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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.


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