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Comparing individual-tree approaches for predicting height growth of underplanted seedlings / John M. Lhotka in Annals of Forest Science, vol 72 n° 4 (June 2015)  

Public [article]  inAnnals of Forest Science > vol 72 n° 4 (June 2015) . - pp 469 - 477 Titre : Comparing individual-tree approaches for predicting height growth of underplanted seedlings Type de document : Article/Communication Auteurs : John M. Lhotka, Auteur ; Edward F. Loewenstein, Auteur Année de publication : 2015 Article en page(s) : pp 469 - 477 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Végétation [Termes IGN] canopée [Termes IGN] Géorgie (Etats-Unis) [Termes IGN] hauteur des arbres [Termes IGN] inventaire forestier étranger (données) [Termes IGN] Liriodendron tulipifera [Termes IGN] modèle de croissance végétale [Termes IGN] plantation forestière [Termes IGN] Quercus nigra [Termes IGN] sous-bois [Termes IGN] sylviculture Résumé : (auteur) Key message : Individual-tree seeding height growth models developed using tree inventory data were comparable to those requiring the unique observation of point-based canopy structure data at each seedling. Context : Quantitative approaches describing the relationship between canopy structure and seedling growth can inform silvicultural decision making regarding the development of tree reproduction beneath a dominant forest canopy. Aims : Individual-tree seedling growth models with canopy structure predictors derived from tree inventory data have not been well-explored. This study compared a model framework fit using point-based measures of canopy structure observed at the seedling level to one fit using area-wide canopy structure variables derived from standard inventory plot data. Methods : Species-specific models predicting 5-year height growth were fit for cherrybark oak (Quercus pagoda Raf.), water oak (Quercus nigra L.), and yellow-poplar (Liriodendron tulipifera L.) underplanted within a canopy structure gradient created by silvicultural manipulation of a closed-canopy forest in Georgia, USA. Results : Though the species varied in shade tolerance and growth rates, the general relationship between the predictor variables and height growth was similar among species and model type. Models highlight the importance of including predictor variables that describe seedling size along with openness and vertical structure of the forest canopy. Conclusion : While the two model frameworks had comparable fit statistics, the one with predictors derived from tree inventory data may have enhanced utility as it can be directly integrated into existing individual-tree forest growth simulators. Numéro de notice : A2015-424 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1007/s13595-014-0453-6 Date de publication en ligne : 16/01/2015 En ligne : https://doi.org/10.1007/s13595-014-0453-6 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77014 [article]