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

Estimating crown fuel loading for calabrian pine and Anatolian black pine

Ömer Küçük A , Ertuğrul Bilgili B D and Bülent Sağlam C
+ Author Affiliations
- Author Affiliations

A Kastamonu University, Faculty of Forestry, 37100 Kastamonu, Turkey.

B Karadeniz Technical University, Faculty of Forestry, 61080 Trabzon, Turkey.

C Artvin Çoruh University, Faculty of Forestry, 08000 Artvin, Turkey.

D Corresponding author. Email: bilgili@ktu.edu.tr

International Journal of Wildland Fire 17(1) 147-154 https://doi.org/10.1071/WF06092
Submitted: 13 June 2006  Accepted: 7 January 2008   Published: 15 February 2008

Abstract

Fuels are of great importance in fire behaviour prediction. This paper deals with the prediction of aboveground foliage and branch biomass of calabrian pine (Pinus brutia Ten.) and Anatolian black pine (P. nigra J.F. Arnold subsp. nigra var. caramanica (Loudon) Rehder). The study was based on a total of 418 destructively sampled calabrian and black pine trees and saplings. As a result of the analyses, several regression equations were developed for predicting foliage, fine branch (<0.6 cm), medium branch (0.6–1.0 cm), active fuels (foliage + fine branch), thick branch (1.0–2.5 cm), and total fuel loading. The relationships between fuel biomass and tree properties were determined by multiple linear regressions, considering tree properties as the independent variables, and foliage, branch, active fuel and total biomass as the dependent variables. Tree properties included tree height, crown length, crown width, diameter at breast height and root collar diameter. Results indicated that foliage, branch and total biomass could all be accurately predicted based on the readily measurable and/or predictable tree characteristics. Of the fuel characteristics, crown length, crown width, and height were the three most significant predictors of fuel biomass. The results of this study will not only contribute to the prediction of fire behaviour, but will also be of invaluable use in other forestry disciplines.

Additional keywords: biomass, fire, fuel, regression equation, Turkey.


References


Baskerville GL (1972) Use of logarithmic regression in the estimation of plant biomass. Canadian Journal of Forest Research  13, 1248–1251.
Brown JK (1965) Estimating crown fuel weights of red pine and jack pine. USDA Forest Service, Research Paper LS-20. (St Paul, MN)

Brown JK (1978) Weight and density of crowns of Rocky Mountains conifers. USDA Forest Service, Research Paper INT-197. (Ogden, UT)

Brown JK (1982) Fuel and fire behavior predicting in big sagebrush. USDA Forest Service, Research Paper INT-290. (Ogden, UT)

Call PT , Albini FA (1997) Aerial and surface fuel consumption in crown fires. International Journal of Wildland Fire  7, 259–264.
Crossref | GoogleScholarGoogle Scholar | Gray KL, Reinhardt E (2003) Analysis of algorithms for predicting canopy fuel. In ‘Proceedings of the Second International Wildland Fire Ecology and Fire Management Congress and Fifth Symposium on Fire and Forest Meteorology, November 16–20, 2003, Orlando, FL’. Paper P5.8. (American Meteorological Society: Boston, MA)

Harding RB , Grigal DF (1985) Individual tree biomass estimation equations for plantation-grow white spruce in northern Minnesota. Canadian Journal of Forest Research  15, 738–739.
Crossref | GoogleScholarGoogle Scholar | Kiil AD (1967) Fuel weight tables for white spruce and lodgepole pine crowns in Alberta. Canadian Department of Forestry & Rural Development Publication 1196.

Kucuk O (2000) Karaçamda yanıcı madde miktarının tespiti ve yanıcı madde özelliklerine bağlı yanıcı madde modelleri. KTÜ Fen Bilimleri Enstitüsü, Yüksek Lisans Tezi (Yayımlanmamış) Trabzon. [In Turkish]

Kucuk O (2004) Yanıcı madde özellikleri ve yangın davranışına bağlı yangın potansiyelinin belirlenmesi ve haritalanması. KTU Fen Bilimleri Enstitüsü, Doktora Tezi (Yayımlanmamış) Trabzon. [In Turkish]

Kucuk O, Saglam B , Bilgili E (2007) Canopy fuel characteristics and fuel load in young black pine trees. Biotechnology and Biotechnological Equipment  21(2), 235–240.
Loomis RM, Roussopoulos PJ (1978) Estimating aspen crown fuels in northern Minnesota. USDA Forest Service, Research Paper NC-156. (St Paul, MN)

Madgwick HAI , Satoo T (1975) On estimating the aboveground weights of tree stands. Ecology  56, 1446–1450.
Crossref | GoogleScholarGoogle Scholar | OGM (2007) Orman Atlası, Orman Genel Müdürlüğü, Ankara, [In Turkish]

Oladi D (1996) Developing a framework a methodology for plantation assessment using remotely-sensed data. PhD Thesis, University of New Brunswick, Faculty of Forestry and Environmental Management, Canada.

