Modelling initial attack success on forest fires suppressed by air attack in the province of Ontario, Canada
Melanie Wheatley A * , B. Mike Wotton A B , Douglas G. Woolford C , David L. Martell A and Joshua M. Johnston B
+ Author Affiliations
- Author Affiliations
A Institute of Forestry and Conservation, John H. Daniels Faculty of Architecture, Landscape and Design, University of Toronto, Toronto, ON M5S 3B3, Canada.
B Great Lakes Forestry Centre, Canadian Forest Service, Natural Resources Canada, Sault Ste Marie, ON P6A 2E5, Canada.
C Department of Statistical and Actuarial Sciences, University of Western Ontario, London, ON N6A 5B7, Canada.
* Correspondence to: melanie.wheatley@mail.utoronto.ca
International Journal of Wildland Fire 31(8) 774-785 https://doi.org/10.1071/WF22006
Submitted: 20 January 2022 Accepted: 21 June 2022 Published: 13 July 2022
© 2022 The Author(s) (or their employer(s)). Published by CSIRO Publishing on behalf of IAWF.
Abstract
Airtankers are often used on initial attack (IA) to suppress unwanted wildland fires quickly and contain them before they grow large. Skimmer airtankers are commonly used in the province of Ontario owing to its abundance of waterbodies. We examined the influence of airtanker use on IA success on fires actioned by air attack in Ontario using historical fire records and developed three statistical models to estimate the probability of IA success using information available at three different times during the fire response process. These models include information available to the fire management agency at the time the fire was reported, when IA began and during the IA suppression operations. Our findings indicate that the situational information about a fire obtained during IA provides better estimates of the probability of IA success, as demonstrated by increases in the predictive accuracy and area under the receiver operating characteristic curve compared with a model that is based only on information available at the time a fire is reported. Our results can inform pre-suppression planning and suppression resource allocation decision-making, particularly on days during which many new fires are expected to be reported.
Keywords: aerial suppression, airtankers, fire behaviour, fire containment, fire management, fire suppression effectiveness, fire weather indices, logistic regression.
References
Arienti MC, Cumming SG, Boutin S (2006) Empirical models of forest fire initial attack success probabilities: The effects of fuels, anthropogenic linear features, fire weather, and management. Canadian Journal of Forest Research 36, 3155–3166.| Empirical models of forest fire initial attack success probabilities: The effects of fuels, anthropogenic linear features, fire weather, and management.Crossref | GoogleScholarGoogle Scholar |
Beverly JL (2017) Time since prior wildfire affects subsequent fire containment in black spruce. International Journal of Wildland Fire 26, 919–929.
| Time since prior wildfire affects subsequent fire containment in black spruce.Crossref | GoogleScholarGoogle Scholar |
Brier GW (1950) Verification of forecasts expressed in terms of probability. Monthly weather review 78, 1–3.
| Verification of forecasts expressed in terms of probability.Crossref | GoogleScholarGoogle Scholar |
British Columbia Wildfire Service (2021) Wildfire rank, fire characteristics. Available at https://www2.gov.bc.ca/gov/content/safety/wildfire-status/wildfire-response/about-wildfire/wildfire-rank [Verified 05 July 2022]
Brown AA, Davis KP (1973) ‘Forest fire: control and use.’ (McGraw-Hill Book Company: New York, USA)
Calkin DE, Gebert KM, Jones JG, Neilson RP (2005) Forest service large fire area burned and suppression expenditure trends, 1970–2002. Journal of Forestry 103, 179–183.
| Forest service large fire area burned and suppression expenditure trends, 1970–2002.Crossref | GoogleScholarGoogle Scholar |
Calkin DE, Stonesifer CS, Thompson MP, McHugh CW (2014) Large airtanker use and outcomes in suppressing wildland fires in the United States. International Journal of Wildland Fire 23, 259–271.
| Large airtanker use and outcomes in suppressing wildland fires in the United States.Crossref | GoogleScholarGoogle Scholar |
Calkin DE, Thompson MP, Finney MA (2015) Negative consequences of positive feedbacks in US wildfire management. Forest Ecosystems 2, 1–10.
| Negative consequences of positive feedbacks in US wildfire management.Crossref | GoogleScholarGoogle Scholar |
Cardil A, Lorente M, Boucher D, Boucher J, Gauthier S (2019) Factors influencing fire suppression success in the province of Quebec (Canada). Canadian Journal of Forest Research 49, 531–542.
