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

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dc.contributor.author Mitchard, Edward T. A. en
dc.contributor.author Feldpausch, Ted R. en
dc.contributor.author Brienen, Roel J. W. en
dc.contributor.author Lopez-Gonzalez, Gabriela en
dc.contributor.author Monteagudo, Abel en
dc.contributor.author Baker, Timothy R. en
dc.contributor.author Lewis, Simon L. en
dc.contributor.author Lloyd, Jon en
dc.contributor.author Quesada, Carlos A. en
dc.contributor.author Gloor, Manuel en
dc.contributor.author ter Steege, Hans en
dc.contributor.author Meir, Patrick en
dc.contributor.author Alvarez, Esteban en
dc.contributor.author Araujo-Murakami, Alejandro en
dc.contributor.author Aragão, Luiz E. O. C. en
dc.contributor.author Arroyo, Luzmila en
dc.contributor.author Aymard, Gerardo en
dc.contributor.author Banki, Olaf en
dc.contributor.author Bonal, Damien en
dc.contributor.author Brown, Sandra en
dc.contributor.author Brown, Foster I. en
dc.contributor.author Cerón, Carlos E. en
dc.contributor.author Chama Moscoso, Victor en
dc.contributor.author Chave, Jerome en
dc.contributor.author Comiskey, James A. en
dc.contributor.author Cornejo, Fernando en
dc.contributor.author Corrales Medina, Massiel en
dc.contributor.author Da Costa, Lola en
dc.contributor.author Costa, Flavia R. C. en
dc.contributor.author Di Fiore, Anthony en
dc.contributor.author Domingues, Tomas F. en
dc.contributor.author Erwin, Terry L. en
dc.contributor.author Frederickson, Todd en
dc.contributor.author Higuchi, Niro en
dc.contributor.author Honorio Coronado, Euridice N. en
dc.contributor.author Killeen, Tim J. en
dc.contributor.author Laurance, William F. en
dc.contributor.author Levis, Carolina en
dc.contributor.author Magnusson, William E. en
dc.contributor.author Marimon, Beatriz S. en
dc.contributor.author Marimon Junior, Ben Hur en
dc.contributor.author Mendoza Polo, Irina en
dc.contributor.author Mishra, Piyush en
dc.contributor.author Nascimento, Marcelo T. en
dc.contributor.author Neill, David en
dc.contributor.author Núñez Vargas, Mario P. en
dc.contributor.author Palacios, Walter A. en
dc.contributor.author Parada, Alexander en
dc.contributor.author Pardo Molina, Guido en
dc.contributor.author Peña-Claros, Marielos en
dc.contributor.author Pitman, Nigel en
dc.contributor.author Peres, Carlos A. en
dc.contributor.author Poorter, Lourens en
dc.contributor.author Prieto, Adriana en
dc.contributor.author Ramirez-Angulo, Hirma en
dc.contributor.author Restrepo Correa, Zorayda en
dc.contributor.author Roopsind, Anand en
dc.contributor.author Roucoux, Katherine H. en
dc.contributor.author Rudas, Agustin en
dc.contributor.author Salomão, Rafael P. en
dc.contributor.author Schietti, Juliana en
dc.contributor.author Silveira, Marcos en
dc.contributor.author de Souza, Priscila F. en
dc.contributor.author Steininger, Marc K. en
dc.contributor.author Stropp, Juliana en
dc.contributor.author Terborgh, John en
dc.contributor.author Thomas, Raquel en
dc.contributor.author Toledo, Marisol en
dc.contributor.author Torres-Lezama, Armando en
dc.contributor.author van Andel, Tinde R. en
dc.contributor.author van der Heijden, Geertje M.F. en
dc.contributor.author Vieira, Ima C. G. en
dc.contributor.author Vieira, Simone en
dc.contributor.author Vilanova-Torre, Emilio en
dc.contributor.author Vos, Vincent A. en
dc.contributor.author Wang, Ophelia en
dc.contributor.author Zartman, Charles E. en
dc.contributor.author Malhi, Yadvinder en
dc.contributor.author Phillips, Oliver L. en
dc.date.accessioned 2015-01-21T19:21:59Z
dc.date.available 2015-01-21T19:21:59Z
dc.date.issued 2014
dc.identifier.citation 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. et al. 2014. "<a href="https://repository.si.edu/handle/10088/22712">Markedly divergent estimates of Amazon forest carbon density from ground plots and satellites</a>." <em>Global Ecology and Biogeography</em>. 23 (8):935&ndash;946. <a href="https://doi.org/10.1111/geb.12168">https://doi.org/10.1111/geb.12168</a> en
dc.identifier.issn 1466-822X
dc.identifier.uri http://hdl.handle.net/10088/22712
dc.description.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 &gt;?25%, whereas regional uncertainties for the maps were reported to be &lt;?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. en
dc.relation.ispartof Global Ecology and Biogeography en
dc.title Markedly divergent estimates of Amazon forest carbon density from ground plots and satellites en
dc.type Journal Article en
dc.identifier.srbnumber 120886
dc.identifier.doi 10.1111/geb.12168
rft.jtitle Global Ecology and Biogeography
rft.volume 23
rft.issue 8
rft.spage 935
rft.epage 946
dc.description.SIUnit NH-Entomology en
dc.description.SIUnit NMNH en
dc.description.SIUnit STRI en
dc.description.SIUnit Peer-reviewed en
dc.citation.spage 935
dc.citation.epage 946


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