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Additive prediction of aboveground biomass for Pinus radiata (D. Don) plantations

Bi, H., Long, Y., Turner, J., Lei, Y., Snowdon, P., Li, Y., Harper, R.ORCID: 0000-0003-0268-2917, Zerihun, A. and Ximenes, F. (2010) Additive prediction of aboveground biomass for Pinus radiata (D. Don) plantations. Forest Ecology and Management, 259 (12). pp. 2301-2314.

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A general and two country-specific systems of additive equations were developed to predict aboveground biomass of Pinus radiata plantations from stand variables that are routinely measured in inventory plots and predicted by conventional growth and yield models. The data for this work consisted of 319 plot-based biomass estimates that were derived from individual tree biomass equations developed in situ. These plot-based biomass estimates were compiled from studies reported in the forestry and ecological literature since 1960 and also from personal communications. They represent more than 60 sites worldwide with a majority in Australia and New Zealand. The systems of additive biomass equations developed from these data provide an alternative and addition to the current methods of estimating the aboveground biomass of P. radiata plantations. They also provide a direct linkage between forest inventory measures, outputs from conventional growth and yield models and biomass and carbon stock estimates at the same spatial scale. This direct linkage provides a new basis for scaling to a remote sensing image from which biomass and carbon stocks across the landscape can be mapped. Comparisons of prediction accuracies between this approach and other methods such as scaling up from individual tree biomass estimates and biomass expansion factors highlighted considerable methodological differences in the estimates of aboveground biomass and associated uncertainties over a range of stand age and conditions. These differences should be carefully evaluated before adopting a particular method to estimate aboveground biomass and carbon stocks of P. radiata plantations at a local, regional or national scale.

Item Type: Journal Article
Publisher: Elsevier BV
Copyright: © 2010 Elsevier B.V.
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