scholarly journals Long-Term Effects of Fuel Reduction Treatments on Surface Fuel Loading in the Blue Mountains of Oregon

Forests ◽  
2021 ◽  
Vol 12 (10) ◽  
pp. 1306
Author(s):  
Kat E. Morici ◽  
John D. Bailey
Keyword(s):  
Fire Behavior ◽  
Fuel Load ◽  
Fire Season ◽  
Fuel Reduction ◽  
Prescribed Burn ◽  
Long Term Effects ◽  
Fuel Loading ◽  
Fuel Treatments ◽  
Blue Mountains ◽  
Pre Treatment

Fire exclusion and a lengthening fire season has resulted in an era of megafires. Fuel reduction treatments in forested ecosystems are designed to guard against future extreme wildfire behavior. Treatments create a heterogenous landscape and facilitate ecosystem function and resilience in fire-adapted forests of the western United States. Despite widespread recognition that repeated fuel treatments are needed to maintain desired stand characteristics over time, few field studies have evaluated treatment longevity. The Blue Mountains Fire and Fire Surrogate site in northeastern Oregon presented an opportunity to investigate woody fuel loading 15–17 years after four treatments: mechanical thin, prescribed burn, both thin and burn, and no treatment control. The principal findings were: (1) fine fuel load 15 years post-burn remained slightly below pre-treatment values; (2) rotten coarse fuel load was reduced post-burn, but sound coarse fuel was not altered by any active treatment; and (3) total woody fuel load 15–17 years post-treatment was similar to pre-treatment values. Understanding surface fuel loading is essential for predicting fire behavior. Overall, the effects of fuel reduction treatments on woody surface fuels were transitory in dry mixed conifer forests. Frequent maintenance treatments are recommended to protect values at risk in areas with high fire hazards. Quantifying the persistence of changes in forest conditions aids in the planning and analysis of future fuel treatments, along with scheduling maintenance of existing treated areas.

scholarly journals Prediction of Fuel Loading Following Mastication Treatments in Forest Stands in North Idaho, USA

2020 ◽  
Vol 12 (17) ◽  
pp. 7025
Author(s):  
Ryer Becker ◽  
Robert Keefe
Keyword(s):  
Fire Behavior ◽  
Stand Density ◽  
Post Treatment ◽  
Behavior Modeling ◽  
Fuel Reduction ◽  
Fuel Loading ◽  
Stem Size ◽  
Fuel Loads ◽  
Pre Treatment ◽  
Mean Square Errors

Fuel reduction in forests is a high management priority in the western United States and mechanical mastication treatments are implemented common to achieve that goal. However, quantifying post-treatment fuel loading for use in fire behavior modeling to forecast treatment effectiveness is difficult due to the high cost and labor requirements of field sampling methods and high variability in resultant fuel loading within stands after treatment. We evaluated whether pre-treatment LiDAR-derived stand forest characteristics at 20 m × 20 m resolution could be used to predict post-treatment surface fuel loading following mastication. Plot-based destructive sampling was performed immediately following mastication at three stands in the Nez Perce Clearwater National Forest, Idaho, USA, to correlate post-treatment surface fuel loads and characteristics with pre-treatment LiDAR-derived forest metrics, specifically trees per hectare (TPH) and stand density index (SDI). Surface fuel loads measured in the stand post-treatment were consistent with those reported in previous studies. A significant relationship was found between the pre-treatment SDI and total resultant fuel loading (p = 0.0477), though not between TPH and fuel loading (p = 0.0527). SDI may more accurately predict post-treatment fuel loads by accounting for both tree number per unit area and stem size, while trees per hectare alone does not account for variations of tree size and subsequent volume within a stand. Relatively large root-mean-square errors associated with the random forest models for SDI (36%) and TPH (46%) suggest that increased sampling intensity and modified methods that better account for fine spatial variability in fuels resulting from within-stand conditions, treatment prescriptions and machine operators may be needed. Use of LiDAR to predict fuel loading after mastication is a useful approach for managers to understand the efficacy of fuel reduction treatments by providing information that may be helpful for determining areas where treatments can be most beneficial.

