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Predicting individual-tree growth of central European tree species as a function of site, stand, management, nutrient, and climate effects

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Abstract

We used data from representatively sampled trees to identify key drivers of tree growth for central European tree species. Nonlinear mixed models were fitted to individual-tree basal area increments (BAI) from the Swiss national forest inventory. Data from 1983 to 2006 were used for model fitting and data from 2009 to 2013 for model evaluation. We considered 23 potential explanatory variables specifying individual-tree characteristics, site and stand conditions, management, climate, and nitrogen deposition. Model selection was processed separately for Picea abies, Abies alba, Pinus sp., Larix sp., other conifers, Fagus sylvatica, Quercus sp., Fraxinus sp./Acer sp., and other broadleaves. The selected models explained 56–70% of the BAI variance in the model fitting dataset and 21–64% in the evaluation dataset. While some variables were relevant for all species, the combination of further variables differed among the species, reflecting their physiological properties. In general, BAI was positively related to DBH and temperature and negatively related to basal area of larger trees, stand density, mean DBH of the 100 thickest trees per ha, slope, and soil pH. For most species, harvesting had a positive effect on BAI. In general, nitrogen deposition was positively related to BAI, except for spruce and fir, for which the inverse effect was found. Increasing drought reduced BAI for most species, except for pine and oak. These BAI models incorporate many influencing factors while representing large spatial extents, making them useful for both nationwide scenario analyses and deepening the understanding of the main drivers modulating tree growth throughout central Europe.

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Acknowledgements

We would like to thank Jan Remund for providing the climate data and Beat Rihm for modelling and providing the N-deposition data. For many fruitful discussions, we are grateful to Edgar Kaufmann, Jürgen Zell, and Golo Stadelmann. This study was funded by the Swiss Federal Office for the Environment FOEN and the Swiss Federal Institute for Forest, Snow and Landscape Research WSL as part of the research programme ‘Forests and Climate Change’.

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Authors and Affiliations

  1. Forest Resources and Management, Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Zürcherstrasse 111, 8903, Birmensdorf, Switzerland

    Brigitte Rohner, Marco Ferretti & Esther Thürig

  2. Forest Soils and Biogeochemistry, Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Zürcherstrasse 111, 8903, Birmensdorf, Switzerland

    Peter Waldner

  3. Landscape Dynamics, Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Zürcherstrasse 111, 8903, Birmensdorf, Switzerland

    Heike Lischke

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  1. Brigitte Rohner
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  2. Peter Waldner
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  4. Marco Ferretti
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Correspondence to Brigitte Rohner.

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Communicated by Hans Pretzsch.

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Online Resource 1

Pre-selection of competing variables (PDF 81 kb)

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Correlations between the explanatory variables in the ´full model´ after the pre-selection among highly correlated variables (PDF 79 kb)

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Estimated coefficients at the original unscaled and uncentred scale of the variables (PDF 112 kb)

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Sensitivity analysis for all species and species groups (PDF 223 kb)

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Rohner, B., Waldner, P., Lischke, H. et al. Predicting individual-tree growth of central European tree species as a function of site, stand, management, nutrient, and climate effects. Eur J Forest Res 137, 29–44 (2018). https://doi.org/10.1007/s10342-017-1087-7

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  • DOI: https://doi.org/10.1007/s10342-017-1087-7

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