Canadian Forest Fire Behavior Prediction Research Articles

Improved logistic models of crown fire probability in Canadian conifer forests

Background Crown fires are an ecologically necessary but hazardous process in conifer forests. Prediction of their behaviour in Canada has largely depended on the Canadian Forest Fire Behaviour Prediction System, in which fire weather indices drive primarily fixed fuel type models. The Crown Fire Initiation and Spread (CFIS) system presents a more flexible approach to predicting crown fire occurrence than fixed fuel type models. Aims Using a multi-decadal database of experimental fires carried out in conifer plots (1960–2019, n = 113), our aim was to develop updated models based on the CFIS system approach, fitting crown fire occurrence models to fire environment variables using logistic regression. Methods We tested alternative fuel moisture estimates and compared various model forms using repeated cross-validation. In two-storeyed stands, crown fire occurrence was defined as the involvement of lower canopy stratum fuels. Key results Final models based on wind speed, fuel strata gap, litter moisture and surface fuel consumption predicted crowning events correctly in up to 92% of cases in training data (89% in cross-validation). Conclusions and implications These new models offer improved accuracy and flexibility that will help users assess how competing environmental factors interact under different fuel treatments and wildfire scenarios.

Classification of forest fuels in selected fire-prone ecosystems of Alberta, Canada—implications for crown fire behaviour prediction and fuel management

Key messageWe used clustering to construct fuel classes from fuel inventory data based on three stand attributes relevant to crown fire behaviour: surface fuel load (SFL), canopy base height (CBH) and canopy bulk density (CBD). Resulting fuel classes explained more of the stand-to-stand variability in predicted crown fire behaviour than fuel types of the Canadian Forest Fire Behaviour Prediction (FBP) System.ContextWildfire behaviour is partly determined by stand structure and composition. Fuel characterization is essential for predicting fire behaviour and managing vegetation. Currently, categorical fuel types based on associations with major forested or open vegetated landcovers are used nationally in Canada for fire research and management applications.AimTo provide an alternative description of selected forest fuels in Alberta, Canada, using direct classification in which fuel categories are constructed from data using analytical methods.MethodsFuel inventory data for 476 stands were used to construct fuel classes with clustering. Potential crown fire behaviour was modelled for resulting fuel class clusters (FCCs) and FCCs were compared with assigned FBP System fuel types. Tree-based modelling was used to identify stand characteristics most influential on FCC membership. Fuel treatment effects on FCC and modelled crown fire behaviour were explored for the FCC most susceptible to crown fire.ResultsFour FCCs were identified: Red (low SFL, low CBH, low CBD); Green (high SFL, low-moderate CBH, low CBD); Blue (low SFL, high CBH, low-moderate CBD); and Black (low SFL, moderate CBH, high CBD). Stand density of live conifers and FBP System fuel type were the most important variables influencing FCC membership; however, FCCs did not align directly with assigned FBP System fuel types. Fuel reduction treatments in the Black FCC were effective at shifting the stand to a less flammable FCC.ConclusionFCCs explained more of the stand-to-stand variability in predicted crown fire behaviour than assigned FBP System fuel types, which suggests FCCs could be used to improve fire behaviour predictions and aid fire managers in prioritizing areas for fuel treatments. Future technological and remote sensing advances could enable mapping FCCs across large regions.

Cell2Fire: A Cell-Based Forest Fire Growth Model to Support Strategic Landscape Management Planning

