Biomass : an r package for estimating above-ground biomass and its uncertainty in tropical forests
Abstract
1. Estimating forest above-ground biomass (AGB), or carbon (AGC), in tropical forests has become a major
concern for scientists and stakeholders. However, AGB assessment procedures are not fully standardized and
even 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 uncertainty
from forest plot datasets, using a Bayesian inference procedure. The package builds upon previous work on
pantropical and regional biomass allometric equations and published datasets by default but it can also
integrate unpublished or complementary datasets in many steps.
3. BIOMASS performs a number of standard tasks on input forest tree inventories: i) tree species
identification, 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 from
pantropical or regional models; iv) finally, AGB/AGC are estimated by propagating the errors associated with
all the calculation steps up to the final estimate. R code is given in the paper and in the appendix for
illustration purpose.
4. The BIOMASS package should contribute to improved standards for AGB calculation for tropical forest
stands, and will encourage users to report the uncertainties associated with stand-level AGB/AGC estimates
in future studies.