A prescribed fire cost model for public lands in south-east Queensland

Forest Policy and Economics(2021)

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Abstract
Prescribed fire is a management tool in many Australian and international ecosystems, where it can benefit biodiversity conservation and potentially reduce the risk of extreme wildfires threatening highly valued assets. However, the economic efficiency of prescribed fire is poorly understood. The aim of this study was to progress this understanding by improving estimates of prescribed fire costs. A generalized linear prescribed fire cost model for south-east Queensland has been developed from a dataset of 527 prescribed fire on public land over the period 2004 to 2015, to estimate prescribed fire costs per hectare as a function of environmental predictors. The best model explained 88% of the variance, and significant predictor variables were prescribed fire burned area, fire vegetation group (FVG), forest fire danger index (FFDI), fuel quantity, distance to the nearest building, distance to the nearest Queensland Parks and Wildlife Service and Partnerships (QPWS&P) base, and distance to the nearest freshwater body. Prescribed fire costs per hectare were negatively related to prescribed fire burned area, distances to the nearest building and nearest freshwater body and the FFDI, but positively related to fuel quantity and distance to nearest QPWS&P base. Prescribed fire costs also varied significantly between some FVGs. Prescribed fire burned area had the strongest influence on prescribed fire costs (83% of variation in cost explained). Prescribed fire cost for riparian, foredune and beach ridge vegetation was significantly higher than for heath, while prescribed fire cost for melaleuca vegetation was significantly lower than heath. Higher costs were associated with prescribed fires within 500 m of the nearest building. The model can support the estimation and justification of annual operational budgets for prescribed fire.
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Key words
Planned burn,Fuel reduction,Generalized liner model,Wildland-urban interface,Risk mitigation,Cost estimation
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