Visual assessments of fuel loads are poorly related to destructively sampled fuel loads in eucalypt forests
Liubov Volkova A C , Andrew L. Sullivan B , Stephen H. Roxburgh B and Christopher J. Weston A
+ Author Affiliations
- Author Affiliations
A Department of Ecosystem and Forest Sciences, Faculty of Science, University of Melbourne, Water Street, Creswick, Vic. 3363, Australia.
B CSIRO Land and Water, GPO Box 1700, Canberra, ACT 2601, Australia.
C Corresponding author. Email: lubav@unimelb.edu.au
International Journal of Wildland Fire 25(11) 1193-1201 https://doi.org/10.1071/WF15223
Submitted: 21 December 2015 Accepted: 7 August 2016 Published: 12 September 2016
Abstract
Fire managers around the world commonly use visual assessment of forest fuels to aid prediction of fire behaviour and plan for hazard reduction burning. In Australia, fuel hazard assessment guides also allow conversion of visual assessments to indicative fuel loads, which is essential for some rate of spread models and calculation of fireline intensity or emissions. The strength of correlation between fuel hazard and destructively sampled (directly measured) fuel load was tested using a comprehensive dataset of >500 points from across a range of eucalypt forests in Australia. Overall, there was poor correlation between the assigned fuel hazard rating and measured biomass for surface, near-surface and elevated fuel components, with a clear tendency for these systems to under-predict fuel load at low hazard ratings, and over-predict it at high hazard ratings. Visual assessment of surface fuels was not statistically different from a random allocation of hazard level. The considerable overlap in fuel load between hazard ratings at higher ranges suggests the need to reduce the number of hazard classes to provide clearer differentiation of fuel hazard. To accurately assess forest fuel condition, improvements in fuel hazard descriptions and calibration of visual assessment with destructively measured fuels is essential.
Additional keywords: fire behaviour, fire hazard, fire management.
References
Barney RJ, Bevins CD, Bradshaw LS (1981) Forest floor fuel loads, depths, and bulk densities in four interior Alaskan cover types. USDA Forest Service, Intermountain Forest and Range Experiment Station, Research Note INT-304. (Fairbanks, AK).Bonham CD (Ed.) (2013) ‘Measurements for terrestrial vegetation.’ (John Wiley & Sons: West Sussex)
Burrows ND, Liddelow GL B W (2015) ‘A guide to estimating fire rate of spread in Spinifex Grasslands of Western Australia (Mk2v2).’ (Science and Conservation Division Department of Parks and Wildlife: Perth)
Catchpole WR, Wheeler CJ (1992) Estimating plant biomass: a review of techniques. Australian Journal of Ecology 17, 121–131.
| Estimating plant biomass: a review of techniques.Crossref | GoogleScholarGoogle Scholar |
Cheney NP, Gould JS, McCaw WL, Anderson WR (2012) Predicting fire behaviour in dry eucalypt forest in southern Australia. Forest Ecology and Management 280, 120–131.
| Predicting fire behaviour in dry eucalypt forest in southern Australia.Crossref | GoogleScholarGoogle Scholar |
Cruz MG, Gould JG (2015) Bushfire fuel classification – top and mid-tier fuel types. National Burning Project: Sub-Project 5 Technical Report. (CSIRO, Canberra; and AFAC, Melbourne)
Davies GM, Hamilton A, Smith A, Legg CJ (2008) Using visual obstruction to estimate heathland fuel load and structure. International Journal of Wildland Fire 17, 380–389.
| Using visual obstruction to estimate heathland fuel load and structure.Crossref | GoogleScholarGoogle Scholar |
Ferster CJ, Coops NC (2014) Assessing the quality of forest fuel loading data collected using public participation methods and smartphones. International Journal of Wildland Fire 23, 585–590.
| Assessing the quality of forest fuel loading data collected using public participation methods and smartphones.Crossref | GoogleScholarGoogle Scholar |
Gosper CR, Yates CJ, Prober SM, Wiehl G (2014) Application and validation of visual fuel hazard assessments in dry Mediterranean-climate woodlands. International Journal of Wildland Fire 23, 385–393.
| Application and validation of visual fuel hazard assessments in dry Mediterranean-climate woodlands.Crossref | GoogleScholarGoogle Scholar |
Gould JS, McCaw WL, Cheney NP, Ellis PF, Matthews S (2007) ‘Field guide: fire in dry eucalypt forest.’ (Ensis–CSIRO: Canberra; and WA Department of Environment and Conservation: Perth)
Gould JS, McCaw WL, Cheney NP (2011) Quantifying fine fuel dynamics and structure in dry eucalypt forest (Eucalyptus marginata) in Western Australia for fire management. Forest Ecology and Management 262, 531–546.
