@Article{MitchardFBLMBLLQGSMAAAAABBBBCMCCCMCCFDEFHCKLLMMMPMNNVPPMPPPPPRCRRRSSSSSSTTTTAHVVVVWZMP:2014:MaDiEs,
author = "Mitchard, Edward T. A. and Feldpausch, Ted R. and Brienen, Roel J.
W. and Lopez-Gonzalez, Gabriela and Monteagudo, Abel and Baker,
Timothy R. and Lewis, Simon L. and Lloyd, Jon and Quesada, Carlos
A. and Gloor, Manuel and ter Steege, Hans and Meir, Patrick and
Alvarez, Esteban and Araujo-Murakami, Alejandro and Arag{\~a}o,
Luiz Eduardo Oliveira e Cruz de and Arroyo, Luzmila and Aymard,
Gerardo and Banki, Olaf and Bonal, Damien and Brown, Sandra and
Brown, Foster I. and Cer{\'o}n, Carlos E. and Moscoso, Victor
Chama and Chave, Jerome and Comiskey, James A. and Cornejo,
Fernando and Medina, Massiel Corrales and Costa, Lola Da and
Costa, Flavia R. C. and Fiore, Anthony Di and Domingues, Tomas F.
and Erwin, Terry L. and Frederickson, Todd and Higuchi, Niro and
Coronado, Euridice N. Honorio and Killeen, Tim J. and Laurance,
William F. and Levis, Carolina and Magnusson, William E. and
Marimon, Beatriz S. and Marimon Junior, Ben Hur and Polo, Irina
Mendoza and Mishra, Piyush and Nascimento, Marcelo T. and Neill,
David and Vargas, Mario P. N{\'u}ñez and Palacios, Walter A. and
Parada, Alexander and Molina, Guido Pardo and Peña-Claros,
Marielos and Pitman, Nigel and Peres, Carlos A. and Poorter,
Lourens and Prieto, Adriana and Ramirez-Angulo, Hirma and Correa,
Zorayda Restrepo and Roopsind, Anand and Roucoux, Katherine H. and
Rudas, Agustin and Salom{\~a}o, Rafael P. and Schietti, Juliana
and Silveira, Marcos and Souza, Priscila F. de and Steininger,
Marc K. and Stropp, Juliana and Terborgh, John and Thomas, Raquel
and Toledo, Marisol and Torres-Lezama, Armando and van Andel,
Tinde R. and van der Heijden, Geertje M. F. and Vieira, Ima C. G.
and Vieira, Simone and Vilanova-Torre, Emilio and Vos, Vincent A.
and Wang, Ophelia and Zartman, Charles E. and Malhi, Yadvinder and
Phillips, Oliver L.",
affiliation = "{} and {} and {} and {} and {} and {} and {} and {} and {} and {}
and {} and {} and {} and {} and {Instituto Nacional de Pesquisas
Espaciais (INPE)}",
title = "Markedly divergent estimates of Amazon forest carbon density from
ground plots and satellites",
journal = "Global Ecology and Biogeography",
year = "2014",
volume = "23",
pages = "935–946",
keywords = "above-ground biomass, allometry, carbon cycle, REDD+, remote
sensing, satellite mapping, wood density.",
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/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.",
doi = "10.1111/geb.12168",
url = "http://dx.doi.org/10.1111/geb.12168",
issn = "1466-822X",
label = "self-archiving-INPE-MCTI-GOV-BR",
language = "en",
targetfile = "geb12168.pdf",
urlaccessdate = "04 maio 2024"
}