PARC FIRE BEHAVIOR POTENTIAL IN CENTRAL SASKATCHEWAN UNDER PREDICTED CLIMATE CHANGE SUMMARY DOCUMENT. No

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1 FIRE BEHAVIOR POTENTIAL IN CENTRAL SASKATCHEWAN UNDER PREDICTED CLIMATE CHANGE PARC PRAIRIE ADAPTATION RESEARCH COLLABORATIVE SUMMARY DOCUMENT Marc-André Parisien, Canadian Forest Service Victor Kafka, Parks Canada Nadele Flynn, University of Alberta Kelvin Hirsch, Canadian Forest Service Bernie Todd, Canadian Forest Service Mike Flannigan, Canadian Forest Service No

2 PARC PRAIRIE ADAPTATION RESEARCH COLLABORATIVE Acknowledgments This study was made possible wi e financial support of e Prairie Adaptation Research Collaborative. Daniel Caya and René Laprise of e Canadian Regional Climate Model team at l Université du Québec à Montréal and e Ouranos Consortium made e CRCM-II data available to e CFS fire research group. We ank Mike Wotton, Kimberly Logan, Erin Bosch, of e CFS Great Lakes Forestry Centre, as well as Peter Englefield, Kerry Anderson, and Suzanne Lavoie of e CFS Norern Forestry Centre, for eir assistance at various stages of e project. Saskatchewan Environment is also gratefully acknowledged for providing data and support. Oer publications in e PARC Summary Series: Climate Change Impact on e Island Forests of e Great Plains and e Implications for Nature Conservation Policy Aridity on e Canadian Plains: Future Trends and Past Variability Socio-Economic Vulnerability of Prairie Communities to Climate Change Political Climate Modeling: Predicting sociopolitical responses to climate change in e Prairie Provinces Assessment of Climate Change on e Agricultural Resource of e Canadain Prairies General for PARC: info@parc.uregina.ca. Telephone: (306) Fax: (306) Website: 2

3 SYNOPSIS The effect of climate change on fire behavior may become a critical issue for resource management in e Canadian boreal forest. This study applies a procedure to assess e effects of climate change on fire behavior 2 potential in central Saskatchewan (135,000 km ), an area at characterizes e transition from mixedwoods to pure coniferous forest types. Head fire intensity (HFI), a measure of e fire s energy output, was used to quantify fire behavior potential because it can be related to fire behavior characteristics, suppression effectiveness, and fire effects. Percentile HFI maps were created wi fuels data and fire weaer from ree simulated climate scenarios produced by e Canadian Regional Climate Model (CRCM). These scenarios represent base (1 CO 2), double (2 CO 2), and triple (3 CO 2) levels of carbon dioxide in e atmosphere. Our results show a marked increase in fire behavior potential in a 2 CO2 environment, whereas little change was observed from 2 CO2to 3 CO 2. According to our results, e number of days at could support extreme fire behavior potential may quadruple in a 2 CO2 climate. Furermore, fires are also expected to be more intense, on average. An increase in fire intensity would likely be translated into greater fire spread and more erratic fire behavior, leading to increased area burned. However, a changing climate does not necessarily entail a ubiquitous or uniform increase in fire potential roughout an area. Indeed, we found at ere was significant spatial variation in e effects of climate change on HFI values, due to e interaction and spatial variation between fuel types and weaer patterns. Role of fire in e western boreal forest The boreal forest covers 35% of Canada s landmass and stretches from coast to coast. Historically, fire has been a dominant disturbance in e boreal forest; and as such, several species have co-evolved wi it. Fire is needed for maintenance of boreal forest ecosystems, but it also has negative socioeconomic consequences and safety implications. Sound fire management aims to minimize ese negative impacts. To is end, a orough understanding of e factors driving fire behavior topography, forest fuels (i.e., vegetation), and weaer is crucial. Changing weaer patterns can dramatically alter wildfire activity. In fact, climate models used to predict fire danger have shown at for future climate conditions Saskatchewan might exhibit one of e largest increases in fire danger in Nor America (Flannigan et al. 1998), as well as a potential lengening of e fire season (Wotton and Flannigan 1993). A changing climate could erefore have far-reaching implications on sustainable