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A stand-level growth and yield model for thinned and unthinned even-aged Scots pine forests in Norway / Christian Kuehne in Silva fennica, vol 56 n° 1 (January 2022)  

Public [article]  inSilva fennica > vol 56 n° 1 (January 2022) . - n° 1 Titre : A stand-level growth and yield model for thinned and unthinned even-aged Scots pine forests in Norway Type de document : Article/Communication Auteurs : Christian Kuehne, Auteur ; J. Paul McLean, Auteur ; Kobra Maleki, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 1 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] branche (arbre) [Termes IGN] éclaircie (sylviculture) [Termes IGN] forêt équienne [Termes IGN] gestion forestière [Termes IGN] hauteur des arbres [Termes IGN] modèle de croissance végétale [Termes IGN] Norvège [Termes IGN] Pinus sylvestris [Termes IGN] rendement [Termes IGN] surface terrière [Termes IGN] volume en bois [Vedettes matières IGN] Sylviculture Résumé : (auteur) Management of Scots pine (Pinus sylvestris L.) in Norway requires a forest growth and yield model suitable for describing stand dynamics of even-aged forests under contemporary climatic conditions with and without the effects of silvicultural thinning. A system of equations forming such a stand-level growth and yield model fitted to long-term experimental data is presented here. The growth and yield model consists of component equations for (i) dominant height, (ii) stem density (number of stems per hectare), (iii) total basal area, (iv) and total stem volume fitted simultaneously using seemingly unrelated regression. The component equations for stem density, basal area, and volume include a thinning modifier to forecast stand dynamics in thinned stands. It was shown that thinning significantly increased basal area and volume growth while reducing competition related mortality. No significant effect of thinning was found on dominant height. Model examination by means of various fit statistics indicated no obvious bias and improvement in prediction accuracy in comparison to existing models in general. An application of the developed stand-level model comparing different management scenarios exhibited plausible long-term behavior and we propose this is therefore suitable for national deployment. Numéro de notice : A2022-171 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.14214/sf.10627 Date de publication en ligne : 26/01/2022 En ligne : https://doi.org/10.14214/sf.10627 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99806 [article]