Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 490848
Title Seeing Central African forests through their largest trees
Author(s) Bastin, J.F.; Barbier, N.; Réjou-Méchain, M.; Fayolle, A.; Gourlet-Fleury, S.; Maniatis, D.; Haulleville, T. De; Baya, F.; Beeckman, H.; Beina, D.; Couteron, P.; Chuyong, G.; Dauby, G.; Doucet, J.L.; Droissart, V.; Dufrêne, M.; Ewango, C.E.N.; Gillet, F.; Gonmadje, C.H.; Hart, T.; Kavali, T.; Kenfack, D.; Libalah, M.; Malhi, Y.; Makana, J.R.; Pélissier, R.; Ploton, P.; Serckx, S.; Sonké, B.; Stevart, T.; Thomas, D.W.; Cannière, C. De; Bogaert, J.
Source Scientific Reports 5 (2015). - ISSN 2045-2322 - 8 p.
Department(s) Forest Ecology and Forest Management
Publication type Refereed Article in a scientific journal
Publication year 2015
Keyword(s) tropical forest - biomass - size - distributions - diversity - dynamics
Abstract 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.
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