual maps of large wildfires. Herbaceous vegetation aboveground biomass production, bare ground cover, and long-term drought indices were the most important predictors of fire probability. Across 32 fire seasons, >80% of the area burned in large wildfires coincided with predicted fire probabilities ≥0.5. At the scale of the Great Basin, several metrics of fire season severity were moderately to strongly correlated with average fire probability, including total area burned in large wildfires, number of large wildfires, and average and maximum fire size. Our findings show that recent years of exceptional fire activity in the Great Basin were predictable based on antecedent weather and biomass of fine fuels, and reveal a significant increasing trend in fire probability over the last three decades driven by widespread changes in fine fuel characteristics.

Measuring A Fire: The Story of the January 2019 Fire Told from Measurements at the Warra Supersite, Tasmania

Non-stand-replacing wildfires are the most common natural disturbance in the tall eucalypt forests of Tasmania, yet little is known about the conditions under which these fires burn and the effects they have on the forest. A dry lightning storm in January 2019 initiated the Riveaux Road fire. This fire burnt nearly 64,000 ha of land, including tall eucalypt forests at the Warra Supersite. At the Supersite, the passage of the fire was recorded by a suite of instruments measuring weather conditions and fluxes (carbon, water and energy), while a network of permanent plots measured vegetation change. Weather conditions in the lead-up and during the passage of the fire through the Supersite were mild—a moderate forest fire danger index. The passage of the fire through the Supersite caused a short peak in air temperature coinciding with a sharp rise in CO2 emissions. Fine fuels and ground vegetation were consumed but the low intensity fire only scorched the understorey trees, which subsequently died and left the Eucalyptus obliqua canopy largely intact. In the aftermath of the fire, there was prolific seedling regeneration, a sustained reduction in leaf area index, and the forest switched from being a carbon sink before the fire to becoming a carbon source during the first post-fire growing season.

Evolution of Plume Core Structures and Turbulence during a Wildland Fire Experiment

Micrometeorological observations were made during a prescribed fire experiment conducted in a region of complex terrain with grass fuels and weak ambient winds of 3 m s−1. The experiment allowed for the analysis of plume and turbulence structures including individual plume core evolution during fire front passage. Observations were made using a suite of in situ and remote sensing instruments strategically placed at the base of a gully with a 24° slope angle. The fire did not spread upwards along the gully because the ambient wind was not in alignment with the slope, demonstrating that unexpected fire spread can occur under weak wind conditions. Our observational results show that plume overturning caused downward heat transport of −64 kW m−2 to occur and that this mixing of warmer plume air downward to the surface may result in increased preheating of fine fuels. Plume evolution was associated with the formation of two plume cores, caused by vigorous entrainment and mixing into the plume. Furthermore, the turbulence kinetic energy observed within the plume was dominated by horizontal velocity variances, likely caused by increased fire-induced circulations into the plume core. These observations highlight the nature of plume core separation and evolution and provide context for understanding the plume dynamics of larger and more intense wildfires.

Fuel dynamics during oak woodland and savanna restoration in the Mid-South USA

Thinning and burning can restore imperilled oak woodlands and savannas in the Southern Appalachian and Central Hardwood regions of the USA, but concomitant effects on fuels are less understood. We monitored (2008 to 2016) fuel load response to replicated combinations of thinning (none, 7, and 14m2ha−1 residual basal area) and seasonal fire (none, March, and October) at three sites. All treatments except burn-only increased total fuel loading. Thinning doubled (+16Mgha−1) 1000-h fuels relative to controls, and three fires in 6 years did not eliminate this difference. Increasing thinning intensity did not consistently enhance the combustion of larger fuels. October fires reduced 100- and 10-h fuels more than March fires. Burning alone reduced leaf litter and 1-h twigs by 30%. Burning after thinning doubled this reduction but increased herbaceous fuels 19-fold. Herbaceous fuels increased at a rate that suggests compensation for losses in woody fine fuels with continued burning. Where fuel reduction is a goal, restoration strategies could be more intentionally designed; however, oak woodlands and savannas are inherently more flammable than closed-canopy forests. Management decisions will ultimately involve weighing the risks associated with increased fuel loads against the benefits of restoring open oak communities.

