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European Journal of Forest Research

, Volume 135, Issue 2, pp 263–282 | Cite as

A climate-sensitive empirical growth and yield model for forest management planning of even-aged beech stands

  • Antoni Trasobares
  • Andreas Zingg
  • Lorenz Walthert
  • Christof Bigler
Original Paper

Abstract

The optimization of forest management under climate change uncertainty requires a comparison of many alternative management options under different climate scenarios and the use of stochastic and adaptive approaches. Empirical growth and yield models are highly suitable for this, provided they include sensitivity to environmental influences. Here, we present a climate-sensitive empirical growth and yield model that is based on the direct integration of environmental effects in dynamic growth and survival functions, which allows for the evaluation of changing site conditions over time. Individual-tree diameter and height growth and the probability of a tree to survive any 5-year period were modelled for even-aged beech (Fagus sylvatica) stands in Switzerland using a distance-independent approach. Changing site conditions were based on a drought index (locally adjusted water balance) and sum of degree-days. The data for fitting the model were taken from 30 permanent yield plots repeatedly measured from 1930 to 2010. Reasonable results were obtained in the model evaluation: (1) validation against independent National Forest Inventory data indicated that the incorporation of drought and sum of degree-days in the model was appropriate; (2) accurate simulations over around 50 years of past stand development were achieved (for changes in basal area over 5-year measurements in all plots, the bias was 3 % and the root mean square error 32 %); and (3) the impact of climate change may vary considerably along the range of current site conditions. We thus conclude that the model can be used in management planning under climate change uncertainty.

Keywords

Climate change Soil water holding capacity Forest site evaluation Mixed models Simulation Optimization 

Notes

Acknowledgments

We thank Matthias Dobbertin (WSL) for the provision of Level I (Sanasilva) and Level II forest inventory and soil data. It was nice working with him. We also thank U.-B. Brändli (WSL) for the provision of the SNFI data and Dirk Schmatz and Nick Zimmermann (WSL) for the provision of downscaled climate scenario data. Harald Bugmann is acknowledged for participating actively in the development of the presented approach and providing important support. We thank Jerry Vanclay, Jari Miina, Jette B. Jacobsen, Annikki Mäkelä and the two reviewers for their comments. This research was funded by the MOTIVE project within the European commission’s 7th framework program (Grant agreement No. 226544).

Supplementary material

10342_2015_934_MOESM1_ESM.docx (234 kb)
Supplementary material 1 (DOCX 235 kb)

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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Antoni Trasobares
    • 1
  • Andreas Zingg
    • 2
  • Lorenz Walthert
    • 2
  • Christof Bigler
    • 1
  1. 1.Forest Ecology, Institute of Terrestrial EcosystemsDepartment of Environmental Systems Science, ETH ZurichZurichSwitzerland
  2. 2.Swiss Federal Institute for ForestSnow and Landscape ResearchBirmensdorfSwitzerland

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