Free Standard AU & NZ Shipping For All Book Orders Over $80!
Register      Login
International Journal of Wildland Fire International Journal of Wildland Fire Society
Journal of the International Association of Wildland Fire
RESEARCH ARTICLE

The relationship of post-fire white ash cover to surface fuel consumption

Andrew T. Hudak A D , Roger D. Ottmar B , Robert E. Vihnanek B , Nolan W. Brewer C , Alistair M. S. Smith C and Penelope Morgan C
+ Author Affiliations
- Author Affiliations

A USDA Forest Service, Rocky Mountain Research Station, Forestry Sciences Laboratory, 1221 S Main Street, Moscow, ID 83843, USA.

B USDA Forest Service, Pacific Northwest Research Station, Pacific Wildland Fire Sciences Laboratory, 400 N 34th Street, Suite 201, Seattle, WA 98103, USA.

C Department of Forest, Rangeland, and Fire Sciences, University of Idaho, 6th and Line Street, Moscow, ID 83844, USA.

D Corresponding author. Email: ahudak@fs.fed.us

International Journal of Wildland Fire 22(6) 780-785 https://doi.org/10.1071/WF12150
Submitted: 27 February 2012  Accepted: 28 January 2013   Published: 16 May 2013

Abstract

White ash results from the complete combustion of surface fuels, making it a logically simple retrospective indicator of surface fuel consumption. However, the strength of this relationship has been neither tested nor adequately demonstrated with field measurements. We measured surface fuel loads and cover fractions of white ash and four other surface materials (green vegetation, brown non-photosynthetic vegetation, black char and mineral soil) immediately before and after eight prescribed fires in four disparate fuelbed types: boreal forest floor, mixed conifer woody slash, mixed conifer understorey and longleaf pine understorey. We hypothesised that increased white ash cover should correlate significantly to surface fuel consumption. To test this hypothesis, we correlated field measures of surface fuel consumption with field measures of surface cover change. Across all four fuelbed types, we found increased white ash cover to be the only measure of surface cover change that correlated significantly to surface fuel consumption, supporting our hypothesis. We conclude that white ash load calculated from immediate post-fire measurements of white ash cover, depth and density may provide an even more accurate proxy for surface fuel consumption, and furthermore a more physically based indicator of fire severity that could be incorporated into rapid response, retrospective wildfire assessments.

Additional keywords: black char, fire effects, fire severity, fuelbed, prescribed fire.


References

Bauer DF (1972) Constructing confidence sets using rank statistics. Journal of the American Statistical Association 67, 687–690.
Constructing confidence sets using rank statistics.Crossref | GoogleScholarGoogle Scholar |

Beaufait WR, Hardy CE, Fischer WC (1977) Broadcast burning in larch-fir clearcuts: the Miller Creek–Newman Ridge study. USDA Forest Service, Intermountain Forest and Range Experiment Station, Research Paper INT-175. (Ogden, UT)

Brown JK (1974) Handbook for inventorying downed woody material. USDA Forest Service, Intermountain Forest and Range Experiment Station, General Technical Report INT-16. (Odgen, UT)

Cliff AD, Ord JK (1981) ‘Spatial Processes.’ (Pion Ltd: London)

Dickinson MB, Ryan KC (2010) Introduction: strengthening the foundation of wildland fire effects prediction for research and management. Fire Ecology 6, 1–12.
Introduction: strengthening the foundation of wildland fire effects prediction for research and management.Crossref | GoogleScholarGoogle Scholar |

Goforth BR, Graham RC, Hubbert KR, Zanner CW, Minnich RA (2005) Spatial distribution and properties of ash and thermally altered soils after high-severity forest fire, southern California. International Journal of Wildland Fire 14, 343–354.
Spatial distribution and properties of ash and thermally altered soils after high-severity forest fire, southern California.Crossref | GoogleScholarGoogle Scholar |

