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International Journal of Wildland Fire International Journal of Wildland Fire Society
Journal of the International Association of Wildland Fire
RESEARCH ARTICLE

Experimental investigation of fire propagation in single live shrubs

Jing Li A D , Shankar Mahalingam B and David R. Weise C
+ Author Affiliations
- Author Affiliations

A Department of Fire Science and Professional Studies, University of New Haven, West Haven, CT 06516, USA.

B Department of Mechanical and Aerospace Engineering, University of Alabama in Huntsville, Huntsville, AL 35899, USA.

C US Department of Agriculture, Forest Service, Pacific Southwest Research Station, Riverside, CA 92507, USA.

D Corresponding author. Email: jli@newhaven.edu

International Journal of Wildland Fire 26(1) 58-70 https://doi.org/10.1071/WF16042
Submitted: 15 March 2016  Accepted: 25 October 2016   Published: 19 December 2016

Abstract

This work focuses broadly on individual, live shrubs and, more specifically, it examines bulk density in chaparral and its combined effects with wind and ignition location on the resulting fire behaviour. Empirical functions to predict bulk density as a function of height for 4-year-old chaparral were developed for two typical species of shrub fuels in southern California, USA, namely chamise (Adenostoma fasciculatum Hook & Arn.) and manzanita (Arctostaphylos spp. Adans.). Fuel beds of chamise foliage and small-diameter branches were burned in an open-topped wind tunnel. Three levels of bulk density, two ignition locations and two wind speeds were examined, focusing on overall fire behaviour. Mean maximum mass loss rate, elapsed time at which maximum mass loss rate occurred, flame height, flame angle, peak gas temperature and its peak change rate were measured. The mean maximum mass loss rate was not significantly affected by wind speed, ignition location, bulk density or moisture content. Both wind speed and ignition location significantly affected the time that maximum mass loss rate occurred. Only wind speed affected flame height and flame angle. The peak gas temperature within the shrub burning area was found to be mostly affected by the bulk density.

Additional keywords: bulk density, chamise, fire behaviour, live fuel, manzanita, southern California, wildland fire.


References

Agostinelli C, Lund U (2013) R package ‘circular’: circular statistics (version 0.4–7). Available at https://r-forge.r-project.org/projects/circular/ [Verified 8 November 2016]

Albini FA, Anderson EB (1982) Predicting fire behavior in US Mediterranean ecosystems. In ‘Proceedings of the international symposium on dynamics and management of Mediterranean-type ecosystems’, 22–26 June 1981, San Diego, CA. (Eds CE Conrad, WC Oechel) USDA Forest Service, Pacific Southwest Forest and Range Experiment Station, General Technical Report PSW-58, pp. 483–489. (Berkeley, CA) Available at http://www.treesearch.fs.fed.us/pubs/45222 [Verified 8 November 2016]

Alexander ME, Cruz MG (2012) Interdependencies between flame length and fireline intensity in predicting crown fire initiation and crown scorch height. International Journal of Wildland Fire 21, 95–113.
Interdependencies between flame length and fireline intensity in predicting crown fire initiation and crown scorch height.Crossref | GoogleScholarGoogle Scholar |

Alexander ME, Stefner CN, Mason JA, Stocks BJ, Hartley GR, Maffey ME, Wotton BM, Taylor SW, Lavoie N, Dalrymple GN (2004) Characterizing the jack pine–black spruce fuel complex of the International Crown Fire Modelling Experiment (ICFME). Natural Resources Canada, Canadian Forest Service, Northern Forestry Centre, Information Report NOR-X-393. (Edmonton, AB) Available at http://cfs.nrcan.gc.ca/pubwarehouse/pdfs/24913.pdf [Verified 8 November 2016]

Anderson WR, Cruz MG, Fernandes PM, McCaw L, Vega JA, Bradstock RA, Fogarty L, Gould J, McCarthy G, Marsden-Smedley JB, Matthews S, Mattingley G, Pearce HG, van Wilgen BW (2015) A generic, empirical-based model for predicting rate of fire spread in shrublands. International Journal of Wildland Fire 24, 443–460.
A generic, empirical-based model for predicting rate of fire spread in shrublands.Crossref | GoogleScholarGoogle Scholar |

Brown JK (1981) Bulk densities of non-uniform surface fuels and their application to fire modeling. Forest Science 27, 667–683.

Bruner AD, Klebenow DA (1979) Predicting success of prescribed fires in pinyon–juniper woodlands in Nevada. USDA Forest Service, Intermountain Forest and Range Experiment Station, Research Paper INT-219. (Ogden, UT) Available at http://www.treesearch.fs.fed.us/pubs/33439 [Verified 8 November 2016]

Burrows N, Ward B, Robinson A (1991) Fire behaviour in spinifex fuels on the Gibson Desert Nature Reserve, Western Australia Journal of Arid Environments 20, 189–204.

