@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 {BF-4289, title = {Testing existing models for predicting hourly variation in fine fuel moisture in eucalypt forests}, journal = {Forest Ecology and Management}, volume = {306}, year = {2013}, month = {10/2013}, pages = {202-215}, chapter = {202}, abstract = {Several days of hourly fuel moisture sampling were carried out in Southern Tasmania in dry and damp eucalyptus forest to test fuel moisture prediction models used in Australia, and to provide information on equilibrium moisture content and response time for use in more complex models. Moisture contents of near surface, surface, profile litter and bark fuels were measured, along with standard weather variables. On one set of four consecutive days fuel temperatures were also measured with thermocouples. One of the simple empirical fuel moisture prediction models worked well on the litter fuels for which it was intended, but another of the simple models in common use, predicted poorly, particularly on the damp site. One of the simple models was modified, and gave acceptable predictions for profile litter. Another simple model was calibrated to give good predictions for near surface, bark and litter fuels in the middle of the day. A more physically-based {\textquoteleft}bookkeeping{\textquoteright} model for estimating response time and EMC worked very well on all strata but the litter profile. Response times of all fuel strata were of the order of 1 h. A process based model worked slightly better than the EMC estimation model for near surface, litter and bark fuel and considerably better for profile litter, especially on the damp site. On the whole these models performed better than the simple empirical models, but they were tuned to various degrees by site information.}, keywords = {Bookkeeping model, Eucalyptus forest, Fine fuel moisture, Process-based model}, doi = {http://dx.doi.org/10.1016/j.foreco.2013.06.033}, url = {http://www.sciencedirect.com/science/article/pii/S0378112713004015}, author = {Slijepcevic, A. and Wendy R. Anderson and Stuart Matthews} } @article {BF-3146, title = {Changes in behaviour of fire in dry eucalypt forest as fuel increases with age}, journal = {Forest Ecology and Management}, volume = {271}, year = {2012}, month = {5/2012}, pages = {170 - 181}, abstract = {This paper describes the conduct and results of a series of high-intensity experimental fires in dry eucalypt forest under summer conditions of high fire danger. Simultaneous experimental fires were conducted at two locations with contrasting understorey and fuel structures that had developed over periods of 2{\textendash}22 years after prescribed burning. Fuel characteristics (load, height, and visual scores that gave a numerical rating of structure) and wind speed were correlated with fire spread, flame height, firebrand density and spotting distance, all of which increased with time since the last fire. The near-surface layer was the dominant stratum affecting headfire rate of spread during these experiments and provided a common descriptor for fuel types that were visually very different because of the characteristics of the understorey shrubs. Visual hazard scores that reflected the quantity and arrangement of surface and near-surface fuel were more strongly correlated with most fire behaviour variables than were the corresponding fuel load variables. Visual ratings of fuel structure should be suitable to include in algorithms to predict fire behaviour and fire threat.}, issn = {03781127}, doi = {10.1016/j.foreco.2012.02.003}, author = {Lachlan W. McCaw and J.S. Gould and Phillip Cheney, N. and Ellis, Peter and Wendy R. Anderson} } @article {BF-3467, title = {Fire behaviour modelling in semi-arid mallee-heath shrublands of southern Australia}, journal = {Environmental Modelling \& Software}, year = {2012}, month = {8/2012}, abstract = {Knowledge of fire behaviour potential is necessary for proactive management of fire prone shrublands. Data from two experimental burning programs in mallee-heath shrublands in semi-arid southern Australia were used to develop models for the sustainability of fire spread, fire type, i.e., surface or crown fire, forward spread rate and flame height. The dataset comprised 61 fires burned under a wide range of weather conditions. Rates of fire spread and fireline intensity varied between 4 and 55 m min-1 and 735 and 17,200 kW m-1 respectively. Likelihood of sustained fire spread and active crown fire propagation were modelled using logistic regression analysis. Fire spread sustainability was primarily a function of litter fuel moisture content with wind speed having a secondary but still significant effect. The continuity of fine fuels close to ground level was also significant. Onset of active crowning was mostly determined by wind speed. Rate of fire spread was modelled separately for surface and crown fires through nonlinear regression analysis with wind speed, litter fuel moisture content and overstorey