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International Journal of Wildland Fire International Journal of Wildland Fire Society
Journal of the International Association of Wildland Fire
RESEARCH ARTICLE (Open Access)

Modelling long-term fire regimes of southern California shrublands

Seth H. Peterson A F , Max A. Moritz B , Marco E. Morais C , Philip E. Dennison D and Jean M. Carlson E
+ Author Affiliations
- Author Affiliations

A Department of Geography, University of California – Santa Barbara, Santa Barbara, CA 93106, USA.

B Center for Fire Research and Outreach, Department of Environmental Science, Policy and Management, University of California – Berkeley, Berkeley, CA 94720, USA.

C The Aerospace Corporation, 2350 E El Segundo Boulevard, El Segundo, CA 90245, USA.

D Center for Natural and Technological Hazards, Department of Geography, University of Utah, Salt Lake City, UT 84112, USA.

E Department of Physics, University of California – Santa Barbara, Santa Barbara, CA 93106, USA.

F Corresponding author. Email: seth@geog.ucsb.edu

International Journal of Wildland Fire 20(1) 1-16 https://doi.org/10.1071/WF09102
Submitted: 16 September 2009  Accepted: 27 May 2010   Published: 14 February 2011

Journal Compilation © IAWF 2011

Abstract

This paper explores the environmental factors that drive the southern California chaparral fire regime. Specifically, we examined the response of three fire regime metrics (fire size distributions, fire return interval maps, cumulative total area burned) to variations in the number of ignitions, the spatial pattern of ignitions, the number of Santa Ana wind events, and live fuel moisture, using the HFire fire spread model. HFire is computationally efficient and capable of simulating the spatiotemporal progression of individual fires on a landscape and aggregating results for fully resolved individual fires over hundreds or thousands of years to predict long-term fire regimes. A quantitative understanding of the long-term drivers of a fire regime is of use in fire management and policy.


References

Akaike H (1974) A new look at statistical model identification. IEEE Transactions on Automatic Control 19, 716–723.
A new look at statistical model identification.Crossref | GoogleScholarGoogle Scholar |

Albini FA (1976) Estimating wildfire behavior and effects. USDA Forest Service, Intermountain Forest and Range Experiment Station, General Technical Report GTR-INT-30. (Ogden, UT)

Albini FA, Chase CH (1980) Fire containment equations for pocket calculators. USDA Forest Service, Intermountain Forest and Range Experiment Station, Research Paper RP-INT-268. (Ogden, UT)

Anderson HE (1983) Predicting wind-driven wildland fire size and shape. USDA Forest Service, Intermountain Forest and Range Experiment Station, Research Paper RP-INT-305. (Ogden, UT)

Arca B, Duce P, Laconi M, Pellizzaro G, Salis M, Spano D (2007) Evaluation of FARSITE simulator in Mediterranean maquis. International Journal of Wildland Fire 16, 563–572.
Evaluation of FARSITE simulator in Mediterranean maquis.Crossref | GoogleScholarGoogle Scholar |

Burgan RE, Klaver RW, Klaver JM (1998) Fuel models and fire potential from satellite and surface observations. International Journal of Wildland Fire 8, 159–170.
Fuel models and fire potential from satellite and surface observations.Crossref | GoogleScholarGoogle Scholar |

Cary GJ, Banks JCG (1999) Fire regime sensitivity to global climate change: an Australian perspective. In ‘Advances in Global Change Research: Biomass Burning and its Inter-relationships with the Climate System’. (Eds JL Innes, M Beniston, MM Verstraete) pp. 233–246. (Kluwer Academic Publishers: London)

Cary GJ, Keane RE, Gardner RJ, Lavorel S, Flannigan MD, Davies ID, Li C, Lenihan JM, Rupp TS, Mouillot F (2006) Comparison of the sensitivity of landscape-fire-succession models to variation in terrain, fuel pattern, climate and weather. Landscape Ecology 21, 121–137.
Comparison of the sensitivity of landscape-fire-succession models to variation in terrain, fuel pattern, climate and weather.Crossref | GoogleScholarGoogle Scholar |

Clark RE, Hope AS, Tarantola S, Gatelli D, Dennison PE, Moritz MA (2008) Sensitivity analysis of a fire spread model in a chaparral landscape. Fire Ecology 4, 1–13.
Sensitivity analysis of a fire spread model in a chaparral landscape.Crossref | GoogleScholarGoogle Scholar |

Countryman CM (1974). Can southern California wildland conflagrations be stopped? USDA Forest Service, Pacific Southwest Forest and Range Experiment Station, General Technical Note GTN-PSW-7. (Berkeley, CA)

