A Predictive Model of Leaf Flammability Using Leaf Traits and Radiant Heat Flux for Plants of Fire-Prone Dry Sclerophyll Forest

Krix, DW; Murray, BR

A Predictive Model of Leaf Flammability Using Leaf Traits and Radiant Heat Flux for Plants of Fire-Prone Dry Sclerophyll Forest

Krix, DW Murray, BR

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Publisher:: MDPI AG
Publication Type:: Journal Article
Citation:: Forests, 2022, 13, (2), pp. 152
Issue Date:: 2022-01-20

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Field	Value	Language
dc.contributor.author	Krix, DW
dc.contributor.author	Murray, BR
dc.date.accessioned	2022-02-11T04:07:27Z
dc.date.available	2022-02-11T04:07:27Z
dc.date.issued	2022-01-20
dc.identifier.citation	Forests, 2022, 13, (2), pp. 152
dc.identifier.issn	1999-4907
dc.identifier.issn	1999-4907
dc.identifier.uri	http://hdl.handle.net/10453/154402
dc.description.abstract	<jats:p>The differential flammability of individual plant species in landscape-scale fire behaviour is an important consideration, but one that is often overlooked. This is in part due to a relative dearth in the availability of plant flammability data. Here, we present a highly accurate predictive model of the likelihood of plant leaves entering flaming combustion as a function of leaf mass per area (LMA), leaf area (LA) and radiant heat flux using species of fire-prone dry sclerophyll forests of south-eastern Australia. We validated the performance of the model on two separate datasets, and on plant species not included in the model building process. Our model gives accurate predictions (75–84%) of leaf flaming with potential application in the next generation of fire behaviour models. Given the global wealth of species’ data for LMA and LA, in stark contrast to leaf flammability data, our model has the potential to improve understanding of forest flammability in the absence of leaf flammability information.</jats:p>
dc.language	en
dc.publisher	MDPI AG
dc.relation.ispartof	Forests
dc.relation.isbasedon	10.3390/f13020152
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	0602 Ecology, 0607 Plant Biology, 0705 Forestry Sciences
dc.title	A Predictive Model of Leaf Flammability Using Leaf Traits and Radiant Heat Flux for Plants of Fire-Prone Dry Sclerophyll Forest
dc.type	Journal Article
utslib.citation.volume	13
utslib.for	0602 Ecology
utslib.for	0607 Plant Biology
utslib.for	0705 Forestry Sciences
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Life Sciences
utslib.copyright.status	open_access	*
dc.date.updated	2022-02-11T04:07:23Z
pubs.issue	2
pubs.publication-status	Published online
pubs.volume	13
utslib.citation.issue	2

Abstract:

The differential flammability of individual plant species in landscape-scale fire behaviour is an important consideration, but one that is often overlooked. This is in part due to a relative dearth in the availability of plant flammability data. Here, we present a highly accurate predictive model of the likelihood of plant leaves entering flaming combustion as a function of leaf mass per area (LMA), leaf area (LA) and radiant heat flux using species of fire-prone dry sclerophyll forests of south-eastern Australia. We validated the performance of the model on two separate datasets, and on plant species not included in the model building process. Our model gives accurate predictions (75–84%) of leaf flaming with potential application in the next generation of fire behaviour models. Given the global wealth of species’ data for LMA and LA, in stark contrast to leaf flammability data, our model has the potential to improve understanding of forest flammability in the absence of leaf flammability information.

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http://hdl.handle.net/10453/154402