| Quantifying fine fuel dynamics and structure in dry eucalypt forest (Eucalyptus marginata) in Western Australia for fire management.Crossref | GoogleScholarGoogle Scholar |
Hines F, Tolhurst K, Wilson AAG, McCarthy GJ (2010) Overall fuel hazard assessment guide. 4th edn. Department of Sustainability and Environment, Fire and Adaptive Management Report Number 82. (Melbourne)
Keane RE (2013) Describing wildland surface fuel loading for fire management: a review of approaches, methods and systems. International Journal of Wildland Fire 22, 51–62.
| Describing wildland surface fuel loading for fire management: a review of approaches, methods and systems.Crossref | GoogleScholarGoogle Scholar |
Keane RE, Dickinson LJ (2007) The photoload sampling technique: estimating surface fuel loadings from downward-looking photographs of synthetic fuelbeds. USDA Forest Service, Rocky Mountain Research Station, General Technical Report RMRS-GTR-190. (Fort Collins, CO)
Lydersen JM, Collins BM, Knapp EE, Roller GB, Stephens S (2015) Relating fuel loads to overstorey structure and composition in a fire-excluded Sierra Nevada mixed conifer forest. International Journal of Wildland Fire 24, 484–494.
| Relating fuel loads to overstorey structure and composition in a fire-excluded Sierra Nevada mixed conifer forest.Crossref | GoogleScholarGoogle Scholar |
Manly BFJ (Ed) (2001) ‘Randomization, bootstrap and Monte Carlo methods in biology.’ 3rd ed. (Chapman & Hall/CRC: Boca Raton, FL)
Marsden-Smedley J, Anderson W (2011) Fuel load and fuel hazard prediction in Tasmanian dry forest. Report prepared for the Parks and Wildlife Service. (Department of Primary Industries, Parks, Water and Environment: Hobart)
McArthur AG (1967) Fire behaviour in eucalypt forests. Forestry and Timber Bureau Leaflet 107. (Department of National Development: Canberra)
McCarthy GJ, Tolhurst KG (1998) Effectiveness of firefighting first attack operations by the Department of Natural Resources and Environment from 1991/92–1994/95. Fire Management Branch Research Report No. 47. (Victorian Department of Natural Resources and Environment: Melbourne)
McCaw L (1991) Measurement of fuel quantity and structure for bushfire research and management. In ‘Proceedings: Conference on Bushfire Modelling and Fire Danger Rating Systems’, 11–12 July 1988, Canberra, ACT. (Eds NP Cheney, AM Gill) pp. 147–155 (CSIRO: Canberra)
Miehs A, York A, Tolhurst K, Di Stefano J, Bell T (2010) Sampling downed coarse woody debris in fire-prone eucalypt woodlands. Forest Ecology and Management 259, 440–445.
| Sampling downed coarse woody debris in fire-prone eucalypt woodlands.Crossref | GoogleScholarGoogle Scholar |
Ottmar RD, Hardy CC (1989) Stereo photo series for quantifying forest residues in coastal Oregon forests: second-growth Douglas-fir–western hemlock type, western hemlock–Sitka spruce type, and red alder type. USDA Forest Service, Pacific Northwest Research Station, General Technical Report PNW-GTR-231. (Portland, OR)
Ottmar RD, Vihnanek RE (2002) Stereo photo series for quantifying natural fuels, Volume IIa: hardwoods with spruce in Alaska. National Wildfire Coordinating Group. National Interagency Fire Center, PMS 836. NFES 2668. (Boise, ID)
Ottmar RD, Vihnanek RE, Miranda HS, Sato MN, Andrade SMA (2004) Stereo photo series for quantifying biomass for the Cerrado vegetation in Central Brazil. Floresta 34, 109–112.
| Stereo photo series for quantifying biomass for the Cerrado vegetation in Central Brazil.Crossref | GoogleScholarGoogle Scholar |
Plucinski MP (2012) Factors affecting containment area and time of Australian forest fires featuring aerial suppression. Forest Science 58, 390–398.
| Factors affecting containment area and time of Australian forest fires featuring aerial suppression.Crossref | GoogleScholarGoogle Scholar |
Plucinski MP, McCarthy GJ, Hollis JJ, Gould JS (2012) The effect of aerial suppression on the containment time of Australian wildfires estimated by fire management personnel. International Journal of Wildland Fire 21, 219–229.
| The effect of aerial suppression on the containment time of Australian wildfires estimated by fire management personnel.Crossref | GoogleScholarGoogle Scholar |
SEQFBC (2016) ‘Fire training course: overall fuel hazard assessment.’ Available at https://www.eventbrite.com.au/e/seqfbc-overall-fuel-hazard-assessment-2016-1-day-program [Verified 12 May 2016].