forest management policies and practices in regions at are already experiencing high recurrence of fire. In Saskatchewan, for example, fires consumed almost 800,000 ha of forest in e 2000 fire season alone an area larger at Prince Edward Island in spite of high fire suppression expenditures and some of e most advanced technology available. In fact, analysis has shown at regardless of e level of protection, a small percentage (i.e., 2-3%) of ignitions are likely to continue to escape initial attack (McAlpine and Hirsch 1999), due to multiple fire situations, remote ignitions, and weaer conditions under which fires become uncontrollable. In Canada, such escaped fires generally account for over 95% of e total area burned by all wildfires (Weber and Stocks 1998). Given current and possible future increases in weaer conditions conducive to fire, resource and fire managers need tools to assess fire potential on e landscape and to assist em in strategic planning and risk mitigation. Linking climate models wi fire behavior prediction Recently, models predicting future climatic conditions have been combined to fire danger rating systems in order to understand how a changing climate may affect fire regimes. Tools such as e Canadian Global Climate Model (CGCM) are coarse-scale climate models at simulate e effects of changes in atmospheric CO2 concentrations on future weaer patterns at e continental scale. However, finer spatial resolution models are necessary in order to link weaer patterns to fire danger, because features at influence fire behaviour, such as topography and vegetation, can vary substantially over short distances. The CRCM is such a model specific to Canadian landscapes. Wotton et al. (1998) used weaer data generated from is model to calculate a weaerbased fire danger index, e Canadian Forest Fire Weaer Index (FWI) System, which provides relative measures of fire danger. This modeling exercise showed at e boreal forest of Alberta, Saskatchewan, and Manitoba could be subject to a 50% increase in seasonal fire severity under a doubling of e current CO2 levels. This study builds on e work of Wotton et al. (1998), as we also assessed fire danger in central Saskatchewan wi CRCM, but we used more recent simulations, included e 3 CO2 scenario in e analysis, and incorporated available forest fuels to derive an absolute measure of fire behaviour For each of ese climate scenarios (described below), e CRCM-generated weaer was used as input variables into 3

4 e Canadian Forest Fire Behavior Prediction (FBP) System. Head Fire Intensity (HFI), a variable predicted by e FBP System, is a quantitative measurement of fire potential at has direct fire management relevance. The objectives of is report, which presents e key findings of Kafka et al. (2001), were to 1) analyze fire behavior potential changes in central Saskatchewan wi changes in atmospheric CO2 and 2) discuss eir implications for fire and forest management. The boreal mixedwood of central Saskatchewan The study area (Fig. 1) covers 13,450,150 ha of central Saskatchewan and is predominantly situated in e boreal forest Mixedwood region, whereas e norern part lies in e Norern Coniferous and Upper Churchill regions (Rowe 1972). The climate is one of long cold winters and short cool summers. The mean summer temperature is 16.9 C for e mon of July and annual average precipitation is 400 to 500 mm, peaking during e summer mons. The study area receives approximately 2500 hours of sunshine per year, e highest in Canada. Figure 1. Study area (shaded area) in Saskatchewan, Canada. The study area is flat to gently rolling or undulating terrain, wi an average elevation of 400 m, increasing from noreast to souwest. The topography wiin e Mixedwood region consists mainly of rolling morainic deposits on uplands and smooer glaciolacustrine deposits on lowlands. In contrast, e Norern Coniferous and Upper Churchill regions are wiin e Precambrian Shield and are an assemblage of rocky ridges, sandy plains, poorly drained depressions, and numerous lakes. In e Mixedwood region, white spruce ( Picea glauca (Moench) Voss) and balsam fir ( Abies balsamea (L.) Mill.) are e most common upland coniferous species wi black spruce ( Picea mariana (Mill.) BSP) in e lowlands. Trembling aspen ( Populus tremuloides Michx.) and balsam poplar ( Populus balsamifera L.) are e dominant deciduous species. In e Norern