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Stand density sensitive biomass functions for young oak trees at four different European sites

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Relative biomass of tree compartments is dependent on plant size and stand density, with stand density being an important predictor, especially for belowground biomass and at high stand densities.

Abstract

Estimation of biomass production is an important issue against the background of climate change and carbon storage. Even though many studies investigated the biomass productivity of trees or single compartments, only few considered the belowground biomass. Further, there is a lack of studies focusing on young trees and considering further influencing factors such as the prevailing stand density. In the present study, young Quercus robur trees were sampled on Nelder trials, which comprise different stand densities, on four European sites differing in climatic conditions. Besides the estimation of logarithmically transformed power equations, Dirichlet regressions were applied for deriving biomass functions for the single compartments leaves, branches, stem and roots. Thereby, the dependence of total and compartment biomass allocation on diameter at root collar (d 0), tree height and stand density is tested. The results show that besides d 0, the local Stand Density Index (SDIl) is an important predictor for biomass. Especially, the belowground biomass shows a significant relation to the SDIl, which is less the case for the aboveground biomass. Not considering the SDIl leads to an overestimation of the biomass productivity, especially when the stand density is high. Furthermore, the results show that the belowground biomass is lower than the aboveground biomass, but with 50–80% of the aboveground biomass still of considerable size. This indicates the importance of including stand characteristics when estimating above- and belowground tree biomass in future studies.

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Acknowledgements

We thank AUDI AG, Automobili Lamborghini S.P.A., and AUDI HUNGARIA MOTOR Kft. Thanks to the AUDI Stiftung für Umwelt for funding the project Biodiversity, productivity, and C-sequestration of oak stands (No. 5102150). We also thank the Bavarian State Ministry for Nutrition, Agriculture and Forestry for permanent support of the project W 07 Long term experimental plots for forest growth and yield research (7831-23953-2014). The included trials are located on areas under responsibility of different forest administrations. We are deeply grateful to the respective sponsoring forest administrations.

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Authors and Affiliations

  1. Chair for Forest Growth and Yield Science, Center of Life and Food Sciences Weihenstephan, Technical University of Munich, Hans-Carl-von-Carlowitz-Platz 2, 85354, Freising, Germany

    Jens Dahlhausen, Enno Uhl, Michael Heym, Peter Biber & Hans Pretzsch

  2. Faculty of Science and Technology, Free University of Bolzano, Universitaetsplatz 5, 39100, Bolzano, Italy

    Maurizio Ventura, Pietro Panzacchi & Giustino Tonon

  3. Faculty of Forestry, University of West Hungary, Ady E. u. 5, Sopron, 9400, Hungary

    Tamás Horváth

Authors
  1. Jens Dahlhausen
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  2. Enno Uhl
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  3. Michael Heym
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  4. Peter Biber
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  5. Maurizio Ventura
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  6. Pietro Panzacchi
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  7. Giustino Tonon
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  8. Tamás Horváth
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  9. Hans Pretzsch
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Corresponding author

Correspondence to Jens Dahlhausen.

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Conflict of interest

The authors declare no conflict of interest. The founding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.

Additional information

Communicated by E. van der Maaten.

Appendix

Appendix

See Figs. 9, 10.

Fig. 9
figure 9

Projected biomass productivity per site (a) and relation of total to aboveground biomass (b). Solid lines represent biomass productivity estimations using d 0 and height as predictors (model 4), dashed lines represent total biomass productivity estimations using d 0, height, and SDIl as predictors (model 6) dash-dotted lines represent aboveground biomass productivity estimations using d 0 and height as predictors (model 4)

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Fig. 10
figure 10

Distribution of the study locations across Europe and distribution of Q. robur according EUFORGEN (http://www.euforgen.org)

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Dahlhausen, J., Uhl, E., Heym, M. et al. Stand density sensitive biomass functions for young oak trees at four different European sites. Trees 31, 1811–1826 (2017). https://doi.org/10.1007/s00468-017-1586-7

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