Improved logistic models of crown fire probability in Canadian conifer forests

Daniel D. B. Perrakis; Miguel G. Cruz; Martin E. Alexander; Chelene C. Hanes; Dan K. Thompson; Stephen W. Taylor; Brian J. Stocks

doi:10.1071/WF23074

RESEARCH ARTICLE (Open Access)

Previous Next Contents Vol 32(10)

Improved logistic models of crown fire probability in Canadian conifer forests

Daniel D. B. Perrakis

^A ^B ^* , Miguel G. Cruz

^C , Martin E. Alexander ^D , Chelene C. Hanes ^E , Dan K. Thompson ^E , Stephen W. Taylor ^A and Brian J. Stocks ^F

+ Author Affiliations

- Author Affiliations

^A Natural Resources Canada - Canadian Forest Service, 506 West Burnside Road, Victoria, BC V8P 1Z5, Canada.

^B Department of Geography, University of Victoria, Victoria, BC V8P 5C2, Canada.

^C CSIRO, GPO Box 1700, Canberra, ACT 2601, Australia.

^D Wild Rose Fire Behaviour, 180–50434 Range Road 232, Leduc County, AB T4X 0L1, Canada.

^E Natural Resources Canada - Canadian Forest Service, 1219 Queen Street East, Sault Ste. Marie, ON P6A 2E5, Canada.

^F B.J. Stocks Wildfire Investigations Ltd., 128 Chambers Avenue, Sault Ste. Marie, ON P6A 4V4, Canada.

^* Correspondence to: Daniel.Perrakis@nrcan-rncan.gc.ca

International Journal of Wildland Fire 32(10) 1455-1473 https://doi.org/10.1071/WF23074
Submitted: 12 May 2023 Accepted: 8 August 2023 Published: 25 August 2023

© 2023 The Author(s) (or their employer(s)). Published by CSIRO Publishing on behalf of IAWF. This is an open access article distributed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND)

Abstract

Background

Crown fires are an ecologically necessary but hazardous process in conifer forests. Prediction of their behaviour in Canada has largely depended on the Canadian Forest Fire Behaviour Prediction System, in which fire weather indices drive primarily fixed fuel type models. The Crown Fire Initiation and Spread (CFIS) system presents a more flexible approach to predicting crown fire occurrence than fixed fuel type models.

Aims

Using a multi-decadal database of experimental fires carried out in conifer plots (1960–2019, n = 113), our aim was to develop updated models based on the CFIS system approach, fitting crown fire occurrence models to fire environment variables using logistic regression.

Methods

We tested alternative fuel moisture estimates and compared various model forms using repeated cross-validation. In two-storeyed stands, crown fire occurrence was defined as the involvement of lower canopy stratum fuels.

Key results

Final models based on wind speed, fuel strata gap, litter moisture and surface fuel consumption predicted crowning events correctly in up to 92% of cases in training data (89% in cross-validation).

Conclusions and implications

These new models offer improved accuracy and flexibility that will help users assess how competing environmental factors interact under different fuel treatments and wildfire scenarios.

Keywords: Canadian Forest Fire Behaviour Prediction (FBP) System, Canadian Forest Fire Weather Index (FWI) System, Crown Fire Initiation and Spread (CFIS) system, crown fire occurrence, experimental burning, modelling, wildfire management, wildland fire behaviour.

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