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Modelling Fire Frequency in a Cerrado Savanna Protected Area

Author

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  • Alfredo C Pereira Júnior
  • Sofia L J Oliveira
  • José M C Pereira
  • Maria Antónia Amaral Turkman

Abstract

Covering almost a quarter of Brazil, the Cerrado is the world’s most biologically rich tropical savanna. Fire is an integral part of the Cerrado but current land use and agricultural practices have been changing fire regimes, with undesirable consequences for the preservation of biodiversity. In this study, fire frequency and fire return intervals were modelled over a 12-year time series (1997–2008) for the Jalapão State Park, a protected area in the north of the Cerrado, based on burned area maps derived from Landsat imagery. Burned areas were classified using object based image analysis. Fire data were modelled with the discrete lognormal model and the estimated parameters were used to calculate fire interval, fire survival and hazard of burning distributions, for seven major land cover types. Over the study period, an area equivalent to four times the size of Jalapão State Park burned and the mean annual area burned was 34%. Median fire intervals were generally short, ranging from three to six years. Shrub savannas had the shortest fire intervals, and dense woodlands the longest. Because fires in the Cerrado are strongly responsive to fuel age in the first three to four years following a fire, early dry season patch mosaic burning may be used to reduce the extent of area burned and the severity of fire effects.

Suggested Citation

  • Alfredo C Pereira Júnior & Sofia L J Oliveira & José M C Pereira & Maria Antónia Amaral Turkman, 2014. "Modelling Fire Frequency in a Cerrado Savanna Protected Area," PLOS ONE, Public Library of Science, vol. 9(7), pages 1-11, July.
  • Handle: RePEc:plo:pone00:0102380
    DOI: 10.1371/journal.pone.0102380
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    References listed on IDEAS

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    1. Norman Myers & Russell A. Mittermeier & Cristina G. Mittermeier & Gustavo A. B. da Fonseca & Jennifer Kent, 2000. "Biodiversity hotspots for conservation priorities," Nature, Nature, vol. 403(6772), pages 853-858, February.
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    1. J. N. S. Rubí & Paulo R. L. Gondim, 2024. "A performance comparison of machine learning models for wildfire occurrence risk prediction in the Brazilian Federal District region," Environment Systems and Decisions, Springer, vol. 44(2), pages 351-368, June.
    2. Maciel, Everton A. & Martins, Valeria F. & de Paula, Mateus D. & Huth, Andreas & Guilherme, Frederico A.G. & Fischer, Rico & Giles, André & Barbosa, Reinaldo I. & Cavassan, Osmar & Martins, Fernando R, 2021. "Defaunation and changes in climate and fire frequency have synergistic effects on aboveground biomass loss in the brazilian savanna," Ecological Modelling, Elsevier, vol. 454(C).

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