In-Situ and Remote Sensing Platforms for Mapping Fine-Fuels and Fuel-Types in Sonoran Semi-Desert Grasslands

Fire has historically played an important role in shaping the structure and composition of Sonoran semi-desert grassland vegetation. Yet, human use and land management activities have significantly altered arid grassland ecosystems over the last century, often producing novel fuel conditions. The variety of continuously updated satellite remote sensing systems provide opportunities for efficiently mapping combustible fine-fuels and fuel-types (e.g., grass, shrub, or tree cover) over large landscapes that are helpful for evaluating fire hazard and risk. For this study, we compared field ceptometer leaf area index (LAI) measurements to conventional means for estimating fine-fuel biomass on 20, 50 m × 20 m plots and 431, 0.5 m × 0.5 m quadrats on the Buenos Aires National Wildlife Refuge (BANWR) in southern Arizona. LAI explained 65% of the variance in fine-fuel biomass using simple linear regression. An additional 19% of variance was explained from Random Forest regression tree models that included herbaceous plant height and cover as predictors. Field biomass and vegetation measurements were used to map fine-fuel and vegetation cover (fuel-type) from plots on BANWR comparing outcomes from multi-date (peak green and dormant period) Worldview-3 (WV3) and Landsat Operational Land Imager (OLI) imagery. Fine-fuel biomass predicted from WV3 imagery combined with terrain information from a digital elevation model explained greater variance using regression tree models (65%) as compared to OLI models (58%). Vegetation indices developed using red-edge bands as well as modeled bare ground and herbaceous cover were important to improve WV3 biomass estimates. Land cover classification for 11 cover categories with high spatial resolution WV3 imagery showed 80% overall accuracy and highlighted areas dominated by non-native grasses with 87% user’s class accuracy. Mixed native and non-native grass and shrublands showed 59% accuracy and less common areas dominated by native grasses on plots showed low class accuracy (23%). Digital data layers from WV3 models showed a significantly positive relationship (r2 = 0.68, F = 119.2, p < 0.001) between non-native grass cover (e.g., Eragrostis lehmanniana) and average fine-fuel biomass within refuge fire management units. Overall, both WV3 and OLI produced similar fine-fuel biomass estimates although WV3 showed better model performance and helped characterized fine-scale changes in fuel-type and continuity across the study area.

Effects of post-fire logging on fuel dynamics in a mixed-conifer forest, Oregon, USA: a 10-year assessment

Removal of fire-killed trees (i.e. post-fire or salvage logging) is often conducted in part to reduce woody fuel loads and mitigate potential reburn effects. Studies of post-salvage fuel dynamics have primarily used chronosequence or modelling approaches, with associated limitations; longitudinal studies tracking fuels over time have been rare. We resampled a network of post-fire plots, comprising a range of logging intensities, 10 years after the 2002 Biscuit Fire (Oregon, USA). For surface woody fuels, which started from large treatment differences immediately following logging (stepwise increases with harvest intensity), we found converging trends among treatments at 10 years, with convergence nearly complete for fine fuels but not for coarse fuels. Fire-killed snags for the dominant species (Pseudotsuga menziesii) decayed while standing at a statistically significant rate (single-exponential k = 0.011), similar to or only slightly slower than down wood, suggesting that not all snag biomass will reach the forest floor. Live vegetation (largely resprouting sclerophyllous vegetation) is beginning to dominate surface fuel mass and continuity (>100% cover) and likely moderates differences associated with woody fuels. Post-fire logging had little effect on live fuels or their change over time, suggesting high potential for stand-replacing early-seral fire regardless of post-fire harvest treatments.