Coniferous and Upper Churchill regions, black spruce is e dominant species wi jack pine ( Pinus banksiana Lamb.) on uplands and sandy plains, and tamarack ( Larix laricina (Du Roi) K. Koch) on lowlands. Saskatchewan has a very active fire environment. Between 1945 and 2000, e average area burned was 270,000 ha/yr. Large fires have occurred roughout e study area, but some areas have historically experienced more area burned an oers, generally because of e distribution of more flammable fuels (Parisien et al. 2004). The study area is located in e full response zone, which means at most fires undergo aggressive initial attack, and ere is maximum fire suppression effort. Towns and infrastructure are largely concentrated in e souern part of e study area, and is is erefore where most human-caused ignitions occur. Forestry is practiced roughout e sector, whereas agriculture is generally confined to e souern portion (aspen parkland) and in e more suitable sites to e nor. Mining and tourism are also common in some areas. The Canadian Forest Fire Danger Rating System The Canadian Forest Fire Danger Rating System (CFFDRS) consists of two main subsystems: e Canadian Forest Fire Weaer Index (FWI) System (Van Wagner 1987) and e Canadian Forest Fire Behavior Prediction (FBP) System (Forestry Canada Fire Danger Group 1992). The FWI System and e FBP System have been used extensively by operational fire management agencies since e 1970s and 1990s, respectively, to improve prediction of fire danger in Canada. The FWI System assigns a relative rating of fire danger using simple weaer observations to produce ree fuel moisture codes: Fine Fuel Moisture Code (FFMC), Duff Moisture Code (DMC), Drought Code (DC) and ree fire behavior indices: Initial Spread Index (ISI), Buildup Index (BUI), Fire Weaer Index (FWI). The Fire Weaer Index is e index of e FWI System at encompasses e most information because it is derived from all e oer FWI System components. The FBP System uses e ree fuel moisture codes of e FWI System in addition to information on forest fuels, topography, wind speed, and wind direction to provide a quantitative measure of fire behavior. The FBP System uses 16 fuel types based on fire behavior characteristics under specific weaer and fuel conditions (Table 1). The FBP System fuels of our study were mapped at a resolution of 100 m (Fig. 2 on page 7). 4

5 Table 1. The Canadian FBP System fuel types found in e study area and eir main characteristics. Source: Forestry Canada Fire Danger Group (1992). Alough e FBP System requires more data an e FWI System for e user, it has e advantage of providing a direct, quantitative measure of fire behavior potential such as head fire intensity (HFI) (used in is study), rate of spread, and crown fraction burned. The HFI is defined as e rate of energy release per unit time per unit leng of fire front (measured in kilowatts per meter) and is a good measure of fire behavior potential, as it is related to fire Photo 2: Fire wi head fire intensity estimated at 6,500 kw/m. Photo 1: Fire wi head fire intensity estimated at 1,500 kw/m. behavior characteristics, fire effects, and fire suppression effectiveness. In terms of fire suppression success, HFI values can be grouped into ree general categories: at HFI values below 2000 kw/m (Photo 1), initial attack crews can generally contain fires, as ey are slowspreading surface fires, wi only intermittent crowning of individual trees; at HFI values between 2000 and 10,000 kw/m (Photo 2) fires exhibit more crowning, making em difficult to control wi machinery and aircrafts; and 5

6 used to interpret e spatial variation in fire behavior potential (Fig. 2). The Norern Region, an 80 to 100-km wide zone at follows e norern limit of e study area, is characterized mostly by e Boreal Spruce, Mature Jack Pine, and Mixedwood fuel types; e Central Region is mainly composed of large tracts of e Boreal Spruce fuel type; e Souwest Region has a significant Aspen fuel type component; and e Soueast Region, which combines several fuel types, including a large area (e Cumberland Delta) covered by e Grass (O-1) fuel type. Photo 3: Fire wi head fire intensity estimated at greater an 10,000 kw/m. at HFI values greater an 10,000 kw/m (Photo 3), fire behavior becomes extreme wi full-blown crown fires, and direct attack of e fire front is generally impossible (Hirsch et al. 1998). In Canada, HFI