Annals of Forest Science

, Volume 72, Issue 3, pp 289–301 | Cite as

Developing predictive models of wind damage in Austrian forests

  • Ferenc Pasztor
  • Christoph Matulla
  • Maja Zuvela-Aloise
  • Werner Rammer
  • Manfred J. Lexer
Original Paper



Among natural disturbances, wind storms cause the greatest damage to forests in Austria.


The aim of this study is to quantify the effects of site, stand and meteorological attributes on the wind disturbance regime at the operational scale of forest stands.


We used binomial generalized linear mixed models (GLMMs) to quantify the probability of damage events and linear mixed models (LMMs) to explain the damage intensity at the forest stand level in four management units with a total forest area of approximately 28,800 ha.


Timber stock volume, stand age, elevation, previous disturbances, wind gust speed and frozen state of soil contributed in explaining probability of wind damage. While the model of disturbance probability correctly classified 90 % of all cases in the data set (specificity 95 %, sensitivity 26 %), the model for damage intensity explained only low percentages of the variation in the observed damage data (full model R 2 = 0.38, fixed effects-only model R 2 = 0.09; cross-validation in the four forest management units yielded similar R 2 values).


The developed models indicated that decreasing the proportion of Norway spruce (Picea abies [L.] Karst), limiting stand age and reducing the timber stock in course of tending treatments in stands exposed to wind disturbance can mitigate the risk and the expected damage intensity. High gust speeds and salvage cuts after earlier damage increase the probability of further wind disturbance events.


Storm Disturbance Windthrow Forest management Stand scale Risk 



We are indebted to the Austrian Federal Forests for making internal data available. Two anonymous referees provided detailed and helpful comments on an earlier version of the manuscript.


This study was funded by the Austrian Climate Research Program (ACRP), under grant no. K09AC0K00042.


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Copyright information

© INRA and Springer-Verlag France 2014

Authors and Affiliations

  • Ferenc Pasztor
    • 1
  • Christoph Matulla
    • 2
  • Maja Zuvela-Aloise
    • 2
  • Werner Rammer
    • 1
  • Manfred J. Lexer
    • 1
  1. 1.Institute of Silviculture, Department of Forest and Soil SciencesUniversity of Natural Resources and Life Sciences (BOKU) ViennaViennaAustria
  2. 2.Central Institute for Meteorology and GeodynamicsViennaAustria

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