Allometric options for predicting tropical tree height and crown area from stem diameter
2023
Libalah Bakonck, Moses | Fayolle, Adeline | Barbier, Nicolas | Picard, Nicolas | Momo Takoudjou, Stephane | Bocko, Yannick Enock | Ii Mofack, Gislain | Katembo, John, Mukirania | Loumeto, Joel | Yongo, Olga Diane | Ngomanda, Alfred | Ngomanda, Alfred | Couteron, Pierre | Sonké, Bonaventure | Rossi, Vivien | Université de Yaoundé I | Université de Liège - Gembloux | Botanique et Modélisation de l'Architecture des Plantes et des Végétations (UMR AMAP) ; Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université de Montpellier (UM) | Groupement d'Interêt Public Ecosystèmes Forestiers GIP ECOFOR (GIP ECOFOR ) | University Marien Ngouabi of Brazzaville (umng) | Forêts et Sociétés (UPR Forêts et Sociétés) ; Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad) | Département Environnements et Sociétés (Cirad-ES) ; Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)
publié sur la plateforme de prerpints : Research Square
Mostrar más [+] Menos [-]Inglés. Tree height and crown area are important predictors of aboveground biomass but difficult to measure on the ground. Numerous allometric models have been established to predict tree height from diameter (H–D) and crown area from diameter (CA–D). A major challenge is to select the most precise and accurate allometric model among existing ones, depending on the species composition and forest type where the model is to be applied. To propose a principle to select tree H–D and tree CA–D allometric models, we build a method based on k -fold cross-validation using a large dataset spanning six forest types from central Africa. We then compared the errors and biases using 22 previously established H–D and CA–D allometric model forms via three inter-comparable scenarios: locally derived for the forest type vs. regional vs. pantropical; regional (encompassing the forest type) vs . pantropical; regional (not encompassing the forest type) vs. pantropical model. H–D allometries were more variable across forest types in central Africa than CA–D allometries: (i) forest type explained 6% of the variance in H–D allometry and 2% of the variance in CA–D allometry, while species explained 9% and 2% of the variance in H–D allometry and CA–D allometry, respectively; (ii) for H–D allometry, the six forest types resulted in five best-fit models whereas, for CA–D allometry, four models provided the best fit for the six forest types. We recommend using allometric models specific to the forest type, preferentially to regional ones. Regional models should in turn be preferred to pantropical allometric models.
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