prilagoðeno pretraživanje po punom tekstu

ŠUMARSKI LIST 11-12/2015 str. 71     <-- 71 -->        PDF

However, higher discrepancies were found for the elevated fuel complexes dominated by live fuels, especially for tall maquis, due to known deficiencies in Rothermel’s fire spread model. A larger and more robust experimental database will be needed before representative fuel models for maquis vegetation can be built. On the other hand, BehavePlus was quite effective at describing the temporal dynamics of fire hazard decrease in slash.
U.S. fire modeling systems can be powerful tools to use in fire research and management applications but are based in laboratory experimental conditions and have been poorly tested. Consequently, their use should rest on sound experimental data. This study is the first to attempt to develop fuel models in Turkey, and one of the first in the Mediterranean Basin that resorts to experimental fire data to do so. Future studies will be dedicated to gather additional fire behavior data for a range of vegetation types and weather conditions in Turkey.
This study was conducted with the cooperation and efforts of many people. This study was partially supported by EFIMED and The Scientific and Technological Research Council of Turkey, Project No: TOVAG-108 O 327.
Alexander M.E., B.J. Stocks, B.D. Lawson, 1991: Fire behavior in black spruce-lichen woodland: the Porter Lake Project. Forest Canada. Northern Forestry Centre, Information Report NOR-X-310. (Edmonton, Alberta) pp. 44.
Allgöwer B., S. Harvey, M. Rüegsegger, 1998: Fuel models for Switzerland: description, spatial pattern, index for torching and crowning, In: Viegas D.X. (ed.), Proc. 3rd International Conference on Forest Fire Research & 14th Fire and Forest Meteorology Conference, ADAI, Coimbra, pp. 2605–2620.
Anderson, H.E, 1982: Aids to determining fuel models for estimating fire behavior, USDA Forest Service, Ogden, 22p,
Anderson, W.R., M.G. Cruz., P.M. Fernandes, L.Mccaw, J.A. Vega, R. Bradstock, L. Fogarty, J. Gould, G. Mccarthy, J.B. Marsden-Smedley, S. Matthews, G. Mattıngly, G. Pearce, B. Van Wılgen, 2015: A generic, empirical-based model for predicting rate of fire spread in shrublands, Int J Wildland Fire 24(4): 443–460.
Andrews, P.L., C.D. Bevins, R.C. Seli, 2005: BehavePlus fire modeling system, version 4.0: User’s Guide, Gen. Tech. Rep. RMRS-GTR-106WWW Revised. Ogden, UT: Department of Agriculture, Forest Service, Rocky Mountain Research Station. 132 pp.
Bilgili, E., B.D. Durmaz, B. Saglam, O. Kucuk, İ. Baysal, 2006: Fire behavior in immature calabrian pine plantations, Forest Ecol Manag 234S: S77–S112.
Bilgili E., B. Saglam, 2003: Fire behaviour in maquis in Turkey, Forest Ecol Manag 184: 201–207.
Burgan R., R. Rothermel, 1984: BEHAVE: fire behaviour prediction and fuel modeling system – FUEL subsystem, USDA Forest Service, Ogden, pp 137.
BYram, G.M, 1959: Combustion of forest fuels, In: Davis, K.P. (Ed.), Forest fire control and use, McGraw-Hill, New York, pp. 90–123.
Catchpole, E.A., W.R. Cathcpole, 1991: Modeling moisture damping for fire spread in a mixture of live and dead fuel, Intl J Wildland Fire 1(2): 101–106.
Chandler, C., P. Cheney, P. Thomas, L. Trabaud, D. Williams, 1983: Fire in forestry. Vol. 1: Forest fire behavior and effects, Krieger Publishing, Florida, pp. 450.
Cohen, M., P. Cuiñas, C. Diez, P. Fernandes, M. Guijarro, C. Moro, 2003: Wildland fuel particles characterization database content. Deliverable D6-03-A1, Fire Star: a decision support system for fuel management and fire hazard reduction in Mediterranean wildland-urban interfaces, Contract No. EVG1-CT-2001-00041.
Cruz, M.G., P.M. Fernandes, 2008: Development of fuel models for fire behaviour prediction in maritime pine (Pinus pinaster Ait.) stands, Int J Wildland Fire 17: 194–204.
Deeming, J.E., J.W. Lancester, M.A. Fosberg, R.W. Furman, M.J. Schroeder, 1972: The National Fire-Danger Rating System. USDA Forest Service, Research Paper, RM-84, pp.165
Dimitrakopoulos, A.P., 2001: A statistical classification of Mediterranean species based on their flammability components, Int J Wildland Fire 10(2): 113–118.
Dimitrakopoulos, A.P., 2002: Mediterranean fuel models and potential fire behaviour in Greece, Int J Wildland Fire 11: 127–130.
Fernandes, P.M., 2001: Fire spread prediction in shrub fuels in Portugal, Forest Ecol Manag 144: 67–74.
Fernandes, P.M., 2009: Combining forest structure data and fuel modeling to classify fire hazard in Portugal, Ann Forest Sci 66: 415.
Fernandes, P.M., H.S. Botelho, F.C. Rego, C. Loureiro, 2009: Empirical modelling of surface fire behaviour in maritime pine stands, Int J Wildland Fire 18: 697–710.
Hirsch, K.G.,1996: Canadian Forest Fire Behavior Prediction System User Guide, Nat. Res. Can. For. Serv., Nor. For. Cent. Special Rep., Edmonton, Alta.
ICONA, 1990: Clave fotografica para la indenditicación de modelos de combustible, Defensa contra incendios forestales, MAPA, Madrid.
Krivtsov, V., O. Vigy, C. Legg, E.Rigolot, et al., 2009: Fuel modelling in terrestrial ecosystems: An overwiev in the context of the development of an object-orientated database for wild fire analysis, Ecol Model 220(21): 2915–2926.
Küçük, Ö., E. Bilgili, İ. Baysal, 2007: Fire development from a point source in surface fuels of a mature Anatolian black pine stand, Turk J Agric For 31(4): 263–273.
Küçük, Ö., E. Bilgili, B. Sağlam, ª. Baºkaya, B. Durmaz, 2008: Fire behavior in Anatolian black pine (Pinus nigra Arnold) slash, Turk J Agric For 32(2): 121–129.
Küçük, Ö., E. Bilgili, S. Bulut, M. Fernandes, 2012: Rates of surface fire spread in a young calabrian pine (Pinus brutia Ten.) plantation, Environ Eng Manag J 11(8): 1475–1480.