A Simulation Study to Estimate Effects of Wildfire and Forest Management on Hydrology and Sediment in a Forested Watershed, Northwestern U.S.

2018 ◽  
Vol 61 (5) ◽  
pp. 1579-1601 ◽  
Author(s):  
Anurag Srivastava ◽  
Joan Q. Wu ◽  
William J. Elliot ◽  
Erin S. Brooks ◽  
Dennis C. Flanagan
Keyword(s):  
Sediment Yield ◽  
Post Treatment ◽  
Water Yield ◽  
National Forest ◽  
Fuel Reduction ◽  
Fuel Treatments ◽  
Peak Flows ◽  
Treatment Conditions ◽  
Forest Fuel ◽  
Pre Treatment

Abstract. Suitable fuel reduction treatments are needed in the Colville National Forest, Washington, to reduce the risk of severe wildfire. This study aimed to identify high-risk erosion hillslopes following wildfire to aid in forest fuel reduction planning and to evaluate the effects of fuel treatments on the watershed hydrological response. The specific objectives were (1) to assess the soil burn severity associated with wildfires and use that information to identify critical hillslopes for forest fuel treatments, and (2) to evaluate the potential changes in water yield and peak flows from pre-treatment (undisturbed forest) to post-treatment (thinning and prescribed burn) conditions, in the East Deer Creek Watershed (EDCW), a subwatershed of the Colville National Forest. Assessments were made using a modeling approach for hypothetical wildfire and fuel treatment scenarios. FlamMap, a fire behavior model, was used to predict the spatial distribution of wildfire intensity for a hypothetical event under current vegetation conditions. WEPP simulations were subsequently completed to obtain sediment and water yields based on fire intensity and topography. WEPP erosion estimations following a simulated wildfire showed hillslope sediment yield varying from 0 to 49.4 Mg ha-1 year-1 from the 777 hillslopes, which were ranked in descending order of sediment yield to identify critical hillslopes for fuel treatments. The WEPP model calibrated for a nearby gauged watershed was then applied to the EDCW for pre-treatment and post-treatment conditions. At the watershed scale, the increase in water yield from pre-treatment to post-treatment conditions ranged from 0.7% to 5.6% on hillslopes delivering 10% to 50% of the predicted post-fire sediment. Simulated water balance components at the treated hillslopes showed substantial changes. Surface runoff, subsurface lateral flow, and deep percolation increased 150% (5 mm), 50% (9 mm), and 40% (41 mm), respectively, whereas evapotranspiration (ET) decreased 23% (124 mm). The relative differences between pre- and post-harvest peak flows showed no clear trends as treatment area increased. The results suggest that thinning and prescribed burns to treated hillslopes in the EDCW may lead to an increase in water yield and significant alterations in hydrological processes. Keywords: Fuel treatments, Modeling, Peak flows, Sediment, Water yield, Wildfire.

Fuel treatments alter the effects of wildfire in a mixed-evergreen forest, Oregon, USA

2005 ◽  
Vol 35 (12) ◽  
pp. 2981-2995 ◽  
Author(s):  
Crystal L Raymond ◽  
David L Peterson
Keyword(s):  
Tree Mortality ◽  
Fire Regime ◽  
Fire Severity ◽  
Fire Behavior ◽  
Evergreen Forest ◽  
Fire Intensity ◽  
Crown Fire ◽  
Fuel Loading ◽  
Fuel Treatments ◽  
Surface Fire

We had the rare opportunity to quantify the relationship between fuels and fire severity using prefire surface and canopy fuel data and fire severity data after a wildfire. The study area is a mixed-evergreen forest of southwestern Oregon with a mixed-severity fire regime. Modeled fire behavior showed that thinning reduced canopy fuels, thereby decreasing the potential for crown fire spread. The potential for crown fire initiation remained fairly constant despite reductions in ladder fuels, because thinning increased surface fuels, which contributed to greater surface fire intensity. Thinning followed by underburning reduced canopy, ladder, and surface fuels, thereby decreasing surface fire intensity and crown fire potential. However, crown fire is not a prerequisite for high fire severity; damage to and mortality of overstory trees in the wildfire were extensive despite the absence of crown fire. Mortality was most severe in thinned treatments (80%–100%), moderate in untreated stands (53%–54%), and least severe in the thinned and underburned treatment (5%). Thinned treatments had higher fine-fuel loading and more extensive crown scorch, suggesting that greater consumption of fine fuels contributed to higher tree mortality. Fuel treatments intended to minimize tree mortality will be most effective if both ladder and surface fuels are treated.

