Biophysical mechanistic modelling quantifies the effects of plant traits on fire severity : species, not surface fuel loads, determine flame dimensions in eucalypt forests

Philip Zylstra; Ross A. Bradstock; Michael Bedward; Trent D. Penman; Michael D. Doherty; Rodney O. Weber; A. Malcolm Gill; Geoffrey J. Cary

doi:10.1371/journal.pone.0160715

Biophysical mechanistic modelling quantifies the effects of plant traits on fire severity : species, not surface fuel loads, determine flame dimensions in eucalypt forests

Philip Zylstra, Ross A. Bradstock, Michael Bedward, Trent D. Penman, Michael D. Doherty, Rodney O. Weber, A. Malcolm Gill, Geoffrey J. Cary

Western Sydney University

Research output: Contribution to journal › Article › peer-review

100 Citations (Scopus)

Abstract

The influence of plant traits on forest fire behaviour has evolutionary, ecological and management implications, but is poorly understood and frequently discounted. We use a process model to quantify that influence and provide validation in a diverse range of eucalypt forests burnt under varying conditions. Measured height of consumption was compared to heights predicted using a surface fuel fire behaviour model, then key aspects of our model were sequentially added to this with and without species-specific information. Our fully specified model had a mean absolute error 3.8 times smaller than the otherwise identical surface fuel model (p < 0.01), and correctly predicted the height of larger (≥1 m) flames 12 times more often (p < 0.001). We conclude that the primary endogenous drivers of fire severity are the species of plants present rather than the surface fuel load, and demonstrate the accuracy and versatility of the model for quantifying this.

Original language	English
Article number	e0160715
Number of pages	24
Journal	PLoS One
Volume	11
Issue number	8
DOIs	https://doi.org/10.1371/journal.pone.0160715
Publication status	Published - 2016

Open Access - Access Right Statement

© 2016 Zylstra et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Zylstra, P., Bradstock, R. A., Bedward, M., Penman, T. D., Doherty, M. D., Weber, R. O., Gill, A. M., & Cary, G. J. (2016). Biophysical mechanistic modelling quantifies the effects of plant traits on fire severity : species, not surface fuel loads, determine flame dimensions in eucalypt forests. PLoS One, 11(8), Article e0160715. https://doi.org/10.1371/journal.pone.0160715

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abstract = "The influence of plant traits on forest fire behaviour has evolutionary, ecological and management implications, but is poorly understood and frequently discounted. We use a process model to quantify that influence and provide validation in a diverse range of eucalypt forests burnt under varying conditions. Measured height of consumption was compared to heights predicted using a surface fuel fire behaviour model, then key aspects of our model were sequentially added to this with and without species-specific information. Our fully specified model had a mean absolute error 3.8 times smaller than the otherwise identical surface fuel model (p < 0.01), and correctly predicted the height of larger (≥1 m) flames 12 times more often (p < 0.001). We conclude that the primary endogenous drivers of fire severity are the species of plants present rather than the surface fuel load, and demonstrate the accuracy and versatility of the model for quantifying this.",

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AU - Bedward, Michael

AU - Penman, Trent D.

AU - Doherty, Michael D.

AU - Weber, Rodney O.

AU - Gill, A. Malcolm

AU - Cary, Geoffrey J.

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AB - The influence of plant traits on forest fire behaviour has evolutionary, ecological and management implications, but is poorly understood and frequently discounted. We use a process model to quantify that influence and provide validation in a diverse range of eucalypt forests burnt under varying conditions. Measured height of consumption was compared to heights predicted using a surface fuel fire behaviour model, then key aspects of our model were sequentially added to this with and without species-specific information. Our fully specified model had a mean absolute error 3.8 times smaller than the otherwise identical surface fuel model (p < 0.01), and correctly predicted the height of larger (≥1 m) flames 12 times more often (p < 0.001). We conclude that the primary endogenous drivers of fire severity are the species of plants present rather than the surface fuel load, and demonstrate the accuracy and versatility of the model for quantifying this.

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Biophysical mechanistic modelling quantifies the effects of plant traits on fire severity : species, not surface fuel loads, determine flame dimensions in eucalypt forests

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