Oswald BP, Fancher JT, Kulhavy DL , Reeves HC (1999) Classifying fuels with aerial photography in east Texas. International Journal of Wildland Fire  9(2), 109–113.
Crossref | GoogleScholarGoogle Scholar | Rothermel RC (1991) Predicting behavior and size of crown fires in the Northern Rocky Mountains. USDA Forest Service, Intermountain Research Station, Research Paper INT-438. (Ogden, UT)

Roussopoulos PJ, Loomis RM (1979) Weights and dimensional properties of shrubs and small trees of the Great Lakes conifer forest. USDA Forest Service North Central Experiment Station. Research Paper 178. (Newtown Square, PA)

Saglam B , Bilgili E (2002) Maki tipi yanıcı maddelerde yanıcı madde miktarının belirlenmesi. Kastamonu Eğitim Dergisi  10(1), 181–186.
Sando RW, Wick CH (1972) A method of evaluating crown fuels in forest stands. USDA Forest Service, Research paper NC-84. (St Paul, MN)

Schmitt MDC , Grigal DF (1981) Generalized biomass estimations for Betula papyrifera Marsh. Canadian Journal of Forest Research  11, 837–840.
Crossref | GoogleScholarGoogle Scholar | Scott JH, Reinhardt ED (2001) Assessing crown fire potential by linking models of surface and crown fire behavior. USDA Forest Service, Research paper RMRS-RP-29. (Fort Collins, CO)

Scott JH , Reinhardt ED (2002) Estimating canopy fuels in conifer forests. Fire Management Today  62(4), 45–50.
Scott JH, Reinhardt ED (2005) Stereo photo guide for estimating canopy fuel characteristics in conifer stands. USDA General Technical Report, RMRS-GTR-145. (Fort Collins, CO)

Scott K, Oswald B, Farrish K , Unger D (2002) Fuel loading prediction models developed from aerial photographs of the Sanre de Cristo and Jemez mountains of New Mexico, USA. International Journal of Wildland Fire  11, 85–90.
Crossref | GoogleScholarGoogle Scholar | Smith WB, Brand GJ (1983) Allometric equations for 98 species of herbs, shrubs, and small trees. USDA Forest Service, Research Note, NC 229. (East Lansing, MI)

Sprugel DG (1983) Correcting for bias in log-transformed allometric equations. Ecology  64, 209–210.
Crossref | GoogleScholarGoogle Scholar | SPSS (1999) ‘Statistical Package For Social Sciences (SPSS) 10.0 for Windows.’ (SPSS: Chicago, IL)

Stocks BJ (1980) Black spruce crown fuel weights in northern Ontario. Canadian Journal of Forest Research  10, 498–501.


Stocks BJ, Alexander ME, Wotton BM, Stefner CN , Flannigan MD (2004) Crown fire behavior in a northern jack pine-black spruce forest. Canadian Journal of Forest Research  34, 1548–1560.
Crossref | GoogleScholarGoogle Scholar |

Ter-Mikaelian MT , Korzukhin MD (1997) Biomass equations for sixty-five North American tree species. Forest Ecology and Management  97, 1–24.
Crossref | GoogleScholarGoogle Scholar |

Turna I , Bilgili E (2006) Effect of heat on seed germination of Pinus sylvestris and Pinus nigra ssp. pallasiana. International Journal of Wildland Fire  15, 283–286.
Crossref | GoogleScholarGoogle Scholar |

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

Wagner RG , Ter-Mikaelian MT (1999) Comparison of biomass component equations for four species of northern coniferous tree seedling. Annals of Forest Science  56, 193–199.
Crossref | GoogleScholarGoogle Scholar |

Zar JH (1968) Calculation and miscalculation of the allometric equation as a model in biological data. Bioscience  18, 1118–1120.
Crossref | GoogleScholarGoogle Scholar |