TY - JOUR
T1 - Reframing wildfire simulations for understanding complex human-landscape interactions in cross-cultural contexts
T2 - A case study from northern Australia
AU - Fisher, Rohan
AU - Heckbert, Scott
AU - Garnett, Stephen
N1 - Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2021/9
Y1 - 2021/9
N2 - An increase in the frequency of severe fire events, as well as a growing interest in wildfire mitigation strategies, has created a demand for skilled managers of landscape fire and a better community understanding of fire behaviour. While on-ground experience is essential, there is potential to substantially enhance training and community engagement with explanatory simulations. Through this work, we explore landscape fire behaviour as a complex system where understanding key behaviour characteristics is often more important and achievable than prediction. It is argued that this approach has particular value in Northern Australia, where fires burn across vast and sparsely inhabited landscapes that are largely under Indigenous ownership. Land and fire management in such complex cross-cultural contexts requires combining traditional and local knowledge with science and technology to achieve the best outcomes. We describe the workings of the model, a stochastic cellular automata fire behaviour simulation, developed through a participatory modelling approach for Northern Australia; the outputs generated; and a range of operational applications. We found that simulation assisted training and engagement through the development of an understanding of fire dynamics through visualisation, underpinned by landscape data sets, and engaging a culturally diverse set of land managers in discussions of fire management. We conclude that there is scope for a broader use of explanatory fire simulations to support development of shared understandings of fire management objectives.
AB - An increase in the frequency of severe fire events, as well as a growing interest in wildfire mitigation strategies, has created a demand for skilled managers of landscape fire and a better community understanding of fire behaviour. While on-ground experience is essential, there is potential to substantially enhance training and community engagement with explanatory simulations. Through this work, we explore landscape fire behaviour as a complex system where understanding key behaviour characteristics is often more important and achievable than prediction. It is argued that this approach has particular value in Northern Australia, where fires burn across vast and sparsely inhabited landscapes that are largely under Indigenous ownership. Land and fire management in such complex cross-cultural contexts requires combining traditional and local knowledge with science and technology to achieve the best outcomes. We describe the workings of the model, a stochastic cellular automata fire behaviour simulation, developed through a participatory modelling approach for Northern Australia; the outputs generated; and a range of operational applications. We found that simulation assisted training and engagement through the development of an understanding of fire dynamics through visualisation, underpinned by landscape data sets, and engaging a culturally diverse set of land managers in discussions of fire management. We conclude that there is scope for a broader use of explanatory fire simulations to support development of shared understandings of fire management objectives.
KW - Fire spread simulation
KW - Indigenous knowledge
KW - Modelling
KW - Savanna landscapes
UR - http://www.scopus.com/inward/record.url?scp=85114044030&partnerID=8YFLogxK
U2 - 10.3390/fire4030046
DO - 10.3390/fire4030046
M3 - Article
AN - SCOPUS:85114044030
SN - 2571-6255
VL - 4
JO - Fire
JF - Fire
IS - 3
M1 - 46
ER -