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Controls on the spatial pattern of wildfire ignitions in Southern California

Nicolas Faivre A C , Yufang Jin B , Michael L. Goulden A and James T. Randerson A

A Department of Earth System Science, University of California, 2101 E Croul Hall, Irvine, CA 92697-3100, USA.
B Department of Land, Air and Water Resources, University of California, Davis, CA 95616-8627, USA.
C Corresponding author. Email: nfaivre@uci.edu

International Journal of Wildland Fire - http://dx.doi.org/10.1071/WF13136
Submitted: 21 August 2013  Accepted: 7 May 2014   Published online: 28 July 2014


 
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Abstract

Wildfire ignition requires a combination of an open spark, and suitable weather and fuel conditions. Models of fire occurrence and burned area provide a good understanding of the physical and climatic factors that constrain and promote fire spread and recurrence, but information on how humans influence ignition patterns is still lacking at a scale compatible with integrated fire management. We investigated the relative importance of the physical, climatic and human factors regulating ignition probability across Southern California’s National Forests. A 30-year exploratory analysis of one-way relationships indicated that distance to a road, distance to housing and topographic slope were the major determinants of ignition frequency. We used logistic and Poisson regression analyses to model ignition occurrence and frequency as a function of the dominant covariates. The resulting models explained ~70% of the spatial variability in ignition likelihood and 45% of the variability in ignition frequency. In turn, predicted ignition probability contributed to some of the spatial variability in burned area, particularly for summer fires. These models may enable estimates of fire ignition risk for the broader domain of Southern California and how this risk may change with future population and housing development. Our spatially explicit predictions may also be useful for strategic fire management in the region.

Additional keywords: biophysical drivers, fire frequency, fire ignition, human influence, Mediterranean ecosystems, spatial regression model, wildland fire risk.


References

Agee JK (1993) ‘Fire Ecology of Pacific Northwest Forests.’ (Island Press: Washington, DC)

Agresti A (2002) ‘Categorical Data Analysis.’ (Wiley: Hoboken, NJ)

Akaike H (1974) A new look at the statistical model identification. Transactions on Automatic Control 19, 716–723.
CrossRef |

Alexander JD, Seavy NE, Ralph CJ, Hogoboom B (2006) Vegetation and topographical correlates of fire severity from two fires in the Klamath–Siskiyou region of Oregon and California. International Journal of Wildland Fire 15, 237–245.
CrossRef |

Archibald S, Roy DP, Van Wilgen BW, Scholes RJ (2009) What limits fire? An examination of drivers of burnt area in southern Africa. Global Change Biology 15, 613–630.
CrossRef |

Arroyo MTK, Zedler PH, Fox MD (1995) ‘Ecology and Biogeography of Mediterranean Ecosystems in Chile, California, and Australia.’ (Springer: London)

Badia-Perpinyá A, Pallares-Barbera M (2006) Spatial distribution of ignitions in Mediterranean periurban and rural areas: the case of Catalonia. International Journal of Wildland Fire 15, 187–196.
CrossRef |

Bailey HP (1966) ‘The Climate of Southern California.’ (University of California Press: Berkeley, CA)

Bar Massada A, Radeloff VC, Stewart SI, Hawbaker TJ (2009) Wildfire risk in the wildland–urban interface: a simulation study in northwestern Wisconsin. Forest Ecology and Management 258, 1990–1999.
CrossRef |

Beaty RM, Taylor AH (2001) Spatial and temporal variation of fire regimes in a mixed conifer forest landscape, Southern Cascades, California, USA. Journal of Biogeography 28, 955–966.
CrossRef |

Beers TW, Dress PE, Wensel LC (1966) Aspect transformation in site productivity research. Journal of Forestry 64, 691–692.

Bradstock RA, Gill AM, Kenny BJ, Scott J (1998) Bushfire risk at the urban interface estimated from historical weather records: consequences for the use of prescribed fire in the Sydney region of south-eastern Australia. Journal of Environmental Management 52, 259–271.
CrossRef |

Callaway R, Davis F (1993) Vegetation dynamics, fire, and the physical environment in coastal central California. Ecology 74, 1567–1578.
CrossRef |

Catry FX, Rego FC, Bação FL, Moreira F (2009) Modeling and mapping wildfire ignition risk in Portugal. International Journal of Wildland Fire 18, 921–931.
CrossRef |

Cayan DR, Maurer EP, Dettinger MD, Tyree M, Hayhoe K (2008) Climate change scenarios for the California region. Climatic Change 87, 21–42.
CrossRef |

Cayan DR, Das T, Pierce DW, Barnett TP, Tyree M, Gershunov A (2010) Future dryness in the southwest US and the hydrology of the early 21st century drought. Proceedings of the National Academy of Sciences of the United States of America 107, 21 271–21 276.
CrossRef | CAS |

