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Canopy Fuels

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Abstract

Biomass that is 2 m above the ground is considered canopy fuels and this chapter discusses the biophysical aspects of the forest and shrub canopies and then presents how canopy fuels are used to simulate fire behavior to identify the five canopy fuel characteristics that are needed as inputs to the fire models.

A forest of these trees is a spectacle too much for one man to see

David Douglas Scottish Botanist

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References

  • Agee JK (1996) The influence of forest structure on fire behavior. In: Proceedings of the 17th annual forest vegetation management conference, Redding. CA, USA, January 16–18, pp 52–68

    Google Scholar 

  • Alexander ME (1988) Help with making crown fire hazard assessments. In: Fischer W, Arno SF (eds) Protecting people and homes from wildfire in the interior West: proceedings of the symposium and workshop. General Technical Report INT-251. USDA Forest Service, Intermountain Research Station, Ogden, pp 147–153

    Google Scholar 

  • Alexander ME (1998) Crown fire thresholds in exotic pine plantations of Australasia. Ph.D. dissertation, Australian National University. Canberra, Australia

    Google Scholar 

  • Alexander ME, Cruz MG (2013) Are the applications of wildland fire behaviour models getting ahead of their evaluation again? Environ Model Softw 41:65–71. doi:http://dx.doi.org/10.1016/j.envsoft.2012.11.001

    Article  Google Scholar 

  • Alexander ME, Cruz MG (2014) Tables for estimating canopy fuel characteristics from stand variables in four Interior West conifer forest types. Forest Science 60(4)784–794

    Google Scholar 

  • Anderson HE (1982) Aids to determining fuel models for estimating fire behavior. General technical report INT-122, USDA Forest Service Intermountain Research Station, Ogden, Utah, USA, 22 pp

    Google Scholar 

  • Brown JK, Reinhardt E (1991) Estimating and regulating fuel consumption to manage smoke in the Interior West. In: Proceedings of the 11th conference on fire and forest meterology, Missoula, Montana. Society of American Foresters, Bethesda, MD, USA, pp 419–429

    Google Scholar 

  • Call PT, Albini FA (1997) Aerial and surface fuel consumption in crown fires. Int J Wildland Fire 7(3):259–264

    Article  Google Scholar 

  • Cruz MG, Alexander ME (2010) Assessing crown fire potential in coniferous forests of western North America: a critique of current approaches and recent simulation studies. Int J Wildland Fire 19(4):377–398. doi:http://dx.doi.org/10.1071/WF08132

    Article  Google Scholar 

  • Cruz MG, Alexander ME, Wakimoto RH (2003) Assessing canopy fuel stratum characteristics in crown fire prone fuel types of western North America. Int J Wildland Fire 12:39–50

    Article  Google Scholar 

  • Fahnestock GB (1970) Two keys for appraising forest fire fuels. USDA Forest Service, Pacific Northwest Forest and Range Experiment Station, Res. Bull. PNW-RB-099, Portland, OR, 31 pp

    Google Scholar 

  • Finney MA (1998) FARSITE: Fire Area Simulator—model development and evaluation. Research Paper RMRS-RP-4, United States Department of Agriculture, Forest Service Rocky Mountain Research Station, Fort Collins, CO, USA, 47 pp

    Google Scholar 

  • Forestry Canada Fire Danger Group FCFDG (1992) Development and structure of the Canadian Forest Fire Behavior Prediction System. Information Report ST-X-3, Forestry Canada, Science and Sustainable Development Directorate, Minister of Supply and Services Ottawa, Ontario, 62 pp

    Google Scholar 

  • Keane RE, Reinhardt ED, Scott J, Gray K, Reardon JJ (2005) Estimating forest canopy bulk density using six indirect methods. Can J For Res 35:724–739

    Article  Google Scholar 

  • Keane RE, Frescino TL, Reeves MC, Long J (2006) Mapping wildland fuels across large regions for the LANDFIRE prototype project. In: Rollins MG, Frame C (eds) The LANDFIRE prototype project: nationally consistent and locally relevant geospatial data for wildland fire management. USDA Forest Service Rocky Mountain Research Station, pp 367–396

    Google Scholar 

  • Keane R, Gray K, Bacciu V, Leirfallom S (2012a) Spatial scaling of wildland fuels for six forest and rangeland ecosystems of the northern Rocky Mountains, USA. Landsc Ecol 27(8):1213–1234. doi:10.1007/s10980-012-9773-9

    Google Scholar 

  • Keane RE, Gray K, Bacciu V (2012b) Spatial variability of wildland fuel characteristics in northern Rocky Mountain ecosystems. Research Paper RMRS-RP-98, USDA Forest Service Rocky Mountain Research Station, Fort Collins, Colorado, USA, 58 pp

    Google Scholar 

  • Linn RR (1997) A transport model for prediction of wildfire behavior. Ph.D. dissertation, New Mexico State University, Las Cruces, New Mexico, USA

    Google Scholar 

  • Nabel JEMS, Kirchner JW, Zurbriggen N, Kienast F, Lischke H (2014) Extrapolation methods for climate time series revisited—spatial correlations in climatic fluctuations influence simulated tree species abundance and migration. Ecol Complex. doi:http://dx.doi.org/10.1016/j.ecocom.2014.02.006

  • Nadkarni NM (1994) Diversity of species and interactions in the upper tree canopy of forest ecosystems. Am Zool 34(1):70–78. doi:10.1093/icb/34.1.70