canopy cover as significant variables. Flame height was modelled as a function of fireline intensity. A model system to predict the full range of fire behaviour in mallee-heath shrubland is proposed relying on a combined method that links the surface and crown fire rate of spread models. This model system was evaluated against independent data from large scale prescribed burns and wildfires with encouraging results. The best models for fire-spread sustainability and active crown fire propagation predicted correctly 75\% and 79\% respectively of the fires in the evaluation dataset. Rate of spread models produced mean absolute percent errors between 53\% and 58\% with only small bias. The models have applicability in planning and conducting prescribed fire operations but can also be extended to produce first order predictions of wildfire behaviour.}, issn = {13648152}, doi = {10.1016/j.envsoft.2012.07.003}, author = {Cruz, Miguel G. and Lachlan W. McCaw and Wendy R. Anderson and J.S. Gould} } @article {BF-3262, title = {Predicting fire behaviour in dry eucalypt forest in southern Australia}, journal = {Forest Ecology and Management}, volume = {280}, year = {2012}, month = {9/2012}, pages = {120 - 131}, abstract = {This paper describes the development of two empirical models to predict the potential spread of an established line of fire in dry eucalypt forest with a shrubby understorey. These models use inputs of fine fuel moisture, wind speed, near-surface fuel height, and either a numerical fuel hazard score or a descriptive fuel rating for the surface and near-surface fuel. A model to predict flame height from rate of spread and elevated fuel height is also presented as a guide to suppression difficulty. Models were developed using data from a series of simultaneous experimental fires in fuels of different fuel ages ranging from 2 to 22 years since last fire. They were tested against data from independent experimental fires and well documented wildfires that were assigned reliability ratings for fuel, weather and spread rate. Models performed reliably when the reliability of wildfire data ratings for fuel and weather were also high. Models predict the potential rate of spread and are likely to over-predict the spread of fires starting from a point ignition during the early stages of development when the headfire is less than 120 m wide. Existing guides should be used for prescribed burning operations based on point ignition, and the models described here can be used to predict rate of spread from line ignition. Predictions from the new models will be more reliable when rate of spread is averaged over an interval of 30 min or longer. The reliability will be low when compared to observations made over short time intervals, at specific points in the topography, or when very large fires interact to produce wind speeds that are very different to the ambient wind in the open.}, issn = {03781127}, doi = {10.1016/j.foreco.2012.06.012}, author = {Cheney, NP and J.S. Gould and Lachlan W. McCaw and Wendy R. Anderson} } @article {BF-3183, title = {The relationship between fire behaviour measures and community loss: an exploratory analysis for developing a bushfire severity scale}, journal = {Natural Hazards}, year = {2012}, abstract = {Current fire danger scales do not adequately reflect the potential destructive force of a bushfire in Australia and, therefore, do not provide fire prone communities with an adequate warning for the potential loss of human life and property. To determine options for developing a bushfire severity scale based on community impact and whether a link exists between the energy release rate (power) of a fire and community loss, this paper reviewed observations of 79 wildfires (from 1939 to 2009) across Victoria and other southern states of Australia. A methodology for estimating fire power based on fuel loading, fire size and progression rate is presented. McArthur{\textquoteright}s existing fire danger indices (FDIs) as well as fuel- and slope-adjusted FDIs were calculated using fire weather data. Analysis of possible relationships between fire power, FDIs, rate of spread and Byram{\textquoteright}s fireline intensity and community loss was performed using exposure as a covariate. Preliminary results showed that a stronger relationship exists between community loss and the power of the fire than between loss and FDI, although fuel-adjusted FDI was also a good predictor of loss. The database developed for this study and the relationships established are essential for undertaking future studies that require observations of past fire behaviour and losses and also to form the basis of developing a new severity scale}, issn = {0921-030X}, doi = {10.1007/s11069-012-0156-y}, author = {Sarah Harris and Wendy R. Anderson and Kilinc, Musa and Fogarty, Liam} } @article {BF-3088, title = {Behind the flaming zone: Predicting woody fuel consumption in eucalypt forest fires in southern Australia}, journal = {Forest Ecology and