Détail de l'auteur
Auteur Maja Zuvela-Aloise |
Documents disponibles écrits par cet auteur (1)
Ajouter le résultat dans votre panier
Visionner les documents numériques
Affiner la recherche Interroger des sources externes
Developing predictive models of wind damage in Austrian forests / Ferenc Pasztor in Annals of Forest Science, vol 72 n° 3 (May 2015)
[article]
Titre : Developing predictive models of wind damage in Austrian forests Type de document : Article/Communication Auteurs : Ferenc Pasztor, Auteur ; Christoph Matulla, Auteur ; Maja Zuvela-Aloise, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 289 - 301 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Végétation
[Termes IGN] Autriche
[Termes IGN] discrétisation
[Termes IGN] dommage matériel
[Termes IGN] forêt
[Termes IGN] modèle linéaire
[Termes IGN] Picea abies
[Termes IGN] station forestière
[Termes IGN] tempête
[Termes IGN] ventRésumé : (auteur) 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.Numéro de notice : A2015-452 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1007/s13595-014-0386-0 Date de publication en ligne : 11/06/2014 En ligne : https://doi.org/10.1007/s13595-014-0386-0 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77108
in Annals of Forest Science > vol 72 n° 3 (May 2015) . - pp 289 - 301[article]