Forest stand and site characteristics influence fuel consumption in repeat prescribed burns

2020 ◽  
Vol 29 (2) ◽  
pp. 148
Author(s):  
Jacob I. Levine ◽  
Brandon M. Collins ◽  
Robert A. York ◽  
Daniel E. Foster ◽  
Danny L. Fry ◽  
...  
Keyword(s):  
Fuel Consumption ◽  
Canopy Cover ◽  
Basal Area ◽  
Structural Diversity ◽  
Study Data ◽  
Fuel Load ◽  
Prescribed Burn ◽  
Fuel Type ◽  
Tree Species Composition ◽  
Prescribed Burns

Prescribed fire is a vital tool for mitigating wildfire hazard and restoring ecosystems in many western North American forest types. However, there can be considerable variability in fuel consumption from prescribed burns, which affects both hazard mitigation and emissions. In the present study, data from replicated, repeat-entry burns following a period of 100+ years of fire exclusion were used to provide a detailed quantification of fuel consumption as it varies by fuel type, size class, stand and prescribed burn number (first, second or third). Using model selection on a series of linear mixed-effects models, it was determined that total fuel load, proportion of overstorey pine, slope, canopy cover, basal area of live trees, burn number and stand influenced fuel consumption at a 0.04-ha scale. Specifically, overstorey pine composition had a positive effect on fuel consumption. Overall fuel consumption across the three burns averaged 45% of pre-burn fuel loads. Overall consumption was highest for the first burn at 65%, decreasing by 15–20% with each successive burn number. Fuel consumption was highly variable by fuel type, stand and tree species composition. This variability may be advantageous for managers seeking to foster structural diversity and resilience in forest stands.

scholarly journals Silviculture can facilitate repeat prescribed burn programs with long-term strategies

2022 ◽  
pp. 104-111
Author(s):  
Robert A. York ◽  
Jacob Levine ◽  
Daniel Foster ◽  
Scott Stephens ◽  
Brandon Collins
Keyword(s):  
Fuel Consumption ◽  
Prescribed Fire ◽  
Fire Suppression ◽  
Relative Proportion ◽  
Canopy Cover ◽  
Basal Area ◽  
Fuel Load ◽  
Prescribed Burn ◽  
Wildfire Hazard ◽  
Initial Entry

A significant expansion of prescribed fire activity will be necessary to mitigate growing wildfire hazard in California forests. Forest managers can facilitate this expansion by promoting forest structures that allow for more effective implementation of prescribed fire, for both initial-entry and repeat burns. We analyzed changes in surface fuel during a series of three burns in replicated mixed-conifer stands following a period of over 100 years of fire suppression and exclusion. Total fuel load, proportion of pine present, canopy cover and basal area of live trees were relevant forest-structure components that influenced plot-scale fuel consumption. The study highlighted the importance of pre-fire fuel load and the relative proportion of pine in the overstory, which both led to greater amounts of fuel consumption. The initial-entry burn dramatically reduced all fuel categories (fine fuel, coarse wood and duff). Following each burn, fuel recovered until the next burn reduced loads enough to maintain low fuel levels. We apply the results to provide an example of how to determine the timing of prescribed fires.

Characterisation of the fuel and fire environment in southern Ontario’s tallgrass prairie

2015 ◽  
Vol 24 (8) ◽  
pp. 1118 ◽  
Author(s):  
Susan Kidnie ◽  
B. Mike Wotton
Keyword(s):  
Moisture Content ◽  
Tallgrass Prairie ◽  
Prescribed Burning ◽  
Fire Spread ◽  
Fuel Load ◽  
Prairie Restoration ◽  
Prescribed Burn ◽  
Spread Rate ◽  
Prescribed Burns ◽  
Tallgrass Prairie Restoration

Prescribed burning can be an integral part of tallgrass prairie restoration and management. Understanding fire behaviour in this fuel is critical to conducting safe and effective prescribed burns. Our goal was to quantify important physical characteristics of southern Ontario’s tallgrass fuel complex prior to and during prescribed burns and synthesise our findings into useful applications for the prescribed fire community. We found that the average fuel load in tallgrass communities was 0.70 kg m–2. Fuel loads varied from 0.38 to 0.96 kg m–2. Average heat of combustion did not vary by species and was 17 334 kJ kg–1. A moisture content model was developed for fully cured, matted field grass, which was found to successfully predict moisture content of the surface layers of cured tallgrass in spring. We observed 25 head fires in spring-season prescribed burns with spread rates ranging from 4 to 55 m min–1. Flame front residence time averaged 27 s, varying significantly with fuel load but not fire spread rate. A grassland spread rate model from Australia showed the closest agreement with observed spread rates. These results provide prescribed-burn practitioners in Ontario better information to plan and deliver successful burns.

