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Uncertainty in the spatial distribution of tropical forest biomass: a comparison of pan-tropical maps

BACKGROUND: Mapping the aboveground biomass of tropical forests is essential both for implementing conservation policy and reducing uncertainties in the global carbon cycle. Two medium resolution (500 m – 1000 m) pantropical maps of vegetation biomass have been recently published, and have been wide...

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Autores principales: Mitchard, Edward TA, Saatchi, Sassan S, Baccini, Alessandro, Asner, Gregory P, Goetz, Scott J, Harris, Nancy L, Brown, Sandra
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4175488/
https://www.ncbi.nlm.nih.gov/pubmed/24161143
http://dx.doi.org/10.1186/1750-0680-8-10
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author Mitchard, Edward TA
Saatchi, Sassan S
Baccini, Alessandro
Asner, Gregory P
Goetz, Scott J
Harris, Nancy L
Brown, Sandra
author_facet Mitchard, Edward TA
Saatchi, Sassan S
Baccini, Alessandro
Asner, Gregory P
Goetz, Scott J
Harris, Nancy L
Brown, Sandra
author_sort Mitchard, Edward TA
collection PubMed
description BACKGROUND: Mapping the aboveground biomass of tropical forests is essential both for implementing conservation policy and reducing uncertainties in the global carbon cycle. Two medium resolution (500 m – 1000 m) pantropical maps of vegetation biomass have been recently published, and have been widely used by sub-national and national-level activities in relation to Reducing Emissions from Deforestation and forest Degradation (REDD+). Both maps use similar input data layers, and are driven by the same spaceborne LiDAR dataset providing systematic forest height and canopy structure estimates, but use different ground datasets for calibration and different spatial modelling methodologies. Here, we compare these two maps to each other, to the FAO’s Forest Resource Assessment (FRA) 2010 country-level data, and to a high resolution (100 m) biomass map generated for a portion of the Colombian Amazon. RESULTS: We find substantial differences between the two maps, in particular in central Amazonia, the Congo basin, the south of Papua New Guinea, the Miombo woodlands of Africa, and the dry forests and savannas of South America. There is little consistency in the direction of the difference. However, when the maps are aggregated to the country or biome scale there is greater agreement, with differences cancelling out to a certain extent. When comparing country level biomass stocks, the two maps agree with each other to a much greater extent than to the FRA 2010 estimates. In the Colombian Amazon, both pantropical maps estimate higher biomass than the independent high resolution map, but show a similar spatial distribution of this biomass. CONCLUSIONS: Biomass mapping has progressed enormously over the past decade, to the stage where we can produce globally consistent maps of aboveground biomass. We show that there are still large uncertainties in these maps, in particular in areas with little field data. However, when used at a regional scale, different maps appear to converge, suggesting we can provide reasonable stock estimates when aggregated over large regions. Therefore we believe the largest uncertainties for REDD+ activities relate to the spatial distribution of biomass and to the spatial pattern of forest cover change, rather than to total globally or nationally summed carbon density.
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spelling pubmed-41754882014-09-27 Uncertainty in the spatial distribution of tropical forest biomass: a comparison of pan-tropical maps Mitchard, Edward TA Saatchi, Sassan S Baccini, Alessandro Asner, Gregory P Goetz, Scott J Harris, Nancy L Brown, Sandra Carbon Balance Manag Research BACKGROUND: Mapping the aboveground biomass of tropical forests is essential both for implementing conservation policy and reducing uncertainties in the global carbon cycle. Two medium resolution (500 m – 1000 m) pantropical maps of vegetation biomass have been recently published, and have been widely used by sub-national and national-level activities in relation to Reducing Emissions from Deforestation and forest Degradation (REDD+). Both maps use similar input data layers, and are driven by the same spaceborne LiDAR dataset providing systematic forest height and canopy structure estimates, but use different ground datasets for calibration and different spatial modelling methodologies. Here, we compare these two maps to each other, to the FAO’s Forest Resource Assessment (FRA) 2010 country-level data, and to a high resolution (100 m) biomass map generated for a portion of the Colombian Amazon. RESULTS: We find substantial differences between the two maps, in particular in central Amazonia, the Congo basin, the south of Papua New Guinea, the Miombo woodlands of Africa, and the dry forests and savannas of South America. There is little consistency in the direction of the difference. However, when the maps are aggregated to the country or biome scale there is greater agreement, with differences cancelling out to a certain extent. When comparing country level biomass stocks, the two maps agree with each other to a much greater extent than to the FRA 2010 estimates. In the Colombian Amazon, both pantropical maps estimate higher biomass than the independent high resolution map, but show a similar spatial distribution of this biomass. CONCLUSIONS: Biomass mapping has progressed enormously over the past decade, to the stage where we can produce globally consistent maps of aboveground biomass. We show that there are still large uncertainties in these maps, in particular in areas with little field data. However, when used at a regional scale, different maps appear to converge, suggesting we can provide reasonable stock estimates when aggregated over large regions. Therefore we believe the largest uncertainties for REDD+ activities relate to the spatial distribution of biomass and to the spatial pattern of forest cover change, rather than to total globally or nationally summed carbon density. BioMed Central 2013-10-26 /pmc/articles/PMC4175488/ /pubmed/24161143 http://dx.doi.org/10.1186/1750-0680-8-10 Text en Copyright © 2013 Mitchard et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Mitchard, Edward TA
Saatchi, Sassan S
Baccini, Alessandro
Asner, Gregory P
Goetz, Scott J
Harris, Nancy L
Brown, Sandra
Uncertainty in the spatial distribution of tropical forest biomass: a comparison of pan-tropical maps
title Uncertainty in the spatial distribution of tropical forest biomass: a comparison of pan-tropical maps
title_full Uncertainty in the spatial distribution of tropical forest biomass: a comparison of pan-tropical maps
title_fullStr Uncertainty in the spatial distribution of tropical forest biomass: a comparison of pan-tropical maps
title_full_unstemmed Uncertainty in the spatial distribution of tropical forest biomass: a comparison of pan-tropical maps
title_short Uncertainty in the spatial distribution of tropical forest biomass: a comparison of pan-tropical maps
title_sort uncertainty in the spatial distribution of tropical forest biomass: a comparison of pan-tropical maps
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4175488/
https://www.ncbi.nlm.nih.gov/pubmed/24161143
http://dx.doi.org/10.1186/1750-0680-8-10
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