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

High-resolution observations of combustion in heterogeneous surface fuels

E. Louise Loudermilk A C , Gary L. Achtemeier A , Joseph J. O’Brien A , J. Kevin Hiers B and Benjamin S. Hornsby A

A USDA Forest Service, Center for Forest Disturbance Science, 320 Green Street, Athens, GA, 30602, USA. Email: gachtemeier@fs.fed.us; jjobrien@fs.fed.us; bhornsby@fs.fed.us

B Eglin Air Force Base, Jackson Guard, Niceville, FL, 32578, USA. Email: john.hiers@eglin.af.mil

C Corresponding author. Email: elloudermilk@fs.fed.us

International Journal of Wildland Fire 23(7) 1016-1026 http://dx.doi.org/10.1071/WF13160
Submitted: 19 September 2013  Accepted: 28 March 2014   Published: 11 September 2014

Abstract

In ecosystems with frequent surface fires, fire and fuel heterogeneity at relevant scales have been largely ignored. This could be because complete burns give an impression of homogeneity, or due to the difficulty in capturing fine-scale variation in fuel characteristics and fire behaviour. Fire movement between patches of fuel can have implications for modelling fire spread and understanding ecological effects. We collected high resolution (0.8 × 0.8-cm pixels) visual and thermal imaging data during fire passage over 4 × 4-m plots of mixed fuel beds consisting of pine litter and grass during two prescribed burns within the longleaf pine forests of Eglin Air Force Base, FL in February 2011. Fuel types were identified by passing multi-spectral digital images through a colour recognition algorithm in ‘Rabbit Rules,’ an experimental coupled fire-atmosphere fire spread model. Image fuel types were validated against field fuel types. Relationships between fuel characteristics and fire behaviour measurements at multiple resolutions (0.8 × 0.8 cm to 33 × 33 cm) were analysed using a regression tree approach. There were strong relationships between fire behaviour and fuels, especially at the 33 × 33-cm scale (R2 = 0.40–0.69), where image-to-image overlap error was reduced and fuels were well characterised. Distinct signatures were found for individual and coupled fuel types for determining fire behaviour, illustrating the importance of understanding fire-fuel heterogeneity at fine-scales. Simulating fire spread at this fine-scale may be critical for understanding fire effects, such as understorey plant community assembly.

Additional keywords: fire heterogeneity, fuel type, image recognition, IR imagery, longleaf pine, regression tree.


References

Achtemeier GL (2013) Field validation of a free-agent cellular automata model of fire spread with fire–atmosphere coupling. International Journal of Wildland Fire 22, 148–156.
Field validation of a free-agent cellular automata model of fire spread with fire–atmosphere coupling.CrossRef | open url image1 [Published online 25 September 2012]

Arroyo LA, Pascual C, Manzanera JA (2008) Fire models and methods to map fuel types: the role of remote sensing. Forest Ecology and Management 256, 1239–1252.
Fire models and methods to map fuel types: the role of remote sensing.CrossRef | open url image1

Berjak SG, Hearne JW (2002) An improved cellular automaton model for simulating fire in a spatially heterogeneous Savanna system. Ecological Modelling 148, 133–151.
An improved cellular automaton model for simulating fire in a spatially heterogeneous Savanna system.CrossRef | open url image1

Breiman L, Friedman JH, Olshen RA, Stone CJ (1984) ‘Classification and Regression Trees.’ (Eds PJ Bickel, WS Cleveland, RM Dudley) (Wadsworth, Inc.: Belmont, CA)

De’ath G, Fabricius KE (2000) Classification and regression trees: a powerful yet simple technique for ecological data analysis. Ecology 81, 3178–3192.
Classification and regression trees: a powerful yet simple technique for ecological data analysis.CrossRef | open url image1

Fonda RW (2001) Burning characteristics of needles from eight pine species. Forest Science 47, 390–396.

Fonda R, Varner J (2004) Burning characteristics of cones from eight pine species. Northwest Science 78, 322–333.

Gagnon PR, Harms KE, Platt WJ, Passmore HA, Myers JA (2012) Small-scale variation in fuel loads differentially affects two co-dominant bunchgrasses in a species-rich pine savanna. PLoS ONE 7, e29674
Small-scale variation in fuel loads differentially affects two co-dominant bunchgrasses in a species-rich pine savanna.CrossRef | 1:CAS:528:DC%2BC38XhslKhtL4%3D&md5=5f8bf4f9b743883f784cdba5e87b6758CAS | 22272241PubMed | open url image1

Grunwald S, Daroub SH, Lang TA, Diaz OA (2009) Tree-based modeling of complex interactions of phosphorus loadings and environmental factors. The Science of the Total Environment 407, 3772–3783.
Tree-based modeling of complex interactions of phosphorus loadings and environmental factors.CrossRef | 1:CAS:528:DC%2BD1MXltVamu74%3D&md5=7491619e2c9548ed74624f5704c87c2cCAS | 19324395PubMed | open url image1

Hendricks JJ, Wilson CA, Boring LR (2002) Foliar litter position and decomposition in a fire-maintained longleaf pine–wiregrass ecosystem. Canadian Journal of Forest Research 32, 928–941.
Foliar litter position and decomposition in a fire-maintained longleaf pine–wiregrass ecosystem.CrossRef | open url image1