Chambers JM, Hastie TJ (1992) Linear models. In ‘Statistical models in S’. (Eds JM Chambers and TJ Hastie) pp. 95–144. (Wadsworth & Brooks/Cole: Pacific Grove, CA).

Chambers JM, Freeny AE, Heiberger RM (1992) Analysis of variance; designed experiments. In ‘Statistical models in S’. (Eds JM Chambers, TJ Hastie) pp. 145–103. (Wadsworth & Brooks/Cole: Pacific Grove, CA).

Cohen J, Bradshaw B (1986) Fire behavior modeling – a decision tool. In ‘Proceedings of symposium on prescribed burning in the Midwest: state-of-the-art’, 3–6 March 1986, Stevens Point, WI. (University of Wisconsin: Stevens Point, WI) Available at http://www.treesearch.fs.fed.us/pubs/47678 [Verified 8 November 2016]

Cole WJ, Dennis MH, Fletcher TH, Weise DR (2011) The effects of wind on the flame characteristics of individual leaves. International Journal of Wildland Fire 20, 657–667.
The effects of wind on the flame characteristics of individual leaves.Crossref | GoogleScholarGoogle Scholar |

Countryman CM, Dean WA (1979) Measuring moisture content in living chaparral: a field user’s manual. USDA Forest Service, Pacific Southwest Research Station, General Technical Report PSW-036. (Berkeley, CA) Available at http://www.treesearch.fs.fed.us/pubs/24092 [Verified 8 November 2016]

Countryman CM, Philpot CW (1970) Physical characteristics of chamise as a wildland fuel. USDA Forest Service, Pacific Southwest Forest and Range Experiment Station, Research Paper PSW-66. (Berkeley, CA) Available at http://www.treesearch.fs.fed.us/pubs/28638 [Verified 8 November 2016]

Cruz MG, McCaw WL, Anderson WR, Gould JS (2013) Fire behaviour modelling in semi-arid mallee-heath shrublands of southern Australia. Environmental Modelling & Software 40, 21–34.
Fire behaviour modelling in semi-arid mallee-heath shrublands of southern Australia.Crossref | GoogleScholarGoogle Scholar |

Dahale A, Ferguson S, Shotorban B, Mahalingam S (2013) Effects of distribution of bulk density and moisture content on shrub fires. International Journal of Wildland Fire 22, 625–641.
Effects of distribution of bulk density and moisture content on shrub fires.Crossref | GoogleScholarGoogle Scholar |

Finney MA, Cohen JD, Grenfell IC, Yedinak KM (2010) An examination of fire spread thresholds in discontinuous fuel beds. International Journal of Wildland Fire 19, 163–170.
An examination of fire spread thresholds in discontinuous fuel beds.Crossref | GoogleScholarGoogle Scholar |

Finney MA, Cohen JD, McAllister SS, Jolly WM (2013) On the need for a theory of wildland fire spread. International Journal of Wildland Fire 22, 25–36.
On the need for a theory of wildland fire spread.Crossref | GoogleScholarGoogle Scholar |

Fisher NI, Lee AJ (1992) Regression models for an angular response. Biometrics 48, 665–677.
Regression models for an angular response.Crossref | GoogleScholarGoogle Scholar |

Frandsen WH (1983) Modeling big sagebrush as a fuel. Journal of Range Management 36, 596–600.
Modeling big sagebrush as a fuel.Crossref | GoogleScholarGoogle Scholar |

Hastie T, Tibshirani R (1990) ‘Generalized additive models.’ (Chapman and Hall/CRC: New York)

Hierro J, Branch L, Villarreal D, Clark K (2000) Predictive equations for biomass and fuel characteristics of Argentine shrubs. Journal of Range Management 53, 617–621.
Predictive equations for biomass and fuel characteristics of Argentine shrubs.Crossref | GoogleScholarGoogle Scholar |

Hosseini S, Shrivastava M, Qi L, Weise DR, Cocker DR, Miller JW, Jung HS (2014) Effect of low-density polyethylene on smoke emissions from burning of simulated debris piles. Journal of the Air & Waste Management Association 64, 690–703.
Effect of low-density polyethylene on smoke emissions from burning of simulated debris piles.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC2cXovVGrsrw%3D&md5=516cb1155cfc802d4b0329092669f602CAS |

Hukseflux Thermal Sensors (2010) RC01 Radiation/Convection (Radcon) Heat Flux Sensor RC01 manual v1004. (Hukseflux B.V.: Delft, Netherlands)

Keeley JE (2000) Chaparral. In ‘North American terrestrial vegetation’, 2nd edn. (Eds MG Barbour, WD Billings) pp. 203–253. (Cambridge University Press: New York)

Li J (2011) Experimental investigation of bulk density and its role in fire behavior in live shrub fuels. MSc thesis, University of California, Riverside, CA.

