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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

Effects of curing on grassfires: I. Fuel dynamics in a senescing grassland

Susan Kidnie A D , Miguel G. Cruz B , Jim Gould B , David Nichols A , Wendy Anderson C and Rachel Bessell A
+ Author Affiliations
- Author Affiliations

A CFA, Fire and Emergency Management, PO Box 701, Mt Waverley, Vic. 3149, Australia.

B CSIRO Land & Water Flagship, GPO Box 1700, Canberra, ACT 2601, Australia.

C School of Physical, Environmental and Mathematical Sciences, University of New South Wales, PO Box 1796, Canberra, ACT 2610, Australia.

D Corresponding author. Email: S.Kidnie@cfa.vic.gov.au

International Journal of Wildland Fire 24(6) 828-837 https://doi.org/10.1071/WF14145
Submitted: 18 August 2014  Accepted: 8 April 2015   Published: 13 July 2015

Abstract

Grass senescence, or grassland curing, is a dynamic process in which grass fuels transition from a live to dead state and, in turn, influence fire dynamics. In the present study we examined the process of curing with specific consideration of changes in fuel structure that will affect potential fire behaviour. Our sampling protocol expanded the fuel component groups from two (live and dead) to four (green, senescing, new dead and old dead fuel). We found that all these components had significant fuel moisture content differences, thereby justifying our sampling protocol. Visual curing assessment predominantly resulted in an over-prediction bias of curing level and failed to capture the effect of the senescing process on fuel availability to combust due to misclassification of fuel components (e.g. senescing fuels with high fuel moisture content were classified as dead fuels because of their colouration). Models were developed to estimate the: (1) proportion of senescing and green fuels from knowledge of the current year’s dead fuel proportion; and (2) actual curing level from fuel moisture content and soil dryness level.


References

Alexander ME (2008) ‘Proposed revision of fire danger class criteria for forest and rural areas of New Zealand,’ 2nd edn. (National Rural Fire Authority in association with the Scion Rural Fire Research Group: Wellington and Christchurch, New Zealand)

Allan G, Johnson A, Cridland S, Fitzgerald N (2003) Application of NDVI for predicting fuel curing at landscape scales in northern Australia: can remotely sensed data help schedule fire management operations? International Journal of Wildland Fire 12, 299–308.
Application of NDVI for predicting fuel curing at landscape scales in northern Australia: can remotely sensed data help schedule fire management operations?Crossref | GoogleScholarGoogle Scholar |

Anderson SAJ, Pearce HG (2003) Improved methods for the assessment of grassland curing. In ‘3rd International Wildland Conference’, 3–6 October 2003, Sydney, NSW. (Australasian Fire Authorities Council: Melbourne, Vic.)

Anderson SAJ, Anderson WR, Hollis JJ, Botha EJ (2011) A simple method for field-based grassland curing assessment. International Journal of Wildland Fire 20, 804–814.
A simple method for field-based grassland curing assessment.Crossref | GoogleScholarGoogle Scholar |

Andrews PL, Anderson SAJ, Anderson WR (2006) Evaluation of a dynamic load transfer function using grassland curing data. In ‘Fuels management: how to measure success’, 28–30 March 2006. (Eds PL Andrews and BW Butler.) RMRS-P-41, pp. 381–394. (USDA Forest Service: Fort Collins, CO)

Barber J (1990) ‘Monitoring the curing of grassland fire fuels in Victoria Australia with sensors in satellites and aircraft. A Country Fire Authority study in remote sensing.’ Technical Report. (Country Fire Authority: Melbourne, Vic.)

Burgan RE (1979) Estimating live fuel moisture for the 1978 National Fire Danger Rating System. USDA Forest Service, Intermountain Forest and Rangeland Experiment Station, Research Paper INT-226. (Ogden, UT)

Burgan RE, Hartford RA (1993) Monitoring vegetation greenness with satellite data. USDA Forest Service, Intermountain Research Station, Research Paper INT-297. (Ogden, UT)

Burrows ND, Ward B, Robinson A (2009) Fuel dynamics and fire spread in spinifex grasslands of the western desert. In ‘The Proceedings of the Royal Society of Queensland–Bushfire 2006 Conference’, 6–9 June 2006, Brisbane. (Ed. C. Tran.) pp. 69–76. (Royal Society of Queensland: Brisbane, Qld)

Country Fire Authority (CFA) (2014) ‘Grassland curing guide. Fire and emergency management.’ (CFA: Melbourne, Vic.)