| Factors influencing fire suppression success in the province of Quebec (Canada).Crossref | GoogleScholarGoogle Scholar |
CIFFC (Canadian Interagency Forest-Fire Center) (2021) Canadian wildland fire glossary. Available at www.ciffc.ca/sites/default/files/2021-03/CWFM_glossary_v2021-03-18-EN.pdf [Verified 24 September 2021]
Collins KM, Price OF, Penman TD (2018) Suppression resource decisions are the dominant influence on containment of Australian forest and grass fires. Journal of Environmental Management 228, 373–382.
| Suppression resource decisions are the dominant influence on containment of Australian forest and grass fires.Crossref | GoogleScholarGoogle Scholar | 30243073PubMed |
Finney M, Grenfell IC, McHugh CW (2009) Modeling containment of large wildfires using generalized linear mixed-model analysis. Forest Science 55, 249–255.
| Modeling containment of large wildfires using generalized linear mixed-model analysis.Crossref | GoogleScholarGoogle Scholar |
Forestry Canada Fire Danger Group (1992) Development of the Canadian forest fire behavior prediction system. Information Report ST-X-3. Available at https://cfs.nrcan.gc.ca/publications?id=10068 [Verified 24 September 2021]
Gordon (2014) Developing more common language, terminology and data standards for wildland fire management in Canada. Available at https://www.ciffc.ca/sites/default/files/2019-03/Developing_More_Common_Terminolgy_-_Final_Report.pdf [Verified 23 November 2021]
Hanes CC, Wang X, Jain P, Parisien MA, Little JM, Flannigan MD (2019) Fire-regime changes in Canada over the last half century. Canadian Journal of Forest Research 49, 256–269.
| Fire-regime changes in Canada over the last half century.Crossref | GoogleScholarGoogle Scholar |
Hirsch KG, Corey PN, Martell DL (1998) Using expert judgment to model initial attack fire crew effectiveness. Forest Science 44, 539–549.
| Using expert judgment to model initial attack fire crew effectiveness.Crossref | GoogleScholarGoogle Scholar |
Hosmer DW, Lemeshow S, Sturdivant, RX (2013) ‘Applied Logistic Regression’, 3rd edn. (John Wiley & Sons)
Katuwal H, Hand MS, Thompson M, Stonesifer C, Calkin D (2018) Predict and attack (or don’t): an econometric approach to large wildfire early detection and suppression effectiveness. Paper presented at the 2018 Agricultural and Applied Economics Association Annual Meeting, Washington, DC, August 5–7. Available at https://www.fs.fed.us/rm/pubs_journals/2018/rmrs_2018_katuwal_h001.pdf [Verified 23 March 2022]
Keating EG, Morral AR, Price CC, Woods D, Norton D, Panis C, Saltzman E, Sanchez R (2012) ‘Air attack against wildfires: understanding US Forest Service requirements for large aircraft.’ (RAND Corporation) Available at http://www.rand.org/content/dam/rand/pubs/monographs/2012/RAND_MG1234.pdf [Verified 24 March 2022]
McCarthy GJ (2003) Effectiveness of aircraft operations by the Department of Natural Resources and Environment and The Country Fire Authority 1997-98. Research Report No. 52. Available at https://ffm.vic.gov.au/__data/assets/pdf_file/0010/21061/Report-52-Effectiveness-of-Aircraft-Operations-by-the-Department-of-Natural-Resources-and-Environment-and.pdf [Verified 24 September 2021]
Merrill D, Alexander M (1987) Glossary of Forest Fire Management Terms. Canadian Committee on Forest Fire Management, National Research Council of Canada, Ottawa, ON. Pub NRCC No. 26516.
Murphy PJ, Woodard PM, Quintilio D, Titus SJ (1991) Exploratory analysis of the variables affecting initial attack hot-spotting containment rate. Canadian Journal of Forest Research 21, 540–544.
| Exploratory analysis of the variables affecting initial attack hot-spotting containment rate.Crossref | GoogleScholarGoogle Scholar |
Nychka D, Furrer R, Paige J, Sain S (2017) fields: Tools for spatial data (R package version 10.3).
| Crossref |
Ontario Ministry of Natural Resources (2004) ‘Forest Fire Management Strategy for Ontario.’ (Queen’s Printer for Ontario: Toronto, ON, Canada)
Ontario Ministry of Natural Resources and Forestry (2014) ‘Wildland Fire Management Strategy.’ (Queen’s Printer for Ontario: Toronto, ON, Canada) Available at https://www.ontario.ca/page/wildland-fire-management-strategy [Verified 24 March 2022]
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 (2019a) Contain and control: wildfire suppression effectiveness at incidents and across landscapes. Current Forestry Reports 5, 20–40.