Cell2Fire is a new cell-based wildland fire growth simulator designed to integrate data-driven landscape management planning models. The fire environment is modeled by partitioning the landscape into cells characterized by fuel, weather, moisture content, and topographic attributes. The model can use existing fire spread models such as the Canadian Forest Fire Behavior Prediction System to model fire growth. Cell2Fire is structured to facilitate its use for predicting the growth of individual fires or by embedding it in landscape management simulation models. Decision-making models such as fuel treatment/harvesting plans can be easily integrated and evaluated. It incorporates a series of out-of-the-box planning heuristics that provide benchmarks for comparison. We illustrate their use by applying and evaluating a series of harvesting plans for forest landscapes in Canada. We validated Cell2Fire by using it to predict the growth of both real and hypothetical fires, comparing our predictions with the fire scars produced by a validated fire growth simulator (Prometheus). Cell2Fire is implemented as an open-source project that exploits parallelism to efficiently support the modeling of fire growth across large spatial and temporal scales. Our experiments indicate that Cell2Fire is able to efficiently simulate wildfires (up to 30x faster) under different conditions with similar accuracy as state-of-the-art simulators (above 90% of accuracy). We demonstrate its effectiveness as part of a harvest planning optimization framework, identifying relevant metrics to capture and actions to mitigate the impact of wildfire uncertainty.

Potential climate change impacts on fire intensity and key wildfire suppression thresholds in Canada

Much research has been carried out on the potential impacts of climate change on forest fire activity in the boreal forest. Indeed, there is a general consensus that, while change will vary regionally across the vast extent of the boreal, in general the fire environment will become more conducive to fire. Land management agencies must consider ways to adapt to these new conditions. This paper examines the impact of that changed fire environment on overall wildfire suppression capability. We use multiple General Circulation Models and carbon emission pathways to generate future fire environment scenarios for Canada’s forested region. We then use these scenarios with the Canadian Forest Fire Behaviour Prediction System and spatial coverages of the current forest fuel composition across the landscape to examine potential variation in key fire behaviour outputs that influence whether fire management resources can effectively suppress fire. Specifically, we evaluate how the potential for crown fire occurrence and active growth of fires changes with the changing climate. We also examine future fire behaviour through the lens of operational fire intensity thresholds used to guide decisions about resources effectiveness. Results indicate that the proportion of days in fire seasons with the potential for unmanageable fire will increase across Canada’s forest, more than doubling in some regions in northern and eastern boreal forest.

Emissions of air pollutants by Canadian wildfires from 2000 to 2004

A wildfire emission model, based on the Canadian Forest Fire Behaviour Prediction System and the Canadian weather forecast Global Environmental Multiscale model, was applied to forest fires that occurred in Canada between 2000 and 2004. Emissions of 21 chemical species and injection heights were calculated hourly for a regular 0.4° grid, with injection heights corresponding to the maximum altitude reached by a convective plume over a fire every hour. Wildfire emissions were compared with anthropogenic fossil fuel combustion sources at provincial, territorial and national levels. The 2002 fire season in central Quebec accounted for ~30, 60 and 80% of the annual primary greenhouse gases, carbon monoxide and black carbon emissions respectively for that province. In 2003, fires represented 60 and 20% of greenhouse gas emissions in Manitoba and British Columbia respectively. During the 2004 fire season in north-western Canada, when area burned was above average, fires were responsible for almost all greenhouse gas emissions occurring in the sparsely populated Yukon Territory and Northwest Territories. On average, between 2000 and 2004, fires contributed 10, 30 and 40% of Canadian annual greenhouse gases, CO and black carbon emissions respectively. This methodology for calculating wildland fire emissions is also applicable to other regions of the world.

Defining fire spread event days for fire-growth modelling

Forest fire managers have long understood that most of a fire’s growth typically occurs on a small number of days when burning conditions are conducive for spread. Fires either grow very slowly at low intensity or burn considerable area in a ‘run’. A simple classification of days into ‘spread events’ and ‘non-spread events’ can greatly improve estimates of area burned. Studies with fire-growth models suggest that the Canadian Forest Fire Behaviour Prediction System (FBP System) seems to predict growth well during high-intensity ‘spread events’ but tends to overpredict rate of spread for non-spread events. In this study, we provide an objective weather-based definition of ‘spread events’, making it possible to assess the probability of having a spread event on any particular day. We demonstrate the benefit of incorporating this ‘spread event’ day concept into a fire-growth model based on the Canadian FBP System.