Cheney NP, Sullivan AL (2008) ‘Grassfires: fuel, weather and fire behaviour’, 2nd edn. (CSIRO Publishing: Melbourne, Vic.)

Cheney NP, Gould JS, Catchpole WR (1998) Prediction of fire spread in grassland. International Journal of Wildland Fire 8, 1–13.
Prediction of fire spread in grassland.Crossref | GoogleScholarGoogle Scholar |

Chladil M (1989) The application of remote sensing to the assessment of grassland moisture and biomass in Tasmania: a preliminary report. In ‘Proceedings of the Third Australian Fire Weather Conference’, 18–20 May 1989, Hobart, Tas.

Chuvieco E, Cocero D, Riano D, Martin P, Martinez-Vega J, de la Riva J, Perez F (2004) Combining NDVI and surface temperature for the estimation of live fuel moisture content in forest fire danger rating. Remote Sensing of Environment 92, 322–331.
Combining NDVI and surface temperature for the estimation of live fuel moisture content in forest fire danger rating.Crossref | GoogleScholarGoogle Scholar |

Cruz MG, Gould J, Kidnie S, Bessell R, Nichols D (2015) Effects of curing on grassfires: II. The effect of grass senescence on the rate of fire spread. International Journal of Wildland Fire
Effects of curing on grassfires: II. The effect of grass senescence on the rate of fire spread.Crossref | GoogleScholarGoogle Scholar |

Deeming JE, Lancaster JW, Fosberg MA, Furman RW, Schroeder MJ (1972) The National Fire-Danger Rating System. USDA Forest Service, Rocky Mountain Forest and Range Experiment Station, Research Paper RM-84. (Fort Collins, CO)

Everson TM, Everson CS, Dicks HM, Poulter AG (1988) Curing rates in the grass sward of the Highland Sourveld in the Natal Drakensburg. South African Forestry Journal 145, 1–8.
Curing rates in the grass sward of the Highland Sourveld in the Natal Drakensburg.Crossref | GoogleScholarGoogle Scholar |

Forestry Canada Fire Danger Group (1992) Development and structure of the Canadian Forest Fire Behavior Prediction System. Information Report ST-X-3, Forestry Canada (Ottawa, ON)

Fosberg MA, Schroeder MJ (1971) ‘Fine herbaceous fuels in fire danger rating.’ USDA Forest Service, Rocky Mountain Forest and Range Experimental Station, Research Note RM-185. (Fort Collins, CO)

Garvey M, Millie S (2000) ‘Grassland curing guide.’ (Community Safety Department, Victorian Country Fire Authority: Melbourne, Vic.)

Hörtensteiner S, Lee DW (2007) Chlorophyll catabolism and leaf coloration. In ‘Annual plant reviews volume 26: senescence processes in plants’. (Ed. S Gan.) pp. 12–31. (Blackwell Publishing: Oxford, UK)

Hothorn T, Bretz F, Westfall P (2008) Simultaneous inference in general parametric models. Biometrical Journal 50, 346–363.
Simultaneous inference in general parametric models.Crossref | GoogleScholarGoogle Scholar | 18481363PubMed |

Keetch JJ, Byram GM (1968) ‘A drought index for forest fire control.’ USDA Forest Service, Research Paper SE-38. (Asheville, NC)

Levy EB, Madden EA (1933) The point method of pasture analysis. New Zealand Journal of Agriculture 46, 267–279.

Luke RH, McArthur AG (1978) ‘Bushfires in Australia.’ (Australian Government Publishing Service: Canberra, ACT)

Martin D, Grant I, Jones S, Anderson S (2009) Development of satellite vegetation indices to assess grassland curing across Australia and New Zealand. In ‘Innovations in remote sensing and photogrammetry’. (Eds S Jones and K Reinke.) pp. 211–227. (Springer-Verlag: Berlin, Germany)

Martin D, Chen T, Nichols D, Bessell R, Kidnie S, Alexander J (2015) Integrating ground and satellite-based observations to determine the degree of grassland curing. International Journal of Wildland Fire 24, 329–339.
Integrating ground and satellite-based observations to determine the degree of grassland curing.Crossref | GoogleScholarGoogle Scholar |

Matthews S (2010) Effect of drying temperature on fuel moisture measurements. International Journal of Wildland Fire 19, 800–802.
Effect of drying temperature on fuel moisture measurements.Crossref | GoogleScholarGoogle Scholar |

McArthur AG (1966) ‘Weather and grassland fire behaviour.’ (Department of National Development, Forestry and Timber Bureau: Canberra, ACT)

McArthur AG (1973) ‘Grassland fire danger meter Mk IV.’ (Forest Research Institute, Forestry and Timber Bureau: Canberra, ACT)

McArthur AG (1977a) ‘Grassland fire danger meter Mk V.’ CSIRO Division of Forest Research Annual Report 1976–1977. (CSIRO: Canberra, ACT)

McArthur AG (1977b) ‘Grassland fire danger meter MkV.’ (Country Fire Authority of Victoria: Melbourne, Vic.)