Jenkins BM, Baxter LL, Miles TR, Miles TR (1998) Combustion properties of biomass. Fuel Processing Technology 54, 17–46.
Combustion properties of biomass.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaK1cXitlSrs7s%3D&md5=2bedd6cdbdd52888422f1b84b2e8d665CAS |

Kremens R, Smith AMS, Dickinson M (2010) Fire metrology: current and future directions in physics-based measurements. Fire Ecology 6, 13–35.
Fire metrology: current and future directions in physics-based measurements.Crossref | GoogleScholarGoogle Scholar |

Lewis SA, Hudak AT, Lentile LB, Ottmar RD, Cronan JB, Hood SM, Robichaud PR, Morgan P (2011) Using hyperspectral imagery to estimate forest floor consumption from wildfire in boreal forests of Alaska, USA. International Journal of Wildland Fire 20, 255–271.
Using hyperspectral imagery to estimate forest floor consumption from wildfire in boreal forests of Alaska, USA.Crossref | GoogleScholarGoogle Scholar |

Lutes DC, Keane RE, Caratti JF, Key CH, Benson NC, Sutherland S, Gangi LJ (2006) FIREMON: Fire effects monitoring and inventory system. USDA Forest Service, Rocky Mountain Research Station, General Technical Report RMRS-GTR-164CD. (Fort Collins, CO)

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 | GoogleScholarGoogle Scholar |

Ottmar RD, Vihnanek RE (1998) Stereo photo series for quantifying natural fuels. Volume II: black spruce and white spruce types in Alaska. National Wildfire Coordinating Group, National Interagency Fire Center, PMS 831. (Boise, ID)

Ottmar RD, Vihnanek RE, Wright CS (1998) Stereo photo series for quantifying natural fuels. Volume I: mixed-conifer with mortality, western juniper, sagebrush, and grassland types in the interior Pacific Northwest. National Wildfire Coordinating Group, National Interagency Fire Center, PMS 830. (Boise, ID)

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

R Core Team (2012) ‘R: a Language and Environment for Statistical Computing.’ (R Foundation for Statistical Computing: Vienna, Austria) Available at http://www.R-project.org [Verified 26 March 2013]

Robichaud PR, Lewis SA, Laes DYM, Hudak AT, Kokaly RF, Zamudio JA (2007) Post-fire soil burn severity mapping with hyperspectral image unmixing. Remote Sensing of Environment 108, 467–480.
Post-fire soil burn severity mapping with hyperspectral image unmixing.Crossref | GoogleScholarGoogle Scholar |

Robinson JM (1991) Fire from space: Global fire evaluation using infrared remote sensing. International Journal of Remote Sensing 12, 3–24.
Fire from space: Global fire evaluation using infrared remote sensing.Crossref | GoogleScholarGoogle Scholar |

Royston P (1982) Algorithm AS 181: the W test for normality. Applied Statistics 31, 176–180.
Algorithm AS 181: the W test for normality.Crossref | GoogleScholarGoogle Scholar |

Royston P (1995) Remark AS R94: a remark on algorithm AS 181: the W test for normality. Applied Statistics 44, 547–551.
Remark AS R94: a remark on algorithm AS 181: the W test for normality.Crossref | GoogleScholarGoogle Scholar |

Rupp TS, Ottmar RD, Butler B (2011) Quantifying the effects of fuels reduction treatments on fire behavior and post-fire vegetation dynamics. Joint Fire Science Program, Final Report – Project 06–2-1–39. (Boise, ID)

Smith AMS, Hudak AT (2005) Estimating combustion of large downed woody debris from residual white ash. International Journal of Wildland Fire 14, 245–248.
Estimating combustion of large downed woody debris from residual white ash.Crossref | GoogleScholarGoogle Scholar |

Stronach NRH, McNaughton SJ (1989) Grassland fire dynamics in the Serengeti ecosystem, and a potential method of retrospectively estimating fire energy. Journal of Applied Ecology 26, 1025–1033.
Grassland fire dynamics in the Serengeti ecosystem, and a potential method of retrospectively estimating fire energy.Crossref | GoogleScholarGoogle Scholar |