Statistical analysis of fire frequency models for Catalonia (NE Spain), 1975–1998) based on fire scar maps from Landsat MSS dataRicardo Díaz-Delgado A D , Francisco Lloret A B and Xavier Pons A C
A CREAF, Facultat de Ciències, Universitat Autònoma de Barcelona, Bellaterra, 08193 Barcelona, Spain.
B email: firstname.lastname@example.org
C Departament de Geografia, Universitat Autònoma de Barcelona, Bellaterra, 08193 Barcelona, Spain. email: email@example.com
D Corresponding author. Present address: Estación Biológica de Doñana, Avda María Luisa s/n., 41013 Sevilla, Spain. Telephone: +34 5 423 2340, ext. 119; fax: +34 5 462 1125; email: firstname.lastname@example.org
International Journal of Wildland Fire 13(1) 89-99 https://doi.org/10.1071/WF02051
Submitted: 15 July 2002 Accepted: 20 August 2003 Published: 8 April 2004
This paper estimates fire frequency in Catalonia (NE Spain) for the last quarter of the 20th Century (1975–1998) from historical burned area maps. Remote sensing images provided perimeters of fires ≥ 30 ha, which were used to characterize the temporal patterns of fire occurrence in Catalonia. Several fire frequency models were used to reproduce the observed pattern of wildfires occurrence in the study period. Natural fire rotation period was estimated to be 133 years. Poisson tests were carried out to check random fire occurrence either along the time period or across the analysed region. Observed fires were not randomly generated either in space or in time, despite being sampled using two different plot sizes. This sampling design was also used for Mean Fire Interval (MFI) analysis, which allowed us to significantly fit a Weibull distribution to the observed proportion of fire intervals (for both sample sizes), enabling us to estimate the hazard of burning, mortality, and survivorship functions. Finally, MFI was also applied to forest regions of Catalonia, which are defined according to forest management plans based on their homogeneous climatic conditions. Such an analysis revealed relevant differences in forest management and their consequences on fire occurrence.
The authors express their gratitude to the ICC for technical assistance. We also appreciate the help from the DMA who supplied the GIS layers of 1994 and 1995 wildfire perimeters; and to the DARP and the old ICONA, for the fire statistics. We also thank Joseph Fall from the Forest Ecology Group (REM, SFU) for his Tutorial on Common Methods for Determining Fire Frequency, which greatly helped the authors to understand fire frequency methods and to Jordi Bascompte who kindly read the manuscript and offered positive comments on it. Financial support for this work came from the CICYT-MEC (AMB94–0881 and AGL2000–0678 projects), and a grant to R. Díaz-Delgado by MEC. The study was also partially funded by the Lucifer EC project.
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