Li J, Mahalingam S, Weise DR (2016) Chaparral shrub bulk density and fire behavior. USDA Forest Service Research Data Archive RDS-2016-0031. (Fort Collins, CO)10.2737/RDS-2016-0031

Lozano JS (2011) An investigation of surface and crown fire dynamics in shrub fuels. PhD thesis, University of California, Riverside, CA.

Marino E, Dupuy J-L, Pimont F, Guijarro M, Hernando C, Linn R (2012) Fuel bulk density and fuel moisture content effects on fire rate of spread: a comparison between FIRETEC model predictions and experimental results in shrub fuels. Journal of Fire Sciences 30, 277–299.
Fuel bulk density and fuel moisture content effects on fire rate of spread: a comparison between FIRETEC model predictions and experimental results in shrub fuels.Crossref | GoogleScholarGoogle Scholar |

Martin RE, Cushwa CT, Miller RL (1969) Fire as a physical factor in wildland management. In ‘Proceedings of the 9th Tall Timbers fire ecology conference’ Tallahassee, FL (Ed. EV Komarek, Sr). pp. 271–288. (Tall Timbers Research Station: Tallahassee, FL) Available at http://talltimbers.org/wp-content/uploads/2014/03/Martinetal1969_op.pdf [Verified 8 November 2016]

Martins Fernandes PA (2001) Fire spread prediction in shrub fuels in Portugal. Forest Ecology and Management 144, 67–74.
Fire spread prediction in shrub fuels in Portugal.Crossref | GoogleScholarGoogle Scholar |

Mason RL, Gunst RF, Hess JL (1989) ‘Statistical design and analysis of experiments (with applications to engineering and science).’ (Wiley: New York)

McCaw WL (1997) Predicting fire spread in Western Australian mallee–heath shrubland. PhD thesis, Australian Defence Force Academy, University of New South Wales, Canberra, ACT.

Papió C, Trabaud L (1991) Comparative study of the aerial structure of five shrubs of Mediterranean shrublands. Forest Science 37, 146–159.

Pearce HG, Anderson WR, Fogarty LG, Todoroki CL, Anderson SAJ (2010) Linear mixed-effects models for estimating biomass and fuel loads in shrublands. Canadian Journal of Forest Research 40, 2015–2026.
Linear mixed-effects models for estimating biomass and fuel loads in shrublands.Crossref | GoogleScholarGoogle Scholar |

Pereira JMC, Sequeira NMS, Carreiras JMB (1995) Structural properties and dimensional relations of some mediterranean shrub fuels. International Journal of Wildland Fire 5, 35–42.
Structural properties and dimensional relations of some mediterranean shrub fuels.Crossref | GoogleScholarGoogle Scholar |

Pinheiro JC, Bates DM (2000) ‘Mixed-effects models in S and S-PLUS.’ (Springer: New York, NY)

Prince DR (2014) Measurement and modeling of fire behavior in leaves and sparse shrubs. PhD thesis, Brigham Young University, Provo, UT.

Rothermel RC (1972) A mathematical model for predicting fire spread in wildland fuels. USDA Forest Service, Intermountain Forest and Range Experiment Station, Research Paper INT-RP-115. (Ogden, UT)

Sala A, Sabaté S, Gracia C, Tenhunen JD (1994) Canopy structure within a Quercus ilex forested watershed: variations due to location, phenological development, and water availability. Trees 8, 254–261.
Canopy structure within a Quercus ilex forested watershed: variations due to location, phenological development, and water availability.Crossref | GoogleScholarGoogle Scholar |

Sando RW, Wick CH (1972) A method of evaluating crown fuel in forest stands. USDA Forest Service, North Central Forest Experiment Station, Research Paper NC-84. (St Paul, MN) Available at http://www.treesearch.fs.fed.us/pubs/10605.[Verified 8 November 2016]

Sullivan AL (2009) Wildland surface fire spread modelling, 1990–2007. 1: Physical and quasi-physical models. International Journal of Wildland Fire 18, 349–368.
Wildland surface fire spread modelling, 1990–2007. 1: Physical and quasi-physical models.Crossref | GoogleScholarGoogle Scholar |

Syphard AD, Radeloff VC, Hawbaker TJ, Stewart SI (2009) Conservation threats due to human-caused increases in fire frequency in Mediterranean-climate ecosystems Conservation Biology 23, 758–769.
Conservation threats due to human-caused increases in fire frequency in Mediterranean-climate ecosystemsCrossref | GoogleScholarGoogle Scholar |

Tachajapong W (2008) Understanding crown fire initiation via experimental and computational modeling. PhD thesis, University of California, Riverside, CA.