Millie S, Adams R (1999) Measures of grassland curing: a comparison of destructive sampling with visual and satellite estimates. In ‘Proceedings of the Australian bushfire conference’, July 1999, Albury, NSW. (Eds I. Lunt, D. G. Green) School of Environmental and Information Sciences, Charles Sturt University, pp. 257–263. (Charles Sturt University: Albury, NSW)

Mount AB (1972) ‘The derivation and testing of a soil dryness index using runoff data.’ Bulletin No. 4. (Tasmania Forestry Commission: Hobart, Tas.)

Mutch RW (1967) Cheatgrass coloration: a key to flammability? Journal of Range Management 20, 259–260.
Cheatgrass coloration: a key to flammability?Crossref | GoogleScholarGoogle Scholar |

Newnham GJ, Grant IF, Martin DN, Anderson SAJ (2010) ‘Improved methods for assessment and prediction of grassland curing: satellite based curing methods and mapping.’ Bushfire Cooperative Research Centre Project A1.4 Report. (Bushfire Cooperative Research Centre: Melbourne, Vic.)

Northcote KH, Beckmann GG, Bettenay E, Churchward HM, Van Dijk DC, Dimmock GM, Hubble GD, Isbell RF, McArthur WM, Murtha GG, Nicolls KD, Paton TR, Thompson CH, Webb AA, Wright MJ (1968) ‘Atlas of Australian soils, sheets 1 to 10. With explanatory data.’ (CSIRO and Melbourne University Press: Melbourne, Vic.)

Pairman D, Barens EJ, Fogarty LG (1995) ‘Initial evaluation of satellite derived NDVA to estimate fuel moisture content in grassland.’ New Zealand Forest Research Institute, Project Record Number 5291. (New Zealand Forest Research Institute: Rotorua, New Zealand)

Paltridge GE, Barber J (1988) Monitoring grassland dryness and fire potential in Australia with NOAA/AHRR data. Remote Sensing of Environment 25, 381–394.
Monitoring grassland dryness and fire potential in Australia with NOAA/AHRR data.Crossref | GoogleScholarGoogle Scholar |

Parkes D, Newell G, Cheal D (2003) Assessing the quality of native vegetation: the ‘habitat hectares’ approach. Ecological Management & Restoration 4, 29–38.
Assessing the quality of native vegetation: the ‘habitat hectares’ approach.Crossref | GoogleScholarGoogle Scholar |

Pearce HG, Anderson WR, Fogarty LG, Todoroki C, Anderson SAJ (2010) Linear mixed effects models for estimating biomass and fuel loads in shrublands. Canadian Journal of Forest Research 40, 2015–2026.
Linear mixed effects models for estimating biomass and fuel loads in shrublands.Crossref | GoogleScholarGoogle Scholar |

Pinheiro JC, Bates DM (2000) ‘Mixed-effects models in S and S-PLUS.’ (Springer-Verlag: New York, NY)

Pinheiro J, Bates D, DebRoy S, Sarkar D, R Core Team (2014) ‘nlme: linear and nonlinear mixed effects models. R package version 3.1–117.’ Available at http://CRAN.R-project.org/package=nlme [Verified 5 May 2015]

R Core Team (2014) ‘R: a language and environment for statistical computing.’ (R Foundation for Statistical Computing: Vienna, Austria)

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

Turner H, Firth D (2014) Generalized nonlinear models. Available at http://go.warwick.ac.uk/gnm [Verified 5 May 2015]

Wittich KP (2011) Phenological observation of grass curing in Germany. International Journal of Biometeorology 55, 313–318.
Phenological observation of grass curing in Germany.Crossref | GoogleScholarGoogle Scholar | 20574670PubMed |

Wotton BM, Alexander ME, Taylor SW (2009) Updates and revisions to the 1992 Canadian Forest Fire Behaviour Prediction Systems. Natural Resources Canada, Canadian Forest Service, Great Lakes Forestry Centre, Information Report GLC-X-10. (Sault Ste Marie, ON)