Surface fire spread potential in trembling aspen during summer in the Boreal Forest Region of Canada

In Canada, the importance of seasonality in forest fire danger rating associated with phenological changes in deciduous tree leaves and lesser ground vegetation has historically been taken into account by dividing the fire season into three distinct periods (i.e., spring, summer, and fall). During the mid-1980s, the developers of the Canadian Forest Fire Behavior Prediction (FBP) System did not envision that the M-2 Boreal Mixedwood – Green fuel type with 100% hardwood composition would eventually be explicitly interpreted by field users and other researchers to represent a trembling aspen (Populus tremuloides Michx.) fuel type in the summer following green-up or flushing of the overstory canopy and understory vegetation. Interest in what has become to be known as the D-2 FBP System fuel type to represent leafed-out trembling aspen stands during the summer fire season has steadily increased since. Formal recognition of such a fuel type may very well constitute an example of overextending the original basis and heuristics associated with the rate of fire spread model for the M-2 FBP System fuel type. Thus, the assumptions underlying a D-2 fuel type are explicitly restated here for the benefit of fire managers and researchers alike. Furthermore, an interim guideline is presented with respect to the threshold condition in fuel dryness necessary for surface fire spread in the D-2 fuel type to occur based on existing empirical observations garnered from experimental fires, prescribed burns and wildfires. This criterion was deduced from existing information and knowledge, and is expressed in terms of the Buildup Index (BUI) component of the Canadian Forest Fire Weather Index System. The rationale for the descriptive name assigned to the D-2 fuel type and the corresponding fuel strata characteristics are given. Improvements in the present basis of the D-2 fuel type could be realized from monitoring selected wildfires and operational prescribed fires and/or by carrying out an experimental burning study. Key words: Canadian Forest Fire Behavior Prediction System,Canadian Forest Fire Danger Rating System,Canadian Forest Fire Weather Index System,deciduous,fire behavior, fire danger, fire environment, fire hazard, fire potential, fire risk, forest flammability, fuel type, fuel moisture, green-up, hardwood, rate of fire spread.

Modelling emissions from Canadian wildfires: a case study of the 2002 Quebec fires

The present paper proposes an original approach to estimate gaseous and particulate emissions from boreal forest fires based on the Canadian Forest Fire Behaviour Prediction (FBP) System. The FBP System permits calculation of fuel consumption and rate of spread for individual fires on an hourly basis from meteorological conditions and fuel patterns. Weather data are obtained by running the Canadian weather forecast model GEM (Global Environmental Multiscale). Hourly emission point sources can then be generated from a given wildfire database. The smoke emission model was first applied to the boreal forest fires in Quebec in the summer of 2002. Geographical distribution and temporal variability of emission amounts, as well as injection heights, were assessed hourly. In July, ~150 wildfires released 39 Mt of CO2 equivalent of greenhouse gases and 470 kt of fine particulate matter to the atmosphere. They contributed 32 and 5% of Quebec’s and Canada’s annual greenhouse gas emissions, respectively. Black carbon was estimated to account for 4% of the total fine particulate matter. Wildfires were responsible for 51 and 90% of all Canada’s black carbon and particulate organic matter sources, respectively.

Modeling Canadian wildland fire carbon emissions with the Boreal Fire Effects (BORFIRE) model