scholarly journals Emissions from prescribed fires in temperate forest in south-east Australia: implications for carbon accounting

2015 ◽  
Vol 12 (1) ◽  
pp. 257-268 ◽  
Author(s):  
M. Possell ◽  
M. Jenkins ◽  
T. L. Bell ◽  
M. A. Adams
Keyword(s):  
Coarse Woody Debris ◽  
Woody Debris ◽  
Carbon Accounting ◽  
Fuel Load ◽  
Fuel Type ◽  
Information Quantity ◽  
Prescribed Burns ◽  
Near Surface ◽  
Before And After ◽  
National Inventory Report

Abstract. We estimated emissions of carbon, as equivalent CO2 (CO2e), from planned fires in four sites in a south-eastern Australian forest. Emission estimates were calculated using measurements of fuel load and carbon content of different fuel types, before and after burning, and determination of fuel-specific emission factors. Median estimates of emissions for the four sites ranged from 20 to 139 Mg CO2e ha−1. Variability in estimates was a consequence of different burning efficiencies of each fuel type from the four sites. Higher emissions resulted from more fine fuel (twigs, decomposing matter, near-surface live and leaf litter) or coarse woody debris (CWD; > 25 mm diameter) being consumed. In order to assess the effect of declining information quantity and the inclusion of coarse woody debris when estimating emissions, Monte Carlo simulations were used to create seven scenarios where input parameters values were replaced by probability density functions. Calculation methods were (1) all measured data were constrained between measured maximum and minimum values for each variable; (2) as in (1) except the proportion of carbon within a fuel type was constrained between 0 and 1; (3) as in (2) but losses of mass caused by fire were replaced with burning efficiency factors constrained between 0 and 1; and (4) emissions were calculated using default values in the Australian National Greenhouse Accounts (NGA), National Inventory Report 2011, as appropriate for our sites. Effects of including CWD in calculations were assessed for calculation Method 1, 2 and 3 but not for Method 4 as the NGA does not consider this fuel type. Simulations demonstrate that the probability of estimating true median emissions declines strongly as the amount of information available declines. Including CWD in scenarios increased uncertainty in calculations because CWD is the most variable contributor to fuel load. Inclusion of CWD in scenarios generally increased the amount of carbon lost. We discuss implications of these simulations and how emissions from prescribed burns in temperate Australian forests could be improved.

scholarly journals Vegetation structure and fire weather influence variation in burn severity and fuel consumption during peatland wildfires

2016 ◽  
Vol 13 (2) ◽  
pp. 389-398 ◽  
Author(s):  
G. M. Davies ◽  
R. Domènech ◽  
A. Gray ◽  
P. C. D. Johnson
Keyword(s):  
Fuel Consumption ◽  
Linear Mixed Model ◽  
Burn Severity ◽  
Fuel Load ◽  
Fire Weather ◽  
Prescribed Burns ◽  
Fire Weather Index ◽  
Fuel Loads ◽  
Blanket Bog ◽  
Generalised Linear Mixed Model

Abstract. Temperate peatland wildfires are of significant environmental concern but information on their environmental effects is lacking. We assessed variation in burn severity and fuel consumption within and between wildfires that burnt British moorlands in 2011 and 2012. We adapted the composite burn index (pCBI) to provide semi-quantitative estimates of burn severity. Pre- and post-fire surface (shrubs and graminoids) and ground (litter, moss, duff) fuel loads associated with large wildfires were assessed using destructive sampling and analysed using a generalised linear mixed model (GLMM). Consumption during wildfires was compared with published estimates of consumption during prescribed burns. Burn severity and fuel consumption were related to fire weather, assessed using the Canadian Fire Weather Index System (FWI System), and pre-fire vegetation type. pCBI varied 1.6 fold between, and up to 1.7 fold within, wildfires. pCBI was higher where moisture codes of the FWI System indicated drier fuels. Spatial variation in pre- and post-fire fuel load accounted for a substantial proportion of the variance in fuel loads. Average surface fuel consumption was a linear function of pre-fire fuel load. Average ground fuel combustion completeness could be predicted by the Buildup Index. Carbon release ranged between 0.36 and 1.00 kg C m−2. The flammability of ground fuel layers may explain the higher C release-rates seen for wildfires in comparison to prescribed burns. Drier moorland community types appear to be at greater risk of severe burns than blanket-bog communities.