scholarly journals Chronosequence of Fuel Loading and Fuel Depth Following Forest Rehabilitation Frill Treatment of Tanoak to Release Douglas-Fir: A Case Study from Northern California

Forests ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 691
Author(s):  
Raven M. Krieger ◽  
Brian E. Wall ◽  
Cody W. Kidd ◽  
John-Pascal Berrill
Keyword(s):  
Woody Debris ◽  
Fire Severity ◽  
Fire Behavior ◽  
Fire Effects ◽  
Behavior Modeling ◽  
Northern California ◽  
Fuel Loading ◽  
Excessive Competition ◽  
Pre Treatment ◽  
Forest Rehabilitation

There is concern that forest management activities such as chemical thinning may increase hazardous fuel loading and therefore increase risk of stand-replacing wildfire. Chemical thinning, often accomplished by frill treatment of unwanted trees, leaves trees standing dead for a time before they fall and become surface fuels. In coastal northern California, frill treatment is used as a forest rehabilitation treatment that removes tanoak (Notholithocarpus densiflorus) to release merchantable conifers from excessive competition. We studied fuel bed depth and fuel loading after frill treatment of tanoak along a 16-year chronosequence that substituted space for time. The total depth of fuel bed was separated into woody fuels, litter, and duff. The height of each layer was variable and greatest on average in post-treatment year 5 after treated tanoak had begun to break apart and fall. Initially, the evergreen tanoak trees retained their foliage for at least a year after treatment. Five years after treatment, many tanoak had fallen and transitioned to become fine- and coarse woody debris. After 11 years, the larger pieces of down wood were mostly classified as rotten. After 16 years, the fuel loading appeared roughly equivalent to pre-treatment levels, however we did not explicitly test for differences due to potential confounding between time and multiple factors such as inter-annual climate variations and site attributes. Nevertheless, our data provide some insight into changes in surface fuel characteristics due to rehabilitation treatments. These data can be used as inputs for fire behavior modeling to generate indicative predictions of fire effects such as fire severity and how these change over time since treatment.

The influence of fuelbed properties on moisture drying rates and timelags of longleaf pine litter

2008 ◽  
Vol 38 (9) ◽  
pp. 2394-2404 ◽  
Author(s):  
Ralph M. Nelson ◽  
J. Kevin Hiers
Keyword(s):  
Longleaf Pine ◽  
Fire Behavior ◽  
Pinus Palustris ◽  
Moisture Loss ◽  
Fuel Load ◽  
Drying Rate ◽  
Fuel Loading ◽  
Drying Rates ◽  
Fine Fuels ◽  
Individual Particles

Fire managers often model pine needles as 1 h timelag fuels, but fuelbed properties may significantly change the rate at which needles exchange moisture with the atmosphere. The problem of determining whether moisture loss from fine fuels is being controlled by individual particles or by the fuelbed remains unresolved. Results from this laboratory experiment indicate that first-period timelags of longleaf pine ( Pinus palustris Mill.) needles are altered by fuelbed loading and needle arrangement. Timelags of individual needles ranged from 3.3 to 5.3 h; timelags of beds of vertically oriented needles (4.4 to 8.6 h) approximated those of individual particles, but were slightly influenced by loading. Beds of horizontal needles dried with load-dependent timelags that varied from 6.5 to 31.6 h. Fuel loads ranged from 0.04 (for individual particles) to 1.07 kg·m–2. We report a new metric, the area drying rate, which is analogous to a unit-area burning rate. For beds of flat needles, plots of the area drying rate versus fuel load illustrate a transition from control by individual particles to control by the bed structure when fuel loading is approximately 0.33 kg·m–2. Beds of vertical needles were particle controlled. Results should be useful to fire managers when modeling fire behavior.

