Evaluating the 3-m tree crown spacing guideline for the prevention of crowning wildfires in lodgepole pine forests, Alberta

A 3-m between crown spacing is a commonly cited criterion found in the wildland-urban interface fire literature for minimizing the likelihood of a fully-developed crown fire from occurring in a conifer forest on level terrain. The validity of this general recommendation is examined here in light of our current state-of-knowledge regarding crown fire propagation in relation to canopy bulk density. Given the characteristics of the overstory structure for 20 lodgepole pine (Pinus contorta Dougl. ex Loud. var. latifolia Engelm.) stands located in Alberta, as sourced from the literature, the canopy fuel properties following a virtual thinning to a 3-m crown spacing and then to a targeted canopy bulk density of 0.05 kg/m3 were computed. On the basis of these computations, crown fire potential was then analyzed and interpreted. The conclusion reached is that, in the majority of cases, a less widely spaced stand would be adequate for preventing crown fire development in lodgepole pine forests.

Estimating Canopy Fuel Attributes from Low-Density LiDAR

Simulations of wildland fire risk are dependent on the accuracy and relevance of spatial data inputs describing drivers of wildland fire, including canopy fuels. Spatial data are freely available at national and regional levels. However, the spatial resolution and accuracy of these types of products often are insufficient for modeling local conditions. Fortunately, active remote sensing techniques can produce accurate, high-resolution estimates of forest structure. Here, low-density LiDAR and field-based data were combined using randomForest k-nearest neighbor imputation (RF-kNN) to estimate canopy bulk density, canopy base height, and stand age across the Boundary Waters Canoe Area in Minnesota, USA. RF-kNN models produced strong relationships between estimated canopy fuel attributes and field-based data for stand age (Adj. R2 = 0.81, RMSE = 10.12 years), crown fuel base height (Adj. R2 = 0.78, RMSE = 1.10 m), live crown base height (Adj. R2 = 0.7, RMSE = 1.60 m), and canopy bulk density (Adj. R2 = 0.48, RMSE = 0.09kg/m3). These results suggest that low-density LiDAR can help estimate canopy fuel attributes in mixed forests, with robust model accuracies and high spatial resolutions compared to currently utilized fire behavior model inputs. Model map outputs provide a cost-efficient alternative for data required to simulate fire behavior and support local management.

Evaluating Unmanned Aerial Vehicle Images for Estimating Forest Canopy Fuels in a Ponderosa Pine Stand

Forests in the Southwestern United States are becoming increasingly susceptible to large wildfires. As a result, forest managers are conducting forest fuel reduction treatments for which spatial fuels and structure information are necessary. However, this information currently has coarse spatial resolution and variable accuracy. This study tested the feasibility of using unmanned aerial vehicle (UAV) imagery to estimate forest canopy fuels and structure in a southwestern ponderosa pine stand. UAV-based multispectral images and Structure-from-Motion point clouds were used to estimate canopy cover, canopy height, tree density, canopy base height, and canopy bulk density. Estimates were validated with field data from 57 plots and aerial photography from the U.S. Department of Agriculture National Agriculture Imaging Program. Results indicate that UAV imagery can be used to accurately estimate forest canopy cover (correlation coefficient (R2) = 0.82, root mean square error (RMSE) = 8.9%). Tree density estimates correctly detected 74% of field-mapped trees with a 16% commission error rate. Individual tree height estimates were strongly correlated with field measurements (R2 = 0.71, RMSE = 1.83 m), whereas canopy base height estimates had a weaker correlation (R2 = 0.34, RMSE = 2.52 m). Estimates of canopy bulk density were not correlated to field measurements. UAV-derived inputs resulted in drastically different estimates of potential crown fire behavior when compared with coarse resolution LANDFIRE data. Methods from this study provide additional data to supplement, or potentially substitute, traditional estimates of canopy fuel.

Estimating canopy fuel characteristics for predicting crown fire potential in common forest types of the Atlantic Coastal Plain, USA

We computed four stand-level canopy stratum variables important for crown fire modelling – canopy cover, stand height, canopy base height and canopy bulk density – from forest inventory data. We modelled the relationship between the canopy variables and a set of common inventory parameters – site index, stem density, basal area, stand age or stand height – and number of prescribed burns. We used a logistic model to estimate canopy cover, a linear model to estimate the other canopy variables, and the information theoretic approach for model selection. Coefficients of determination across five forest groups were 0.72–0.91 for stand height, 0.36–0.83 for canopy base height, 0.39–0.80 for canopy cover, and 0.63–0.78 for canopy bulk density. We assessed crown fire potential (1) for several sets of environmental conditions in all seasons, and (2) with increasing age, density and number of prescribed burns using our modelled canopy bulk density and canopy base height variables and local weather data to populate the Crown Fire Initiation and Spread model. Results indicated that passive crown fire is possible in any season in Atlantic coastal plain pine stands with heavy surface fuel loads and active crown fire is most probable in infrequently burned, dense stands at low fuel moistures.

