Novel approach to assessing residual biomass from pruning: A case study in Atlantic Pinus pinaster Ait. timber forests

RENEWABLE ENERGY

卷:107

Article

Hevia, Andrea¹  Crabiffosse, Alejandra²  Gabriel Alvarez-Gonzalez, Juan²  Dania Ruiz-Gonzalez, Ana²  Majada, Juan¹ 

[1] Forest & Wood Technol Res Ctr CETEMAS, Carbayin S-N, Siero 33936, Asturias, Spain

[2] Univ Santiago de Compostela, High Polytech Sch, Agroforestry Engn Dept, Sustainable Forest Management Unit UXFS, Campus Univ S-N, Lugo 27002, Spain

关键词: Maritime pine;    Forest biomass waste;    Weibull distribution function;    Forestry modelling;    Silviculture;   

DOI  :  10.1016/j.renene.2017.02.029

来源: Elsevier

【 摘 要 】

Forestry residual biomass from pruning operations is an important, though little studied, potential resource. Residues normally remain in the stand, since tools for their accurate quantification do not exist and it has no particular end use. Traditional tree biomass estimation models consider the whole-tree, but estimating pruned biomass requires the development of more specific equations. This work provides a modelling approach for assessing biomass along the stem and the corresponding residual biomass from forest pruning, and quantitative results from different pruning intensities in Pinus pinaster Ait. are presented: Two types of models were considered: allometric biomass equations (whole-tree) and biomass ratio equations (tree by height along the stem), and the 2-parameter Weibull distribution function resulted in the best characterization. Diameter at breast height was the best explanatory variable in all equations, and model accuracy increased when models were combined with total tree height for the tree stem and thicker branches, or with crown ratio for the remaining tree crown components. This study provides a powerful tool to estimate residual pruned biomass, enabling its better management as a valuable source of bioenergy, as well as the importance in nutrient balance and fire risk which it plays in a sustainable forestry production. (C) 2017 Elsevier Ltd. All rights reserved.

【 授权许可】

Free