Estimating fine fuel loads in Eucalypt forests using forest inventory data and a modelling approach

Forest Ecology and Management(2024)

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摘要
Eucalypt forests are vital for biodiversity and fire dynamics, with fine fuels serving as the primary ignition source and critical factors in determining fire intensity. Accurate measurement of fine fuel via destructive field methods is location and time-restricted, hindering the tracking of their dynamic variations across diverse landscapes. In response, this study utilised forest inventory data collected by the Victorian Forest Monitoring Program (VFMP) in Victoria, southeastern Australia, along with allometric models, to estimate fine fuel loads across four vertical layers (surface, near-surface, elevated, and canopy). The average total fine fuel load in Victorian Eucalypt forests was estimated at 18.45 t ha−1 (ranging from 2.23 to 39.54 t ha−1), with surface litter contributing 58.2% of this total, followed by canopy (22.1%), near-surface (13.4%), and elevated (6.6%) fine fuels. We also conducted a comprehensive investigation and found distinct variations in fine fuel loads across different bioregions, forest covers, and vegetation types. Furthermore, stepwise multiple regression was employed to develop predictive models for estimating fine fuel loads from forest structural and environmental variables. Results show that total and canopy fine fuels can be reasonably explained by forest height, density, and climate-related variables (with R2 = 0.38 and 0.51, respectively). However, the explanatory power of these models diminished when applied to elevated, near-surface, and surface fine fuels. This study underscores the intricacies of fine fuel distribution in Eucalypt forests, emphasising the necessity for comprehensive factors in fire management planning. Further research is needed to better comprehend the relationship between forest characteristics and fine fuel dynamics to enhance wildfire risk assessment and mitigation strategies.
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关键词
Fine fuel loads,Eucalypt forests,Fine fuel variations,Fine fuel modelling
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