varies substantially by fuel type under similar fire weaer conditions. For example, e Leafless Aspen (D-1) fuel type (Photo 4) does not burn as readily Photo 5: Boreal Spruce (C-2) fuel type in e FBP System Climate Scenarios The simulated fire weaer used in is analysis consisted of second-run CRCM outputs generated by Laprise et al. (2003) for ree climate scenarios representing base (1 CO 2), double (2 CO 2) and triple (3 CO 2) atmospheric CO2 concentrations. These scenarios represent past and future atmospheric conditions for e (1 CO 2), (2 CO 2), and (3 CO 2) decades. Weaer for each climate scenario was simulated Photo 4: Leafless Aspen (D-1) fuel type in e FBP System. as e coniferous fuel types and often act as effective fuel breaks. The Boreal Spruce (C-2) fuel type (Photo 5), which covers 37.7% of e study area (Fig. 2), is e most flammable fuel type because it represents well-stocked stands of conifers at have an abundance of ladder fuels, which increases e likelihood of a fire crowning. Anoer coniferous fuel type, Mature Jack or Lodgepole Pine (C-3) (Photo 6) is also highly flammable, but only burns into e tree crowns under extreme conditions, due to e absence of ladder fuels. In e study area, four regions wi distinct fuel type compositions were arbitrarily delineated and were Photo 6: Mature Jack or Lodgepole Pine (C-3) fuel type in e FBP System. 6

7 daily over a period of 10 years; however, we only used e data from May 1st to August 31st, because is period is representative of a typical fire season in Saskatchewan. Spatially, e CRCM produced weaer outputs for 169 points separated by a distance of 45 km arranged in a grid. The noon-hour local standard time weaer variables (temperature, relative humidity, wind speed, and 24-hour precipitation) generated by e CRCM were used as inputs for e FWI System and FBP System. These were combined wi fuel information to generate HFI percentile maps for all ree climate scenarios. Predicting Head Fire Intensity for Climatic Scenarios Percentile HFI values were calculated using a raster grid representing FBP System fuel types, as well as e required fire weaer outputs. A percentile is a measure of relative standing in which a certain proportion (i.e., percentage) of e data lies below e percentile value. Topography was not considered because it did not vary much roughout e study area. Because intense fire behavior does not occur under average conditions we built percentile HFI maps for e 80 and 95 percentiles. This corresponds to e minimum HFI value at can be expected on e landscape, roughout e fire season, 20% (80 percentile) and 5% (95 percentile) of e time. Figure 2. Fire Behavior Prediction (FBP) System fuel types in e study area. 7

8 For each climate scenario, an HFI map was created for e 80 and 95 percentiles. Even ough outputs of bo percentiles were considered for analysis, only e 80 percentile maps are presented. To build ese maps e following steps were undertaken: At each CRCM point, e 80 and 95 percentile Fire Weaer Index values were selected for each of e scenarios. The FFMC, BUI, and wind speed associated wi e selected percentile Fire Weaer Index values, along wi dominant wind directions, were obtained and interpolated using an inverse distance weighted function between e CRCM points in e Spatial Fire Management System (sfms). In sfms, e interpolated fire weaer grids were used wi e fuel type coverage to calculate HFI at each pixel. For each climate scenario at e 80 and 95 percentile, changes in e frequency distribution of HFI values were compared aspatially. For interpretation purposes, values of e percentile HFI maps were classified in ree HFI classes based on relevance to fire suppression effectiveness: e < 2,000 kw/m class; e 2,000 9,999 kw/m class; and e 10,000 kw/m class. For e ree climate scenarios at e 80 percentile, we examined e spatial distribution of mapped HFI classes as well as absolute and relative change of HFI values from 1 CO2 to a 2 CO 2. In is study, we define absolute change in HFI as e difference in HFI between climate scenarios (2 CO2 1 CO 2), whereas relative change in HFI as e ratio of HFI between e climate scenarios (2 CO 1 CO ). 