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Gewählte Publikation:

Pasztor, F; Matulla, C; Zuvela-Aloise, M; Rammer, W; Lexer, MJ.
(2015): Developing predictive models of wind damage in Austrian forests
ANN FOREST SCI. 2015; 72(3): FullText FullText_BOKU

Abstract:
Context Among natural disturbances, wind storms cause the greatest damage to forests in Austria. Aim 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. Methods 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. Results 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). Conclusion 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.
Autor*innen der BOKU Wien:
Lexer Manfred Josef
Pasztor Ferenc
Rammer Werner
BOKU Gendermonitor:


Find related publications in this database (Keywords)
Storm
Disturbance
Windthrow
Forest management
Stand scale
Risk


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