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

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 direct...

Full description

Saved in:
Bibliographic Details
Published inGlobal ecology and biogeography Vol. 23; no. 8; pp. 935 - 946
Main Authors 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, 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, Tomas 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, Souza, Priscila F, Steininger, Marc K, Stropp, Juliana, Terborgh, John, Thomas, Raquel, Toledo, Marisol, Torres‐Lezama, Armando, Andel, Tinde R, Heijden, Geertje M. F, Vieira, Ima C. G, Vieira, Simone, Vilanova‐Torre, Emilio, Vos, Vincent A, Wang, Ophelia, Zartman, Charles E, Malhi, Yadvinder, Phillips, Oliver L
Format Journal Article
LanguageEnglish
Published Oxford Blackwell Science 01.08.2014
Blackwell Publishing Ltd
John Wiley & Sons Ltd
Blackwell
Wiley Subscription Services, Inc
Wiley
BlackWell Publishing Ltd
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary: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: http://dx.doi.org/10.5521/FORESTPLOTS.NET/2014_1 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.
Bibliography:http://dx.doi.org/10.1111/geb.12168
Natural Environment Research Council (NERC) Urgency
Universal/CNPq - No. 473308/2009-6
Gordon and Betty Moore Foundation
Hidroveg FAPESP/FAPEAM
Investissement d'Avenir grants of the French ANR - No. ANR-10-LABX-0025; No. ANR-10-LABX-0041
ERC Advanced Grant
European Union's Seventh Framework Programme - No. 283080; No. 282664
ark:/67375/WNG-1KL4DB01-3
Figure S1 Semivariogram showing how variance between biomass values for the field plots varies with distance. Table S1 Parameters for the fits in Figure 2. The permanent archive of the field plot data can be accessed at: http://dx.doi.org/10.5521/FORESTPLOTS.NET/2014_1
Royal Society Fellowship
NERC - No. NE/I021217/1; No. NE/I021160/1
ERC
INCT-CENBAM
Royal Society Wolfson Research Merit Award
PRONEX - FAPEAM/CNPq - No. 1600/2006
ArticleID:GEB12168
istex:28D85ADAEEE541E98C3CA7421B26F6684219AF60
NERC Consortium - No. NE/F005806/1; No. NE/D005590/1
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
PMCID: PMC4579864
Editor: Jeremy Kerr
ISSN:1466-822X
1466-8238
1466-822X
DOI:10.1111/geb.12168