Free Standard AU & NZ Shipping For All Book Orders Over $80!
Register      Login
International Journal of Wildland Fire International Journal of Wildland Fire Society
Journal of the International Association of Wildland Fire
RESEARCH ARTICLE

1984–2010 trends in fire burn severity and area for the conterminous US

Joshua J. Picotte A C , Birgit Peterson A , Gretchen Meier A and Stephen M. Howard C
+ Author Affiliations
- Author Affiliations

A ASRC Federal InuTeq, LLC, Contractor to the United States Geological Survey (USGS), Earth Resources Observation and Science (EROS) Center, 47914 252nd Street, Sioux Falls, SD 57198, USA.1

B United States Geological Survey (USGS), Earth Resources Observation and Science (EROS) Center, 47914 252nd Street, Sioux Falls, SD 57198, USA.

C Corresponding author. Email: jpicotte@usgs.gov

International Journal of Wildland Fire 25(4) 413-420 https://doi.org/10.1071/WF15039
Submitted: 17 May 2014  Accepted: 11 December 2015   Published: 10 March 2016

Abstract

Burn severity products created by the Monitoring Trends in Burn Severity (MTBS) project were used to analyse historical trends in burn severity. Using a severity metric calculated by modelling the cumulative distribution of differenced Normalized Burn Ratio (dNBR) and Relativized dNBR (RdNBR) data, we examined burn area and burn severity of 4893 historical fires (1984–2010) distributed across the conterminous US (CONUS) and mapped by MTBS. Yearly mean burn severity values (weighted by area), maximum burn severity metric values, mean area of burn, maximum burn area and total burn area were evaluated within 27 US National Vegetation Classification macrogroups. Time series assessments of burned area and severity were performed using Mann–Kendall tests. Burned area and severity varied by vegetation classification, but most vegetation groups showed no detectable change during the 1984–2010 period. Of the 27 analysed vegetation groups, trend analysis revealed burned area increased in eight, and burn severity has increased in seven. This study suggests that burned area and severity, as measured by the severity metric based on dNBR or RdNBR, have not changed substantially for most vegetation groups evaluated within CONUS.

Additional keywords: differenced Normalized Burn Ratio, LANDFIRE Environmental Site Potential, Landsat, MTBS, Relativized differenced Normalized Burn Ratio, sigmoid distribution, wildfire.


References

Cansler CA, McKenzie D (2012) How robust are burn severity indices when applied in a new region? Evaluation of alternate field-based and remote-sensing methods. Remote Sensing 4, 456–483.
How robust are burn severity indices when applied in a new region? Evaluation of alternate field-based and remote-sensing methods.Crossref | GoogleScholarGoogle Scholar |

Cansler CA, McKenzie D (2014) Climate, fire size, and biophysical setting control fire severity and spatial pattern in the northern Cascade Range, USA. Ecological Applications 24, 1037–1056.
Climate, fire size, and biophysical setting control fire severity and spatial pattern in the northern Cascade Range, USA.Crossref | GoogleScholarGoogle Scholar | 25154095PubMed |

De Santis A, Asner GP, Vaughan PJ, Knapp DE (2010) Mapping burn severity and burning efficiency in California using simulation models and Landsat imagery. Remote Sensing of Environment 114, 1535–1545.
Mapping burn severity and burning efficiency in California using simulation models and Landsat imagery.Crossref | GoogleScholarGoogle Scholar |

Dennison PE, Brewer SC, Arnold JD, Moritz MA (2014) Large wildfire trends in the western United States, 1984–2011. Geophysical Research Letters 41, 2928–2933.
Large wildfire trends in the western United States, 1984–2011.Crossref | GoogleScholarGoogle Scholar |

Dillon GK, Holden ZA, Morgan P, Crimmins MA, Heyerdahl EK, Luce CH (2011) Both topography and climate affected forest and woodland burn severity in two regions of the western US, 1984 to 2006. Ecosphere 2, art130
Both topography and climate affected forest and woodland burn severity in two regions of the western US, 1984 to 2006.Crossref | GoogleScholarGoogle Scholar |

Eidenshink J, Schwind B, Brewer K, Zhu Z, Quayle B, Howard S (2007) A project for monitoring trends in burn severity. Fire Ecology 3, 3–21.
A project for monitoring trends in burn severity.Crossref | GoogleScholarGoogle Scholar |

Finco M, Quayle B, Zhang Y, Lecker J, Megown KA, Brewer CK (2012) Monitoring Trends and Burn Severity (MTBS): monitoring wildfire activity for the past quarter century using Landsat data. USDA Forest Service, Northern Research Station, General Technical Report NRS-P-105. (Newtown Square, PA)

Hartigan P (1985) AS217 computation of the dip statistic to test for unimodality. Applied Statistics 34, 320–325.
AS217 computation of the dip statistic to test for unimodality.Crossref | GoogleScholarGoogle Scholar |

Hartigan JA, Hartigan P (1985) The dip test of unimodality. Annals of Statistics 13, 70–84.
The dip test of unimodality.Crossref | GoogleScholarGoogle Scholar |

