No abstract

Background: Pacific Northwest USA oak woodlands and savannas are fire-resilient communities dependent on frequent, low-severity fire to maintain their structure and understory species diversity, and to prevent encroachment by fire-sensitive competitors. The re-introduction of fire into degraded ecosystems is viewed as essential to their restoration, yet can be fraught with unintended negative consequences. We examined the response of mature Oregon white oak (Quercus garryana Douglas ex Hook.; Garry oak) to "first entry" woodland restoration burns following long fire-free periods. Results: Thirteen to twenty-five months post burn, topkill of oaks was minimal (3%) and mortality was rare in three prescribed burns, despite high levels (mean = 92%) of crown scorching, and irrespective of proportional duff consumption around oak bases (mean = 21%). Percentage of crown scorch volume was the strongest predictor of oak crown dieback, but response was highly variable, especially when canopy scorch was ≥80%. Comparison of our results with FOFEM (First Order Fire Effects Model), a common fire effects model, revealed high model inaccuracy, likely due to lack of a species-specific equation for prediction of Oregon white oak mortality. Conclusions: The results of this study indicate that Oregon white oak is highly resistant to mortality in restoration burns, even following long fire-free intervals. Prescribed fire is not contraindicated in areas with extant mature oaks, and may promote oak regeneration via basal sprouting.

Quantifying wildland fires is of interest to both the fires science and land management communities. Remote sensing of these events has exclusively focused on electromagnetic spectra emissions. However, wildland fires also produce sound. Unraveling their acoustic profile will likely reveal new information unrealized through traditional remote sensing techniques. We start with the “crackling” sounds often associated with burning live vegetation. The data in these acoustic impulse events are rich, yielding information about the specific plants involved. In work presented here, acoustic impulse events are used to tease apart the influences of species, age, and plant moisture during combustion of live conifer needles. Needles were collected and burned onsite for six species within the Priest River Experimental Forest. Replicate measurements were carried out in order to reduce the influence of individual branches or trees. Moisture of the needles was ascertained just prior to the experiment through both predawn leaf water potential as well as gravimetric fuel moisture. The burning material was recorded at 50 kHz with a ½ in. measurement microphone. The acoustic impulse events were isolated and analyzed to determine likelihood of unique character traits. We present results of investigating the potential differences in acoustic signature based on species and age.

Recent wildfires across western North America have burned with uncharacteristically high severity, representing a substantial departure from natural fire regimes. In mixed‐conifer and pine–oak ecosystems of the southern Cascade Range, widespread shifts in stand structure and composition have led to a diversity of post‐wildfire vegetation responses. When recent wildfire “footprints” reburn in subsequent fires, their recovery pathways are complex. In order to understand the effects of overlapping mixed‐severity fires, we quantified changes in overstory and midstory structure and species composition for time periods prior to and following two large overlapping wildfires in the southern Cascades: the 2000 Storrie and 2012 Chips Fires. Plots were stratified into 16 severity combinations (unburned, low, moderate, and high in the Storrie Fire combined with the same four categories in the Chips Fire: e.g., moderate Storrie/high Chips) across the 9000‐ha overlapping burned area. Following the two fires, tree quadratic mean diameter and stand density declined for most species, but changes were species‐specific. Compared with preburn values, importance values for fire‐sensitive white fir (Abies concolor) were reduced by 66%, while resprouting fire‐resilient California black oak (Quercus kelloggii) importance values increased by 37% in severity combinations that included at least one high‐severity fire. Greatest shifts were documented in sites that burned twice at high severity, where resulting vegetation was dominated by oak sprout clumps and resprouting and fire‐stimulated montane chaparral species, while unburned and low‐severity strata retained a substantial component of Douglas‐fir (Pseudotsuga menziesii) and white fir. Results suggest that repeated moderate‐ and high‐severity fires can result in ecosystem state shifting toward fire‐resilient oak‐shrub communities in this fire‐prone landscape. Managers seeking greater landscape resilience can implement treatments such as thinning and prescribed burning, while taking advantage of fire‐created patches such as these in areas where the likelihood of a hotter and drier future makes the reestablishment of continuous forest cover unrealistic.

No abstract

Electromagnetic radiation at 1550 nm is highly absorbed by water and offers a novel way to collect fuel moisture data, along with 3D structures of wildland fuels/vegetation, using lidar. Two terrestrial laser scanning (TLS) units (FARO s350 (phase shift, PS) and RIEGL vz-2000 (time of flight, TOF)) were assessed in a series of laboratory experiments to determine if lidar can be used to estimate the moisture content of dead forest litter. Samples consisted of two control materials, the angle and position of which could be manipulated (pine boards and cheesecloth), and four single-species forest litter types (Douglas-fir needles, ponderosa pine needles, longleaf pine needles, and southern red oak leaves). Sixteen sample trays of each material were soaked overnight, then allowed to air dry with scanning taking place at 1 h, 2 h, 4 h, 8 h, 12 h, and then in 12 h increments until the samples reached equilibrium moisture content with the ambient relative humidity. The samples were then oven-dried for a final scanning and weighing. The spectral reflectance values of each material were also recorded over the same drying intervals using a field spectrometer. There was a strong correlation between the intensity and standard deviation of intensity per sample tray and the moisture content of the dead leaf litter. A multiple linear regression model with a break at 100% gravimetric moisture content produced the best model with R2 values as high as 0.97. This strong relationship was observed with both the TOF and PS lidar units. At fuel moisture contents greater than 100% gravimetric water content, the correlation between the pulse intensity values recorded by both scanners and the fuel moisture content was the strongest. The relationship deteriorated with distance, with the TOF scanner maintaining a stronger relationship at distance than the PS scanner. Our results demonstrate that lidar can be used to detect and quantify fuel moisture across a range of forest litter types. Based on our findings, lidar may be used to quantify fuel moisture levels in near real-time and could be used to create spatial maps of wildland fuel moisture content.

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