Abstract
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.
Highlights
Predicting the biomass of various tree parts using allometric models is crucial in multiple disciplines including forest utilization, management, and ecology
This study developed a localized allometric model for estimating total aboveground biomass (TAGB) in oven-dry kilograms (ODKg) for coast redwood in northwestern California based on the tree dbh
Eleven allometric coefficients were developed for coast redwood to predict biomass in various tree components and other structural tree dimensions by sampling trees from an industrial timberland (Table 4)
Summary
Predicting the biomass of various tree parts using allometric models is crucial in multiple disciplines including forest utilization, management, and ecology. Allometric models can be applied to all trees regardless of size, as long as they are growing under the same conditions [1] These models consist of measureable independent variables, such as tree diameter or height, and have been used to obtain structural and functional characteristics for estimating biomass, net primary production, and biogeochemical budgets for forest ecosystems [2,3]. Biomass models are finding a wide variety of other applications They have been applied in predicting crown fire behavior [7], estimating potential conditions for drought, insect and disease outbreaks [8], estimating tree volume in remote sensing [9], and determining productivity and actual amount of biomass recovered during forest harvesting operations [10,11]
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