Hiers JK, O’Brien JJ, Mitchell RJ, Grego JM, Loudermilk EL (2009) The wildland fuel cell concept: an approach to characterize fine-scale variation in fuels and fire in frequently burned longleaf pine forests. International Journal of Wildland Fire 18, 315–325.
The wildland fuel cell concept: an approach to characterize fine-scale variation in fuels and fire in frequently burned longleaf pine forests.CrossRef | open url image1

Holliday P (2001) Going, going... saving the longleaf pine ecosystem before it’s gone. In ‘The Fire Forest: Longleaf Pine–Wiregrass Ecosystem’, The Natural Georgia Series. pp. 55–68. (Georgia Wildlife: Atlanta, GA)

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.
Mapping wildland fuels for fire management across multiple scales: integrating remote sensing, GIS, and biophysical modeling.CrossRef | open url image1

Kirkman LK, Mitchell RJ, Helton RC, Drew MB (2001) Productivity and species richness across an environmental gradient in a fire-dependent ecosystem. American Journal of Botany 88, 2119–2128.
Productivity and species richness across an environmental gradient in a fire-dependent ecosystem.CrossRef | 1:STN:280:DC%2BC3Mngt1ahug%3D%3D&md5=f900e0484c65a337da064a7edc8fe635CAS | 21669643PubMed | open url image1

Loudermilk EL, O’Brien JJ, Mitchell RJ, Cropper WP, Hiers JK, Grunwald S, Grego J, Fernandez-Diaz JC (2012) Linking complex forest fuel structure and fire behaviour at fine scales. International Journal of Wildland Fire 21, 882–893.
Linking complex forest fuel structure and fire behaviour at fine scales.CrossRef | open url image1

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 southeastern United States. Canadian Journal of Forest Research 36, 2724–2736.
Silviculture that sustains: the nexus between silviculture, frequent prescribed fire, and conservation of biodiversity in longleaf pine forests of the southeastern United States.CrossRef | open url image1

Mitchell RJ, Hiers JK, O’Brien J, Starr G (2009) Ecological forestry in the Southeast: understanding the ecology of fuels. Journal of Forestry 107, 391–397.

Morvan D, Dupuy JL (2001) Modeling of fire spread through a forest fuel bed using a multiphase formulation. Combustion and Flame 127, 1981–1994.
Modeling of fire spread through a forest fuel bed using a multiphase formulation.CrossRef | 1:CAS:528:DC%2BD3MXotVyhs7s%3D&md5=8a0cfa3a0e5e5deb5c48d83bd73c3e8bCAS | open url image1

Mutlu M, Popescu SC, Stripling C, Spencer T (2008) Mapping surface fuel models using LIDAR and multispectral data fusion for fire behavior. Remote Sensing of Environment 112, 274–285.
Mapping surface fuel models using LIDAR and multispectral data fusion for fire behavior.CrossRef | open url image1

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, Hiers JK (2008) The influence of fuelbed properties on moisture drying rates and timelags of longleaf pine litter. Canadian Journal of Forest Research 38, 2394–2404.
The influence of fuelbed properties on moisture drying rates and timelags of longleaf pine litter.CrossRef | open url image1

O’Brien JJ, Hiers JK, Callaham MA, Mitchell RJ, Jack SB (2008) Interactions among overstory structure, seedling life-history traits, and fire in frequently burned neotropical pine forests. Ambio 37, 542–547.
Interactions among overstory structure, seedling life-history traits, and fire in frequently burned neotropical pine forests.CrossRef | 19205176PubMed | open url image1

Overing JD, Weeks HH, Wilson JP, Sullivan J, Ford RD (1995) Soil Survey of Okaloosa County, Florida. USDA Natural Resource Conservation Service, (Washington, DC)

Prasad A, Iverson L, Liaw A (2006) Newer classification and regression tree techniques: bagging and random forests for ecological prediction. Ecosystems 9, 181–199.
Newer classification and regression tree techniques: bagging and random forests for ecological prediction.CrossRef | open url image1

R Core Team (2013) ‘R: A Language and Environment for Statistical Computing.’ (R Foundation for Statistical Computing: Vienna, Austria)

Smith FB, Carson DJ, Oliver HR (1972) Mean wind-direction shear through a forest canopy. Boundary-Layer Meteorology 3, 178–190.
Mean wind-direction shear through a forest canopy.CrossRef | open url image1

Thaxton JM, Platt WJ (2006) Small-scale fuel variation alters fire intensity and shrub abundance in a pine savanna. Ecology 87, 1331–1337.
Small-scale fuel variation alters fire intensity and shrub abundance in a pine savanna.CrossRef | 16761611PubMed | open url image1

Varner JM, III, Kush JS, Meldahl RS (2000) Ecological restoration of an old-growth longleaf pine stand utilizing prescribed fire. In ‘Fire and Forest Ecology: Innovative Silviculture and Vegetation Management. Tall Timbers Fire Ecology Conference Proceedings’, 14–16 April 1998, Tallahassee, FL. (Eds WK Moser, CE Moser) pp. 216–219. (Allen Press, Inc.: Lawrence, KS, USA)

Wiggers MS, Kirkman LK, Boyd RS, Hiers JK (2013) Fine-scale variation in surface fire environment and legume germination in the longleaf pine ecosystem. Forest Ecology and Management 310, 54–63.
Fine-scale variation in surface fire environment and legume germination in the longleaf pine ecosystem.CrossRef | open url image1



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