Management}, volume = {261}, year = {2011}, month = {6/2011}, pages = {2049 - 2067}, abstract = {Pre-fire woody fuel (diameter > 0.6 cm) structure and its consumption by fire were measured at experimental/prescribed fires and high intensity wildfires in eucalypt forests in southern Australia in order to better understand and model the dynamics of woody fuel consumption. Two approaches were used in model development: (1) a fire or plot level analysis, based on a dataset which includes the proportion of the pre-fire woody fuel load consumed at each fire; and (2) a stage level analysis, based on a dataset where woody fuel consumption was measured at a woody fuel particle level (i.e. pre-fire and post-fire diameter). For the plot level analysis a generalised linear model (GLM) approach identified the Forest Fire Danger Index (FFDI) as the best predictor of the proportion of woody fuel consumed, with an R2 of 0.58 and mean absolute error of 10\%. The stage level analysis recognised the various combustion stages through which a burning woody particle would pass, but failed to develop an accurate model that predicted the ignition, partial and full consumption of woody fuels based on fuel, fire behaviour and environmental variables. Analysis showed that consumption of woody fuel particles is highly variable and that variation in fire behaviour potentially has a greater impact on woody fuel consumption, than does variation in fuel characteristics (e.g. state of decay, fuel suspension and interactions with other fuel particles). The FFDI GLM provides forest and fire managers with a tool to manage woody fuel consumption objectives and may assist fire managers with forecasting post-frontal fire behaviour. The FFDI GLM may also assist forest and fire managers to better meet land management goals and to comply with air quality and emission targets.}, doi = {10.1016/j.foreco.2011.02.031}, author = {Jennifer J Hollis and Stuart Matthews and Wendy R. Anderson and Cruz, Miguel G. and Burrows, N.D.} } @article {BF-3087, title = {The Effect of Fireline Intensity on Woody Fuel Consumption in Southern Australian Eucalypt Forest Fires}, journal = {Australian Forestry}, volume = {74}, year = {2011}, pages = {81-96}, abstract = {The relationship between woody fuel consumption and fireline intensity was assessed using data collected at controlled fires and wildfires in south-western Western Australia, central Victoria and south-eastern New South Wales. The combined dataset consisted of fires in a range of dry eucalypt forests. Fire behaviour varied from slow, self-extinguishing prescribed burns to intense, fast-moving fires burning under conditions of extreme fire danger. Fireline intensity ranged from 50 kW m-1 to > 31 000 kW m-1. Woody fuel consumption ranged from 31\% to 100\%, and generally increased with fire intensity. Percentage consumption was highest for small woody fuels where the diameter was between 0.6 cm and 2.5 cm. Fireline intensity had a statistically significant, positive relationship with the proportion of woody fuel consumed by both controlled fires and wildfires. Two generalised linear models (GLM) describing woody fuel consumption as a function of fireline intensity were developed, one applicable to the prescribed fire environment (with fireline intensities typically < 750 kW m-1) and the other to the full range of fireline intensities. The prescribed burning model produced the best fit and lowest error statistics. The findings of this research have important practical implications for the management of fire to reduce fuel loads, maintain habitat and manage carbon stocks in fire-prone eucalypt forests. The woody fuel consumption models presented may assist the assessment of potential climate change impacts on coarse woody debris in Australian southern eucalypt forests. The results of this research suggest that predicted changes to fire regimes and fire intensity associated with climate change in southern Australia could result in greater woody fuel consumption and carbon release during bushfires and a reduction in woody fuel loads in dry eucalypt forests. Use of low-intensity prescribed fires may provide a practical way of managing woody fuel stocks to achieve particular land management objectives.}, url = {http://search.informit.com.au/documentSummary;dn=365294696940897;res=IELHSS}, author = {Jennifer J Hollis and Wendy R. Anderson and Lachlan W. McCaw and Cruz, Miguel G. and Burrows, N.D. and Ward, B. and Tolhurst, K.G. and J.S. Gould} } @article {BF-3090, title = {A simple method for field-based grassland curing assessment}, journal = {International Journal of Wildland Fire}, volume = {20}, year = {2011}, month = {2011}, pages = {804}, abstract = {The degree of grassland curing represents the proportion of dead material in a grassland fuel complex, expressed as a percentage. It is an important input for models to predict rate of fire spread and determine fire danger levels in grasslands. The degree of curing is currently determined in Australia