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Large-scale patterns in forest growth rates are mainly driven by climatic variables and stand characteristics / Hao Zhang in Forest ecology and management, vol 435 (1 March 2019)  

Public [article]  inForest ecology and management > vol 435 (1 March 2019) . - pp 120 - 127 Titre : Large-scale patterns in forest growth rates are mainly driven by climatic variables and stand characteristics Type de document : Article/Communication Auteurs : Hao Zhang, Auteur ; Kelin Wang, Auteur ; Zhaoxia Zeng, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 120 - 127 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] biomasse [Termes IGN] changement climatique [Termes IGN] Chine [Termes IGN] croissance des arbres [Termes IGN] forêt [Termes IGN] modèle de croissance végétale [Termes IGN] plantation forestière [Termes IGN] puits de carbone [Vedettes matières IGN] Végétation et changement climatique Résumé : (Auteur) Comparing the growth rate of natural forest and plantation forest may be useful to better understand rates of carbon sequestration and carbon turnover. However, the large-scale patterns of biomass growth rates in China’s forests are still not well defined. We analyzed the growth rates of forest leaves, branches, stems, and roots across forest communities in China by using data collection, collation, and systematic analysis of published research and our unpublished data. The biomass growth rates in all forests exhibited negative latitudinal trends and negative altitudinal trends, with significant influence from climatic variables and stand characteristics. Stand characteristics explained more variation in growth rates of forest biomass than did climatic variables, and growth rates of forest leaves, branches, stems, and roots varied in relation to climate, stand characteristics, and forest origin. The cross-validated results of stepwise multiple regression (SMR) models and neural network models (NNM) indicated that the prediction accuracy of growth rate of forest biomass by NNM was better than that of the SMR models. Our results improve understanding of the environmental factors affecting Chinese forest growth and inform efforts to model dynamics of carbon accumulation in China’s forests. Numéro de notice : A2019-184 Affiliation des auteurs : non IGN Thématique : FORET/MATHEMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.foreco.2018.12.054 Date de publication en ligne : 04/01/2019 En ligne : https://doi.org/10.1016/j.foreco.2018.12.054 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92718 [article]