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We used simulation modelling to analyse spatial variation in wildfire exposure relative to key social and economic features on the island of Sardinia, Italy. Sardinia contains a high density of urban interfaces, recreational value...
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We used simulation modelling to analyse spatial variation in wildfire exposure relative to key social and economic features on the island of Sardinia, Italy. Sardinia contains a high density of urban interfaces, recreational values and highly valued agricultural areas that are increasingly being threatened by severe wildfires. Historical fire data and wildfire simulations were used to estimate burn probabilities, flame length and fire size. We examined how these risk factors varied among and within highly valued features located on the island. Estimates of burn probability excluding non-burnable fuels, ranged from 0-1.92x10-3, with a mean value of 6.48x10-5. Spatial patterns in modelled outputs were strongly related to fuel loadings, although topographic and other influences were apparent. Wide variation was observed among the land parcels for all the key values, providing a quantitative approach to inform wildfire risk management activities.
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We used simulation modeling to analyze wildfire exposure to social and ecological values on a 0.6 million ha national forest in central Oregon, USA. We simulated 50,000 wildfires that replicated recent fire events in the area and ...
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We used simulation modeling to analyze wildfire exposure to social and ecological values on a 0.6 million ha national forest in central Oregon, USA. We simulated 50,000 wildfires that replicated recent fire events in the area and generated detailed maps of burn probability (BP) and fire intensity distributions. We also recorded the ignition locations and size of each simulated fire and used these outputs to construct a fire source-sink ratio as the ratio of fire size to burn probability. Fire behavior was summarized for federal land management designations, including biological conservation reserves, recreational sites, managed forest, and wildland urban interface. Burn probability from the simulations ranged from 0.00001 to 0.026 within the study area (mean=0.0023), and exhibited substantial variation among and within land designations. Simulated fire behavior was broadly related to gradients in fire regimes, although the combined effects of fuel, topography, and simulated weather resulted in fine scale patterns not reflected in ecological and vegetation data. Average BP for the northern spotted owl (Strix occidentalis caurina) nesting sites ranged from 0.0002 to 0.04. Among the 130 different wildland urban interface areas, average BP varied from 0.0001 to 0.02. Spatial variation in the source-sink ratio was pronounced, and strongly affected by the continuity and arrangement of surface and canopy fuel. We discuss the management implications in terms of prioritizing fuel management activities and designing conservation strategies on fire prone landscapes within the 177 million ha national forest network.Digital Object Identifier http://dx.doi.org/10.1016/j.foreco.2011.11.021
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We explore the basis of understanding wildland fire behaviour with the intention of stimulating curiosity and promoting fundamental investigations of fire spread problems that persist even in the presence of tremendous modelling a...
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We explore the basis of understanding wildland fire behaviour with the intention of stimulating curiosity and promoting fundamental investigations of fire spread problems that persist even in the presence of tremendous modelling advances. Internationally, many fire models have been developed based on a variety of assumptions and expressions for the fundamental heat transfer and combustion processes. The diversity of these assumptions raises the question as to whether the absence of a sound and coherent fire spread theory is partly responsible. We explore the thesis that, without a common understanding of what processes occur and how they occur, model reliability cannot be confirmed. A theory is defined as a collection of logically connected hypotheses that provide a coherent explanation of some aspect of reality. Models implement theory for a particular purpose, including hypotheses of phenomena and practical uses, such as prediction. We emphasise the need for theory and demonstrate the difference between theory and modelling. Increasingly sophisticated fire management requires modelling capabilities well beyond the fundamental basis of current models. These capabilities can only be met with fundamental fire behaviour research. Furthermore, possibilities as well as limitations for modelling may not be known or knowable without first having the theory.Digital Object Identifier http://dx.doi.org/10.1071/WF11117
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In this paper we review progress towards the implementation of a risk management framework for US federal wildland fire policy and operations. We first describe new developments in wildfire simulation technology that catalyzed the...
