Fuel loads and fuel structure in Austrian coniferous forests
Mathias Neumann
A * , Lena Vilà-Vilardell B , Mortimer M. Müller A and Harald Vacik A
+ Author Affiliations
- Author Affiliations
A Institute of Silviculture, Department of Forest and Soil Sciences, University of Natural Resources and Life Sciences, Vienna, 1190 Austria.
B Joint Research Unit CTFC – AGROTECNIO, Ctra de Street Llorenç de Morunys, km 2, 25280 Solsona, Spain.
* Correspondence to: mathias.neumann@boku.ac.at
International Journal of Wildland Fire 31(7) 693-707 https://doi.org/10.1071/WF21161
Submitted: 8 November 2021 Accepted: 17 May 2022 Published: 22 June 2022
© 2022 The Author(s) (or their employer(s)). Published by CSIRO Publishing on behalf of IAWF. This is an open access article distributed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND)
Abstract
Understanding fires in temperate European coniferous forests is hindered by a lack of reliable field observations on fuel load and structure. Fuel load influences the spread, intensity and spotting distance of a surface fire, torching likelihood and potential carbon emissions. We quantified fuel load and structure for Austrian coniferous forests using 93 sample plots across Austria. We compared Austrian fuel types with fuels collected in other regions and biomes. We found significant differences among regions and forest types. Fuel load was more dependent on region and forest type than on age class. Highest fuel load was found in Picea abies stands, lowest in Pinus nigra forests. Dead fuel loads were positively correlated with basal area, while live fuels were negatively correlated, suggesting that basal area drives accumulation of dead fuels and suppresses growth of understorey vegetation. Fuel loads in Austria are similar to published data for other temperate forests. The large variation in observed fuel loads and lack of previous studies highlight the need to further develop fuel models for mixed conifer–broadleaf forests. This pilot study underpins that consistent terminology and fuel classification are important to interpret differences between regions and forest types.
Keywords: carbon emissions, destructive sampling, fire hazard, fire severity, fuel sampling, fuel types, line-intercept method, stand structure, wildfire.
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