Journal cover Journal topic
Biogeosciences An interactive open-access journal of the European Geosciences Union
Biogeosciences, 12, 6205-6217, 2015
https://doi.org/10.5194/bg-12-6205-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research article
29 Oct 2015
Influence of wood density in tree-ring-based annual productivity assessments and its errors in Norway spruce
O. Bouriaud1, M. Teodosiu2, A. V. Kirdyanov3,4, and C. Wirth5,6 1National Research and Development Institute for Forestry, National Forest Inventory, Calea Bucovinei 73b, 725100 Câmpulung Moldovenesc, Romania
2National Research and Development Institute for Forestry, Calea Bucovinei 73b, 725100 Câmpulung Moldovenesc, Romania
3V.N. Sukachev Institute of Forest SB RAS, Akademgorodok, Krasnoyarsk, 660036, Russia
4Siberian Federal University, Krasnoyarsk, 660041, Russia
5Institute of Biology, University of Leipzig, Johannisallee 21-23, 04103 Leipzig, Germany
6German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Deutscher Platz 5e, 04103 Leipzig, Germany
Abstract. Estimations of tree annual biomass increments are used by a variety of studies related to forest productivity or carbon fluxes. Biomass increment estimations can be easily obtained from diameter surveys or historical diameter reconstructions based on tree rings' records. However, the biomass models rely on the assumption that wood density is constant. Converting volume increment into biomass also requires assumptions about the wood density. Wood density has been largely reported to vary both in time and between trees. In Norway spruce, wood density is known to increase with decreasing ring width. This could lead to underestimating the biomass or carbon deposition in bad years. The variations between trees of wood density have never been discussed but could also contribute to deviations. A modelling approach could attenuate these effects but will also generate errors.

Here a model of wood density variations in Norway spruce, and an allometric model of volume growth were developed. We accounted for variations in wood density both between years and between trees, based on specific measurements. We compared the effects of neglecting each variation source on the estimations of annual biomass increment. We also assessed the errors of the biomass increment predictions at tree level, and of the annual productivity at plot level.

Our results showed a partial compensation of the decrease in ring width in bad years by the increase in wood density. The underestimation of the biomass increment in those years reached 15 %. The errors related to the use of an allometric model of volume growth were modest, around ±15 %. The errors related to variations in wood density were much larger, the biggest component being the inter-tree variability. The errors in plot-level annual biomass productivity reached up to 40 %, with a full account of all the error sources.


Citation: Bouriaud, O., Teodosiu, M., Kirdyanov, A. V., and Wirth, C.: Influence of wood density in tree-ring-based annual productivity assessments and its errors in Norway spruce, Biogeosciences, 12, 6205-6217, https://doi.org/10.5194/bg-12-6205-2015, 2015.
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Annual variations in wood density partially compensated ring-width variations in Picea abies. If neglected, annual biomass increment was underestimated by up to 15%. The relative prediction interval of plot-level annual biomass increment ranged from 20 to 40%. The uncertainty related to the allometric models parameters was only about 10%. The errors related to variations in wood density were much larger, the biggest component being the variability between trees.
Annual variations in wood density partially compensated ring-width variations in Picea abies. If...
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