@article{fdi:010064920,
  title = {{S}eeing {C}entral {A}frican forests through their largest trees},
  author = {{B}astin, {J}. {F}. and {B}arbier, {N}icolas and {R}{\'e}jou-{M}{\'e}chain, {M}axime and {F}ayolle, {A}. and {G}ourlet-{F}leury, {S}. and {M}aniatis, {D}. and de {H}aulleville, {T}. and {B}aya, {F}. and {B}eeckman, {H}. and {B}eina, {D}. and {C}outeron, {P}ierre and {C}huyong, {G}. and {D}auby, {G}. and {D}oucet, {J}. {L}. and {D}roissart, {V}incent and {D}ufrene, {M}. and {E}wango, {C}. and {G}illet, {J}. {F}. and {G}onmadje, {C}. {H}. and {H}art, {T}. and {K}avali, {T}. and {K}enfack, {D}. and {L}ibalah, {M}. and {M}alhi, {Y}. and {M}akana, {J}. {R}. and {P}{\'e}lissier, {R}apha{\¨e}l and {P}loton, {P}ierre and {S}erckx, {A}. and {S}onke, {B}. and {S}tevart, {T}. and {T}homas, {D}. {W}. and {D}e {C}anniere, {C}. and {B}ogaert, {J}.},
  editor = {},
  language = {{ENG}},
  abstract = {{L}arge tropical trees and a few dominant species were recently identified as the main structuring elements of tropical forests. {H}owever, 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. {H}ere 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 {C}entral {A}frica. {W}e 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. {F}or the first time in {A}frica, 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}. {C}onsequently, focusing on large trees and dominant species provides precise information on the whole forest stand. {T}his offers new perspectives for understanding the functioning of tropical forests and opens new doors for the development of innovative monitoring strategies.},
  keywords = {{AFRIQUE} {CENTRALE} ; {CAMEROUN} ; {CENTRAFRIQUE} ; {GABON} ; {REPUBLIQUE} {DEMOCRATIQUE} {DU} {CONGO}},
  booktitle = {},
  journal = {{S}cientific {R}eports - {N}ature},
  volume = {5},
  numero = {},
  pages = {13156 [8 ]},
  ISSN = {2045-2322},
  year = {2015},
  DOI = {10.1038/srep13156},
  URL = {https://www.documentation.ird.fr/hor/fdi:010064920},
}