Tachajapong W, Lozano J, Mahalingam S, Zhou X, Weise DR (2008) An investigation of crown fuel bulk density effects on the dynamics of crown fire initiation in shrublands. Combustion Science and Technology 180, 593–615.
An investigation of crown fuel bulk density effects on the dynamics of crown fire initiation in shrublands.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1cXhvFWhsbg%3D&md5=780fc70adc16951a35574ec0223b981bCAS |

Tachajapong W, Lozano J, Mahalingam S, Weise DR (2014) Experimental modelling of crown fire initiation in open and closed shrubland systems. International Journal of Wildland Fire 23, 451–462.
Experimental modelling of crown fire initiation in open and closed shrubland systems.Crossref | GoogleScholarGoogle Scholar |

USDA Natural Resources Conservation Service (2016) The PLANTS Database. Available at http://plants.usda.gov [Verified 25 August 2016]

Van Wagner CE (1973) Height of crown scorch in forest fires. Canadian Journal of Forest Research 3, 373–378.
Height of crown scorch in forest fires.Crossref | GoogleScholarGoogle Scholar |

Van Wagner CE (1977) Conditions for the start and spread of crown fire. Canadian Journal of Forest Research 7, 23–34.
Conditions for the start and spread of crown fire.Crossref | GoogleScholarGoogle Scholar |

Van Wilgen B, Higgins K, Bellstedt D (1990) The role of vegetation structure and fuel chemistry in excluding fire from forest patches in the fire-prone fynbos shrublands of South Africa. Journal of Ecology 78, 210–222.
The role of vegetation structure and fuel chemistry in excluding fire from forest patches in the fire-prone fynbos shrublands of South Africa.Crossref | GoogleScholarGoogle Scholar |

Vose JM, Clinton BD, Sullivan NH, Bolstad PV (1995) Vertical leaf area distribution, light transmittance, and application of the Beer–Lambert Law in four mature hardwood stands in the southern Appalachians. Canadian Journal of Forest Research 25, 1036–1043.
Vertical leaf area distribution, light transmittance, and application of the Beer–Lambert Law in four mature hardwood stands in the southern Appalachians.Crossref | GoogleScholarGoogle Scholar |

Weise DR, Wright CS (2013) Wildland fire emissions, carbon and climate: characterizing wildland fuels. Forest Ecology and Management 317, 26–40.
Wildland fire emissions, carbon and climate: characterizing wildland fuels.Crossref | GoogleScholarGoogle Scholar |

Weise DR, Zhou X, Sun L, Mahalingam S (2005) Fire spread in chaparral – ‘go or no go’? International Journal of Wildland Fire 14, 99–106.
Fire spread in chaparral – ‘go or no go’?Crossref | GoogleScholarGoogle Scholar |

Weise DR, Koo E, Zhou X, Mahalingam S (2011) A laboratory-scale comparison of rate of spread model predictions using chaparral fuel beds – preliminary results. In ‘Proceedings of third fire behavior and fuels conference’, 25–29 October, Seattle, WA. (Ed. DD Wade) (International Association of Wildland Fire: Birmingham, AL). Available at http://www.treesearch.fs.fed.us/pubs/38809 [Verified 8 November 2016]

Weise DR, Koo E, Zhou X, Mahalingam S, Morandini F, Balbi J-H (2016) Fire spread in chaparral – a comparison of laboratory data and model predictions in burning live fuels. International Journal of Wildland Fire 25, 980–994.
Fire spread in chaparral – a comparison of laboratory data and model predictions in burning live fuels.Crossref | GoogleScholarGoogle Scholar |

Wood S (2006) ‘Generalized additive models: an introduction with R.’ (Chapman and Hall/CRC: Boca Raton, FL)

Zhou X, Pakdee W, Mahalingam S (2004) Assessment of a flame surface density-based subgrid turbulent combustion model for non-premixed flames of wood pyrolysis gas. Physics of Fluids 16, 3795
Assessment of a flame surface density-based subgrid turbulent combustion model for non-premixed flames of wood pyrolysis gas.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2cXnsVCht70%3D&md5=e041f8071a313d6ffbb31b41871cfbddCAS |

Zhou X, Weise D, Mahalingam S (2005) Experimental measurements and numerical modeling of marginal burning in live chaparral fuel beds. Proceedings of the Combustion Institute 30, 2287–2294.
Experimental measurements and numerical modeling of marginal burning in live chaparral fuel beds.Crossref | GoogleScholarGoogle Scholar |