Keane RE, Ryan KC, Veblen TT, Allen CD, Logan JA, Hawkes B (2002) Cascading effects of fire exclusion in Rocky Mountain ecosystems: a literature review. USDA Forest Service, Rocky Mountain Research Station, General Technical Report RMRS-GTR-91. (Fort Collins, CO)

Keeley JE, Brennan T, Pfaff AH (2008) Fire severity and ecosystem responses following crown fires in California shrublands. Ecological Applications 18, 1530–1546.
Fire severity and ecosystem responses following crown fires in California shrublands.Crossref | GoogleScholarGoogle Scholar | 18767627PubMed |

Kendall MG (1975) ‘Rank correlation methods.’ (Griffin: London)

Key CH (2005) Remote sensing sensitivity to fire severity and fire recovery. In ‘Proceedings of the 5th international workshop on remote sensing and GIS applications to forest fire management: fire effects assessment’, 16–18 June 2005, Zaragoza, Spain. (Eds J De la Riva, F Perez-Cabello, E Chuvieco) pp. 29–39. (Universidad de Zaragoza: Spain)

Key CH, Benson NC (2006) Landscape assessment (LA): sampling and assessment methods. USDA Forest Service, Rocky Mountain Research Station, General Technical Report RMRS-GTR-164-CD. (Fort Collins, CO)

Lutz JA, van Wagtendonk JW, Thode AE, Miller JD, Franklin JF (2009) Climate, lightning ignitions, and fire severity in Yosemite National Park, California, USA. International Journal of Wildland Fire 18, 765–774.
Climate, lightning ignitions, and fire severity in Yosemite National Park, California, USA.Crossref | GoogleScholarGoogle Scholar |

Lutz JA, Key CH, Kolden CA, Kane JT, van Wagendonk JW (2011) Fire frequency, area burned, and severity: a quantitative approach to defining a normal fire year. Fire Ecology 7, 51–65.
Fire frequency, area burned, and severity: a quantitative approach to defining a normal fire year.Crossref | GoogleScholarGoogle Scholar |

Mächler M (2004) The diptest package. Statistics 34, 320–325.

Mallek C, Safford H, Viers J, Miller J (2013) Modern departures in fire severity and area vary by forest type, Sierra Nevada and Southern Cascades, California, USA. Ecosphere 4, art153
Modern departures in fire severity and area vary by forest type, Sierra Nevada and Southern Cascades, California, USA.Crossref | GoogleScholarGoogle Scholar |

Mann HB (1945) Non-parametric tests against trend. Econometrica 13, 245–259.
Non-parametric tests against trend.Crossref | GoogleScholarGoogle Scholar |

Miller JD, Safford H (2012) Trends in wildfire severity: 1984 to 2010 in the Sierra Nevada, Modoc Plateau, and Southern Cascades, California, USA. Fire Ecology 8, 41–57.
Trends in wildfire severity: 1984 to 2010 in the Sierra Nevada, Modoc Plateau, and Southern Cascades, California, USA.Crossref | GoogleScholarGoogle Scholar |

Miller JD, Thode AE (2007) Quantifying burn severity in a heterogeneous landscape with a relative version of the delta Normalized Burn Ratio (dNBR). Remote Sensing of Environment 109, 66–80.
Quantifying burn severity in a heterogeneous landscape with a relative version of the delta Normalized Burn Ratio (dNBR).Crossref | GoogleScholarGoogle Scholar |

Miller JD, Knapp EE, Key CH, Skinner CN, Isbell CJ, Creasy RM, Sherlock JW (2009) Calibration and validation of the relative differenced Normalized Burn Ratio (RdNBR) to three measures of fire severity in the Sierra Nevada and Klamath Mountains, California, USA. Remote Sensing of Environment 113, 645–656.
Calibration and validation of the relative differenced Normalized Burn Ratio (RdNBR) to three measures of fire severity in the Sierra Nevada and Klamath Mountains, California, USA.Crossref | GoogleScholarGoogle Scholar |

Miller JD, Collins BM, Lutz JA, Stephens SL, Van Wagendonk JW, Yasuda DA (2012) Differences in wildfires among ecoregions and land management agencies in the Sierra Nevada region, California, USA. Ecosphere 3, art80
Differences in wildfires among ecoregions and land management agencies in the Sierra Nevada region, California, USA.Crossref | GoogleScholarGoogle Scholar |

Morton D, Collatz G, Wang D, Randerson J, Giglio L, Chen Y (2013) Satellite-based assessment of climate controls on US burned area. Biogeosciences 10, 247–260.
Satellite-based assessment of climate controls on US burned area.Crossref | GoogleScholarGoogle Scholar |

Parks SA, Dillon GK, Miller C (2014a) A new metric for quantifying burn severity: the Relativized Burn Ratio. Remote Sensing 6, 1827–1844.
A new metric for quantifying burn severity: the Relativized Burn Ratio.Crossref | GoogleScholarGoogle Scholar |