Wildland fires in Canada burn an average of2.8 million hectares of forest annually. In years of extreme forest fire activity. total carbon emissions from wildland fires approach levels similar to industrial carbon emissions. Quantifying annual wildland fire carbon emissions is required for Canada to meet its international reporting obligations. Carbon emission rates within a fire vary considerably due to fire behaviour within the burn perimeter. Large fires typically burn a wide range of fuel types under weather conditions that change as the fire spreads across the landscape. This causes huge spatial and temporal variation in fuel consumption. which is directly related to carbon emissions. To capture spatial and temporal variability. the Boreal Fire Effects (BORFIRE) model estimates carbon emissions using detailed fuel and weather data. BORFIRE is initialized with forest inventory data to establish preburn fuel loads for forest stand components. including live tree material (coarse roots. fine roots. stemwood. branchwood, foliage). standing dead trees (stemvI'ood. branchwood). dead and downed wood (coarse woody debris, medium woody debris). and forest floor organic matter (surface litter. duff). Carbon loss from each component is based on fuel consumption. which is calculated using fuel-specific fire behaviour models and burning conditions quantified by the Canadian Forest Fire Weather Index (FWI) System. Fire rate of spread is determined using the Initial Spread Index (lSI) of the FWI System and rate of spread algorithms of the Canadian Forest Fire Behavior Prediction System. This is combined with surface fuel consumption to calculate surface fire intensity using Byram's equation. I l' surface fire intensity exceeds the crown fire threshold. fuel consumption of aerial fuels is calculated. After determining carbon emissions. BORFIRE calculates the carbon transfers between stand components. BORFIRE has been incorporated as a submodel in the Canadian Wildland Fire Information System (CWFIS). and procedures have been developed to link CWFIS with the Carbon Budget Model of the Canadian Forest Sector to operationally calculate carbon emissions for Canadian wildland tires.

Development of the Indonesian and Malaysian Fire Danger Rating Systems

Forest and land fires in Southeast Asia have many social, economic, and environ- mental impacts. Tropical peatland fires affect global carbon dynamics, and haze from peat fires has serious negative impacts on the regional economy and human health. To mitigate these fire-related problems, forest and land management agencies require an early warning system to assist them in implementing fire prevention and management plans before fire prob- lems begin. Fire Danger Rating Systems (FDRS) were developed for Indonesia and Malaysia to provide early warning of the potential for serious fire and haze events. In particular, they identify time periods when fires can readily start and spread to become uncontrolled fires and time periods when smoke from smouldering fires will cause an unacceptably high level of haze. The FDRS were developed by adapting components of the Canadian Forest Fire Danger Rating System, including the Canadian Forest Fire Weather Index (FWI) System and the Canadian Forest Fire Behavior Prediction (FBP) System, to local vegetation, climate, and fire regime conditions. A smoke potential indicator was developed using the Drought Code (DC) of the FWI System. Historical air quality analysis showed that the occurrence of severe haze events increased substantially when DC was above 400. An ignition potential indicator was developed using the Fine Fuel Moisture Code (FFMC) of the FWI System. Historical hot spot analysis, grass moisture, and grass ignition studies showed that fire occurrence and the ability for grass fires to start and spread dramatically increased when FFMC > 82. The Initial Spread Index (ISI) of the FWI System was used to develop a difficulty of control indicator for grassland fires, a fuel type that can exhibit high rates of spread and fire intensity.

Simulation of historical and current fire regimes in central Saskatchewan

Evaluation and implementation of the forest policy of emulating natural fire patterns in harvest planning require a good understanding of both natural and human influenced fire regimes. The SEM-LAND model (Spatially Explicit Model for LANdscape Dynamics) was employed to simulate both natural and current fire regimes in central Saskatchewan. The model used the indexes and relationships summarized in the Canadian Forest Fire Weather Index System and the Canadian Forest Fire Behavior Prediction System to simulate the interactions among fire events, landscape structures, topography, and weather conditions. The impact of fire suppression operations on fire spread simulated the following three stages: fire ignition, initial attack, and fire escape. Our results suggest that fire suppression could lead to longer fire cycles, smaller mean fire sizes, more fire numbers per year, and increased mean forest age (time-since-fire). The relationship between mean forest age and annual area burned was estimated from the results of this model experiment. This relationship can be used to determine the ideal fire management target of annual allowable area burned from expected future forest conditions. We conclude that the SEM-LAND model was capable of simulating fire regimes in Saskatchewan.

