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Journal Articles Global Ecology and Biogeography Year : 2014

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

Edward T. A. Mitchard (1) , Ted R. Feldpausch (2, 3) , Roel J. W. Brienen (3) , Gabriela Lopez-Gonzalez (3) , Abel Monteagudo (4) , Timothy R. Baker (3) , Simon L. Lewis (5, 3) , Jon Lloyd (6) , Carlos A. Quesada (7) , Manuel Gloor (3) , Hans ter Steege (8, 9) , Patrick Meir (10, 1) , Esteban Alvarez , Alejandro Araujo-Murakami (11, 12) , Luiz E. O. C. Aragao (13, 2) , Luzmila Arroyo (12, 11) , Gerardo Aymard (14) , Olaf Banki (15) , Damien Bonal (16) , Sandra Brown (17) , Foster I. Brown (18, 19) , Carlos E. Ceron (20) , Victor Chama Moscoso (4) , Jerome Chave (21) , James A. Comiskey , Fernando Cornejo (22) , Massiel Corrales Medina (23) , Lola da Costa (24) , Flavia R. C. Costa (7) , Anthony Di Fiore (25) , Tomas F. Domingues (26) , Terry L. Erwin (27) , Todd Frederickson , Niro Higuchi (7) , Euridice N. Honorio Coronado (28, 3) , Tim J. Killeen (29) , William F. Laurance (30) , Carolina Levis (7) , William E. Magnusson (7) , Beatriz S. Marimon (31) , Ben Hur Marimon Junior (31) , Irina Mendoza Polo , Piyush Mishra (32) , Marcelo T. Nascimento (33) , David Neill (34) , Mario P. Nunez Vargas (35) , Walter A. Palacios , Alexander Parada (12, 11) , Guido Pardo Molina (36) , Marielos Pena-Claros (37, 38) , Nigel Pitman (39) , Carlos A. Peres (40) , Lourens Poorter (37) , Adriana Prieto (41) , Hirma Ramirez-Angulo (42) , Zorayda Restrepo Correa , Anand Roopsind (43) , Katherine H. Roucoux (3) , Agustin Rudas (41) , Emilio Salomao (28) , Juliana Schietti (7) , Marcos Silveira (18) , Priscila F. de Souza (3) , Marc K. Steininger , Juliana Stropp , John Terborgh , Raquel Thomas , Marisol Toledo (11, 38) , Armando Torres-Lezama (42) , Tinde R. van Andel (8) , Geertje M. F. van Der Heijden (44, 45) , Ima Vieira (28) , Simone Vieira (46) , Emilio Vilanova-Torre (42) , Vincent A. Vos , Ophelia Wang (47) , Charles E. Zartman (7) , Yadvinder Malhi (48) , Oliver L. Phillips (3)
1 School of Geosciences [Edinburgh]
2 University of Exeter
3 School of Geography [Leeds]
4 Missouri Botanical Garden
5 UCL - University College of London [London]
6 Imperial College London
7 INPA - Instituto Nacional de Pesquisas da Amazônia = National Institute of Amazonian Research
8 Naturalis Biodiversity Center [Leiden]
9 Universiteit Utrecht / Utrecht University [Utrecht]
10 Research School of Biology [Canberra, Australia]
11 UAGRM - Universidad Autonoma Gabriel René Moreno
12 Jardín Botánico de Medellín
13 INPE - Instituto Nacional de Pesquisas Espaciais
14 Programa Cienclas Agro & Mar, UNELLEZ Guanare
15 IBED - Institute for Biodiversity and Ecosystem Dynamics
16 EEF - Ecologie et Ecophysiologie Forestières [devient SILVA en 2018]
17 Ecosystem Services Unit, Winrock International
18 UFAC - Universidade Federal do Acre
19 WHOI - Woods Hole Oceanographic Institution
20 Herbario Nacional del Ecuador
21 EDB - Evolution et Diversité Biologique
22 UNALM - Universidad Nacional Agraria La Molina
23 UNSA - Universidad Nacional de San Agustín
24 UFPA - Federal University of Para - Universidade Federal do Pará - UFPA [Belém, Brazil]
25 University of Texas at Austin [Austin]
26 USP - Universidade de São Paulo = University of São Paulo
27 Smithsonian Institution
28 Museu Paraense Emílio Goeldi
29 WWF - World Wide Fund
30 JCU - James Cook University
31 UNEMAT - Universidade do Estado de Mato Grosso
32 Department of Electronics and Communication Engineering [Roorkee]
33 Norte Fluminense State University
34 Universidad Estatal Amazonica
35 UNSAAC - Universidad Nacional de San Antonio Abad del Cusco
36 Universidad Autonoma del Beni
37 WUR - Wageningen University and Research [Wageningen]
38 Inst Boliviano Invest Forestal, Santa Cruz 10260, Bolivia
39 Duke University [Durham]
40 UEA - University of East Anglia [Norwich]
41 UNAL - Universidad Nacional de Colombia [Bogotà]
42 UNIANDES - Universidad de los Andes [Bogota]
43 UF|Biology - Department of Biology [Gainesville]
44 University of Wisconsin - Milwaukee
45 Smithsonian Tropical Research Institute
46 UNICAMP - Universidade Estadual de Campinas = University of Campinas
47 Northern Arizona University [Flagstaff]
48 University of Oxford
Esteban Alvarez
  • Function : Author
Jerome Chave
James A. Comiskey
  • Function : Author
Todd Frederickson
  • Function : Author
Tim J. Killeen
  • Function : Author
Irina Mendoza Polo
  • Function : Author
Walter A. Palacios
  • Function : Author
Zorayda Restrepo Correa
  • Function : Author
Marcos Silveira
Marc K. Steininger
  • Function : Author
Juliana Stropp
  • Function : Author
John Terborgh
Raquel Thomas
  • Function : Author
Ima Vieira
Vincent A. Vos
  • Function : Author
Yadvinder Malhi
Oliver L. Phillips

Abstract

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.bases-doc.univ-lorraine.fr/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.

Dates and versions

hal-01555979 , version 1 (04-07-2017)

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Cite

Edward T. A. Mitchard, Ted R. Feldpausch, Roel J. W. Brienen, Gabriela Lopez-Gonzalez, Abel Monteagudo, et al.. Markedly divergent estimates of Amazon forest carbon density from ground plots and satellites. Global Ecology and Biogeography, 2014, 23 (8), pp.935 - 946. ⟨10.1111/geb.12168⟩. ⟨hal-01555979⟩
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