Éditeur(s) : HAL CCSD Wiley
Résumé : International audience
1. Estimating forest above-ground biomass (AGB), or carbon (AGC), in tropical forests has become a majorconcern for scientists and stakeholders. However, AGB assessment procedures are not fully standardized andeven more importantly the uncertainty associated with AGB estimates is seldom assessed.2. Here, we present an R package designed to compute both AGB/AGC estimate and its associated uncertaintyfrom forest plot datasets, using a Bayesian inference procedure. The package builds upon previous work onpantropical and regional biomass allometric equations and published datasets by default but it can alsointegrate unpublished or complementary datasets in many steps.3. BIOMASS performs a number of standard tasks on input forest tree inventories: i) tree speciesidentification, if available, is automatically corrected; ii) wood density is estimated from tree species identity;iii) if height data are available, a local height-diameter allometry may be built; else height is inferred frompantropical or regional models; iv) finally, AGB/AGC are estimated by propagating the errors associated withall the calculation steps up to the final estimate. R code is given in the paper and in the appendix forillustration purpose.4. The BIOMASS package should contribute to improved standards for AGB calculation for tropical foreststands, and will encourage users to report the uncertainties associated with stand-level AGB/AGC estimatesin future studies.
ISSN: 2041-210X

hal-01558180
https://hal.archives-ouvertes.fr/hal-01558180
DOI : 10.1111/2041-210X.12753

Éditeur(s) : HAL CCSD Nature Publishing Group
Résumé : While Amazonian forests are extraordinarily diverse, the abundance of trees is skewed strongly towards relatively few 'hyperdominant' species. In addition to their diversity, Amazonian trees are a key component of the global carbon cycle, assimilating and storing more carbon than any other ecosystem on Earth. Here we ask, using a unique data set of 530 forest plots, if the functions of storing and producing woody carbon are concentrated in a small number of tree species, whether the most abundant species also dominate carbon cycling, and whether dominant species are characterized by specific functional traits. We find that dominance of forest function is even more concentrated in a few species than is dominance of tree abundance, with only ≈1% of Amazon tree species responsible for 50% of carbon storage and productivity. Although those species that contribute most to biomass and productivity are often abundant, species maximum size is also influential, while the identity and ranking of dominant species varies by function and by region.
ISSN: 2041-1723

hal-01204225
https://hal.archives-ouvertes.fr/hal-01204225
DOI : 10.1038/ncomms7857
PRODINRA : 305614
PUBMED : 25919449