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

The wildland fuel cell concept: an approach to characterize fine-scale variation in fuels and fire in frequently burned longleaf pine forests

J. Kevin Hiers A , Joseph J. O’Brien B E , R. J. Mitchell A , John M. Grego C and E. Louise Loudermilk D
+ Author Affiliations
- Author Affiliations

A Joseph W. Jones Ecological Research Center at Ichauway, Route 2, Box 2324, Newton, GA 39870, USA.

B USDA Forest Service, Center for Forest Disturbance Science, 320 Green Street, Athens, GA 30602, USA.

C Department of Statistics, University of South Carolina, Columbia, SC 29208, USA.

D School of Natural Resources and Environment, University of Florida, Gainesville, FL, USA.

E Corresponding author. Email: jjobrien@fs.fed.us

International Journal of Wildland Fire 18(3) 315-325 https://doi.org/10.1071/WF08084
Submitted: 29 May 2007  Accepted: 1 July 2008   Published: 28 May 2009

Abstract

In ecosystems with frequent surface fire regimes, fire and fuel heterogeneity has been largely overlooked owing to the lack of unburned patches and the difficulty in measuring fire behavior at fine scales (0.1–10 m). The diverse vegetation in these ecosystems varies at these fine scales. This diversity could be driven by the influences of local interactions among patches of understorey vegetation and canopy-supplied fine fuels on fire behavior, yet no method we know of can capture fine-scale fuel and fire measurements such that these relationships could be rigorously tested. We present here an original method for inventorying of fine-scale fuels and in situ measures of fire intensity within longleaf pine forests of the south-eastern USA. Using ground-based LIDAR (Light Detection and Ranging) with traditional fuel inventory approaches, we characterized within-fuel bed variation into discrete patches, termed wildland fuel cells, which had distinct fuel composition, characteristics, and architecture that became spatially independent beyond 0.5 m2. Spatially explicit fire behavior was measured in situ through digital infrared thermography. We found that fire temperatures and residence times varied at similar scales to those observed for wildland fuel cells. The wildland fuels cell concept could seamlessly connect empirical studies with numerical models or cellular automata models of fire behavior, representing a promising means to better predict within-burn heterogeneity and fire effects.

Additional keywords: fire behavior, fire effects, fuel heterogeneity, Pinus palustris, prescribed fire.


Acknowledgements

Funding for the present work was provided by the Joseph W. Jones Ecological Research Center and the Robert W. Woodruff foundation as well as the USDA Forest Service Southern Research Station.


References


Andrews PL , Queen PL (2001) Fire modeling and information system technology. International Journal of Wildland Fire  10, 343–352.
CrossRef |

Andrews PL, Bevins CD, Seli RC (2005) BehavePlus fire modeling system, version 3.0: User’s guide revised. USDA Forest Service, Rocky Mountain Research Station, General Technical Report RMRS-GTR-106WWW Revised. (Ogden, UT)

Barnes BV, Pregitzetr KS, Spies TA , Spooner VH (1982) Ecological forest site classification. Journal of Forestry  80, 493–498.


Boyer WD (1979) Regenerating the natural longleaf pine forest. Journal of Forestry  77(9), 572–575.


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


Brown JK, Bevins CD (1986) Surface fuel loadings and predicted fire behavior for vegetation types in the northern Rocky Mountains. USDA Forest Service, Intermountain Forest and Range Experiment Station, Research Note INT-358. (Ogden, UT)

Brown PM , Sieg CH (1999) Historical variability in fire at the ponderosa pine–Northern Great Plains prairie ecotone, south-eastern Black Hills, South Dakota. Ecoscience  6, 539–547.


Byram GM (1959) Combustion of forest fuels. In ‘Forest Fire: Control and Use’. (Eds KP Davis, GM Byram, WR Krumm) pp. 61–89. (McGraw-Hill: New York)

Catchpole EA, Hatton TJ , Catchpole WR (1989) Fire spread through non-homogeneous fuel modelled as a Markov process. Ecological Modelling  48, 101–112.
CrossRef | CAS |

Cleveland WS, Grosse E, Shyu WM (1992) Local regression models. In ‘Statistical Models in S’. (Eds JM Chambers, TJ Hastie) pp. 309–376. (Chapman & Hall: New York)