scholarly journals Vegetation structure and fire weather influence variation in burn severity and fuel consumption during peatland wildfires

2015 ◽  
Vol 12 (18) ◽  
pp. 15737-15762 ◽  
Author(s):  
G. M. Davies ◽  
R. Domènech ◽  
A. Gray ◽  
P. C. D. Johnson
Keyword(s):  
Fuel Consumption ◽  
Linear Mixed Model ◽  
Burn Severity ◽  
Fuel Load ◽  
Fire Weather ◽  
Prescribed Burns ◽  
Fire Weather Index ◽  
Fuel Loads ◽  
Blanket Bog ◽  
Generalised Linear Mixed Model

Abstract. Temperate peatland wildfires are of significant environmental concern but information on their environmental effects is lacking. We assessed variation in burn severity and fuel consumption within and between wildfires that burnt British moorlands in 2011 and 2012. We adapted the Composite Burn Index (pCBI) to provide semi-quantitative estimates of burn severity. Pre- and post-fire surface (shrubs and graminoids) and ground (litter, moss, duff) fuel loads associated with large wildfires were assessed using destructive sampling and analysed using a Generalised Linear Mixed Model (GLMM). Consumption during wildfires was compared with published estimates of consumption during prescribed burns. Burn severity and fuel consumption were related to fire weather, assessed using the Canadian Fire Weather Index System (FWI System), and pre-fire fuel structure. pCBI varied 1.6 fold between, and up to 1.7 fold within, wildfires. pCBI was higher where moisture codes of the FWI System indicated drier fuels. Spatial variation in pre- and post-fire fuel load accounted for a substantial proportion of the variance in fuel loads. Average surface fuel consumption was a linear function of pre-fire fuel load. Average ground fuel combustion completeness could be predicted by the Buildup Index. Carbon release ranged between 0.36 and 1.00 kg C m−2. The flammability of ground fuel layers may explain the higher C release-rates seen for wildfires in comparison to prescribed burns. Drier moorland community types appear to be at greater risk of severe burns than blanket-bog communities.

scholarly journals Emissions from prescribed fire in temperate forest in south-east Australia: implications for carbon accounting

2014 ◽  
Vol 11 (9) ◽  
pp. 13809-13839
Author(s):  
M. Possell ◽  
M. Jenkins ◽  
T. L. Bell ◽  
M. A. Adams
Keyword(s):  
Woody Debris ◽  
Carbon Accounting ◽  
Fuel Load ◽  
Fuel Type ◽  
Prescribed Burns ◽  
Near Surface ◽  
Before And After ◽  
Efficiency Factors ◽  
National Inventory Report

Abstract. We estimated of emissions of carbon, as CO2-equivalents, from planned fire in four sites in a south-eastern Australian forest. Emission estimates were calculated using measurements of fuel load and carbon content of different fuel types, before and after burning, and determination of fuel-specific emission factors. Median estimates of emissions for the four sites ranged from 20 to 139 T CO2–e ha−1. Variability in estimates was a consequence of different burning efficiencies of each fuel type from the four sites. Higher emissions resulted from more fine fuel (twigs, decomposing matter, near-surface live and leaf litter) or coarse woody debris (CWD; > 25 mm diameter) being consumed. In order to assess the effect of estimating emissions when only a few fuel variables are known, Monte-Carlo simulations were used to create seven scenarios where input parameters values were replaced by probability density functions. Calculation methods were: (1) all measured data were constrained between measured maximum and minimum values for each variable, (2) as for (1) except the proportion of carbon within a fuel type was constrained between 0 and 1, (3) as for (2) but losses of mass caused by fire were replaced with burning efficiency factors constrained between 0 and 1; and (4) emissions were calculated using default values in the Australian National Greenhouse Accounts (NGA), National Inventory Report 2011, as appropriate for our sites. Effects of including CWD in calculations were assessed for calculation Method 1, 2 and 3 but not for Method 4 as the NGA does not consider this fuel type. Simulations demonstrate that the probability of estimating true median emissions declines strongly as the amount of information available declines. Including CWD in scenarios increased uncertainty in calculations because CWD is the most variable contributor to fuel load. Inclusion of CWD in scenarios generally increased the amount of carbon lost. We discuss implications of these simulations and how emissions from prescribed burns in temperate Australian forests could be improved.

