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A simple model for shrub-strata-fuel dynamics in Quercus coccifera L. communities

Abstract : Key message We model the dynamics of fuel characteristics in shrub strata dominated by Quercus coccifera L. with data gathered in available literature. The model expresses the variability of this important fire-prone fuel type thanks to yield classes, and it can be used to investigate management scenarios. The approach could easily be applied to other shrub communities. Context Characterizing fuel is a basic requirement for fire hazard assessment. Quercus coccifera L. is present in several Mediterranean fire-prone communities, and its fuel characteristics have been studied over various Mediterranean countries, but no general model describes its dynamics. Aims Herein, we present such a general model, initially developed for operational purposes at the French Forest Service. Methods We review available literature and fit statistical relationships to predict the dynamics of fuel height and biomass, by size categories of fine fuel elements. Results The model estimates fuel characteristics from shrub-strata age, overstorey cover, and yield class with a reasonable degree of accuracy considering the heterogeneity of the datasets. It shows that bulk density is highly sensitive to overstorey, and in a lesser extent to strata age, which could lead to significant bias when assessing fuel properties from general allometries. The model is integrated in the FuelManager software, which is devoted to fuel modeling for physics-based-fire-behavior models. Conclusion This simple approach enables to provide a fuel model for the Quercus coccifera L. shrub strata in the Mediterranean basin. It is more general than the existing relationships available for local data. This approach could be generalized to other fire-prone communities.
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Submitted on : Tuesday, May 26, 2020 - 1:17:09 AM
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François Pimont, Jean-Luc Dupuy, Eric Rigolot. A simple model for shrub-strata-fuel dynamics in Quercus coccifera L. communities. Annals of Forest Science, Springer Nature (since 2011)/EDP Science (until 2010), 2018, 75 (2), ⟨10.1007/s13595-018-0713-y⟩. ⟨hal-02621175⟩



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