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Stand-level mortality models for Nordic boreal forests / Jouni Siipilehto in Silva fennica, vol 54 n° 5 (December 2020)  

Public [article]  inSilva fennica > vol 54 n° 5 (December 2020) . - n° 10414 Titre : Stand-level mortality models for Nordic boreal forests Type de document : Article/Communication Auteurs : Jouni Siipilehto, Auteur ; Micky Allen, Auteur ; Urban Nilsson, Auteur ; Andreas Brunner, Auteur ; et al., Auteur ; Urban Nilsson Année de publication : 2020 Article en page(s) : n° 10414 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] âge du peuplement forestier [Termes IGN] Finlande [Termes IGN] forêt boréale [Termes IGN] inventaire forestier étranger (données) [Termes IGN] modèle de simulation [Termes IGN] modélisation de la forêt [Termes IGN] mortalité [Termes IGN] Norvège [Termes IGN] régression logistique [Termes IGN] Suède [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) New mortality models were developed for the purpose of improving long-term growth and yield simulations in Finland, Norway, and Sweden and were based on permanent national forest inventory plots from Sweden and Norway. Mortality was modelled in two steps. The first model predicts the probability of survival, while the second model predicts the proportion of basal area in surviving trees for plots where mortality has occurred. In both models, the logistic function was used. The models incorporate the variation in prediction period length and in plot size. Validation of both models indicated unbiased mortality rates with respect to various stand characteristics such as stand density, average tree diameter, stand age, and the proportion of different tree species, Scots pine (Pinus sylvestris L.), Norway spruce (Picea abies (L.) Karst.), and broadleaves. When testing against an independent dataset of unmanaged spruce-dominated stands in Finland, the models provided unbiased prediction with respect to stand age. Numéro de notice : A2020-854 Affiliation des auteurs : non IGN Thématique : FORET/MATHEMATIQUE Nature : Article DOI : 10.14214/sf.10414 Date de publication en ligne : 01/12/2020 En ligne : https://doi.org/10.14214/sf.10414 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98710 [article]