Climate change and mixed forests: how do altered survival probabilities impact economically desirable species proportions of Norway spruce and European beech?

  • Carola PaulEmail author
  • Susanne Brandl
  • Stefan Friedrich
  • Wolfgang Falk
  • Fabian Härtl
  • Thomas Knoke
Research Paper
Part of the following topical collections:
  1. Forest Adaptation and Restoration under Global Change


Key message

Economic consequences of altered survival probabilities under climate change should be considered for regeneration planning in Southeast Germany. Findings suggest that species compositions of mixed stands obtained from continuous optimization may buffer but not completely mitigate economic consequences. Mixed stands of Norway spruce ( Picea abies L. Karst . ) and European beech ( Fagus sylvatica L.) (considering biophysical interactions between tree species) were found to be more robust, against both perturbations in survival probabilities and economic input variables, compared to block mixtures (excluding biophysical interactions).


Climate change is expected to increase natural hazards in European forests. Uncertainty in expected tree mortality and resulting potential economic consequences complicate regeneration decisions.


This study aims to analyze the economic consequences of altered survival probabilities for mixing Norway spruce (Picea abies L. Karst.) and European beech (Fagus sylvatica L.) under different climate change scenarios. We investigate whether management strategies such as species selection and type of mixture (mixed stands vs. block mixture) could mitigate adverse financial effects of climate change.


The bio-economic modelling approach combines a parametric survival model with modern portfolio theory. We estimate the economically optimal species mix under climate change, accounting for the biophysical and economic effects of tree mixtures. The approach is demonstrated using an example from Southeast Germany.


The optimal tree species mixtures under simulated climate change effects could buffer but not completely mitigate undesirable economic consequences. Even under optimally mixed forest stands, the risk-adjusted economic value decreased by 28%. Mixed stands economically outperform block mixtures for all climate scenarios.


Our results underline the importance of mixed stands to mitigate the economic consequences of climate change. Mechanistic bio-economic models help to understand consequences of uncertain input variables and to design purposeful adaptation strategies.


Survival analysis Value at risk Climate change Species mixture Forest restoration Portfolio theory 



This work is part of the project “SURVIVAL-KW” funded by the Federal Ministry of Food and Agriculture of Germany (Waldklimafonds (FKZ: 28W-C-4-088-01). We would like to thank all members of the project for their contributions and helpful discussions on the topic. We would particularly like to thank Christian Kölling for his valuable ideas and support during project conceptualization. The assistance of Andreas Bender from Ludwig Maximilian University of Munich with statistical model development is gratefully acknowledged. We are furthermore grateful to all members and contributors of the International Co-operative Programme on Assessment and Monitoring of Air Pollution Effects on Forests for providing the valuable dataset used in our study. We also thank Michael Du for language editing the manuscript. We are most grateful to two anonymous reviewers for their valuable and constructive comments which helped to considerably improve the manuscript.


This work was funded by the Federal Ministry of Food and Agriculture of Germany (Waldklimafonds Project SURVIVAL-KW (FKZ: 28W-C-4-088). S.F. acknowledges funding by the Bavarian State Ministry for Food, Agriculture and Forestry (Project H10—“Climate induced risks for mixed stands of spruce and broad-leaved tree species”).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

13595_2018_793_MOESM1_ESM.pdf (914 kb)
ESM 1 (PDF 914 kb)


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© INRA and Springer-Verlag France SAS, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Institute of Forest Management, TUM School of Life Sciences WeihenstephanTechnische Universität MünchenFreisingGermany
  2. 2.Department of Forest Economics and Sustainable Land-use PlanningGeorg-August Universität GöttingenGöttingenGermany
  3. 3.Bavarian State Institute of Forestry (LWF)FreisingGermany

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