Collins SL , Smith MD (2006) Scale-dependent interaction of fire and grazing on community heterogeneity in tallgrass prairie. Ecology  87, 2058–2067.
CrossRef | PubMed |

Cressie N (1993) ‘Statistics for Spatial Data.’ Revised edn. (Wiley: New York)

Dimitrakopoulos AP (2002) Mediterranean fuel models and potential fire behaviour in Greece. International Journal of Wildland Fire  11, 127–130.
CrossRef |

Drewa PB (2003) Effects of fire season and intensity on Prosopis glandulosa Torr. var. glandulosa. International Journal of Wildland Fire  12, 147–157.
CrossRef |

Everitt BS (1980) ‘Cluster Analysis.’ 2nd edn. (Heineman Educational Books: London)

Fernandes PM, Catchpole WR , Rego FC (2000) Shrubland fire behaviour modelling with microplot data. Canadian Journal of Forest Research  30, 889–899.
CrossRef |

Finney MA (2001) Design of regular landscape fuel treatment patterns for modifying fire growth and behavior. Forest Science  47, 219–228.


Finney MA (2004) FARSITE: Fire Area Simulator – model development and evaluation. USDA Forest Service, Rocky Mountain Research Station, Research Paper RMRS-RP-4 Revised. (Ogden, UT)

Frandsen WH, Andrews PL (1979) Fire behavior in non-uniform fuels. USDA Forest Service, Intermountain Forest and Range Experiment Station, Research Paper INT-232. (Ogden, UT)

Fujioka FM (1985) Estimating wildland fire rate of spread in a spatially non-uniform environment. Forest Science  31, 21–29.


Handcock MS , Wallis JR (1994) An approach to statistical spatial–temporal modeling of meteorological fields (with discussion). Journal of the American Statistical Association  89, 368–390.
CrossRef |

Hobbs RJ , Atkins L (1988) Spatial variability of experimental fires in south-west Western Australia. Austral Ecology  13, 295–299.
CrossRef |

Iverson LR, Yaussy DA, Rebbeck J, Hutchinson TF, Long RP , Prasad AM (2004) A comparison of thermocouples and temperature paints to monitor spatial and temporal characteristics of landscape-scale prescribed fires. International Journal of Wildland Fire  13, 311–322.
CrossRef |

Johnson EA, Miyanishi K (2001) Strengthening fire ecology’s roots. In ‘Forest Fires: Behavior and Ecological Effects’. (Eds EA Johnson, K Miyanishi) pp. 1–9. (Academic Press: San Diego, CA)

Keane RE, Burgan R , van Wagtendonk J (2001) Mapping wildland fuels for fire management across multiple scales: integrating remote sensing, GIS, and biophysical modeling. International Journal of Wildland Fire  10, 301–319.
CrossRef |

Kennard DK, Outcalt KW, Jones D , O’Brien JJ (2005) Comparing techniques for estimating flame temperature of prescribed fires. Fire Ecology  1, 75–84.


Kirkman LK, Goebel PC, Palik BJ , West LT (2004) Predicting plant species diversity in a longleaf pine landscape. Ecoscience  11, 80–93.


Lertzman K, Fall J (1998) From forest stands to landscapes: spatial scales and the roles of disturbances. In ‘Ecological Scale’. (Eds DL Peterson, VT Parker) pp. 339–367. (Columbia University Press: New York)

Linn R, Winterkamp J, Colman JJ, Edminster C , Bailey JD (2005) Modeling interactions between fire and atmosphere in discrete element fuel beds. International Journal of Wildland Fire  14, 37–48.
CrossRef |

Liu H, Menges ES , Quintana-Ascencio PF (2005) Population viability of Chamaecrista keyensis – effects of fire, season and frequency. Ecological Applications  15, 210–221.
CrossRef |

Loudermilk EL , Cropper W (2007) Multiscale modeling of longleaf pine (Pinus palustris). Canadian Journal of Forest Research  37, 2080–2089.
CrossRef |

McNab H, Avers PA (1994) ‘Ecological Subregions of the United States: Section Descriptions.’ (USDA Forest Service: Washington, DC)

Menges ES, Ascencio PFQ, Weekley CW , Gaoue OG (2006) Population viability analysis and fire return intervals for an endemic Florida scrub mint. Biological Conservation  127, 115–127.
CrossRef |

Miller C , Urban DL (1999) Interactions between forest heterogeneity and surface fire regimes in the southern Sierra Nevada. Canadian Journal of Forest Research  29, 202–212.
CrossRef |