Assessing the probability of crown fire initiation based on fire danger indices

The initiation of crown fires in conifer stands was modelled through logistic regression analysis by considering as independent variables a basic physical descriptor of the fuel complex structure and selected components of the Canadian Forest Fire Weather Index (FWI) System. The study was based on a fire behaviour research database consisting of 63 experimental fires covering a relatively wide range of burning conditions and fuel type characteristics. Four models were built with decreasing input needs. Significant predictors of crown fire initiation were: canopy base height, wind speed measured at a height of 10 m in the open, and four components of the FWI System (i.e., Fine Fuel Moisture Code, Drought Code, Initial Spread Index and Buildup Index). The models predicted correctly the type of fire (i.e., surface or crown) between 90% and 66% of the time. The C index, a statistical measure, varied from 0.94 to 0.71, revealing good concordance between predicted probabilities and observed events. A comparison between the logistic models and Canadian Forest Fire Behaviour Prediction System models did not show any conclusive differences. The results of a limited evaluation involving two independent experimental fire data sets for distinctly different fuel complexes were encouraging. The logistic models built may have applicability in fire management decision support systems, allowing for the estimation of the probability of crown fire initiation at small and large spatial scales from commonly available fire environment and fire danger rating information. The relationships presented are considered valid for free-burning fires on level terrain in coniferous forests that have reached a pseudo steady-state and are not deemed applicable to dead conifer forests (i.e., insect-killed stands). Key words: Canadian Forest Fire Danger Rating System, crown fire initiation, fire behaviour, fire danger indices, logistic regression

Perspectives on carbon emissions from Canadian forest fires

How much carbon is released from Canadian forest fires? A recent analysis indicates that Canadian forest fires have released an average of 27 Mt (1012 g) of carbon annually over the past four decades (Amiro et al. 2001a). These emissions are caused by direct combustion. About an equal additional amount of carbon may also be lost through decomposition of fire-killed vegetation and a temporary decrease in the forest sink, although this amount is not well quantified. The carbon emissions were calculated based on the size of each fire, the dates over which it burned, and the fuel consumed based on the Canadian Forest Fire Behavior Prediction System (Forestry Canada 1992). The estimates are a product of the Canadian large-fire database, a geographically referenced data set of all fires greater than 200 ha in area, which includes information on the size of each fire and the start date (Stocks et al. 2002). The emissions vary widely among years ranging from 3 to 115 Mt carbon per year (Fig. 1). This is largely caused by the wide interannual variability in area burned, which ranged from 0.3 to 7.5 million ha/year. Across the country, an average of 1.3 kg of carbon is lost per m2 of burned area, but this varies from about 1 to 2 kg C/m2 on average among different ecozones.

Direct carbon emissions from Canadian forest fires, 1959-1999

Direct emissions of carbon from Canadian forest fires were estimated for all Canada and for each ecozone for the period 1959–1999. The estimates were based on a data base of large fires for the country and calculations of fuel consumption for each fire using the Canadian Forest Fire Behaviour Prediction System. This technique used the fire locations and start dates to estimate prevailing fire weather and fuel type for each of about 11 000 fires. An average of 2 × 106 ha·year–1 was burned in this period, varying from 0.3 × 106 ha in 1978 to 7.5 × 106 ha in 1989. Ecozones of the boreal and taiga areas experienced the greatest area burned, releasing most of the carbon (C). The mean area-weighted fuel consumption for all fires was 2.6 kg dry fuel·m–2 (1.3 kg C·m–2), but ecozones vary from 1.8 to 3.9 kg dry fuel·m–2. The mean annual estimate of direct carbon emissions was 27 ± 6 Tg C·year–1. Individual years ranged from 3 to 115 Tg C·year–1. These direct fire emissions represent about 18% of the current carbon dioxide emissions from the Canadian energy sector, on average, but vary from 2 to 75% among years. Post-fire effects cause an additional loss of carbon and changes to the forest sink condition.