Parks SA, Miller C, Nelson CR, Holden ZA (2014b) Previous fires moderate burn severity of subsequent wildland fires in two large western US wilderness areas. Ecosystems 17, 29–42.
Previous fires moderate burn severity of subsequent wildland fires in two large western US wilderness areas.Crossref | GoogleScholarGoogle Scholar |

Perry DA, Hessburg PF, Skinner CN, Spies TA, Stephens SL, Taylor AH, Franklin JF, McComb B, Riegel G (2011) The ecology of mixed severity fire regimes in Washington, Oregon, and Northern California. Forest Ecology and Management 262, 703–717.
The ecology of mixed severity fire regimes in Washington, Oregon, and Northern California.Crossref | GoogleScholarGoogle Scholar |

Picotte JJ, Robertson KM (2011) Validation of remote sensing of burn severity in south-eastern US ecosystems. International Journal of Wildland Fire 20, 453–464.
Validation of remote sensing of burn severity in south-eastern US ecosystems.Crossref | GoogleScholarGoogle Scholar |

Prichard SJ, Kennedy MC (2014) Fuel treatments and landform modify landscape patterns of burn severity in an extreme fire event. Ecological Applications 24, 571–590.
Fuel treatments and landform modify landscape patterns of burn severity in an extreme fire event.Crossref | GoogleScholarGoogle Scholar | 24834742PubMed |

Rollins MG (2009) LANDFIRE: a nationally consistent vegetation, wildland fire, and fuel assessment. International Journal of Wildland Fire 18, 235–249.
LANDFIRE: a nationally consistent vegetation, wildland fire, and fuel assessment.Crossref | GoogleScholarGoogle Scholar |

Roy DP, Boschetti L, Trigg SN (2006) Remote sensing of fire severity: assessing the performance of the normalized burn ratio. IEEE Transactions on Geoscience and Remote Sensing 3, 112–116.
Remote sensing of fire severity: assessing the performance of the normalized burn ratio.Crossref | GoogleScholarGoogle Scholar |

Sen PK (1968) Estimates of the regression coefficient based on Kendall’s tau. Journal of the American Statistical Association 63, 1379–1389.
Estimates of the regression coefficient based on Kendall’s tau.Crossref | GoogleScholarGoogle Scholar |

Soverel NO, Perrakis DDB, Coops NC (2010) Estimating burn severity from Landsat dNBR and RdNBR indices across western Canada. Remote Sensing of Environment 114, 1896–1909.
Estimating burn severity from Landsat dNBR and RdNBR indices across western Canada.Crossref | GoogleScholarGoogle Scholar |

Stambaugh MC, Hammer LD, Godfrey R (2015) Performance of burn-severity metrics and classification in oak woodlands and grasslands. Remote Sensing 7, 10501–10522.
Performance of burn-severity metrics and classification in oak woodlands and grasslands.Crossref | GoogleScholarGoogle Scholar |

Theil H (1950) A rank-invariant method of linear and polynomial regression analysis. Proceedings of the Royal Netherlands Academy of Sciences 53, 1397–1412.

Thompson JR, Spies TA (2009) Vegetation and weather explain variation in crown damage within a large mixed-severity wildfire. Forest Ecology and Management 258, 1684–1694.
Vegetation and weather explain variation in crown damage within a large mixed-severity wildfire.Crossref | GoogleScholarGoogle Scholar |

van Mantgem PJ, Stephenson NL, Knapp E, Battles J, Keeley JE (2011) Long-term effects of prescribed fire on mixed-conifer forest structure in the Sierra Nevada, California. Forest Ecology and Management 261, 989–994.
Long-term effects of prescribed fire on mixed-conifer forest structure in the Sierra Nevada, California.Crossref | GoogleScholarGoogle Scholar |

von Storch H (1999) Misuses of statistical analysis in climate research. In ‘Analysis of climate variability’. (Eds H von Storch, A Navarra) pp. 11–26. (Springer: New York)

Yue S, Pilon P, Cavadias G (2002) Power of the Mann–Kendall and Spearman’s rho tests for detecting monotonic trends in hydrological series. Journal of Hydrology 259, 254–271.
Power of the Mann–Kendall and Spearman’s rho tests for detecting monotonic trends in hydrological series.Crossref | GoogleScholarGoogle Scholar |

Zhao F, Keane R, Zhu Z, Huang C (2015) Comparing historical and current wildfire regimes in the northern Rocky Mountains using a landscape succession model. Forest Ecology and Management 343, 9–21.
Comparing historical and current wildfire regimes in the northern Rocky Mountains using a landscape succession model.Crossref | GoogleScholarGoogle Scholar |

Zhu Z, Key CH, Ohlen D, Benson NC (2006) Evaluate sensitivities of burn-severity mapping algorithms for different ecosystems and fire histories in the United States. USDI Final Report to the Joint Fire Science Program: Project JFSP 01–1–4–12. (Sioux Falls, SD)