2 2 Effect of Climate Change on Fire Behavior Potential General and regional distribution of HFI In e 1 CO2 scenario, under 80 percentile conditions, most of e study area had HFI values below 10,000 kw/m. By contrast, ere was a significant shift toward more extreme HFI values in e 2 CO2 and 3 CO2 scenarios (Fig. 3); however, ese scenarios had comparable proportions of eir area greater an 10,000 kw/m. From e 1 CO2to e 2 CO2scenario at e 80 HFI percentile, e proportion of HFI values in e 10,000 kw/m class increased by 21%, whereas in e < 2,000 and 2,000 9,999 kw/m classes, e proportion decreased by 11% and 9%, respectively. A similar trend existed at e 95 percentile but e proportion of change was smaller in magnitude; bo <2,000 and 2,000 9,999 kw/m classes decreased by 3% and 6% while e 10,000 kw/m class e proportion increased by 9%. Interestingly, e 1 CO2 scenario predicted at about half of e study area had HFI values greater an 10,000 kw/m on 5% (95 percentile) of fire season days, whereas in e 2 CO2 scenario, half of e study area had HFI values greater an 10,000 kw/m on 20% (80 percentile) of e days (Fig. 3, text insets). Therefore, from a 1 CO2 to a 2 CO2 climate scenario, e number of days in which half or more of e study area could potentially exhibit extreme fire behavior ( 10,000 kw/m) could increase 4-fold. The weight of evidence in is study suggests at fire behavior potential Figure 3. Frequency distribution of head fire intensity (HFI) values in a 1 CO 2, 2 CO 2, and 3 CO2 scenario for e 80 and e 95 percentile and mean HFI and proportion of area covered by HFI 10,000 kw/m. 8

9 in a 2 CO2environment would yield conditions where direct fire suppression by crews and air tankers would be unsafe or unlikely to be effective. Surprisingly, e proportion of e study area by HFI class from e 2 CO2to e 3 CO2scenario varied only slightly, suggesting little change in fire behavior potential from e middle to e end of is century. In fact, e proportion of area wiin each HFI class between ese two scenarios did not vary by more an 2%. However, similar HFI values between ese two scenarios does not imply at ey have e same fire weaer. A more indep examination of e simulated weaer variables generated in e 1 CO 2, 2 CO 2, and 3 CO2 climate scenarios provides a possible explanation for is plateau in fire behavior potential (Fig. 4). Alough average temperature continues to rise from e 2 CO2 to e 3 CO2 scenario, which should translate into more extreme fire behavior potential, ere is in e 3 CO2 scenario a parallel increase in precipitation and relative humidity, as well as a decrease in wind speed, at counteracts e effect of increasing temperature on fire behavior potential. Temperature ( C) Relative humidity (%) CO2climate scenario at e 80 HFI percentile 2 CO2climate scenario at e 80 HFI percentile 1xCO 2 2xCO 2 3xCO 2 1xCO 2 2xCO 2 3xCO 2 Wind speed (km/h) xCO 2 2xCO 2 3xCO 2 Precipitation (mm) xCO 2 2xCO 2 3xCO 2 3 CO2climate scenario at e 80 HFI percentile Figure 4. Means (dots) and standard deviations (whiskers) for noon-hour temperature, relative humidity, wind speed and 24-hour precipitation for e ree CO2 climate change scenarios calculated from e 169 Canadian Regional Climate Model grid points. Alough e regional distribution of HFI also shows at a general trend toward more extreme HFI values in e 2 CO2 scenario as compared to e 1 CO2 scenario (Fig. 5), ere was marked spatial variation roughout e study area in terms of increases in fire behavior potential. The Norern Region and Central Region showed a substantial increase in fire behavior potential, whereas in most of e Soueast Region and part of e Souwest Region ese changes were not as pronounced. These HFI Head fire intensity (kw/m) Figure 5. Maps of 80 percentile head fire intensity values for e 1 CO 2(top), 2 CO 2(middle), and 3 CO 2(bottom) climate scenarios in central Saskatchewan. maps are useful for direct interpretation of fire behavior potential; however, e extent and pattern of spatial changes in eir percentile HFI values can be furer assessed wi maps of absolute change and maps of relative change. 9

