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. 2015 Aug 17:5:13156.
doi: 10.1038/srep13156.

Seeing Central African forests through their largest trees

J-F Bastin  1 , N Barbier  2 , M Réjou-Méchain  3 , A Fayolle  4 , S Gourlet-Fleury  5 , D Maniatis  6 , T de Haulleville  7 , F Baya  8 , H Beeckman  9 , D Beina  10 , P Couteron  2 , G Chuyong  11 , G Dauby  12 , J-L Doucet  4 , V Droissart  2 , M Dufrêne  4 , C Ewango  13 , J F Gillet  4 , C H Gonmadje  14 , T Hart  15 , T Kavali  16 , D Kenfack  17 , M Libalah  18 , Y Malhi  6 , J-R Makana  13 , R Pélissier  2 , P Ploton  2 , A Serckx  19 , B Sonké  20 , T Stevart  21 , D W Thomas  22 , C De Cannière  23 , J Bogaert  4
Affiliations

Seeing Central African forests through their largest trees

J-F Bastin et al. Sci Rep. .

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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Figures

Figure 1
Figure 1. Site locations.
Spatial distribution of the study sites superimposed in white on a false color of Enhanced Vegetation Index (EVI) composite map centred on Central Africa. The map was produced from a yearly synthesis from twelve MODIS-EVI 250 m data (MOD13Q1 c5). The 8th, 1st and 8th, 16-day periods are projected in red, green and blue color channels. Copyright Dr. Valery Gond.
Figure 2
Figure 2. Proportion and prediction of the entire above-ground biomass (AGBTOT) and species richness (speciesTOT) from the largest trees.
Results are displayed for the entire dataset (black dotted-line) superimposed on each study site (coloured lines). Larger trees store most of the AGBTOT (a) and predict most of the AGBTOT variance among plots (b) up to an R2 of 0.87 for the 20 largest trees (c). Species richness is generally high among the largest trees but depends on forest type (d) as shown by the S-shaped curve of the Ituri site, which corresponds to the monodominant Gilbertiodendron dewevrei forests. Species richness of the largest trees often predicts a non-negligible share of total species richness (e) but is strongly dependent on site location (f).
Figure 3
Figure 3. Proportion of AGB hyperdominant species by location.
The sums in the red (local and regional AGB Hyperdominant species) and light grey (local but not regional AGB Hyperdominant species) barplots correspond to the sum of the local AGB dominant species (≥50% of AGBTOT). White integers correspond to the number of species in each fraction.
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