@article{fdi:010074381,
  title = {{A} regional allometry for the {C}ongo basin forests based on the largest ever destructive sampling},
  author = {{F}ayolle, {A}. and {N}gomanda, {A}. and {M}basi, {M}. and {B}arbier, {N}icolas and {B}ocko, {Y}. and {B}oyemba, {F}. and {C}outeron, {P}ierre and {F}onton, {N}. and {K}amdem, {N}. and {K}atembo, {J}. and {K}ondaoule, {H}. {J}. and {L}oumeto, {J}. and {M}aidou, {H}. {M}. and {M}ankou, {G}. and {M}engu, {T}. and {M}ofack, {G}. {I}. {I}. and {M}oundounga, {C}. and {M}oundoung, {Q}. and {N}guimbous, {L}. and {N}chama, {N}. {N}. and {O}biang, {D}. and {A}sue, {F}. {O}. {M}. and {P}icard, {N}. and {R}ossi, {V}. and {S}enguela, {Y}. {P}. and {S}onke, {B}. and {V}iard, {L}. and {Y}ongo, {O}. {D}. and {Z}apfack, {L}. and {M}edjibe, {V}. {P}.},
  editor = {},
  language = {{ENG}},
  abstract = {{T}he estimation and monitoring of the huge amount of carbon contained in tropical forests, and specifically in the above-ground biomass ({AGB}) of trees, is needed for the successful implementation of climate change mitigation strategies. {I}ts accuracy depends on the availability of reliable allometric equations to convert forest inventory data into {AGB} estimates. {I}n this study, we tested whether central {A}frican forests are really different from other tropical forests with respect to biomass allometry, and further examined the regional variation in tropical tree allometry across the {C}ongo basin forests. {F}ollowing the same standardized protocol, trees were destructively sampled for {AGB} in six sites representative of terra fume forests. {W}e fitted regional and local allometric models, including tree diameter, wood specific gravity, tree height, and crown radius in the {AGB} predictors, {W}e also evaluated the {AGB} predictions at the tree level across the six sites of our new models and of existing allometric models, including the pantropical equations developed by {C}have et al. (2014, 2005) and the local equations developed by {N}gomanda et al. (2014) in {G}abon. {W}ith a total of 845 tropical trees belonging to 55 {A}frican species and covering a large range of diameters (up to 200 cm), the original data presented here can be considered as the largest ever destructive sampling for a tropical region. {R}egional allometric models were established and including tree height and crown radius had a small but significant effect on {AGB} predictions. {I}n contrast to our expectations, tree height and crown radius did not explain much between-site variation. {E}xamining the performance of general models (pantropical or regional) versus local models (site-specific), we found little advantage of using local equations. {E}arlier pantropical equations developed for moist forests were found to provide reasonable predictions of tree {AGB} in most sites, though the wettest sites, i. e., evergreen forests in {E}quatorial {G}uinea and, to a lesser extent in {G}abon, tended to show a wet forest allometry. {F}or the {C}ongo basin forests, except in {E}quatorial {G}uinea where local models might be preferred, we recommend using our regional models, and otherwise the most recent pantropical models, that were validated here. {T}hese results constitute a critical step for the estimation and monitoring of biomass/carbon stocks contained in the second largest contiguous block of tropical forests worldwide, and the successful implementation of climate change mitigation strategies, such as {REDD}+.},
  keywords = {{A}llometry ; {B}iomass ; {C}arbon ; {C}ongo basin ; {C}rown radius ; {T}ropical trees ; {T}ree diameter ; {T}otal tree height ; {W}ood specific gravity ; {CAMEROUN} ; {CENTRAFRIQUE} ; {CONGO} ; {GABON} ; {GUINEE} {EQUATORIALE} ; {REPUBLIQUE} {DEMOCRATIQUE} {DU} {CONGO} ; {CONGO} {BASSIN}},
  booktitle = {},
  journal = {{F}orest {E}cology and {M}anagement},
  volume = {430},
  numero = {},
  pages = {228--240},
  ISSN = {0378-1127},
  year = {2018},
  DOI = {10.1016/j.foreco.2018.07.030},
  URL = {https://www.documentation.ird.fr/hor/fdi:010074381},
}