Fuel accumulation and forest structure change following hazardous fuel reduction treatments throughout California

Altered fuel conditions coupled with changing climate have disrupted fire regimes of forests historically characterised by high-frequency and low-to-moderate-severity fire. Managers use fuel treatments to abate undesirable fire behaviour and effects. Short-term effectiveness of fuel treatments to alter fire behaviour and effects is well documented; however, long-term effectiveness is not well known. We evaluated surface fuel load, vegetation cover and forest structure before and after mechanical and fire-only treatments over 8 years across 11 National Forests in California. Eight years post treatment, total surface fuel load returned to 67 to 79% and 55 to 103% of pretreatment levels following fire-only and mechanical treatments respectively. Herbaceous or shrub cover exceeded pretreatment levels two-thirds of the time 8 years after treatment. Fire-only treatments warranted re-entry at 8 years post treatment owing to the accumulation of live and dead fuels and minimal impact on canopy bulk density. In general, mechanical treatments were more effective at reducing canopy bulk density and initially increasing canopy base height than prescribed fire. However, elevated surface fuel loads, canopy base height reductions in later years and lack of restoration of fire as an ecological process suggest that including prescribed fire would be beneficial.

Evaluating regression model estimates of canopy fuel stratum characteristics in four crown fire-prone fuel types in western North America

Two evaluations were undertaken of the regression equations developed by M. Cruz, M. Alexander and R. Wakimoto (2003, International Journal of Wildland Fire 12, 39–50) for estimating canopy fuel stratum characteristics from stand structure variables for four broad coniferous forest fuel types found in western North America. The first evaluation involved a random selection of 10 stands each from the four datasets used in the original study. These were in turn subjected to two simulated thinning regimes (i.e. 25 and 50% basal area removal). The second evaluation involved a completely independent dataset for ponderosa pine consisting of 16 stands sampled by T. Keyser and F. Smith (2010, Forest Science 56, 156–165). Evaluation statistics were comparable for the thinning scenarios and independent evaluations. Mean absolute percentage errors varied between 13.8 and 41.3% for canopy base height, 5.3 and 67.9% for canopy fuel load, and 20.7 and 71% for canopy bulk density. Bias errors were negligible. The results of both evaluations clearly show that the stand-level models of Cruz et al. (2003) used for estimating canopy base height, canopy fuel load and canopy bulk density in the assessment of crown fire potential are, considering their simplicity, quite robust.

Deriving forest canopy fuel parameters for loblolly pine forests in eastern Texas

Crown fires, the fastest spreading of all forest fires, can occur in any forest type throughout the world. The overall aim of this study was to estimate forest canopy fuel parameters including canopy bulk density and canopy base height for loblolly pines ( Pinus taeda L.) at the plot level using both allometric equations and CrownMass/FMAPlus software. Allometric equation results were compared with the CrownMass outputs for validation. According to our results, the calculated average canopy bulk density values, across all 50 plots, were 0.18 and 0.07 kg/m3 for the allometric equation and the CrownMass program, respectively. Lorey’s mean height approach was used in this study to calculate canopy base height at the plot level. The average height values of canopy base height obtained from the Lorey height approach was 10.6 m and from the CrownMass program was 9.1 m. The results obtained for the two methods are relatively close to each other, with the estimate of canopy base height being 1.16 times larger than the CrownMass value. This study provides a practical method for quantifying these parameters and making them directly available to fire managers. The accuracy of these parameters is very important for realistic predictions of wildfire initiation and growth.

Canopy bulk density and canopy base height equations for assessing crown fire hazard in Pinus radiata plantations

Crown fires combine high rates of spread, flame lengths, and intensities, making it virtually impossible to control them by direct action and having significant impact on soils, vegetation, and wildlife habitat. For these reasons, fire managers have great interest in preventive silviculture of forested landscapes to avoid the initiation and propagation of crown fires. The minimum conditions necessary to initiate and propagate crown fires are assumed to be strongly influenced by the stand structural variables canopy bulk density (CBD) and canopy base height (CBH). However, there is a lack of quantitative information on these variables and how to estimate them. To characterize the aerial fuel layers of Pinus radiata D. Don, the vertical profiles of canopy fuel in 180 sample plots of pure and even-aged P. radiata plantations were analysed. Effective CBD and CBH were obtained from the vertical profiles, and equations relating these variables to common stand variables were fitted simultaneously. Inclusion of the fitted equations in existing dynamic growth models, together with the use of current fire behaviour and hazard prediction tools, will provide a decision support system for assessing the crown fire potential of different silvicultural alternatives for this species.