scholarly journals Leveraging TLS as a Calibration and Validation Tool for MLS and ULS Mapping of Savanna Structure and Biomass at Landscape-Scales

2021 ◽  
Vol 13 (2) ◽  
pp. 257 ◽  
Author(s):  
Shaun R. Levick ◽  
Tim Whiteside ◽  
David A. Loewensteiner ◽  
Mitchel Rudge ◽  
Renee Bartolo
Keyword(s):  
Remote Sensing ◽  
Vegetation Structure ◽  
Laser Scanning ◽  
Canopy Cover ◽  
Structural Diversity ◽  
Point Clouds ◽  
Large Area ◽  
Calibration And Validation ◽  
Savanna Vegetation ◽  
Landscape Scales

Savanna ecosystems are challenging to map and monitor as their vegetation is highly dynamic in space and time. Understanding the structural diversity and biomass distribution of savanna vegetation requires high-resolution measurements over large areas and at regular time intervals. These requirements cannot currently be met through field-based inventories nor spaceborne satellite remote sensing alone. UAV-based remote sensing offers potential as an intermediate scaling tool, providing acquisition flexibility and cost-effectiveness. Yet despite the increased availability of lightweight LiDAR payloads, the suitability of UAV-based LiDAR for mapping and monitoring savanna 3D vegetation structure is not well established. We mapped a 1 ha savanna plot with terrestrial-, mobile- and UAV-based laser scanning (TLS, MLS, and ULS), in conjunction with a traditional field-based inventory (n = 572 stems > 0.03 m). We treated the TLS dataset as the gold standard against which we evaluated the degree of complementarity and divergence of structural metrics from MLS and ULS. Sensitivity analysis showed that MLS and ULS canopy height models (CHMs) did not differ significantly from TLS-derived models at spatial resolutions greater than 2 m and 4 m respectively. Statistical comparison of the resulting point clouds showed minor over- and under-estimation of woody canopy cover by MLS and ULS, respectively. Individual stem locations and DBH measurements from the field inventory were well replicated by the TLS survey (R2 = 0.89, RMSE = 0.024 m), which estimated above-ground woody biomass to be 7% greater than field-inventory estimates (44.21 Mg ha−1 vs 41.08 Mg ha−1). Stem DBH could not be reliably estimated directly from the MLS or ULS, nor indirectly through allometric scaling with crown attributes (R2 = 0.36, RMSE = 0.075 m). MLS and ULS show strong potential for providing rapid and larger area capture of savanna vegetation structure at resolutions suitable for many ecological investigations; however, our results underscore the necessity of nesting TLS sampling within these surveys to quantify uncertainty. Complementing large area MLS and ULS surveys with TLS sampling will expand our options for the calibration and validation of multiple spaceborne LiDAR, SAR, and optical missions.

scholarly journals Quantitative Analysis of Forest Fires in Southeastern Australia Using SAR Data

2021 ◽  
Vol 13 (12) ◽  
pp. 2386
Author(s):  
Aqil Tariq ◽  
Hong Shu ◽  
Qingting Li ◽  
Orhan Altan ◽  
Mobushir Riaz Khan ◽  
...  
Keyword(s):  
Forest Fires ◽  
Prescribed Burning ◽  
Fire Risk ◽  
Fire Season ◽  
Prescribed Burn ◽  
Backscatter Coefficient ◽  
Prescribed Burns ◽  
Southeastern Australia ◽  
Sar Data ◽  
Sar Imagery

Prescribed burning is a common strategy for minimizing forest fire risk. Fire is introduced under specific environmental conditions, with explicit duration, intensity, and rate of spread. Such conditions deviate from those encountered during the fire season. Prescribed burns mostly affect surface fuels and understory vegetation, an outcome markedly different when compared to wildfires. Data on prescribed burning are crucial for evaluating whether land management targets have been reached. This research developed a methodology to quantify the effects of prescribed burns using multi-temporal Sentinel-1 Synthetic Aperture Radar (SAR) imagery in the forests of southeastern Australia. C-band SAR datasets were specifically used to statistically explore changes in radar backscatter coefficients with the intensity of prescribed burns. Two modeling approaches based on pre- and post-fire ratios were applied for evaluating prescribed burn impacts. The effects of prescribed burns were documented with an overall accuracy of 82.3% using cross-polarized backscatter (VH) SAR data under dry conditions. The VV polarization indicated some potential to detect burned areas under wet conditions. The findings in this study indicate that the C-band SAR backscatter coefficient has the potential to evaluate the effectiveness of prescribed burns due to its sensitivity to changes in vegetation structure.