Mitchell RJ, Hiers JK, O’Brien JJ, Jack SB , Engstrom RT (2006) Silviculture that sustains: the nexus between silviculture, frequent prescribed fire, and conservation of biodiversity in longleaf pine forests of the south-eastern United States. Canadian Journal of Forest Research  36, 2724–2736.
CrossRef |

Miyanishi K (2003) Towards a sounder fire ecology. Frontiers in Ecology and the Environment  1, 275–276.
CrossRef |

Myers RL (1990) Scrub and high pine. In ‘Ecosystems of Florida’. (Eds RL Myers, JJ Ewel) pp. 150–193. (University of Central Florida Press: Orlando, FL)

Nelson RM , Adkins CW (1986) Flame characteristics of wind-driven surface fires. Canadian Journal of Forest Research  16, 1293–1300.
CrossRef |

Ottmar RD, Vihnanek RE, Mathey JW (2003) Stereo photo series for quantifying natural fuels. Volume VIA: Sand hill, sand pine scrub, and hardwoods with white pine types in the south-east United States with supplemental sites for volume VI. National Wildfire Coordinating Group, National Interagency Fire Center, PMS 838. (Boise, ID)

Ottmar RD, Sandberg DV, Riccardi CL , Prichard SJ (2007) An overview of the Fuel Characteristic Classification System – quantifying, classifying, and creating fuelbeds for resource planning. Canadian Journal of Forest Research  37, 2383–2393.
CrossRef |

Outcalt K (2000) The longleaf pine ecosystem of the South. Native Plants Journal  1, 24–52.


Rebertus AJ (1988) The effects of fire on forest community composition, structure, and pattern in Florida sandhills. PhD dissertation, Louisiana State University.

Rebertus AJ, Williamson GB , Moser EB (1989) Longleaf pine pyrogenicity and turkey oak mortality in Florida xeric sandhills. Ecology  70, 60–70.
CrossRef |

Riccardi CL, Prichard SJ, Sandberg DV , Ottmar RD (2007) Quantifying physical characteristics of wildland fuels using the Fuel Characteristic Classification System. Canadian Journal of Forest Research  37, 2413–2420.
CrossRef |

Rice SK (1993) Vegetation establishment in post-fire Adenostorna chaparral in relation to fine-scale pattern in fire intensity and soil nutrients. Journal of Vegetation Science  4, 115–124.
CrossRef |

Robbins LE, Myers RL (1992) Seasonal effects of prescribed burning in Florida: a review. Tall Timbers Research Station, MISC8, pp. 1–97. (Tallahassee, FL)

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-115. (Ogden, UT)

SAS Institute Inc. (2003) ‘SAS/STAT User’s Guide, Version 9.1.’ (SAS Institute, Inc.: Cary, NC)

Schultze T, Kempka T , Willms I (2006) Audio-video fire-detection of open fires. Fire Safety Journal  41, 311–314.
CrossRef |

Scott JH, Burgan RE (2005) Standard fire behavior fuel models: a comprehensive set for use with Rothermel’s surface fire spread model. USDA Forest Service, Rocky Mountain Research Station, General Technical Report RMRS-GTR-153. (Fort Collins, CO)

Thaxton JM , Platt WJ (2006) Small-scale fuel variation alters fire intensity and shrub abundance in a pine savanna. Ecology  87, 1331–1337.
CrossRef | PubMed |

Turner MG, Baker WL, Peterson CJ , Peet RK (1998) Factors influencing succession: lessons from large, infrequent natural disturbances. Ecosystems  1, 511–523.
CrossRef |

Walker JW , Peet RK (1984) Composition and species diversity of pine–wiregrass savannas of the Green Swamp, North Carolina. Vegetatio  55, 163–179.
CrossRef |

Williams JE, Whelan RJ , Gill AM (1994) Fire and environmental heterogeneity in southern temperate forest ecosystems: implications for management. Australian Journal of Botany  42, 125–137.
CrossRef |

Williamson GB , Black EM (1981) High temperature of forest fires under pines as a selective advantage over oaks. Nature  293, 643–644.
CrossRef |

Wolf PR, Ghilani CD (1997) ‘Adjustment Computations: Statistics and Least Squares in Surveying GIS.’ (Wiley: New York)



Export Citation Cited By (58)