Biogeosciences, 13, 1571-1585, 2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research article
14 Mar 2016
Closing a gap in tropical forest biomass estimation: taking crown mass variation into account in pantropical allometries
Pierre Ploton1,2, Nicolas Barbier1, Stéphane Takoudjou Momo1,3, Maxime Réjou-Méchain1,4,5, Faustin Boyemba Bosela6, Georges Chuyong7, Gilles Dauby8,9, Vincent Droissart1,10, Adeline Fayolle11, Rosa Calisto Goodman12, Matieu Henry13, Narcisse Guy Kamdem3, John Katembo Mukirania6, David Kenfack14, Moses Libalah3, Alfred Ngomanda15, Vivien Rossi4,16, Bonaventure Sonké3, Nicolas Texier1,3, Duncan Thomas17, Donatien Zebaze3, Pierre Couteron1, Uta Berger18, and Raphaël Pélissier1 1Institut de Recherche pour le Développement, UMR-AMAP, Montpellier, France
2Institut des sciences et industries du vivant et de l'environnement, Montpellier, France
3Laboratoire de Botanique systématique et d'Ecologie, Département des Sciences Biologiques, Ecole Normale Supérieure, Université de Yaoundé I, Yaoundé, Cameroon
4Centre de coopération internationale en recherche agronomique pour le développement, Montpellier, France
5Geomatics and Applied Informatics Laboratory (LIAG), French Institute of Pondicherry, Puducherry, India
6Faculté des Sciences, Université de Kisangani, Kisangani, Democratic Republic of Congo
7Department of Botany and Plant Physiology, University of Buea, Buea, Cameroon
8Institut de Recherche pour le Développement, UMR-DIADE, Montpellier, France
9Evolutionary Biology and Ecology, Faculté des Sciences, Université Libre de Bruxelles, Brussels, Belgium
10Herbarium et Bibliothèque de Botanique africaine, Université Libre de Bruxelles, Brussels, Belgium
11Research axis on Forest Resource Management of the Biosystem engineering (BIOSE), Gembloux Agro-Bio Tech, Université de Liège, Gembloux, Belgium
12Yale School of Forestry and Environmental Studies, New Haven, USA
13Food and Agriculture Organization of the United Nations, Rome, Italy
14Center for Tropical Forest Science, Harvard University, Cambridge, USA
15Institut de Recherche en Ecologie Tropicale, Libreville, Gabon
16Département d'Informatique, Université de Yaoundé I, UMMISCO, Yaoundé, Cameroon
17Department of Botany and Plant Pathology, Oregon State University, Corvallis, USA
18Technische Universität Dresden, Faculty of Environmental Sciences, Institute of Forest Growth and Forest Computer Sciences, Tharandt, Germany
Abstract. 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.

Citation: Ploton, P., Barbier, N., Takoudjou Momo, S., Réjou-Méchain, M., Boyemba Bosela, F., Chuyong, G., Dauby, G., Droissart, V., Fayolle, A., Goodman, R. C., Henry, M., Kamdem, N. G., Mukirania, J. K., Kenfack, D., Libalah, M., Ngomanda, A., Rossi, V., Sonké, B., Texier, N., Thomas, D., Zebaze, D., Couteron, P., Berger, U., and Pélissier, R.: Closing a gap in tropical forest biomass estimation: taking crown mass variation into account in pantropical allometries, Biogeosciences, 13, 1571-1585,, 2016.
Publications Copernicus
Short summary
Monitoring forest carbon stocks requires understanding how resources allocation within trees varies across tree size, species and environmental conditions. Using data on tree dimensions and mass, we show that the average tree shape varies along ontogeny, with large canopy trees having a greater proportion of carbon in their crowns (up to 50 %). This variation pattern generates important bias in carbon predictions at both tree and stand levels, which can be corrected using simple crown metrics.
Monitoring forest carbon stocks requires understanding how resources allocation within trees...