10 Head fire intensity (kw/m) Head fire intensity ratio Figure 6. Map of absolute and relative change in head fire intensity from e 1 CO2 to e 2 CO2 climate scenario in central Saskatchewan. Absolute and relative change of HFI The Central Region of e study area had, by far, e highest absolute increase in fire behavior potential (Fig. 6). This increase, which is substantial and likely translates into significantly more frequent high-intensity wildfires and persistent smoldering fires, was due in part to its abundance of e highly flammable Boreal Spruce fuel type, which is more sensitive to change in fire weaer. Even ough e average absolute increase in HFI in e Central Region was substantial at e 80 percentile, e relative change in HFI in is area was comparatively low in comparison wi e Norern Region. This said, results from e map of absolute change in HFI represent little significant change from a fire management perspective in e Central Region, as most of e region was already above 10,000 kw/m in e 1 CO2 scenario (Fig. 4), and erefore, well beyond e ability to control fire using direct attack. Overall, ere was a significant sou to nor gradient towards increasingly higher relative change in fire behavior potential. The Norern Region had e highest relative change in fire behavior potential wi practically e entire section experiencing at least a doubling in HFI. This was due not only to e possibility of a greater proportional increase in fire weaer severity, as documented by Kafka et al. (2001), but also to e fact at e fire behavior potential of Mature Jack or Lodgepole Pine fuel type, which has a higher height to live crown base, increases sharply when intermittent crowning occurs (HFI values above 2,000 kw/m). This crowning reshold was likely overcome in e 2 CO2 scenario, due to more extreme fire weaer conditions. This makes e Norern Region of e study area particularly sensitive in terms of future increases of fire behavior potential, because ere might be a general change from a fire regime of surface or intermittent fires to one at supports more continuous crown fires. This higher frequency of more extreme fire behavior, along wi e remoteness of e Norern Region, could result in more wildfires escaping initial attack and burning out of e control in a 2 CO2 environment. Conversely, analyses revealed at deciduous stands had a significantly milder response to climate change an oer fuel types, making e Soueast and Souwest Region less susceptible to increased fire reat in e upcoming century. Implications for fire and forest management In central Saskatchewan, fires at escape initial attack usually do so under weaer conditions conducive to high fire behavior potential. Until ere is a change to more 10

11 Figure 7. Large fires ( 1000 ha) in Saskatchewan from 1975 to This period corresponds to e 1 CO climate scenario in central Saskatchewan. 2 moderate burning conditions, ese fires cannot easily be contained using available fire suppression resources. Our research suggests at in is area, 2 CO2 and 3 CO2 environments will produce a higher frequency of days of high to extreme fire weaer conditions, as well as more intense fires on average. An increase in fire intensity would likely be translated into greater fire spread and more erratic fire behavior, leading to increased area burned. However, a changing climate does not necessarily entail a ubiquitous or uniform increase in fire potential roughout an area. Indeed, we found at ere was significant spatial variation in e effects of climate change on HFI values, due to e interaction and spatial variation between fuel types and weaer patterns. Due to e different adaptations of boreal species to fire, changes to e fire regime could possibly result in a change in species composition. For instance, ere could be a norern shift in e limit between e grasslands and souern edge of e boreal forest in Saskatchewan. In any case, it is likely at climate-induced changes in e fire regime will have a greater impact on vegetation an e direct effects of climate itself (Weber and Flannigan 1997). Furermore, larger, more intense fires will inevitably be translated into changes in ecological processes. For example, altered regeneration patterns of vegetation could affect stand level composition. In e face of such change to biological communities, and inevitably forest resources such as merchantable timber, e forestry industry will also have to adapt to climate change. Preliminary results from CGCMs predict a significant increase in area burned in our study area by e end of e 21st century (Flannigan et al. 2004). Our results show at from e 1 CO2 to e 2 CO2 climate scenario, we could expect a 4-fold increase in e number of days in which high intensity fires ( 10,000 kw/m) can occur. Alough we did not attempt to correlate is increase in fire weaer to area burned in e 2 CO2 climate scenario, it is possible to appreciate what