scholarly journals Effect of fuel treatments and backfiring on the recovery of an obligate seeder-dominated heathland

2016 ◽  
Vol 25 (3) ◽  
pp. eSC12 ◽  
Author(s):  
Cristina Fernández Filgueira ◽  
José A. Vega Hidalgo
Keyword(s):  
Plant Community ◽  
Prescribed Fire ◽  
Prescribed Burning ◽  
Shrub Cover ◽  
Fuel Reduction ◽  
Fuel Treatments ◽  
Nw Spain ◽  
Different Types ◽  
Pre Treatment ◽  
Experimental Plots

Aim of study: To evaluate how a plant community responded to a backfire that occurred four years after application of different types of fuel-reduction treatments.Area of study: Erica umbellata Loefl. (L.)-dominated heathland in Galicia (NW Spain).Materials and Methods: Shrub cover surveys in 16 experimental plots from 2006 to 2014. Fuel reduction treatments (prescribed burning, clearing and mastication) were applied in the spring of 2006 and the area was burned by a wildfire in the summer of 2010.Main results: Shrub total cover recovered quickly after the backfire in both the treated and untreated areas, and the pre-treatment values were reached four years after the fire. Post-wildfire resprouting species cover recovery was not affected by fuel treatments. As a contrast,  Erica umbellata cover reached levels similar to those in the untreated plots only in the areas treated by prescribed burning. After the wildfire, grasses cover recovery was greater in the treated than in the untreated areas and the effect lasted until the end of the study.Research highlights: Prescribed fire and backfire was favourable for Erica umbellata regeneration compared to clearing and mastication.Keywords: prescribed burning; clearing; mechanical shredding; Erica; wildfire. 

Novel fuelbed characteristics associated with mechanical mastication treatments in northern California and south-western Oregon, USA

2009 ◽  
Vol 18 (6) ◽  
pp. 686 ◽  
Author(s):  
Jeffrey M. Kane ◽  
J. Morgan Varner ◽  
Eric E. Knapp
Keyword(s):  
Time Lag ◽  
Fire Behavior ◽  
Fuel Load ◽  
Northern California ◽  
Fuel Loading ◽  
Quadratic Mean ◽  
Fuel Models ◽  
Quadratic Mean Diameter ◽  
Fuel Particles ◽  
Particle Shapes

Mechanically masticated fuelbeds are distinct from natural or logging slash fuelbeds, with different particle size distributions, bulk density, and particle shapes, leading to challenges in predicting fire behavior and effects. Our study quantified some physical properties of fuel particles (e.g. squared quadratic mean diameter, proportion of non-cylindrical particles) and surface fuel loading with planar intercept and plot-based methods in 10 mechanically masticated sites in northern California and south-western Oregon. Total woody fuel load differed among masticated sites, ranging from 15.3 to 63.4 Mg ha–1, with the majority of the load concentrated in the 10-h (53.7%) and 1-h (29.2%) time-lag classes. Masticated fuels were densely packed, with total depths ranging from 4.6 to 8.0 cm and fuelbed bulk densities ranging from 45.9 to 115.3 kg m–3. To accurately quantify loading in masticated fuelbeds, we recommend using a hybrid methodology, where 1-h and 10-h fuel loadings are estimated using a plot-based method and 100-h and 1000-h fuel loadings are estimated using the standard planar intercept method. Most masticated fuelbeds differed in loading by fuel class and fuelbed depth, when compared with existing natural and slash-based fuelbeds, suggesting new fire behavior fuel models specific to masticated fuelbeds may be warranted.

