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Allometric Equations for Applying Plot Inventory and Remote Sensing Data to Assess Coarse Root Biomass Energy in Subtropical Forests

Author:
Gou, Mengmeng, Xiang, Wenhua, Song, Tongqing, Lei, Pifeng, Zhang, Shengli, Ouyang, Shuai, Zeng, Yelin, Deng, Xiangwen, Fang, Xi, Wang, Kelin
Source:
BioEnergy research 2017 v.10 no.2 pp. 536-546
ISSN:
1939-1234
Subject:
Castanopsis, Liquidambar formosana, Litsea coreana, Pinus massoniana, Quercus, Schima superba, allometry, bioenergy, biomass, carbon, equations, feedstocks, forests, inventories, issues and policy, plant residues, prediction, spatial data, tree and stand measurements, trees
Abstract:
Coarse root biomass (CRB) is an important store of carbon (C) and forest residue for renewable energy, but is often overlooked due to the lack of a simple and effective way to estimate its magnitude. In this study, we developed allometric equations for three functional groups using data from 133 tree samples, with a diameter at breast height (DBH) ranging from 2.6 to 52.0 cm. The functional groups included evergreen coniferous (Pinus massoniana), deciduous broad-leaved (Alniphyllum fortunei, Choerospondias axillaris, Liquidambar formosana and Quercus fabri) and evergreen broad-leaved (Castanopsis carlesii, Cyclobalanopsis glauca, Litsea coreana and Schima superba) species. Allometric equations that related CRB to plot inventory data (e.g. DBH or tree height (H)) and their combinations significantly fitted (P < 0.0001) for the functional groups and all tree species. The equations using DBH or DBH-H as predictor variables were the best fit (R ² ≥ 0.90) and produced good predictions with little bias (less than 21%) for local sites and at regional scales. Allometric equations related to easily obtained remote sensing data (i.e. crown width (CW) and H) were also significantly fitted (P < 0.0001, R ² ≥ 0.76), and predictions were close to the observed CRB, despite a high bias (larger than 98.0%). In conclusion, the use of these equations to estimate CRB is essential to the harvest process and helps to formulate new policies for managing the feedstock supply to bioenergy production in subtropical forests.
Agid:
5728369