Publications des scientifiques de l'IRD

Ploton Pierre, Barbier Nicolas, Momo Takoudjou Stéphane, Réjou-Méchain Maxime, Bosela F. B., Chuyong G., Dauby G., Droissart Vincent, Fayolle A., Goodman R. C., Henry M., Kamdem N. G., Mukirania J. K., Kenfack D., Libalah M., Ngomanda A., Rossi V., Sonke B., Texier Nicolas, Thomas D., Zebaze D., Couteron Pierre, Berger U., Pélissier Raphaël. (2016). Closing a gap in tropical forest biomass estimation : taking crown mass variation into account in pantropical allometries. Biogeosciences, 13 (5), p. 1571-1585. ISSN 1726-4170.

Titre du document
Closing a gap in tropical forest biomass estimation : taking crown mass variation into account in pantropical allometries
Année de publication
2016
Type de document
Article référencé dans le Web of Science WOS:000372082500012
Auteurs
Ploton Pierre, Barbier Nicolas, Momo Takoudjou Stéphane, Réjou-Méchain Maxime, Bosela F. B., Chuyong G., Dauby G., Droissart Vincent, Fayolle A., Goodman R. C., Henry M., Kamdem N. G., Mukirania J. K., Kenfack D., Libalah M., Ngomanda A., Rossi V., Sonke B., Texier Nicolas, Thomas D., Zebaze D., Couteron Pierre, Berger U., Pélissier Raphaël
Source
Biogeosciences, 2016, 13 (5), p. 1571-1585 ISSN 1726-4170
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 < 10Mg (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.
Plan de classement
Sciences fondamentales / Techniques d'analyse et de recherche [020] ; Sciences du milieu [021] ; Etudes, transformation, conservation du milieu naturel [082]
Localisation
Fonds IRD [F B010066675]
Identifiant IRD
fdi:010066675
Contact