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<datestamp>2018-01-11</datestamp>
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<title lang=en>biomass : an r package for estimating above-ground biomass and its uncertainty in tropical forests</title>
<creator>Réjou-Méchain, Maxime</creator>
<creator>Tanguy, Ariane</creator>
<creator>Piponiot, Camille</creator>
<creator>Chave, Jérôme</creator>
<creator>Hérault, Bruno</creator>
<contributor>Laboratoire de Botanique et d'Écologie végétale appliquées (UMR AMAP) ; Institut de Recherche pour le Développement (IRD)</contributor>
<contributor>Institut Français de Pondichéry (IFP) ; Ministère de l'Europe et des Affaires étrangères (MEAE) - Centre National de la Recherche Scientifique (CNRS)</contributor>
<contributor>Ecologie des forêts de Guyane (ECOFOG) ; Centre de Coopération Internationale en Recherche Agronomique pour le Développement (CIRAD) - Institut National de la Recherche Agronomique (INRA) - Université des Antilles et de la Guyane (UAG) - AgroParisTech - Université de Guyane (UG) - Centre National de la Recherche Scientifique (CNRS)</contributor>
<contributor>Evolution et diversité biologique (EDB) ; Université Paul Sabatier - Toulouse 3 (UPS) - Ecole Nationale Supérieure Agronomique de Toulouse - Centre National de la Recherche Scientifique (CNRS)</contributor>
<description>International audience</description>
<source>ISSN: 2041-210X</source>
<source>EISSN: 2041-210X</source>
<source>Methods in Ecology and Evolution</source>
<publisher>Wiley</publisher>
<identifier>hal-01558180</identifier>
<identifier>https://hal.archives-ouvertes.fr/hal-01558180</identifier>
<source>https://hal.archives-ouvertes.fr/hal-01558180</source>
<source>Methods in Ecology and Evolution, Wiley, 2017, 〈http://onlinelibrary.wiley.com/doi/10.1111/2041-210X.12753/abstract〉. 〈10.1111/2041-210X.12753〉</source>
<identifier>DOI : 10.1111/2041-210X.12753</identifier>
<relation>info:eu-repo/semantics/altIdentifier/doi/10.1111/2041-210X.12753</relation>
<source>http://onlinelibrary.wiley.com/doi/10.1111/2041-210X.12753/abstract</source>
<language>en</language>
<subject lang=en>Allometry</subject>
<subject lang=en> Error propagation</subject>
<subject lang=en> Forest Carbon</subject>
<subject lang=en> Height-diameter relationship</subject>
<subject>[SDV] Life Sciences [q-bio]</subject>
<subject>[SDV.SA.SF] Life Sciences [q-bio]/Agricultural sciences/Silviculture, forestry</subject>
<subject>[STAT] Statistics [stat]</subject>
<type>info:eu-repo/semantics/article</type>
<type>Journal articles</type>
<description lang=en>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.</description>
<date>2017-01-26</date>
</dc>
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