Closing a gap in tropical forest biomass estimation : taking crown mass variation into account in pantropical allometries

Pierre Ploton (1, 2) , Nicolas Barbier (2, 3) , Stephane Momo Takoudjou (4, 5, 2) , Maxime Réjou-Méchain (6, 2, 3) , Faustin Boyemba Bosela (7) , Georges Chuyong (8) , Gilles Dauby , Vincent Droissart (2, 3) , Adeline Fayolle (9) , Rosa Calisto Goodman (10) , Matieu Henry (11) , Narcisse Guy Kamdem (5) , John Katembo Mukirania (7) , David Kenfack (12) , Libalah Moses (5) , Alfred Ngomanda (13) , Vivien Rossi (14) , Bonaventure Sonké (5) , Nicolas Texier (5, 1) , Duncan Thomas (15) , Donatien Zebaze (5) , Pierre Couteron (2, 3) , Uta Berger (16) , Raphaël Pélissier (2, 3)

1 AgroParisTech
2 UMR AMAP - Botanique et Modélisation de l'Architecture des Plantes et des Végétations
3 IRD - Institut de Recherche pour le Développement
4 Master Ecologie-Environnement/BVT
5 University of Yaoundé [Cameroun]
6 IFP - Institut Français de Pondichéry
7 KISANGANI UNIVERSITY - Université de Kisangani
8 University of Buea
9 Université de Liège
10 Yale University [New Haven]
11 FAO - Food and Agriculture Organization of the United Nations [Rome, Italie]
12 Harvard University
13 Institut de Recherche en Ecologie Tropicale
14 UPR Forêts et Sociétés - Forêts et Sociétés
15 OSU - Oregon State University
16 TU Dresden - Technische Universität Dresden = Dresden University of Technology

Accurately monitoring tropical forest carbon stocks is a challenge that remains outstanding. Allometric models that consider tree diameter, height and wood density as predictors are currently used in most tropical forest carbon studies. In particular, a pantropical biomass model has been widely used for approximately a decade, and its most recent version will certainly constitute a reference model in the coming years. However, this reference model shows a systematic bias towards the largest trees. Because large trees are key drivers of forest carbon stocks and dynamics, understanding the origin and the consequences of this bias is of utmost concern. In this study, we compiled a unique tree mass data set of 673 trees destructively sampled in five tropical countries (101 trees > 100 cm in diameter) and an original data set of 130 forest plots (1 ha) from central Africa to quantify the prediction error of biomass allometric models at the individual and plot levels when explicitly taking crown mass variations into account or not doing so. We first showed that the proportion of crown to total tree aboveground biomass is highly variable among trees, ranging from 3 to 88 %. This proportion was constant on average for trees < 10 Mg (mean of 34 %) but, above this threshold, increased sharply with tree mass and exceeded 50 % on average for trees  ≥  45 Mg. This increase coincided with a progressive deviation between the pantropical biomass model estimations and actual tree mass. Taking a crown mass proxy into account in a newly developed model consistently removed the bias observed for large trees (> 1 Mg) and reduced the range of plot-level error (in %) from [−23; 16] to [0; 10]. The disproportionally higher allocation of large trees to crown mass may thus explain the bias observed recently in the reference pantropical model. This bias leads to far-from-negligible, but often overlooked, systematic errors at the plot level and may be easily corrected by taking a crown mass proxy for the largest trees in a stand into account, thus suggesting that the accuracy of forest carbon estimates can be significantly improved at a minimal cost.

Mots clés: Tropics; allometrries; tropical forest; biomass estimation

Domaines: Biodiversité et Ecologie

Pierre Ploton, Nicolas Barbier, Stephane Momo Takoudjou, Maxime Réjou-Méchain, Faustin Boyemba Bosela, et al.. Closing a gap in tropical forest biomass estimation : taking crown mass variation into account in pantropical allometries. Biogeosciences, 2016, 13 (5), pp.1571-1585. ⟨10.5194/bg-13-1571-2016⟩. ⟨hal-01358263⟩