@article {bnh-7475, title = {Exploring the key drivers of forest flammability in wet eucalypt forests using expert-derived conceptual models}, journal = {Landscape Ecology}, volume = {35}, year = {2020}, month = {06/2020}, pages = {1775{\textendash}1798}, abstract = {

Context

Fire behaviour research has largely focused on dry ecosystems that burn frequently, with far less attention on wetter forests. Yet, the impacts of fire in wet forests can be high and therefore understanding the drivers of fire in these\ systems\ is vital.

Objectives

We sought to identify and rank by importance the factors plausibly driving flammability in wet eucalypt forests, and describe relationships between them. In doing so, we formulated a set of research priorities.

Methods

Conceptual models of forest flammability in wet eucalypt forests were elicited from 21 fire experts using a combination of elicitation techniques. Forest flammability was defined using fire occurrence and fireline intensity as measures of ignitability and heat release rate, respectively.

Results

There were shared and divergent opinions about the drivers of flammability in wet eucalypt forests. Widely agreed factors were drought, dead fine fuel moisture content, weather and topography. These factors all influence the availability of biomass to burn, albeit their effects and interactions on various dimensions of flammability are poorly understood. Differences between the models related to lesser understood factors (e.g. live and coarse fuel moisture, plant traits, heatwaves) and the links between factors.

Conclusions

By documenting alternative conceptual models, we made shared and divergent opinions explicit about flammability in wet forests. We identified four priority research areas: (1) quantifying drought and fuel moisture thresholds for fire occurrence and intensity, (2) modelling microclimate in dense vegetation and rugged terrain, (3) determining the attributes of live vegetation that influence forest flammability, (4) evaluating fire management strategies.

}, keywords = {Cognitive mapping, Conceptual models, Expert elicitation, Fire behaviour, fire intensity, flammability, Structured decision-making, Structured expert judgement, Wet forest, Wildfire}, doi = {https://doi.org/10.1007/s10980-020-01055-z}, url = {https://link.springer.com/article/10.1007/s10980-020-01055-z}, author = {Jane Cawson and Victoria Hemming and Ackland, A and Wendy R. Anderson and David Bowman and Ross Bradstock and Brown, T and Jamie Burton and Geoffrey J. Cary and Thomas Duff and Alex Filkov and Furlaud, James M. and Tim Gazzard and Kilinc, Musa and Petter Nyman and Ross Peacock and Mike Ryan and Jason J. Sharples and Gary J. Sheridan and Tolhurst, K.G. and Tim Wells and Phil Zylstra and Trent Penman} } @article {bnh-5648, title = {Developing and testing models of the drivers of anthropogenic and lightning-caused wildfire ignitions in south-eastern Australia}, journal = {Journal of Environmental Management}, volume = {235}, year = {2019}, month = {01/2019}, chapter = {34-41}, abstract = {

Considerable investments are made in managing fire risk to human assets, including a growing use of fire behaviour simulation tools to allocate expenditure. Understanding fire risk requires estimation of the likelihood of ignition, spread of the fire and impact on assets. The ability to estimate and predict risk requires both the development of ignition likelihood models and the evaluation of these models in novel environments. We developed models for natural and anthropogenic ignitions in the south-eastern Australian state of Victoria incorporating variables relating to fire weather, terrain and the built environment. Fire weather conditions had a consistently positive effect on the likelihood of ignition, although they contributed much more to lightning (57\%) and power transmission (55\%) ignitions than the 7 other modelled causes (8{\textendash}32\%). The built environment played an important role in driving anthropogenic ignitions. Housing density was the most important variable in most models and proximity to roads had a consistently positive effect. In contrast, the best model for lightning ignitions included a positive relationship with primary productivity, as represented by annual rainfall. These patterns are broadly consistent with previous ignition modelling studies. The models developed for Victoria were tested in the neighbouring fire prone states of South Australia and Tasmania. The anthropogenic ignition model performed well in South Australia (AUC = 0.969) and Tasmania (AUC = 0.848), whereas the natural ignition model only performed well in South Australia (AUC = 0.972; Tasmania AUC = 0.612). Model performance may have been impaired by much lower lightning ignition rates in South Australia and Tasmania than in Victoria. This study shows that the spatial likelihood of ignition can be reliably predicted based on readily available meteorological and biophysical data. Furthermore, the strong performance of anthropogenic and natural ignition models in novel environments suggests there are some universal drivers of ignition likelihood across south-eastern Australia.

