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@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 = "26 nov. 2020"
}


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