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In this paper we review progress towards the implementation of a risk management framework for US federal wildland fire policy and operations. We first describe new developments in wildfire simulation technology that catalyzed the development of risk-based decision support systems for strategic wildfire management. These systems include new analytical methods to measure wildfire risk to human and ecological values and to inform fuel treatment investment strategies at national, regional, and local scales. Application of the risk management framework to support wildfire incidents has been dramatically advanced with the Wildland Fire Decision Support System and allowed policy modifications that encourage management of incidents for multiple objectives. The new wildfire risk management decision support systems we discuss provide Federal agencies in the US the ability to integrate risk-informed approaches to a wide range of wildfire management responsibilities and decisions. While much progress has been made, there remain several barriers that need to be addressed to fully integrate risk science into current wildfire management practices. We conclude by identifying five primary issues that if properly addressed could help public land management better realize the opportunities and potential payoffs from fully adopting a risk management paradigm.
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Wildfire simulation modelling was used to examine whether fuel reduction treatments can potentially reduce future wildfire emissions and provide carbon benefits. In contrast to previous reports, the current study modelled landscap...
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Wildfire simulation modelling was used to examine whether fuel reduction treatments can potentially reduce future wildfire emissions and provide carbon benefits. In contrast to previous reports, the current study modelled landscape scale effects of fuel treatments on fire spread and intensity, and used a probabilistic framework to quantify wildfire effects on carbon pools to account for stochastic wildfire occurrence. The study area was a 68 474 ha watershed located on the Fremont-Winema National Forest in southeastern Oregon, USA. Fuel reduction treatments were simulated on 10% of the watershed (19% of federal forestland). We simulated 30 000 wildfires with random ignition locations under both treated and untreated landscapes to estimate the change in burn probability by flame length class resulting from the treatments. Carbon loss functions were then calculated with the Forest Vegetation Simulator for each stand in the study area to quantify change in carbon as a function of flame length. We then calculated the expected change in carbon from a random ignition and wildfire as the sum of the product of the carbon loss and the burn probabilities by flame length class. The expected carbon difference between the non-treatment and treatment scenarios was then calculated to quantify the effect of fuel treatments. Overall, the results show that the carbon loss from implementing fuel reduction treatments exceeded the expected carbon benefit associated with lowered burn probabilities and reduced fire severity on the treated landscape. Thus, fuel management activities resulted in an expected net loss of carbon immediately after treatment. However, the findings represent a point in time estimate (wildfire immediately after treatments), and a temporal analysis with a probabilistic framework used here is needed to model carbon dynamics over the life cycle of the fuel treatments. Of particular importance is the long-term balance between emissions from the decay of dead trees killed by fire and carbon sequestration by forest regeneration following wildfire.
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Human land use practices, altered climates, and shifting forest and fire management policies have increased the frequency of large wildfires several-fold. Mitigation of potential fire behaviour and fire severity have increasingly ...
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Human land use practices, altered climates, and shifting forest and fire management policies have increased the frequency of large wildfires several-fold. Mitigation of potential fire behaviour and fire severity have increasingly been attempted through pre-fire alteration of wildland fuels using mechanical treatments and prescribed fires. Despite annual treatment of more than a million hectares of land, quantitative assessments of the effectiveness of existing fuel treatments at reducing the size of actual wildfires or how they might alter the risk of burning across landscapes are currently lacking. Here, we present a method for estimating spatial probabilities of burning as a function of extant fuels treatments for any wildland fire-affected landscape. We examined the landscape effects of more than 72 000 ha of wildland fuel treatments involved in 14 large wildfires that burned 314 000 ha of forests in nine US states between 2002 and 2010. Fuels treatments altered the probability of fire occurrence both positively and negatively across landscapes, effectively redistributing fire risk by changing surface fire spread rates and reducing the likelihood of crowning behaviour. Trade offs are created between formation of large areas with low probabilities of increased burning and smaller, well-defined regions with reduced fire risk.
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