}, keywords = {Bushfire, ignition, Risk modelling, Wildfire}, doi = {https://doi.org/10.1016/j.jenvman.2019.01.055}, url = {https://www.sciencedirect.com/science/article/pii/S0301479719300568}, author = {Hamish Clarke and Rebecca Gibson and Brett Cirulis and Ross Bradstock and Trent Penman} } @article {bnh-6393, title = {Frequency of Dynamic Fire Behaviours in Australian Forest Environments}, journal = {Fire}, volume = {3}, year = {2019}, month = {12/2019}, abstract = {

Wildfires can result in significant social, environmental and economic losses. Fires in which dynamic fire behaviours (DFBs) occur contribute disproportionately to damage statistics. Little quantitative data on the frequency at which DFBs occur exists. To address this problem, we conducted a structured survey using staff from fire and land management agencies in Australia regarding their experiences with DFBs. Staff were asked which, if any, DFBs were observed within fires greater than 1000 ha from the period 2006{\textendash}2016 that they had experience with. They were also asked about the nature of evidence to support these observations. One hundred thirteen fires were identified. Eighty of them had between one and seven DFBs with 73\% (58 fires) having multiple types of DFBs. Most DFBs could commonly be identified through direct data, suggesting an empirical analysis of these phenomena should be possible. Spotting, crown fires and pyro-convective events were the most common DFBs (66\%); when combined with eruptive fires and conflagrations, these DFBs comprise 89\% of all cases with DFBs. Further research should be focused on these DFBs due to their high frequencies and the fact that quantitative data are likely to be available.

}, keywords = {anecdotal data, direct data, dynamic fire behaviours, indirect data, Wildfire}, doi = {https://doi.org/10.3390/fire3010001}, url = {https://www.mdpi.com/2571-6255/3/1/1}, author = {Alex Filkov and Thomas Duff and Trent Penman} } @article {bnh-6856, title = {Quantification of inter-regional differences in risk mitigation from prescribed burning across multiple management values}, journal = {International Journal of Wildland Fire}, volume = {29}, year = {2019}, month = {09/2019}, pages = {414-426}, abstract = {

Fire agencies are moving towards planning systems based on risk assessment; however, knowledge of the most effective way to quantify changes in risk to key values by application of prescribed fire is generally lacking. We present a quantification and inter-regional comparison of how risk to management values responds to variations in prescribed burning treatment rate. Fire simulations were run using the PHOENIX RapidFire fire behaviour simulator for two case study landscapes in interface zones in Tasmania and the Australian Capital Territory (ACT), Australia. A Bayesian network approach used these data to explore the influence of treatment and weather on risk from wildfire. Area burnt, length of powerline damaged and length of road damaged responded more strongly to treatment in the ACT than in Tasmania, whereas treatment mitigated house loss and life loss more strongly in Tasmania than the ACT. The effect of prescribed burning treatment rate on area burnt below minimum tolerable fire interval was similar in each case study landscape. Our study shows that the effectiveness of prescribed burning at mitigating area burnt by wildfire and other key values varies considerably across landscapes and values.

}, keywords = {Bushfire, Climate change, trends, Wildfire, wildland fire}, doi = {https://doi.org/10.1071/WF18135}, url = {https://www.publish.csiro.au/WF/WF18135}, author = {Brett Cirulis and Hamish Clarke and Matthias M. Boer and Trent Penman and Owen Price and Ross Bradstock} } @article {bnh-5615, title = {Quantification of inter-regional differences in risk mitigation from prescribed burning across multiple management values}, journal = {International Journal of Wildland Fire}, year = {2019}, month = {06/2019}, abstract = {

Fire agencies are moving towards planning systems based on risk assessment; however, knowledge of the most effective way to quantify changes in risk to key values by application of prescribed fire is generally lacking. We present a quantification and inter-regional comparison of how risk to management values responds to variations in prescribed burning treatment rate. Fire simulations were run using the PHOENIX RapidFire fire behaviour simulator for two case study landscapes in interface zones in Tasmania and the Australian Capital Territory (ACT), Australia. A Bayesian network approach used these data to explore the influence of treatment and weather on risk from wildfire. Area burnt, length of powerline damaged and length of road damaged responded more strongly to treatment in the ACT than in Tasmania, whereas treatment mitigated house loss and life loss more strongly in Tasmania than the ACT. The effect of prescribed burning treatment rate on area burnt below minimum tolerable fire interval was similar in each case study landscape. Our study shows that the effectiveness of prescribed burning at mitigating area burnt by wildfire and other key values varies considerably across landscapes and values.

}, keywords = {Bushfire, Climate change, trends, Wildfire, wildland fire}, doi = {https://doi.org/10.1071/WF18135}, url = {http://www.publish.csiro.au/WF/WF18135}, author = {Brett Cirulis and Hamish Clarke and Matthias M. Boer and Trent Penman and Owen Price and Ross Bradstock} }