Modelling logic and the Canadian Forest Fire Behavior Prediction System

This article outlines the flexible semi-empirical philosophy used throughout six decades of fire research by the Canadian Forest Service, culminating in the development of the Forest Fire Behavior Prediction System. It then describes the principles involved when spread rate and fuel consumption are estimated separately to yield fire intensity, and the anomaly that has resulted from the omission of a foliar-moisture effect on crown-fire spread. Judged on its results so far, this Canadian approach has held its own against any other, and holds full promise for the future as well. Key words: forest fire behavior, Canadian FBP System, fire modelling, crown-fire theory, fire research philosophy

Understory prescribed burning in red pine and white pine

The alarming loss of forested areas containing red pine (Pinus resinosa Ait.) and eastern white pine (Pinus strobus L.) in eastern Canada is a situation that must be addressed promptly by changing management approaches. Since the ecological role of fire in the regeneration and perpetuation of these pines is well known, it makes sense to use fire to maintain pine ecosystems through forest management that uses an understory prescribed burn program. Fears of fire escape and a poor knowledge of applying fire correctly to these ecosystems are the result of poor training in the use of prescribed fire, which normally concentrates solely on post-harvest slash sites; this has prevented extensive use of understory prescribed burning in the past. However, research in Canada, principally using the Canadian Forest Fire Behavior Prediction (FBP) System coupled with the Canadian Forest Fire Weather Index (FWI) System, allows forest managers to develop burning prescriptions that are safe and economical while meeting objectives for seedbed preparation, natural seeding and control of competing vegetation. Key words: crown scorching, eastern white pine, fire, natural regeneration, red pine, seedbed preparation, understory prescribed burning, vegetation control.

The Canadian Forest Fire Danger Rating System: An Overview

Forest fire danger rating research in Canada was initiated by the federal government in 1925. Five different fire danger rating systems have been developed since that time, each with increasing universal applicability across Canada. The approach has been to build on previous danger rating systems in an evolutionary fashion and to use field experiments and empirical analysis extensively. The current system, the Canadian Forest Fire Danger Rating System (CFFDRS), has been under development by Forestry Canada since 1968. The first major subsystem of the CFFDRS, the Canadian Forest Fire Weather Index (FWI) System, provides numerical ratings of relative fire potential based solely on weather observations, and has been in use throughout Canada since 1970. The second major subsystem, the Canadian Forest Fire Behavior Prediction (FBP) System, accounts for variability in fire behavior among fuel types (predicting rate of spread, fuel consumption, and frontal fire intensity), was issued in interim form in 1984 with final production scheduled for 1990. A third major CFFDRS subsystem, the Canadian Forest Fire Occurrence Prediction (FOP) System, is currectly being formulated. This paper briefly outline the history and philosophy of fire danger rating research in Canada discussing in detail the structure of the current CFFDRS and its application and use by fire management agencies throughout Canada. Key words: fire danger, fire behavior, fire occurrence prediction, fuel moisture, fire danger rating system, fire management.

Canadian Forest Fire Danger Rating System: An Overview

Forest fire danger rating research in Canada was initiated by the federal government in 1925. Five different fire danger rating systems have been developed since that time, each with increasing universal applicability across Canada. The approach has been to build on previous danger rating systems in an evolutionary fashion and to use field experiments and empirical analysis extensively. The current system, the Canadian Forest Fire Danger Rating System (CFFDRS), has been under development by Forestry Canada since 1968. The first major subsystem of the CFFDRS, the Canadian Forest Fire Weather Index (FWI) System, provides numerical ratings of relative fire potential based solely on weather observations, and has been in use throughout Canada since 1970. The second major subsystem, the Canadian Forest Fire Behavior Prediction (FBP) System, accounts for variability in fire behavior among fuel types (predicting rate of spread, fuel consumption, and frontal fire intensity), was issued in interim form in 1984 with final production scheduled for 1990. A third major CFFDRS subsystem, the Canadian Forest Fire Occurrence Prediction (FOP) System, is currently being formulated. This paper briefly outlines the history and philosophy of fire danger rating research in Canada discussing in detail the structure of the current CFFDRS and its application and use by fire management agencies throughout Canada. Key words: fire danger, fire behavior, fire occurrence prediction, fuel moisture, fire danger rating system, fire management.