Chou Y, Minnich R, Chase R (1993) Mapping probability of fire occurrence in San Jacinto Mountains, California, USA. Environmental Management 17, 129–140.
CrossRef |

Chuvieco E, Salas FJ, Carvacho L, Rodriguez-Silva F (1999) Integrated fire risk mapping. In ‘Remote Sensing of Large Wildfires’. (Ed. E Chuvieco) pp. 61–100. (Springer: Berlin)

Countryman CM (1972) The fire environment concept. USDA Forest Service, Pacific Southwest Forest and Ranger Experiment Station, Technical Paper. (Berkeley, CA) Available at http://www.firemodels.org/downloads/behaveplus/publications/Countryman/Countryman_1972_TheFireEnvironmentConcept_ocr.pdf [Verified 13 August 2013].

Crane R, Valenzuela A Jr, Chatman D, Schweitzer L, Wong P (2002) California Travel Trends and Demographics Study. University of California, Los Angeles, Institute of Transportation Studies School of Public Policy and Social Research, Final Report 74A0034. (Los Angeles, CA)

Crawley MJ (2005) Multiple regression. In ‘Statistics: An Introduction using R’. pp. 195–208. (Wiley: Hoboken, NJ)

Daly C, Gibson WP, Taylor GH, Johnson GL, Pasteris P (2002) A knowledge-based approach to the statistical mapping of climate. Climate Research 22, 99–113.
CrossRef |

Davis GW, Richardson DM (1995) ‘Mediterranean-type Ecosystems: the Function of Biodiversity.’ (Springer: London)

Dellasala DA, Williams JE, Williams CD, Franklin JF (2004) Beyond smoke and mirrors: a synthesis of fire policy and science. Conservation Biology 18, 976–986.
CrossRef |

Di Castri F, Goodall DW, Specht RL (1981) ‘Mediterranean-type Shrublands.’ (Elsevier: Amsterdam)

Dickson BG, Prather JW, Xu Y, Hampton HM, Aumack EN, Sisk TD (2006) Mapping the probability of large fire occurrence in northern Arizona, USA. Landscape Ecology 21, 747–761.
CrossRef |

Franklin J (1998) Predicting the distribution of shrub species in southern California from climate and terrain-derived variables. Journal of Vegetation Science 9, 733–748.
CrossRef |

FRAP (2002) California Department of Forestry – Fire and Resource Assessment Program Multi-source Land Cover data. Available at http://frap.cdf.ca.gov/data/frapgisdata/download.asp?rec=fveg02_2 [Verified 9 May 2013]

FRAP (2010) California Department of Forestry – Fire and Resource Assessment Program GIS database of fire perimeter polygons. Available at http://frap.cdf.ca.gov/data/frapgisdata/download.asp?rec=fire [Verified 9 May 2013]

Gardner W, Mulvey EP, Shaw EC (1995) Regression analyses of counts and rates: Poisson, overdispersed Poisson, and negative binomial models. Psychological Bulletin 118, 392–404.
CrossRef | CAS | PubMed |

Gelman A, Hill J (2007) ‘Data Analysis using Regression and Multilevel/Hierarchical Models.’ (Cambridge University Press: Cambridge, UK)

Gesch D, Oimoen M, Greenlee S, Nelson C, Steuck M, Tyler D (2002) The national elevation dataset. Photogrammetric Engineering and Remote Sensing 68, 5–11.

Haidinger TL, Keeley JE (1993) Role of high fire frequency in destruction of mixed chaparral. Madrono 40, 141–147.

Haight RG, Cleland DT, Hammer RB, Radeloff VC, Rupp TS (2004) Assessing fire risk in the wildland-urban interface. Journal of Forestry 102, 41–48.

Hammer RB, Stewart SI, Winkler RL, Radeloff VC, Voss PR (2004) Characterizing dynamic spatial and temporal residential density patterns from 1940–1990 across the North Central United States. Landscape and Urban Planning 69, 183–199.
CrossRef |

Hammer RB, Radeloff VC, Fried JS, Stewart SI (2007) Wildland–urban interface housing growth during the 1990s in California, Oregon, and Washington. International Journal of Wildland Fire 16, 255–265.
CrossRef |

Hardin JW, Hilbe J (2007) ‘Generalized Linear Models and Extensions.’ (StataCorp Press: College Station, TX)

Heyerdahl EK, Brubaker LB, Agee JK (2001) Spatial controls of historical fire regimes: a multiscale example from the interior west, USA. Ecology 82, 660–678.
CrossRef |

Hilbe JM (2009) ‘Logistic Regression Models.’ (Chapman & Hall/CRC: Boca Raton, FL)