Countryman CM, Dean WH (1979) Measuring moisture content in living chaparral: a field user’s manual. USDA Forest Service, Pacific Southwest Forest and Range Experiment Station, General Technical Report GTR-PSW-36. (Berkeley, CA)

Cui W, Perera AH (2008) What do we know about fire size distribution, and why is this knowledge useful for forest management? International Journal of Wildland Fire 17, 234–244.
What do we know about fire size distribution, and why is this knowledge useful for forest management?Crossref | GoogleScholarGoogle Scholar |

D’Antonio CM, Vitousek PM (1992) Biological invasions by exotic grasses, the grass-fire cycle, and global change. Annual Review of Ecology and Systematics 23, 63–87..

Dasgupta S, Qu JJ, Hao X, Bhoi S (2007) Evaluating remotely sensed live fuel moisture estimations for fire behavior predictions in Georgia, USA. Remote Sensing of Environment 108, 138–150.
Evaluating remotely sensed live fuel moisture estimations for fire behavior predictions in Georgia, USA.Crossref | GoogleScholarGoogle Scholar |

Davis FW, Burrows DA (1994) Spatial simulation of fire regime in Mediterranean-climate landscapes. In ‘The Role of Fire in Mediterranean-type Ecosystems’. (Eds JM Moreno, WC Oechel) pp. 117–139. (Springer: New York)

Davis FW, Michaelsen J (1995) Sensitivity of fire regime in chaparral ecosystems to climate change. In ‘Global Change and Mediterranean-type Ecosystems’. (Eds JM Moreno, WC Oechel) pp. 203–224. (Springer: New York)

Dennison PE, Moritz MA, Taylor RS (2008) Examining predictive models of chamise critical live fuel moisture in the Santa Monica Mountains, California. International Journal of Wildland Fire 17, 18–27.
Examining predictive models of chamise critical live fuel moisture in the Santa Monica Mountains, California.Crossref | GoogleScholarGoogle Scholar |

Field CB, Daily GC, Davis FW, Gaines S, Matson PA, Melack J, Miller NL (1999) ‘Confronting Climate Change in California: Ecological Impacts on the Golden State.’ (Union of Concerned Scientists: Cambridge, MA and Ecological Society of America: Washington, DC)

Finney MA (1998) FARSITE: Fire Area Simulator – model development and evaluation. USDA Forest Service, Rocky Mountain Research Station, Research Paper RP-RMRS-4. (Ft Collins, CO)

Franklin J (1997) Forest Service Southern California Mapping Project: Santa Monica Mountains National Recreation Area, Final Report. Available at http://www.icess.ucsb.edu/resac/refs/veg93meta.htm [Verified 5 January 2011]

Franklin J, Syphard AD, Mladenoff DJ, He HS, Simons DK, Martin RP, Deutschman D, O’Leary JF (2001) Simulating the effects of different fire regimes on plant functional groups in southern California. Ecological Modelling 142, 261–283.
Simulating the effects of different fire regimes on plant functional groups in southern California.Crossref | GoogleScholarGoogle Scholar |

FRAP (2009) Fuels: surface fuels. Available at http://frap.cdf.ca.gov/data/frapgisdata/select.asp?theme=5 [Verified 15 September 2009]

Hargrove WW, Gardner RH, Turner MG, Romme WH, Despain DG (2000) Simulating fire patterns in heterogeneous landscapes. Ecological Modelling 135, 243–263.
Simulating fire patterns in heterogeneous landscapes.Crossref | GoogleScholarGoogle Scholar |

Haydon DT, Friar JK, Pianka ER (2000) Fire-driven dynamic mosaics in the Great Victoria Desert, Australia. Landscape Ecology 15, 407–423.
Fire-driven dynamic mosaics in the Great Victoria Desert, Australia.Crossref | GoogleScholarGoogle Scholar |

Horton JS, Kraebel CJ (1955) Development of vegetation after fire in the chamise chaparral of southern California. Ecology 36, 244–262.
Development of vegetation after fire in the chamise chaparral of southern California.Crossref | GoogleScholarGoogle Scholar |

Hughes M, Hall A, Kim J (2009) Anthropogenic reduction of Santa Ana winds. California Environmental Protection Agency and California Energy Commission Report CEC-500-2009-030-F. Available at http://www.atmos.ucla.edu/csrl/pub.html [Verified 5 January 2011]

Keane RE, Finney MA (2003) The simulation design for modeling landscape fire, climate, ecosystem dynamics. In ‘Fire and Climatic Change in Temperate Ecosystems of the Western Americas’. (Eds TT Veblen, WL Baker, G Montenegro, TW Swetnam) pp. 32–68. (Springer: New York)

Keane RE, Ryan KC, Running SW (1996) Simulating effects of fire on northern Rocky Mountain landscapes with the ecological process model FIRE-BGC. Tree Physiology 16, 319–331..

