Markedly divergent estimates of Amazon forest carbon density from ground plots and satellites

Mitchard, Edward T.A., Feldpausch, Ted R., Brienen, Roel J.W., Lopez-Gonzalez, Gabriela, Monteagudo, Abel, Baker, Timothy R., Lewis, Simon L., Lloyd, Jon, Quesada, Carlos A., Gloor, Manuel, ter Steege, Hans, Meir, Patrick, Alvarez, Esteban, Araujo-Murakami, Alejandro, Aragão, Luiz E.O.C., Arroyo, Luzmila, Aymard, Gerardo, Banki, Olaf, Bonal, Damien, Brown, Sandra, Brown, Foster I., Cerón, Carlos E., Chama Moscoso, Victor, Chave, Jerome, Comiskey, James A., Cornejo, Fernando, Corrales Medina, Massiel, Da Costa, Lola, Costa, Flavia R.C., Di Fiore, Anthony, Domingues, Thomas F., Erwin, Terry L., Frederickson, Todd, Higuchi, Niro, Honorio Coronado, Euridice N., Killeen, Tim J., Laurance, William F., Levis, Carolina, Magnusson, William E., Marimon, Beatriz S., Marimon Junior, Ben Hur, Mendoza Polo, Irina, Mishra, Piyush, Nascimento, Marcelo T., Neill, David, Núñez Vargas, Mario P., Palacios, Walter A., Parada, Alexander, Pardo Molina, Guido, Peña-Claros, Marielos, Pitman, Nigel, Peres, Carlos A., Poorter, Lourens, Prieto, Adriana, Ramirez-Angulo, Hirma, Restrepo Correa, Zorayda, Roopsind, Anand, Roucoux, Katherine H., Rudas, Agustin, Salomão, Rafael P., Schietti, Juliana, Silveira, Marcos, de Souza, Priscila F., Steininger, Marc K., Stropp, Juliana, Terborgh, John, Thomas, Raquel, Toledo, Marisol, Torres-Lezama, Armando, van Andel, Tinde R., van der Heijden, Geertje M.F., Vieira, Ima C.G., Vieira, Simone, Vilanova-Torre, Emilio, Vos, Vincent A., Wang, Ophelia, Zartman, Charles E., Malhi, Yadvinder, and Phillips, Oliver L. (2014) Markedly divergent estimates of Amazon forest carbon density from ground plots and satellites. Global Ecology and Biogeography, 23 (8). pp. 935-946.

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Aim: The accurate mapping of forest carbon stocks is essential for understanding the global carbon cycle, for assessing emissions from deforestation, and for rational land-use planning. Remote sensing (RS) is currently the key tool for this purpose, but RS does not estimate vegetation biomass directly, and thus may miss significant spatial variations in forest structure. We test the stated accuracy of pantropical carbon maps using a large independent field dataset.

Location: Tropical forests of the Amazon basin. The permanent archive of the field plot data can be accessed at:

Methods: Two recent pantropical RS maps of vegetation carbon are compared to a unique ground-plot dataset, involving tree measurements in 413 large inventory plots located in nine countries. The RS maps were compared directly to field plots, and kriging of the field data was used to allow area-based comparisons.

Results: The two RS carbon maps fail to capture the main gradient in Amazon forest carbon detected using 413 ground plots, from the densely wooded tall forests of the north-east, to the light-wooded, shorter forests of the south-west. The differences between plots and RS maps far exceed the uncertainties given in these studies, with whole regions over- or under-estimated by > 25%, whereas regional uncertainties for the maps were reported to be < 5%.

Main conclusions: Pantropical biomass maps are widely used by governments and by projects aiming to reduce deforestation using carbon offsets, but may have significant regional biases. Carbon-mapping techniques must be revised to account for the known ecological variation in tree wood density and allometry to create maps suitable for carbon accounting. The use of single relationships between tree canopy height and above-ground biomass inevitably yields large, spatially correlated errors. This presents a significant challenge to both the forest conservation and remote sensing communities, because neither wood density nor species assemblages can be reliably mapped from space.

Item ID: 35231
Item Type: Article (Research - C1)
ISSN: 1466-8238
Keywords: above-ground biomass, allometry, carbon cycle, REDD+, remote sensing, satellite mapping, wood density
Additional Information:

This is an open access article published under a CC-BY 3.0 license. AB 19/03/18

Funders: Gordon and Betty Moore Foundation (GBMF), European Union Seventh Framework Programme (EU FP7), Natural Environment Research Council (NERC), French National Research Agency (ANR), CNPq/PELD, Royal Society, European Research Council (ERC), Australian Research Council (ARC)
Projects and Grants: EU FP7 283080 GEOCARBON, EU FP7 282664 AMAZALERT, ERC grant 'Tropical Forests in the Changing Earth System', NERC Urgency Grant, NERC Consortium Grant AMAZONICA NE/F005806/1, NERC Consortium Grant TROBIT NE/D005590/1, ANR CEBA: ANR-10-LABX-0025, ANR TULIP: ANR-10-LABX-0041, CNPq/PELD Proc. 558069/2009-6, NERC grant ref: NE/FI021217/1, NERC grant ref: NE/FI021160/1, Royal Society Fellowship, ERC Advanced Grant, Royal Society Wolfson Research Merit Award, ARC Future Fellowship FT110100457 (FT3)
Research Data:
Date Deposited: 17 Sep 2014 00:22
FoR Codes: 05 ENVIRONMENTAL SCIENCES > 0502 Environmental Science and Management > 050202 Conservation and Biodiversity @ 100%
SEO Codes: 96 ENVIRONMENT > 9608 Flora, Fauna and Biodiversity > 960899 Flora, Fauna and Biodiversity of Environments not elsewhere classified @ 100%
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