Impacts of lodgepole pine dwarf mistletoe (Arceuthobium americanum) infestation on stand structure and fuel load in lodgepole pine dominated forests in central Colorado

Botany ◽  
2017 ◽  
Vol 95 (3) ◽  
pp. 307-321 ◽  
Author(s):  
Scott M. Ritter ◽  
Chad M. Hoffman ◽  
Seth A. Ex ◽  
Jane E. Stewart
Keyword(s):  
Stand Structure ◽  
Temporal Dynamics ◽  
Lodgepole Pine ◽  
Fire Behavior ◽  
Basal Area ◽  
Fuel Load ◽  
Fuel Loading ◽  
Dwarf Mistletoe ◽  
Individual Host ◽  
Live Tree

Parasitic plants are capable of causing substantial alterations to plant communities through impacts on individual host plants. Lodgepole pine dwarf mistletoe is an important parasite in forests of the western USA that causes reductions to productivity and is thought to alter wildland fuel complexes. These impacts are hypothesized to vary with infestation severity. To test this, we used a linear mixed modeling approach to evaluate the relationship between dwarf mistletoe infestation severity and parameters representing stand structure and surface and canopy fuels in infested lodgepole pine stands in central Colorado. Infestation severity was negatively related to live basal area, average tree size, canopy base height, canopy fuel load, and canopy bulk density, and was positively related to the loading of woody surfaces fuels greater than 0.64 cm in diameter. No relationship was detected between infestation severity and live tree density, or live crown ratio. These results confirm the long-held assumption that dwarf mistletoe increases surface fuel loading in lodgepole pine communities, but also suggest that infested stands have reduced amounts of available canopy fuel. These findings have implications for potential fire behavior and highlight the importance of dwarf mistletoe in predicting the spatial and temporal dynamics of wildland fuels.

scholarly journals Generating a Baseline Map of Surface Fuel Loading Using Stratified Random Sampling Inventory Data through Cokriging and Multiple Linear Regression Methods

2021 ◽  
Vol 13 (8) ◽  
pp. 1561
Author(s):  
Chinsu Lin ◽  
Siao-En Ma ◽  
Li-Ping Huang ◽  
Chung-I Chen ◽  
Pei-Ting Lin ◽  
...  
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Random Sampling ◽  
Fuel Load ◽  
Estimation Accuracy ◽  
Slope Aspect ◽  
Stratified Random Sampling ◽  
Inventory Data ◽  
Fuel Loading ◽  
Regression Methods

Surface fuel loading is a key factor in controlling wildfires and planning sustainable forest management. Spatially explicit maps of surface fuel loading can highlight the risks of a forest fire. Geospatial information is critical in enabling careful use of deliberate fire setting and also helps to minimize the possibility of heat conduction over forest lands. In contrast to lidar sensing and/or optical sensing based methods, an approach of integrating in-situ fuel inventory data, geospatial interpolation techniques, and multiple linear regression methods provides an alternative approach to surface fuel load estimation and mapping over mountainous forests. Using a stratified random sampling based inventory and cokriging analysis, surface fuel loading data of 120 plots distributed over four kinds of fuel types were collected in order to develop a total surface fuel loading model (lntSFL-BioTopo model) and a fine surface fuel model (lnfSFL-BioTopo model) for generating tSFL and fSFL maps. Results showed that the combination of topographic parameters such as slope, aspect, and their cross products and the fuel types such as pine stand, non-pine conifer stand, broadleaf stand, and conifer–broadleaf mixed stand was able to appropriately describe the changes in surface fuel loads over a forest with diverse terrain morphology. Based on a cross-validation method, the estimation of tSFL and fSFL of the study site had an RMSE of 3.476 tons/ha and 3.384 tons/ha, respectively. In contrast to the average loading of all inventory plots, the estimation for tSFL and fSFL had a relative error of 38% (PRMSE). The reciprocal of estimation bias of both SFL-BioTopo models tended to be an exponential growth function of the amount of surface fuel load, indicating that the estimation accuracy of the proposed method is likely to be improved with further study. In the regression modeling, a natural logarithm transformation of the surface fuel loading prevented the outcome of negative estimates and thus improved the estimation. Based on the results, this paper defined a minimum sampling unit (MSU) as the area for collecting surface fuels for interpolation using a cokriging model. Allocating the MSUs at the boundary and center of a plot improved surface fuel load prediction and mapping.

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