Hosmer DW, Lemeshow S (2005) Introduction to the Logistic Regression Model. In ‘Applied Logistic Regression’, 2nd edn. pp. 1–30. (Wiley: Hoboken, NJ)

Hughes M, Hall A (2010) Local and synoptic mechanisms causing Southern California’s Santa Ana winds. Climate Dynamics 34, 847–857.
CrossRef |

Jin Y, Randerson JT, Faivre N, Capps S, Hall A, Goulden ML (2014) Contrasting controls on wildland fires in Southern California during periods with and without Santa Ana winds. Journal of Geophysical Research – Biogeosciences 119, 432–450.
CrossRef |

Keeley JE (1982) Distribution of lightning- and man-caused wildfires in California. In ‘Proceedings of the International Symposium on the Dynamics and Management of Mediterranean Type Ecosystems’, 22–26 June 1981, San Diego, CA. (Eds CE Conrad, WC Oechel) USDA Forest Service, Pacific Southwest Forest and Range Experiment Station, General Technical Report PSW-GTR-058, pp. 431–437. (Berkeley, CA)

Keeley J, Fotheringham C (2001) Historic fire regime in southern California shrublands. Conservation Biology 15, 1536–1548.
CrossRef |

Keeley JE, Zedler PH (2009) Large, high intensity fire events in southern California shrublands: debunking the fine-grained age-patch model. Ecological Applications 19, 69–94.
CrossRef | PubMed |

Keeley J, Fotheringham C, Morais M (1999) Reexamining fire suppression impacts on brushland fire regimes. Science 284, 1829–1832.
CrossRef | CAS | PubMed |

Keeley JE, Safford H, Fotheringham CJ, Franklin J, Moritz M (2009) The 2007 Southern California wildfires: lessons in complexity. Journal of Forestry 107, 287–296.

Kleinbaum DG, Klein M, Pryor ER (2002) ‘Logistic Regression: a Self-Learning Text.’ (Springer: New York)

Long JS (1997) ‘Regression models for categorical and limited dependent variables.’ (SAGE Publications Inc.: Thousand Oaks, CA)

Martínez J, Vega-Garcia C, Chuvieco E (2009) Human-caused wildfire risk rating for prevention planning in Spain. Journal of Environmental Management 90, 1241–1252.
CrossRef | PubMed |

Miller C, Abatzoglou J, Brown T, Syphard A (2011) Wilderness Fire Management in a Changing Environment. In ‘The Landscape Ecology of Fire’. (Eds D McKenzie, C Miller, DA Falk) pp. 269–294. (Springer: London)

Moritz MA (2003) Spatiotemporal analysis of controls on shrubland fire regimes: age dependency and fire hazard. Ecology 84, 351–361.
CrossRef |

Moritz MA, Morais ME, Summerell LA, Carlson J, Doyle J (2005) Wildfires, complexity, and highly optimized tolerance. Proceedings of the National Academy of Sciences of the United States of America 102, 17 912–17 917.
CrossRef | CAS |

Moritz MA, Moody TJ, Krawchuk MA, Hughes M, Hall A (2010) Spatial variation in extreme winds predicts large wildfire locations in chaparral ecosystems. Geophysical Research Letters 37, L04801
CrossRef |

Narayanaraj G, Wimberly MC (2012) Influences of forest roads on the spatial pattern of human- and lightning-caused wildfire ignitions. Applied Geography 32, 878–888.
CrossRef |

Pan LL, Chen SH, Cayan D, Lin MY, Hart Q, Zhang MH, Liu YB, Wang JZ (2011) Influences of climate change on California and Nevada regions revealed by a high-resolution dynamical downscaling study. Climate Dynamics 37, 2005–2020.
CrossRef |

Parisien MA, Moritz MA (2009) Environmental controls on the distribution of wildfire at multiple spatial scales. Ecological Monographs 79, 127–154.
CrossRef |

Perry GLW (1998) Current approaches to modelling the spread of wildland fire: a review. Progress in Physical Geography 22, 222–245.
CrossRef |

Preisler HK, Brillinger DR, Burgan RE, Benoit JW (2004) Probability based models for estimation of wildfire risk. International Journal of Wildland Fire 13, 133–142.
CrossRef |

Pyne SJ (2001) ‘Fire: a Brief History.’ (University of Washington Press: Washington, DC)

Pyne SJ, Andrews PJ, Laven RD (1996) ‘Introduction to Wildland Fire’, 2nd edn. (Wiley: New York)

R Development Core Team (2012) ‘R: a Language and Environment for Statistical Computing’ (R Foundation for Statistical Computing: Vienna, Austria)

Radeloff VC, Hammer RB, Stewart SI, Fried JS, Holcomb SS, McKeefry JF (2005) The wildland-urban interface in the United States. Ecological Applications 15, 799–805.
CrossRef |