Keane RE, Cary GJ, Davies ID, Flannigan MD, Gardner RJ, Lavorel S, Lenihan JM, Li C, Rupp TS (2004) A classification of landscape fire succession models: spatial simulations of fire and vegetation dynamics. Ecological Modelling 179, 3–27.
A classification of landscape fire succession models: spatial simulations of fire and vegetation dynamics.Crossref | GoogleScholarGoogle Scholar |

Keeley JE (2000) Chaparral. In ‘North American Terrestrial Vegetation’. 2nd edn. (Eds MG Barbour, WD Billings) pp. 203–253. (Cambridge University Press: New York)

Keeley JE, Fotheringham CJ (2003) Impact of past, present, and future fire regimes on North American Mediterranean shrublands. In ‘Fire and Climatic Change in Temperate Ecosystems of the Western Americas’. (Eds TT Veblen, WL Baker, G Montenegro, TW Swetnam) pp. 218–262. (Springer: New York)

Keeley JE, Fotheringham CJ, Baer-Keeley M (2005) Determinants of post-fire recovery and succession in Mediterranean-climate shrublands of California. Ecological Applications 15, 1515–1534.
Determinants of post-fire recovery and succession in Mediterranean-climate shrublands of California.Crossref | GoogleScholarGoogle Scholar |

Mensing SA, Michaelsen J, Byrne R (1999) A 560-year record of Santa Ana fires reconstructed from charcoal deposited in the Santa Barbara Basin, California. Quaternary Research 51, 295–305.
A 560-year record of Santa Ana fires reconstructed from charcoal deposited in the Santa Barbara Basin, California.Crossref | GoogleScholarGoogle Scholar |

Miller NL, Schlegel NJ (2006) Climate change projected fire weather sensitivity: California Santa Ana wind occurrence. Geophysical Research Letters 33, L15711
Climate change projected fire weather sensitivity: California Santa Ana wind occurrence.Crossref | GoogleScholarGoogle Scholar |

Miller C, Urban DL (2000) Modeling the effects of fire management alternatives on Sierra Nevada mixed-conifer forests. Ecological Applications 10, 85–94.
Modeling the effects of fire management alternatives on Sierra Nevada mixed-conifer forests.Crossref | GoogleScholarGoogle Scholar |

Moritz MA (1997) Analyzing extreme disturbance events: fire in Los Padres National Forest. Ecological Applications 7, 1252–1262.
Analyzing extreme disturbance events: fire in Los Padres National Forest.Crossref | GoogleScholarGoogle Scholar |

Moritz MA (1999) Controls on disturbance regime dynamics: fire in Los Padres National Forest. PhD dissertation, University of California – Santa Barbara.

Moritz MA, Stephens SL (2008) Fire and sustainability: considerations for California’s altered future climate. Climatic Change 87, 265–271.
Fire and sustainability: considerations for California’s altered future climate.Crossref | GoogleScholarGoogle Scholar |

Moritz MA, Morais ME, Summerell LA, Carlson JM, 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.
Wildfires, complexity, and highly optimized tolerance.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2MXhtlersr7L&md5=f7aa0285c8940db292afde43902d5d8bCAS |

National Park Service (2005) Final environmental impact statement for a fire management plan, Santa Monica Mountains National Recreation Area. USDI, National Park Service. (Thousand Oaks, CA) Available at http://www.researchlearningcenter.org/samo/planning/FireEIS/ [Verified 5 January 2011]

Oliveras I, Piñol J, Viegas DX (2005) Modelling the long term effects of changes in fire frequency on the total area burnt. Orsis 20, 73–81..