| Contain and control: wildfire suppression effectiveness at incidents and across landscapes.Crossref | GoogleScholarGoogle Scholar |
Plucinski MP (2019b) Fighting flames and forging firelines: wildfire suppression effectiveness at the fire edge. Current Forestry Reports 5, 1–19.
| Fighting flames and forging firelines: wildfire suppression effectiveness at the fire edge.Crossref | GoogleScholarGoogle Scholar |
Plucinski MP, Gould J, McCarthy G, Hollis J (2007) ‘The effectiveness of aerial firefighting in Australia.’ (Bushfire CRC: Melbourne, Vic., Australia)
Podur J, Martell DL (2007) A simulation model of the growth and suppression of large forest fires in Ontario. International Journal of Wildland Fire 16, 285–294.
| A simulation model of the growth and suppression of large forest fires in Ontario.Crossref | GoogleScholarGoogle Scholar |
R Core Team (2021) ‘R: A language and environment for statistical computing.’ (R Foundation for Statistical Computing: Vienna, Austria) Available at https://www.r-project.org/ [Verified 24 September 2021]
Reimer J, Thompson DK, Povak N (2019) Measuring initial attack suppression effectiveness through burn probability. Fire 2, 60
| Measuring initial attack suppression effectiveness through burn probability.Crossref | GoogleScholarGoogle Scholar |
Stocks BJ, Mason JA, Todd JB, Bosch EM, Wotton BM, Amiro BD, Flannigan MD, Hirsch KG, Logan KA, Martell DL, Skinner WR (2002) Large forest fires in Canada, 1959–1997. Journal of Geophysical Research 108, 8149
| Large forest fires in Canada, 1959–1997.Crossref | GoogleScholarGoogle Scholar |
Stonesifer CS, Calkin DE, Thompson MP, Stockmann KD (2016) Fighting fire in the heat of the day: an analysis of operational and environmental conditions of use for large airtankers in United States fire suppression. International Journal of Wildland Fire 25, 520–533.
| Fighting fire in the heat of the day: an analysis of operational and environmental conditions of use for large airtankers in United States fire suppression.Crossref | GoogleScholarGoogle Scholar |
Stonesifer CS, Calkin DE, Thompson MP, Belval EJ (2021) Is this flight necessary? The Aviation Use Summary (AUS): A framework for strategic, risk-informed aviation decision support. Forests 12, 1078
| Is this flight necessary? The Aviation Use Summary (AUS): A framework for strategic, risk-informed aviation decision support.Crossref | GoogleScholarGoogle Scholar |
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.
| Do one percent of forest fires cause ninety-nine percent of the damage?Crossref | GoogleScholarGoogle Scholar |
Thompson MP, Calkin DE, Herynk J, McHugh CW, Short KC (2013) Airtankers and wildfire management in the US Forest Service: examining data availability and exploring usage and cost trends. International Journal of Wildland Fire 22, 223–233.
| Airtankers and wildfire management in the US Forest Service: examining data availability and exploring usage and cost trends.Crossref | GoogleScholarGoogle Scholar |
Tremblay PO, Duchesne T, Cumming SG (2018) Survival analysis and classification methods for forest fire size. PLoS One 13, 1–16.
| Survival analysis and classification methods for forest fire size.Crossref | GoogleScholarGoogle Scholar |
USDA Forest Service (2015) The rising cost of wildfire operations: effects on the forest service’s non-fire work. August 2015. (USDA Forest Service: Washington, DC) Available at https://www.fs.usda.gov/sites/default/files/2015-Fire-Budget-Report.pdf [Verified 23 March 2022]
USDA Forest Service (2020) Aerial firefighting use and effectiveness (AFUE) Report. (USDA Forest Service: Washington, DC) Available at https://www.fs.usda.gov/sites/default/files/2020-08/08242020_afue_final_report.pdf [Verified 31 March 2022]
Van Wagner CE (1987) Development and structure of the Canadian forest fire weather index system. Forestry Technical Report. (Canadian Forest Service: Ottawa, Canada)
Youden WJ (1950) Index for rating diagnostic tests. Cancer 3, 32–35.
| Index for rating diagnostic tests.Crossref | GoogleScholarGoogle Scholar | 15405679PubMed |
