Article thumbnail

Seeing Central African forests through their largest trees

By J. F. Bastin, Nicolas Barbier, Maxime Réjou-Méchain, A. Fayolle, S. Gourlet-Fleury, D. Maniatis, T. de Haulleville, F. Baya, H. Beeckman, D. Beina, Pierre Couteron, G. Chuyong, G. Dauby, J. L. Doucet, Vincent Droissart, M. Dufrene, C. Ewango, J. F. Gillet, C. H. Gonmadje, T. Hart, T. Kavali, D. Kenfack, M. Libalah, Y. Malhi, J. R. Makana, Raphaël Pélissier, Pierre Ploton, A. Serckx, B. Sonke, T. Stevart, D. W. Thomas, C. De Canniere and J. Bogaert


Large tropical trees and a few dominant species were recently identified as the main structuring elements of tropical forests. However, such result did not translate yet into quantitative approaches which are essential to understand, predict and monitor forest functions and composition over large, often poorly accessible territories. Here we show that the above-ground biomass (AGB) of the whole forest can be predicted from a few large trees and that the relationship is proved strikingly stable in 175 1-ha plots investigated across 8 sites spanning Central Africa. We designed a generic model predicting AGB with an error of 14% when based on only 5% of the stems, which points to universality in forest structural properties. For the first time in Africa, we identified some dominant species that disproportionally contribute to forest AGB with 1.5% of recorded species accounting for over 50% of the stock of AGB. Consequently, focusing on large trees and dominant species provides precise information on the whole forest stand. This offers new perspectives for understanding the functioning of tropical forests and opens new doors for the development of innovative monitoring strategies

Year: 2015
DOI identifier: 10.1038/srep13156
OAI identifier:
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • http://www.documentation.ird.f... (external link)

  • To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.

    Suggested articles