scholarly journals Adjudicating Perspectives on Forest Structure: How Do Airborne, Terrestrial, and Mobile Lidar-Derived Estimates Compare?

2021 ◽  
Vol 13 (12) ◽  
pp. 2297
Author(s):  
Jonathon J. Donager ◽  
Andrew J. Sánchez Meador ◽  
Ryan C. Blackburn
Keyword(s):  
Ponderosa Pine ◽  
Laser Scanning ◽  
Canopy Cover ◽  
Basal Area ◽  
Tree Height ◽  
Absolute Error ◽  
Forest Monitoring ◽  
Individual Tree ◽  
Structural Configurations ◽  
Individual Trees

Applications of lidar in ecosystem conservation and management continue to expand as technology has rapidly evolved. An accounting of relative accuracy and errors among lidar platforms within a range of forest types and structural configurations was needed. Within a ponderosa pine forest in northern Arizona, we compare vegetation attributes at the tree-, plot-, and stand-scales derived from three lidar platforms: fixed-wing airborne (ALS), fixed-location terrestrial (TLS), and hand-held mobile laser scanning (MLS). We present a methodology to segment individual trees from TLS and MLS datasets, incorporating eigen-value and density metrics to locate trees, then assigning point returns to trees using a graph-theory shortest-path approach. Overall, we found MLS consistently provided more accurate structural metrics at the tree- (e.g., mean absolute error for DBH in cm was 4.8, 5.0, and 9.1 for MLS, TLS and ALS, respectively) and plot-scale (e.g., R2 for field observed and lidar-derived basal area, m2 ha−1, was 0.986, 0.974, and 0.851 for MLS, TLS, and ALS, respectively) as compared to ALS and TLS. While TLS data produced estimates similar to MLS, attributes derived from TLS often underpredicted structural values due to occlusion. Additionally, ALS data provided accurate estimates of tree height for larger trees, yet consistently missed and underpredicted small trees (≤35 cm). MLS produced accurate estimates of canopy cover and landscape metrics up to 50 m from plot center. TLS tended to underpredict both canopy cover and patch metrics with constant bias due to occlusion. Taking full advantage of minimal occlusion effects, MLS data consistently provided the best individual tree and plot-based metrics, with ALS providing the best estimates for volume, biomass, and canopy cover. Overall, we found MLS data logistically simple, quickly acquirable, and accurate for small area inventories, assessments, and monitoring activities. We suggest further work exploring the active use of MLS for forest monitoring and inventory.

Prescribed Burning for Stand Conversion in Budworm-killed Balsam Fir: An Ontario Case History

1986 ◽  
Vol 62 (2) ◽  
pp. 96-100 ◽  
Author(s):  
D. J. McRae
Keyword(s):  
Fuel Consumption ◽  
Prescribed Burning ◽  
Choristoneura Fumiferana ◽  
Abies Balsamea ◽  
Spruce Budworm ◽  
Fire Spread ◽  
Fire Effects ◽  
Balsam Fir ◽  
Prescribed Burn ◽  
Stand Conversion

Recent spruce budworm (Choristoneura fumiferana [Clem.]) infestations have resulted in widespread areas of balsam fir (Abies balsamea [L.] Mill.) mortality in Ontario, and there is growing interest in reestablishing these areas quickly as productive forests. One technique being used is prescribed fire after a salvage and bulldozer tramping operation. A 445-ha prescribed burn was carried out under moderate fire danger conditions in northern Ontario. The site, which was covered by balsam fir fuel that had been killed by spruce budworm, was tramped to improve fire spread. Weather, fuel consumption, and fire effects are reported. The burn effectively reduced heavy surface fuel loadings and consequently planting on the site was easier. Key words: Prescribed burning, fire, spruce budworm. Choristoneura fumiferana, balsam fir, Abies balsamea, fuel consumption, site preparation, tramping, stand conversion.

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