Individual-Tree and Stand-Level Models for Estimating Ladder Fuel Biomass Fractions in Unpruned Pinus radiata Plantations.

Autor: Alonso-Rego, Cecilia, Fernandes, Paulo, Álvarez-González, Juan Gabriel, Arellano-Pérez, Stefano, Ruiz-González, Ana Daría
Předmět:
Zdroj: Forests (19994907); Oct2022, Vol. 13 Issue 10, p1697-N.PAG, 19p
Abstrakt: The mild climate and, in recent decades, the increased demand for timber have favoured the establishment of extensive plantations of fast-growing species such as Pinus radiata in Galicia (a fire-prone region in northwestern Spain). This species is characterised by very poor self-pruning; unmanaged pine stands have a worrying vertical continuity of fuels after crown closure because the dead lower branches accumulate large amounts of fine dead biomass including twigs and suspended needles. Despite the important contribution of these dead ladder fuels to the overall canopy biomass and to crown-fire hazards, equations for estimating these fuels have not yet been developed. In this study, two systems of equations for estimating dead ladder fuel according to size class and the vertical distribution in the first 6 m of the crown were fitted: a tree-level system based on individual tree and stand variables and a stand-level system based only on stand variables. The goodness-of-fit statistics for both model systems indicated that the estimates were robust and accurate. At the tree level, fuel biomass models explained between 35% and 59% of the observed variability, whereas cumulative fuel biomass models explained between 62% and 81% of the observed variability. On the other hand, at the stand level, fuel-load models explained between 88% and 98% of the observed variability, whereas cumulative fuel-load models explained more than 98% of the total observed variability. These systems will therefore allow managers to adequately quantify the dead ladder fuels in pure Pinus radiata stands and to identify the treatments required to reduce crown-fire hazard. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index