and New Zealand using a combination of satellite imagery and ground-based visual observations by operational personnel. Both methods present problems. The satellite imagery technique requires updating to accommodate newer satellite technology, as well as extension and validation across all of the major grasslands in both countries. Visual assessments are often both inaccurate and spatially inadequate across the landscape. This paper describes the development of a field-based method to accurately and easily determine curing levels in the field, based on modification of an existing point quadrat method of pasture assessment. This alternative technique minimises subjective assessment by field observers, and involves tallying the number of live and dead touches on a thin steel rod driven into the ground. The average error across sites was lower for exotic improved pastures than native grasslands. Results suggest that this method can be applied across Australasia more accurately than current methods.}, doi = {10.1071/WF10069}, author = {Stuart AJ Anderson and Wendy R. Anderson and Jennifer J Hollis and Botha, Elizabeth J.} } @proceedings {BF-3092, title = {Assessing woody fuel consumption models for application in Australian forest fires}, year = {2010}, author = {Jennifer J Hollis and Stuart Matthews and Ottmar, R.D. and S.J. Prichard and Slijepcevic, A. and Burrows, N.D. and Ward, B. and Tolhurst, K.G. and Wendy R. Anderson and J.S. Gould} } @article {BF-2582, title = {Testing woody fuel consumption models for application in Australian southern eucalypt forest fires}, journal = {Forest Ecology and Management}, volume = {260}, year = {2010}, month = {08/2010}, pages = {948 - 964}, abstract = {Five models for the consumption of coarse woody debris or woody fuels with a diameter larger than 0.6 cm were assessed for application in Australian southern eucalypt forest fires including: CONSUME models for (1) activity fuels, (2) natural western woody and (3) natural southern woody fuels, (4) the BURNUP model and (5) the recommendation by the Australian National Carbon Accounting System which assumes 50\% woody fuel consumption. These models were assessed using field data collected as part of the woody fuel consumption project (WFCP) in south-west Western Australia and northern-central Victoria. Three additional datasets were also sourced to increase variability in forest type, fuel complex and fire characteristics. These datasets comprised data from south-west Western Australia collected as part of Project Aquarius, the Warra Long Term Ecological Research site in Tasmania and Tumbarumba in south-eastern New South Wales. Combined the dataset represents a range of fire behaviour characteristic of prescribed burning conditions with a maximum fireline intensity of almost 4000 kW m-1. Woody fuel consumption was found to be highly variable between sites ranging from 9.1\% to 89.9\%. Relationships between woody fuel consumption and the primary model drivers were weak (maximum R2 = 0.097). Model evaluation statistics were best for the National Carbon Accounting Systems assumption of 50\% with a mean absolute error of 11.1\% fuel consumption and minimal bias (0.12). Nonetheless, this assumption does not capture large deviations where woody fuel consumption has been particularly high or low. The BURNUP model yielded the largest level of error when used with natural fuels however its predictive capacity improved when used with large modified fuel loads resulting from clearcut operations.}, doi = {10.1016/j.foreco.2010.06.007}, author = {Jennifer J Hollis and Stuart Matthews and Ottmar, R.D. and S.J. Prichard and Slijepcevic, A. and Burrows, N.D. and Ward, B. and Tolhurst, K.G. and Wendy R. Anderson and J.S. Gould} } @conference {BF-1012, title = {Evaluation of a dynamic load transfer function using grassland curing data}, booktitle = {1st Fire Behaviour and Fuel Conference, }, year = {2006}, month = {27-30 March 2006}, publisher = {International Association of Wildland Fire}, organization = {International Association of Wildland Fire}, address = {Portland, Oregon }, url = {http://www.treesearch.fs.fed.us/pubs/25963}, author = {Andrews, PL and Stuart AJ Anderson and Wendy R. Anderson} } @article {BF-2350, title = {Woody fuel consumption experiments in an undisturbed forest}, journal = {Forest Ecology and Management}, volume = {234}, year = {2006}, month = {11/2006}, pages = {S109 - S109}, doi = {10.1016/j.foreco.2006.08.145}, author = {Tolhurst, K.G. and Wendy R. Anderson and J.S. Gould} } @article {BF-1014, title = {Determination of field sampling methods for the assessment of curing levels in grasslands}, year = {2005}, month = {11/15/2005}, institution = {Bushfire CRC}, url = {http://www.nzfoa.org.nz/index.php?/File_libraries_resources/Fire/Other_Fire_Research_Publications/Grassland_Curing/Determination_of_field_sampling_methods_for_the_assessment_of_curing_in_grasslands}, author = {Stuart AJ Anderson and Wendy R. Anderson and Hines, F and Fountain, A} }