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Predicting Aboveground Biomass in Second Growth Coast Redwood: Comparing Localized with Generic Allometric Models

1
School of Forest Resources, University of Maine, Orono, ME 04469, USA
2
Department of Forestry and Wildland Resources, Humboldt State University, Arcata, CA 95521, USA
*
Author to whom correspondence should be addressed.
Academic Editor: Timothy A. Martin
Forests 2016, 7(5), 96; https://doi.org/10.3390/f7050096
Received: 28 December 2015 / Revised: 17 April 2016 / Accepted: 19 April 2016 / Published: 27 April 2016
Biomass amounts predicted by generalized models are often not applicable for small regions. Localized allometric models were developed relating tree/biomass components to diameter at breast height (dbh) for coast redwood (Sequoia sempervirens (D. Don) Endl.) from an industrial timberland in northwestern California, USA. dbh for the candidate trees ranged from 2.54 cm to 84.07 cm. Biomass of tree components, such as bole, foliage, bark, live and dead branches, along with the total aboveground biomass (TAGB) were estimated. Other tree dimensions such as tree height, height to live crown, weight and volume of bole wood were also modeled. Localized allometric models were able to explain more than 93% of the variability for most of the tree components (p < 0.001). Biomass amounts predicted from the widely used generalized models were different from that estimated by the localized allometric model developed from this study. However, the results presented in this study should be used carefully to predict the biomass components, if applied outside the stated dbh range or stand conditions on which this study was based. View Full-Text
Keywords: biomass components; California redwood; northern California; Sequoia sempervirens; tree dimensions; tree volume estimation biomass components; California redwood; northern California; Sequoia sempervirens; tree dimensions; tree volume estimation
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Kizha, A.R.; Han, H.-S. Predicting Aboveground Biomass in Second Growth Coast Redwood: Comparing Localized with Generic Allometric Models. Forests 2016, 7, 96.

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