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Height-diameter allometry for tree species in Tanzania mainland / Wilson Ancelm Mugasha in International journal of forestry research, vol 2019 ([01/03/2019])  

Public [article]  inInternational journal of forestry research > vol 2019 [01/03/2019] Titre : Height-diameter allometry for tree species in Tanzania mainland Type de document : Article/Communication Auteurs : Wilson Ancelm Mugasha, Auteur ; E.W. Mauya, Auteur ; et al., Auteur Année de publication : 2019 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] allométrie [Termes IGN] diamètre des arbres [Termes IGN] Eucalyptus (genre) [Termes IGN] hauteur des arbres [Termes IGN] inventaire forestier étranger (données) [Termes IGN] modèle mathématique [Termes IGN] Pinus (genre) [Termes IGN] Tanzanie [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) Total tree height (H) and diameter at beast height (D) are important independent variables in predicting volume, biomass, and other forest stand attributes. However, unlike D measurement, which is easy to measure with high accuracy, H measurement is laborious. This study, therefore, developed H-D relationships for ten different forest types in Tanzania Mainland. Extents in which climate and forest stand variables explain the variation in H-D allometry were also assessed. A total of 31782 sample trees covering miombo woodlands, humid montane, lowland forests, bushlands, grasslands, mangroves, cultivated land, wetlands forests, and pines and Eucalyptus species plantations were used for model development. The H estimating model without climate and forest stand variables referred herein as “base model” was first developed followed by “generalized model” which included climate and stand variables. All the data were fitted using nonlinear mixed effect modelling approach. Results indicated that generalized H estimating models had better fit than the base models. We therefore confirm a significant contribution of climate and forest structure variables in improving H-D allometry. Among the forest structure variables, basal area (BA) was far more important explanatory variable than other variables. In addition, it was found that the mean tree H tends to increase with the increase of mean precipitation (PRA). We therefore conclude that forest specific generalized H model is to be applied when predicting H. When forest type information is not available, generalized regional model may be applied. Base model may be applied when forest stand or climate information are missing. Numéro de notice : A2019-371 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1155/2019/4832849 Date de publication en ligne : 21/04/2019 En ligne : https://doi.org/10.1155/2019/4832849 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93397 [article]