such an increase may have on an area by looking at e large historical fires ( 1000 ha) at occurred during e period of e base scenario (Fig. 7). However, despite more frequent and more extreme fire behavior potential, it is possible at more area burned could result in less available fuels for fire spread in e future and us act as a negative feedback at would eventually reduce e size of large fires. In terms of fire management activities, applications for long-term predictions of fire behavior potential at an operational level are numerous: pre-positioning of resources, preparedness planning, prioritization of fire and forest management activities, wildland-urban interface concerns, and fire reat evaluation. Alough many oer factors will undoubtedly influence e interaction between wildfires and e forest, such as land-use patterns, number of ignitions, public attitudes and policies, an increase in fire behavior potential is expected if e fuels and fire suppression remains similar to present and atmospheric CO2 concentrations continue to rise. Solutions created to respond to climate change will likely need to encompass more an just better and more fire suppression. Notwistanding e possibility of reduced emissions, it seems evident at adaptation strategies such as fire-smart communities (Partners in Protection 2003) and fuels management to limit area burned, as described in Hirsch et al. (2001), will need to be not only considered, but acted upon to reduce e impact of increased fire behavior potential on values at risk. 11

12 LITERATURE CITED Flannigan, M.D., Bergeron, Y., Engelmark, O., and Wotton, B.M Future wildfire in circumboreal forests in relation to global warming. J. Veg. Sci. 9: Flannigan, M.D., Logan, K.A., Amiro, B.D., Skinner, W.R., and Stocks, B.J Future area burned in Canada. Clim. Change. In press. Forestry Canada Fire Danger Group Development and structure of e Canadian Forest Fire Behavior Prediction System. Inf. Rep. ST-X-3, For. Can., Ottawa, ON. Hirsch, K.G., Kafka, V., Tymstra, C., McAlpine, R., Hawkes, B., Stegehuis, H., Quintilio, S., Gauier, S., and Peck, K Fire-smart forest management: a pragmatic approach to sustainable forest management in fire-dominated ecosystems. For. Chron. 77: 1-7. Hirsch, K.G., Corey, P.N., and Martell, D.L Using expert judgment to model initial attack fire crew effectiveness. For. Sci. 44: Kafka, V., Parisien, M.A., Hirsch, K., Flannigan, M., and Todd, B Climate change in e Prairie provinces: assessing landscape fire behavior potential and evaluating fuel treatment as an adaptive strategy. Prairie Adaptation Research Collaborative (PARC) Report. Regina, SK. Laprise, R., Caya, D., Frigon, A., and Paquin, D Current and perturbed climate as simulated by e secondgeneration Canadian Regional Climate Model (CRCM-II) over norwestern Nor America. Clim. Dyn. 21: McAlpine, R.S., and Hirsch, K.G An overview of LEOPARDS: The level of protection analysis system. For. Chron. 75: Parisien, M.A., Hirsch, K.G., Lavoie, S.G., Todd, J.B., and Kafka, V.G Saskatchewan fire regime analysis. Nat. Resour. Can., Can. For. Serv., Nor. For. Cent., Edmonton, AB, Inf. Rep. NOR-X-394. Partners in Protection FireSmart: protecting your community from wildfire. Second Edition. Nat. Resour. Can., Can. For. Serv., Nor. For. Cent., Edmonton, AB, Partners in Protection, Edmonton, AB. Rowe, J.S Forest regions of Canada. Dep. Environ., Can. For. Serv., Ottawa, ON, Publ Van Wagner, C.E Development and structure of e Canadian Forest Fire Weaer Index System. For. Tech. Rep. 35, Can. For. Serv., Ottawa, ON. Weber, M.G., and Flannigan, M.D Canadian boreal forest ecosystem structure and function in a changing climate: Impacts on fire regimes. Environ. Rev. 5: Weber, M.G., and Stocks, B.J Forest fires and sustainability in e boreal forests of Canada. Ambio 27: Wotton, B.M., and Flannigan, M.D Leng of e fire season in a changing climate. For. Chron. 69: Wotton, B.M., Stocks, B.J., Flannigan, M.D., Laprise, R., and Blanchet, J-P Estimating future 2 CO2 fire climates in e boreal forest of Canada using a regional climate model. Pages (vol. II) in e Proceedings of e 3rd International Conference on Forest Fire Research and 14 Conference on Fire and Forest Meteorology, Nov Luso, Portugal. Photo credits Bo covers: W.J. de Groot, Coffee fire, Saskatchewan, 1980 Photo 3: International Crown Fire Modeling Experiment All oer photos: K.G. Hirsch