    Google Scholar 

  • Parsons RA (2006) Fuel 3D: a spatially explicit fractal fuel distribution model. In: Andrews PL, Butler BW (eds) Fuels management—how to measure success, Portland, OR USA. USDA Forest Service, Rocky Mountain Research Station, Proceedings RMRS-P-41. Fort Collins, CO, pp 51–66

    Google Scholar 

  • Parsons RA, Mell WE, McCauley P (2010) Linking 3D spatial models of fuels and fire: effects of spatial heterogeneity on fire behavior. Ecol Model 222(3):679–691

    Article  Google Scholar 

  • Reeves MC, Kost JR, Ryan KC (2006) Fuels products of the LANDFIRE project. In: Andrews PL, Butler BW (eds) Fuels management—how to measure success, Portland OR. USDA Forest Service Rocky Mountain Research Station, Proceedings RMRS-P-41 Fort Collins, CO, pp 239–249

    Google Scholar 

  • Reeves MC, Ryan KC, Rollins MC, Thompson TG (2009) Spatial fuel data products of the LANDFIRE project. Intl J Wildland Fire 18:250–267

    Article  Google Scholar 

  • Reinhardt E, Lutes D, Scott J (2006a) FuelCalc: a method for estimating fuel characteristics. In: Andrews PL, Butler BW (eds) Fuels management—how to measure success, Portland, OR. US Department of Agriculture, Forest Service, Rocky Mountain Research Station, Proceedings RMRS-P-41, Fort Collins, CO, pp 273–287

    Google Scholar 

  • Reinhardt E, Scott J, Gray K, Keane R (2006b) Estimating canopy fuel characteristics in five conifer stands in the western United States using tree and stand measurements. Can J For Res-Rev Can Rech For 36(11):2803–2814. doi:10.1139/X06-157

    Google Scholar 

  • Rothermel RC (1972) A mathematical model for predicting fire spread in wildland fuels. Utah Research Paper INT-115, United States Department of Agriculture, Forest Service, Intermountain Forest and Range Experiment Station, Ogden, 88 pp

    Google Scholar 

  • Rothermel RC (1991) Predicting behavior and size of crown fires in the Northern Rocky Mountains. Research Paper INT-438, US Department of Agriculture, Forest Service Intermountain Forest and Range Experiment Station, Ogden, Utah, USA 46 pp

    Google Scholar 

  • Rothermel RC (1993) Some fire behavior modeling concepts for fire management systems. In: Proceedings of the 12th Annual Conference on Fire and Forest Meteorology, Jekyll Island, GA, Society of American Foresters, Bethesda, MD USA, pp 164–171

    Google Scholar 

  • Sando RW, Wick CH (1972) A method of evaluating crown fuels in forest stands. Research Paper NC-84, United States Department of Agriculture, Forest Service North Central Forest Experiment Station, Saint Paul, Minnesota, USA, 10 pp

    Google Scholar 

  • Scott JH, Reinhardt ED (2001) Assessing crown fire potential by linking models of surface and crown fire behavior. Research Paper RMRS-RP-29, USDA Forest Service Rocky Mountain Research Station, Fort Collins, CO, 59 pp

    Google Scholar 

  • Scott JH, Reinhardt ED (2002) Estimating canopy fuels in conifer forests. Fire Manage Today 62(4):45–50

    Google Scholar 

  • Scott JH, Reinhardt ED (2005) Stereo photo guide for estimating canopy fuel characteristics in conifer stands. General Technical Report RMRS-GTR-145, USDA Forest Service Rocky Mountain Research Station, Fort Collins, CO, 47 pp

    Google Scholar 

  • Stocks BJ, Alexander ME, Wotton BM, Stefner CN, Flannigan MD, Taylor SW, Lavoie N, Mason JA, Hartley GR, Maffey ME, Dalrymple GN, Blake TW, Cruz MG, Lanoville RA (2004) Crown fire behaviour in a northern jack pine-black spruce forest. Can J For Res 34(8):1548–1560. doi:10.1139/x04-054

    Article  Google Scholar 

  • van Wagner CE (1977) Conditions for the start and spread of crown fire. Can J For Res 7:23–34

    Article  Google Scholar 

  • van Wagner CEV (1993) Prediction of crown fire behavior in two stands of jack pine. Can J For Res 23:442–449

    Article  Google Scholar 

  • Ward DE (1995) Smoke emissions from biomass burning. In: Hassol SJ, Katzenberger J (eds) Elements of change. Changes in global vegetation patterns and their relationship to human activity. Aspen Global Change Institute, Aspen, pp 107–111

    Google Scholar 

  • Waring RH, Running SW (1998) Forest ecosystems: analysis at multiple scales, 2nd edn. Academic, San Diego

    Google Scholar 

  • Zhang T, Lichstein JW, Birdsey RA (2014) Spatial and temporal heterogeneity in the dynamics of eastern US forests: implications for developing broad-scale forest dynamics models. Ecol Model 279:89–99. doi:http://dx.doi.org/10.1016/j.ecolmodel.2014.02.011

    Article  Google Scholar 

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Correspondence to Robert E. Keane .

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Keane, R. (2015). Canopy Fuels. In: Wildland Fuel Fundamentals and Applications. Springer, Cham. https://doi.org/10.1007/978-3-319-09015-3_4

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