Seasonal time-course of the above ground biomass production efficiency in beech trees (Fagus sylvatica L.)

  • Laura Heid
  • Christophe Calvaruso
  • Anjy Andrianantenaina
  • André Granier
  • Sébastien Conil
  • Cyrille B. K. Rathgeber
  • Marie-Pierre Turpault
  • Bernard Longdoz
Original Paper
Part of the following topical collections:
  1. Estimation of standing forest biomass


Key message

In order to record the seasonal changes in aboveground biomass production (trunk and branches) in a forest, changes in wood density must be taken into account. A 60-year-old beech forest displayed a large intra-annual variability in its aboveground woody biomass production efficiency. This variation followed a seasonal trend with a maximum during the summer while gross primary production was rather low.


In the current context of land use and climate change, there is a need to precisely quantify the carbon (C) balance of forest ecosystems, and more specifically, of C allocation to tree compartments.


We quantified the seasonal changes in the aboveground biomass production (aBP) of a beech forest growing on two different soils: an alocrisol and a calci-brunisol. In addition, for the alocrisol ecosystem, we assessed the existence and degree of intra-annual variability in the ratio of wood aBP to gross primary production (GPP), i.e., the wood aBP efficiency.


The study site is a 60-year-old beech forest in northeastern France. An eddy covariance tower records continuously net ecosystem exchange. To investigate the temporal changes in aBP, mini-cores were drilled and diameter at breast height measurements were taken on a monthly basis from 45 trees for both stands studied over 2014.


A clear difference in aBP was observed between the two soils with the alocrisol being more productive than the calci-brunisol. For the alocrisol, both woody aBP and GPP changed over the course of the year, reaching peak values during June (6 and 12.5 gC m−2 day−1, respectively). Wood applied bias photon-to-current efficiency aboveground Biomass Production Efficiency (aBPE) also showed important intra-annual variations, ranging from 0.09 in September to 0.58 in July. Wood density varied throughout the year, and not taking it into account would have led to an overestimation of aBP by as much as 20% in April and May.


Our study highlights the importance of taking wood density into account for intra-annual studies of aBP. Wood aBPE cannot be considered as constant as it fluctuated from 0.09 to 0.58 throughout the year for an annual value of 0.34. The potential error in wood aBPE stemming from not taking these changes into account amounts to 15%.


Eddy covariance GPP Beech forest Carbon allocation Biomass production Tree growth Wood density 



This work was supported by the French National Research Agency through the Laboratory of Excellence ARBRE (ANR-12-LABXARBRE-01). The site on which this research has been performed is part of the SOERE F-ORE-T which is supported annually by Ecofor, Allenvi, and the French national research infrastructure ANAEE-F ( We also thank L. Saint-André (INRA-BEF, Nancy, France) for his help for the biomass calculation, as well as B. Garnier, P. Courtois, A. Naiken, F. Geremia (INRA-EEF, Nancy, France), and the technicians from the LERFoB (INRA, Nancy, France), BEF (INRA, Nancy, France), and ANDRA for technical support.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.


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Copyright information

© INRA and Springer-Verlag France SAS, part of Springer Nature 2018

Authors and Affiliations

  • Laura Heid
    • 1
    • 2
  • Christophe Calvaruso
    • 3
  • Anjy Andrianantenaina
    • 1
  • André Granier
    • 1
  • Sébastien Conil
    • 4
  • Cyrille B. K. Rathgeber
    • 1
  • Marie-Pierre Turpault
    • 5
  • Bernard Longdoz
    • 1
    • 6
  1. 1.Université de Lorraine, AgroParisTech, Inra, SilvaNancyFrance
  2. 2.DRD, ANDRABureFrance
  3. 3.EcoSustain, Environmental Engineering OfficeResearch and DevelopmentKanfenFrance
  4. 4.DRD-GES, ANDRABureFrance
  5. 5.Inra, BEFNancyFrance
  6. 6.TERRA, Research Centre, Atmosphere-Ecosystem Exchanges, Gembloux Agro-Bio TechUniversity of LiegeGemblouxBelgium

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