Sikkink PG, Keane RE (2008) A comparison of five sampling techniques to estimate surface fuel loading in montane forests. International Journal of Wildland Fire 17, 363–379.
| A comparison of five sampling techniques to estimate surface fuel loading in montane forests.Crossref | GoogleScholarGoogle Scholar |
Standards Australia (2009) AS3959–2009 Construction of buildings in bushfire-prone areas. Available at http://www.as3959.com.au/ [Verified 22 August 2016]
Sullivan AL, McCaw WL, Cruz MG, Matthews S, Ellis PF (2012) Fuel, fire weather and fire behaviour in Australian ecosystems. In ‘Flammable Australia: fire regimes, biodiversity and ecosystems in a changing world.’ (Eds RA Bradstock, AM Gill, RJ Williams) pp. 51–77. (CSIRO Publishing: Melbourne)
Surawski NC, Sullivan AL, Meyer CP, Roxburgh SH, Polglase PJ (2015) Greenhouse gas emissions from laboratory-scale fires in wildland fuels depend on fire spread mode and phase of combustion. Atmospheric Chemistry and Physics 15, 5259–5273.
| Greenhouse gas emissions from laboratory-scale fires in wildland fuels depend on fire spread mode and phase of combustion.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC2MXptlGhurs%3D&md5=6e77c801c7de21155c9cae3ae09ec3b1CAS |
Tolhurst K, Shields B, Chong D (2008) Phoenix: development and application of a bushfire risk management tool. Australian Journal of Emergency Management 23, 47–54.
van Hees W, Mead BR (2000) Ocular estimates of understory vegetation structure in a closed Picea glauca/Betula papyrifera forest. Journal of Vegetation Science 11, 195–200.
| Ocular estimates of understory vegetation structure in a closed Picea glauca/Betula papyrifera forest.Crossref | GoogleScholarGoogle Scholar |
Van Wagner CE (1968) Line intersect method in forest fuel sampling. Forest Science 14, 20–26.
Volkova L, Weston CJ (2013) Redistribution and emission of forest carbon by planned burning in Eucalyptus obliqua (L. Hérit.) forest of south-eastern Australia. Forest Ecology and Management 304, 383–390.
| Redistribution and emission of forest carbon by planned burning in Eucalyptus obliqua (L. Hérit.) forest of south-eastern Australia.Crossref | GoogleScholarGoogle Scholar |
Volkova L, Weston CJ (2015) Carbon loss from planned fires in southeastern Australian dry Eucalyptus forests. Forest Ecology and Management 336, 91–98.
| Carbon loss from planned fires in southeastern Australian dry Eucalyptus forests.Crossref | GoogleScholarGoogle Scholar |
Volkova L, Meyer CP, Murphy S, Fairman T, Reisen F, Weston CJ (2014) Fuel reduction burning mitigates wildfire effects on forest carbon and greenhouse gas emission. International Journal of Wildland Fire 23, 771–780.
| Fuel reduction burning mitigates wildfire effects on forest carbon and greenhouse gas emission.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC2cXhsFKnsrfJ&md5=83704f38b1949297c006d6a36ae9c3ccCAS |
Watson PJ, Penman SH, Bradstock RA (2012) A comparison of bushfire fuel hazard assessors and assessment methods in dry sclerophyll forest near Sydney, Australia. International Journal of Wildland Fire 21, 755–763.
| A comparison of bushfire fuel hazard assessors and assessment methods in dry sclerophyll forest near Sydney, Australia.Crossref | GoogleScholarGoogle Scholar |
Weise DR, Wright CS (2014) Wildland fire emissions, carbon and climate: characterizing wildland fuels. Forest Ecology and Management 317, 26–40.
| Wildland fire emissions, carbon and climate: characterizing wildland fuels.Crossref | GoogleScholarGoogle Scholar |
Wright CS, Ottmar RD, Vihnanek RE, Weise DR (2002) Stereo photo series for quantifying natural fuels: grassland, shrubland, woodland, and forest types in Hawaii. USDA Forest Service, Pacific Northwest Research Station, Technical Report PNW-GTR-545. (Portland, OR)
Wright CS, Ottmar RD, Vihnanek RE (2010) Critique of Sikkink and Keane’s comparison of surface fuel sampling techniques. International Journal of Wildland Fire 19, 374–376.
| Critique of Sikkink and Keane’s comparison of surface fuel sampling techniques.Crossref | GoogleScholarGoogle Scholar |
