Advertisement

Relations Between Human Factors and Global Fire Activity

  • Emilio ChuviecoEmail author
  • Chris Justice
Chapter

Abstract

Biomass burning is a critical factor to understand both atmospheric and vegetation properties worldwide. Recent changes in global temperatures and socio-economic transformations have affected traditional fire regimes, thus magnifying the negative effects of fire upon human and ecological values. Most sources recognize the importance of human factors in fire ignition, but few studies have tried to understand human patterns of fire at global scale. This paper addresses some of those factors, by using geographical databases covering the whole planet. Fire occurrence was estimated from a database of hot-spots detected by the MODIS sensor, covering the period from 2001 to 2006. Human factors are proven to be related to fire persistency and seasonality, while fire density patterns are associated to human variables for specific climates and vegetation covers.

Keywords

Land Cover Fire Activity Fire Occurrence Boreal Region Fire Season 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

Data for the global analysis of fire characteristics was downloaded from the following sources: Center for International Earth Science Information Network (CIESIN), International Monetary Fund (IMF), and United Nations Environment Program (UNEP). Efforts of these institutions to generate those databases are greatly acknowledged.

References

  1. Chuvieco E, Giglio L, Justice CO (2008) Global characterization of fire activity: towards defining fire regimes from earth observation data. Glob Change Biol 14:1488–1502CrossRefGoogle Scholar
  2. Cochrane MA, Alencar A, Schulze MD, Souza CM, Nepstad DC, Lefebvre P, Davidson EA (1999) Positive feedbacks in the fire dynamic of closed canopy tropical forests. Science 284:1832–1835CrossRefGoogle Scholar
  3. Cortner JH, Gardner PD, Taylor JG (1990) Fire hazards at the urban-wildland interface: what the public expects. Environ Manage 14:57–62CrossRefGoogle Scholar
  4. DeFries RS, Houghton RA, Hansen MC, Field CB, Skole D, Townshend J (2002) Carbon emissions from tropical deforestation and regrowth based on satellite observations for the 1980s and 1990s. Proc Natl Acad Sci 99:14256–14261CrossRefGoogle Scholar
  5. Di Bella CM, Jobbágy EG, Paruelo JM, Pinnock SD (2006) Continental fire density in South America. Global Ecol Biogeogr 15:192–199CrossRefGoogle Scholar
  6. FAO (2007) Fire management – global assessment 2006. A thematic study prepared in the framework of the Global Forest Resources Assessment 2005. Rome, FAO Forestry Paper 151Google Scholar
  7. Giglio L, Csiszar I, Justice CO (2006) Global distribution and seasonality of active fires as observed with the Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. J Geophys Res Biogeosci 111. doi:10.1029/2005JG000142Google Scholar
  8. Goetz S, Fiske G, Bunn A (2006) Using satellite time-series data sets to analyze fire disturbance and forest recovery across Canada. Remote Sens Environ 92:411–423Google Scholar
  9. Healey JF (1993) Statistics: a tool for social research. Wadsworth Pub. Co, Belmont, CAGoogle Scholar
  10. Hobbs NT, Schimel DS, Owensby CE, Ojima DS (1991) Fire and grazing in the tallgrass prairie – contingent effects on nitrogen budgets. Ecology 72:1374–1382CrossRefGoogle Scholar
  11. Johnson EA, Miyanishi K, Bridge SRJ (2001) Wildfire regime in the boreal forest and the idea of suppression and fuel buildup. Conserv Biol 15:1554–1557CrossRefGoogle Scholar
  12. Keeley JE, Fotheringham CJ, Morais M (1999) Reexamining fire suppression impacts on brushland fire regimes. Science 284:1829–1832CrossRefGoogle Scholar
  13. Leemans R (1990) Global data sets collected and compiled by the Biosphere Project. IIASA, Laxenburg, AustriaGoogle Scholar
  14. Leone V, Koutsias N, Martínez J, Vega-García C, Allgöwer B, Lovreglio R (2003) The human factor in fire danger assessment. In: Chuvieco E (ed) Wildland fire danger estimation and mapping. The role of remote sensing data. World Scientific Publishing, Singapore, pp 143–196CrossRefGoogle Scholar
  15. Martínez J, Vega-García C, Chuvieco E (2009) Human-caused wildfire risk rating for prevention planning in Spain. J Environ Manage 90:1241–1252CrossRefGoogle Scholar
  16. Mollicone D, Eva HD, Achard F (2006) Human role in Russian wild fires. Nature 440:436–437CrossRefGoogle Scholar
  17. Parisien MA, Peters VS, Wang YH, Little JM, Bosch EM, Stocks BJ (2006) Spatial patterns of forest fires in Canada, 1980–1999. Int J Wildland Fire 15:361–374CrossRefGoogle Scholar
  18. Pyne SJ (2001) The fires this time, and next. Science 294:1005–1006CrossRefGoogle Scholar
  19. Radeloff VC, Hammer RB, Stewart SI, Fried JS, Holcomb SS, McKeefry JF (2005) The wildland-urban interface in the United States. Ecol Appl 15:799–805CrossRefGoogle Scholar
  20. Randerson JT, van der Werf GR, Collatz GJ, Giglio L, Still CJ, Kasibhatla P, Miller JB, White JWC, DeFries RS, Kasischke ES (2005) Fire emissions from C3 and C 4 vegetation and their influence on interannual variability of atmospheric CO2 and D13 CO2. Global Biogeochem Cycles 19. doi:10.1029/2004GB002366Google Scholar
  21. Reisen F, Brown SK (2006) Implications for community health from exposure to bushfire air toxics. Environ Chem 3:235–243CrossRefGoogle Scholar
  22. SPSS (2006) SPSS Statistics Base 15.0 User’s Guide. Chicago: SPSS IncGoogle Scholar
  23. Tukey JW (1977) Exploratory data analysis. Addison-Wesley, Menlo Park, CAGoogle Scholar
  24. Vega-García C, Woodard T, Adamowicz, Lee B (1995) A logit model for predicting the daily occurence of human caused forest fires. Int J Wildland Fire 5:101–111CrossRefGoogle Scholar
  25. Westerling AL, Hidalgo HG, Cayan DR, Swetnam TW (2006) Warming and earlier spring increase western US forest wildfire activity. Science 313:940–943CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  1. 1.Department of GeographyUniversity of AlcaláAlcalá de HenaresSpain
  2. 2.Geography DepartmentUniversity of MarylandCollege ParkUSA

Personalised recommendations