Pastor E, Zárate L, Planas E, Arnaldos J (2003) Mathematical models and calculation systems for the study of wildland fire behaviour. Progress in Energy and Combustion Science 29, 139–153.
Mathematical models and calculation systems for the study of wildland fire behaviour.Crossref | GoogleScholarGoogle Scholar |

Perera AH, Ouellette M, Cui W, Drescher M, Boychuk D (2008) BFOLDS 1.0: a spatial simulation model for exploring large-scale fire regimes and succession in boreal forest landscapes. Ontario Forest Research Institute, Forest Research Report Number 152. (Sault Ste. Marie, ON)

Peterson SH, Roberts DA, Dennison PE (2008) Mapping live fuel moisture with MODIS data: a multiple regression approach. Remote Sensing of Environment 112, 4272–4284.
Mapping live fuel moisture with MODIS data: a multiple regression approach.Crossref | GoogleScholarGoogle Scholar |

Peterson SH, Morais ME, Carlson JM, Dennison PE, Roberts DA, Moritz MA, Weise DR (2009) Using HFire for spatial modeling of fire in shrublands. USDA Forest Service, Pacific Southwest Research Station, Research Paper PSW-RP-259. (Albany, CA)

R Development Core Team (2008) ‘R: a Language and Environment for Statistical Computing.’ (R Foundation for Statistical Computing: Vienna, Austria) Available at www.R-project.org [Verified 15 September 2009]

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.
The wildland–urban interface in the United States.Crossref | GoogleScholarGoogle Scholar |

Radtke KWH, Arndt AM, Wakimoto RH (1982) Fire history of the Santa Monica Mountains. USDA Forest Service, Pacific Southwest Forest and Range Experiment Station, General Technical Report PSW-58. (Eds CE Conrad, WC Oechel) pp. 438–443. (Berkeley, CA)

Raphael MN (2003) The Santa Ana winds of California. Earth Interactions 7, 1–13.
The Santa Ana winds of California.Crossref | GoogleScholarGoogle Scholar |

Rothermel RC (1972) A mathematical model for predicting fire spread in wildland fuels. USDA Forest Service, Intermountain Forest and Range Experiment Station, Research Paper RP-INT-115. (Ogden, UT)

Rothermel RC (1983) How to predict the spread and intensity of forest and range fires. USDA Forest Service, Intermountain Forest and Range Experiment Station, General Technical Report GTR-INT-143. (Ogden, UT)

Swenson JJ, Franklin J (2000) The effects of future urban development on habitat fragmentation in the Santa Monica Mountains. Landscape Ecology 15, 713–730.
The effects of future urban development on habitat fragmentation in the Santa Monica Mountains.Crossref | GoogleScholarGoogle Scholar |

Syphard AD, Radeloff VC, Keeley JE, Hawbaker TJ, Clayton MK, Stewart SI, Hammer RB (2007) Human influence on California fire regimes. Ecological Applications 17, 1388–1402.
Human influence on California fire regimes.Crossref | GoogleScholarGoogle Scholar | 17708216PubMed |

Syphard AD, Radeloff VC, Keuler NS, Taylor RS, Hawbacker TJ, Stewart SI, Clayton MK (2008) Predicting spatial patterns of fire on a southern California landscape. International Journal of Wildland Fire 17, 602–613.
Predicting spatial patterns of fire on a southern California landscape.Crossref | GoogleScholarGoogle Scholar |

Venevsky S, Thonicke K, Sitch S, Cramer W (2002) Simulating fire regimes in human-dominated ecosystems: Iberian Peninsula case study. Global Change Biology 8, 984–998.
Simulating fire regimes in human-dominated ecosystems: Iberian Peninsula case study.Crossref | GoogleScholarGoogle Scholar |

Weise DR, Regelbrugge JC (1997) Recent chaparral fuel modeling efforts. Resource Management: the Fire Element. USDA Forest Service, Pacific Southwest Research Station, Prescribed Fire and Fire Effects Research Unit, Newsletter of the California Fuels Committee. (Riverside, CA)

Weise DR, Hartford RA, Mahaffey L (1998) Assessing live fuel moisture for fire management applications. In ‘Fire in Ecosystem Management: Shifting the Paradigm from Suppression to Prescription. Tall Timbers Fire Ecology Conference Proceedings’. Vol. 20. (Eds TL Pruden, LA Brennan) pp. 49–55. (Tall Timbers Research Station: Tallahassee, FL)

Westerling AL, Cayan DR, Brown TJ, Hall BL, Riddle LG (2004) Climate, Santa Ana winds, and autumn wildfires in southern California. EOS 85, 289–296.
Climate, Santa Ana winds, and autumn wildfires in southern California.Crossref | GoogleScholarGoogle Scholar |

Zedler PH, Gautier CR, McMaster GS (1983) The effect of a short interval between fires in California chaparral and coastal scrub. Ecology 64, 809–818.
The effect of a short interval between fires in California chaparral and coastal scrub.Crossref | GoogleScholarGoogle Scholar |