@inbook {bnh-8357, title = {Wildland fire}, booktitle = {Handbook of Fire and the Environment }, volume = {The Society of Fire Protection Engineers Series}, year = {2022}, publisher = {Springer}, organization = {Springer}, chapter = {Wildland Fire}, address = {Cham}, abstract = {

Wildfires, and their associated management activities, can have complex social, economic, and environmental impacts. This chapter highlights some of the key impacts of wildfires in six sections. The first section about community focuses on relationships between recent destructive wildfires around the globe and losses to life and property. It also presents the main mechanisms of house loss in the Wildland-Urban Interface. Following that, a section about biodiversity impacts describes the major effects of wildfires and associated fire regimes on plants and animals, underlining both negative and positive effects. Then, the focus shifts to soil and water with a section that highlights how wildfires can have serious implications for downstream water quality and yield, posing a threat to water security for the people and aquatic wildlife. This is followed by a section about air quality, which describes the effect of wildfires on visibility, human health and their contribution to climate change. The next section highlights the role of dynamic fire behaviours that lead to the most severe impacts, describing the fire behaviours themselves and their frequency of occurrence. The chapter closes with a case study describing the extreme impacts of the 2019/2020 fire season in south-eastern Australia on people and the environment.

}, isbn = {978-3-030-94356-1}, doi = {https://doi.org/10.1007/978-3-030-94356-1_7}, url = {https://link.springer.com/chapter/10.1007/978-3-030-94356-1_7}, author = {Alex Filkov and Jane Cawson and Matthew Swan and Trent Penman} } @article {bnh-7343, title = {Effect of weather forecast errors on fire growth model projections}, journal = {International Journal of Wildland Fire}, year = {2020}, month = {08/2020}, abstract = {

Fire management agencies use fire behaviour simulation tools to predict the potential spread of a fire in both risk planning and operationally during wildfires. These models are generally based on underlying empirical or quasi-empirical relations and rarely are uncertainties considered. Little attention has been given to the quality of the input data used during operational fire predictions. We examined the extent to which error in weather forecasts can affect fire simulation results. The study was conducted using data representing the State of Victoria in south-eastern Australia, including grassland and forest conditions. Two fire simulator software packages were used to compare fire growth under observed and forecast weather. We found that error in the weather forecast data significantly altered the predicted size and location of fires. Large errors in wind speed and temperature resulted in an overprediction of fire size, whereas large errors in wind direction resulted in an increased spatial error in the fire{\textquoteright}s location. As the fire weather intensified, fire predictions using forecast weather under predicted fire size, potentially resulting in greater risks to the community. These results highlight the importance of on-ground intelligence during wildfires and the use of ensembles to improve operational fire predictions.

}, keywords = {Bayesian Network, fire prediction, meteorological forecast, sensitivity, simulation}, doi = {https://doi.org/10.1071/WF19199}, url = {https://www.publish.csiro.au/wf/wf19199}, author = {Trent Penman and Dan Ababei and Jane Cawson and Brett Cirulis and Thomas Duff and Swedosh, W and James Hilton} } @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-7708, title = {Leaf traits predict global patterns in the structure and flammability of forest litter beds}, journal = {Journal of Ecology}, year = {2020}, month = {12/2020}, abstract = {
  1. Fallen plant material such as leaves, needles and branches form litter beds which strongly influence fire ignition and spread. Traits of the dominant species influence litter flammability directly by determining how individual leaves burn and indirectly through the structure of the litter bed. However, we are yet to determine the relative importance of these different drivers across a range of plant species from different biomes.
  2. We undertook a meta-analysis, combining leaf trait, litter structure and flammability data for 106 species from North America, South America, Europe, Asia and Australia. The dataset encompassed broad-leaved and coniferous species from seven different experimental studies. Relationships between leaf traits, litter structure and key flammability metrics{\textemdash}sustainability, combustibility and consumability{\textemdash}were analysed using bivariate and piecewise structural equation modelling (SEM).
  3. Traits which characterise the three-dimensional nature of the leaf and how much space a leaf occupies showed much stronger associations to litter structure and flammability than other morphological traits. Leaf curl, surface area to volume ratio (SAV) and SLA predominately influence litter flammability indirectly via litter structure with SLA being the only leaf trait which had a negative direct effect on flame duration. Packing ratio and bulk density were influenced by different combinations of leaf traits and, in turn, they aligned with different flammability metrics. Bulk density predicted flame spread rate and flame duration whereas packing ratio predicted consumption.
  4. Synthesis. We identified key leaf and litter traits which influence different components of litter bed flammability. Importantly, we show that the effects of these leaf and litter traits are consistent across a wide range of taxa and biomes. Our study represents a significant step towards developing trait-based models for predicting surface wildfire behaviour. Such models will more flexibly accommodate future shifts in the composition of plant species triggered by altered fire regimes and climate change.
}, keywords = {Fire behaviour, flammability, leaf traits, litter properties, meta-analysis, surface fuel}, doi = {https://doi.org/10.1111/1365-2745.13561}, url = {https://besjournals.onlinelibrary.wiley.com/doi/full/10.1111/1365-2745.13561}, author = {Jamie Burton and Jane Cawson and Alex Filkov and Trent Penman} }