Radeloff VC, Stewart SI, Hawbaker TJ, Gimmi U, Pidgeon AM, Flather CH, Hammer RB, Helmers DP (2010) Housing growth in and near United States protected areas limits their conservation value. Proceedings of the National Academy of Sciences of the United States of America 107, 940–945.
CrossRef | CAS | PubMed |

Spracklen DV, Mickley LJ, Logan JA, Hudman RC, Yevich R, Flannigan MD, Westerling AL (2009) Impacts of climate change from 2000 to 2050 on wildfire activity and carbonaceous aerosol concentrations in the western United States. Journal of Geophysical Research 114, D20301
CrossRef |

Stephens SL (2005) Forest fire causes and extent on United States Forest Service lands. International Journal of Wildland Fire 14, 213–222.
CrossRef |

Stewart SI, Radeloff VC, Hammer RB, Hawbaker TJ (2007) Defining the wildland–urban interface. Journal of Forestry 105, 201–207.

Strauss D, Bednar L, Mees R (1989) Do one percent of forest fires cause ninety-nine percent of the damage? Forest Science 35, 319–328.

Sugihara NG, VanWagtendonk JW, Fites-Kaufman J, Shaffer KE, Thode AE (2006) The Future of Fire in California’s Ecosystems. In ‘Fire in California’s Ecosystems’. (Eds N Sugihara, J Van Wagtendonk, KE Shaffer, J Fites-Kaufman, AE Thode) pp. 538–543. (The University of California Press: Berkeley, CA)

Swetnam T, Falk D, Hessl A, Farris C (2011) Reconstructing Landscape Pattern of Historical Fires and Fire Regimes. In ‘The Landscape Ecology of Fire’. (Eds D McKenzie, C Miller, DA Falk) pp. 165–192. (Springer: London)

Syphard A, Radeloff V, Keeley J, Hawbaker T, Clayton M, Stewart S, Hammer R (2007) Human influence on California fire regimes. Ecological Applications 17, 1388–1402.
CrossRef | PubMed |

Syphard A, Radeloff V, Keuler N, Taylor R, Hawbaker T, Stewart S, Clayton M (2008) Predicting spatial patterns of fire on a southern California landscape. International Journal of Wildland Fire 17, 602–613.
CrossRef |

Syphard AD, Keeley JE, Massada AB, Brennan TJ, Radeloff VC (2012) Housing arrangement and location determine the likelihood of housing loss due to wildfire. PLoS ONE 7, e33954
CrossRef | CAS | PubMed |

Syphard AD, Bar Massada A, Butsic V, Keeley JE (2013) Land use planning and wildfire: development policies influence future probability of housing loss. PLoS ONE 8, e71708
CrossRef | CAS | PubMed |

US Census Bureau (2000) ‘Census 2000 TIGER/Line Files’ (US Census Bureau: Washington, DC)

US Census Bureau (2001) ‘Census 2001 Population and Housing Block Groups/Shape Files’ (US Census Bureau: Washington, DC)

US Census Bureau (2012) 2010 Census of Population and Housing, Population and Housing Unit Counts, CPH-2-6, California (US Government Printing Office: Washington, DC) Available at http://www.census.gov/prod/cen2010/cph-2-6.pdf [Verified 3 June 2014]

USDA Forest Service (2010) FIRESTAT GIS database of fire origins from the US Department of Agriculture and Forest Service. Available at http://www.fs.fed.us/r5/rsl/projects/frdb/layers/fire.html [Verified 15 April 2013]

Vasconcelos MJP, Silva S, Tome M, Alvim M, Pereira JC (2001) Spatial prediction of fire ignition probabilities: comparing logistic regression and neural networks. Photogrammetric Engineering and Remote Sensing 67, 73–81.

Verdú F, Salas J, Vega-García C (2012) A multivariate analysis of biophysical factors and forest fires in Spain, 1991–2005. International Journal of Wildland Fire 21, 498–509.
CrossRef |

Westerling AL (2006) Warming and earlier spring increase western U.S. forest wildfire activity. Science 313, 940–943.
CrossRef | CAS | PubMed |

Westerling A, Bryant B (2008) Climate change and wildfire in California. Climatic Change 87, 231–249.
CrossRef |

Westerling A, Bryant B, Preisler H, Hidalgo H, Das T, Shrestha S (2009) Climate change, growth, and California wildfire. California Energy Commission, Draft Paper. (Sacramento, CA)

Whelan RJ (1995) ‘The Ecology of Fire.’ (Cambridge University Press: Cambridge, UK)

Yang J, He HS, Shifley SR, Gustafson EJ (2007) Spatial patterns of modern period human-caused fire occurrence in the Missouri Ozark Highlands. Forest Science 53, 1–15.


   
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