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Evaluating spatial coverage of data on the aboveground biomass in undisturbed forests in the Brazilian Amazon

BACKGROUND: Brazilian Amazon forests contain a large stock of carbon that could be released into the atmosphere as a result of land use and cover change. To quantify the carbon stocks, Brazil has forest inventory plots from different sources, but they are unstandardized and not always available to t...

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Autores principales: Tejada, Graciela, Görgens, Eric Bastos, Espírito-Santo, Fernando Del Bon, Cantinho, Roberta Zecchini, Ometto, Jean Pierre
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7226941/
https://www.ncbi.nlm.nih.gov/pubmed/31482475
http://dx.doi.org/10.1186/s13021-019-0126-8
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author Tejada, Graciela
Görgens, Eric Bastos
Espírito-Santo, Fernando Del Bon
Cantinho, Roberta Zecchini
Ometto, Jean Pierre
author_facet Tejada, Graciela
Görgens, Eric Bastos
Espírito-Santo, Fernando Del Bon
Cantinho, Roberta Zecchini
Ometto, Jean Pierre
author_sort Tejada, Graciela
collection PubMed
description BACKGROUND: Brazilian Amazon forests contain a large stock of carbon that could be released into the atmosphere as a result of land use and cover change. To quantify the carbon stocks, Brazil has forest inventory plots from different sources, but they are unstandardized and not always available to the scientific community. Considering the Brazilian Amazon extension, the use of remote sensing, combined with forest inventory plots, is one of the best options to estimate forest aboveground biomass (AGB). Nevertheless, the combination of limited forest inventory data and different remote sensing products has resulted in significant differences in the spatial distribution of AGB estimates. This study evaluates the spatial coverage of AGB data (forest inventory plots, AGB maps and remote sensing products) in undisturbed forests in the Brazilian Amazon. Additionally, we analyze the interconnection between these data and AGB stakeholders producing the information. Specifically, we provide the first benchmark of the existing field plots in terms of their size, frequency, and spatial distribution. RESULTS: We synthesized the coverage of forest inventory plots, AGB maps and airborne light detection and ranging (LiDAR) transects of the Brazilian Amazon. Although several extensive forest inventories have been implemented, these AGB data cover a small fraction of this region (e.g., central Amazon remains largely uncovered). Although the use of new technology such as airborne LiDAR cover a significant extension of AGB surveys, these data and forest plots represent only 1% of the entire forest area of the Brazilian Amazon. CONCLUSIONS: Considering that several institutions involved in forest inventories of the Brazilian Amazon have different goals, protocols, and time frames for forest surveys, forest inventory data of the Brazilian Amazon remain unstandardized. Research funding agencies have a very important role in establishing a clear sharing policy to make data free and open as well as in harmonizing the collection procedure. Nevertheless, the use of old and new forest inventory plots combined with airborne LiDAR data and satellite images will likely reduce the uncertainty of the AGB distribution of the Brazilian Amazon.
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spelling pubmed-72269412020-05-27 Evaluating spatial coverage of data on the aboveground biomass in undisturbed forests in the Brazilian Amazon Tejada, Graciela Görgens, Eric Bastos Espírito-Santo, Fernando Del Bon Cantinho, Roberta Zecchini Ometto, Jean Pierre Carbon Balance Manag Research BACKGROUND: Brazilian Amazon forests contain a large stock of carbon that could be released into the atmosphere as a result of land use and cover change. To quantify the carbon stocks, Brazil has forest inventory plots from different sources, but they are unstandardized and not always available to the scientific community. Considering the Brazilian Amazon extension, the use of remote sensing, combined with forest inventory plots, is one of the best options to estimate forest aboveground biomass (AGB). Nevertheless, the combination of limited forest inventory data and different remote sensing products has resulted in significant differences in the spatial distribution of AGB estimates. This study evaluates the spatial coverage of AGB data (forest inventory plots, AGB maps and remote sensing products) in undisturbed forests in the Brazilian Amazon. Additionally, we analyze the interconnection between these data and AGB stakeholders producing the information. Specifically, we provide the first benchmark of the existing field plots in terms of their size, frequency, and spatial distribution. RESULTS: We synthesized the coverage of forest inventory plots, AGB maps and airborne light detection and ranging (LiDAR) transects of the Brazilian Amazon. Although several extensive forest inventories have been implemented, these AGB data cover a small fraction of this region (e.g., central Amazon remains largely uncovered). Although the use of new technology such as airborne LiDAR cover a significant extension of AGB surveys, these data and forest plots represent only 1% of the entire forest area of the Brazilian Amazon. CONCLUSIONS: Considering that several institutions involved in forest inventories of the Brazilian Amazon have different goals, protocols, and time frames for forest surveys, forest inventory data of the Brazilian Amazon remain unstandardized. Research funding agencies have a very important role in establishing a clear sharing policy to make data free and open as well as in harmonizing the collection procedure. Nevertheless, the use of old and new forest inventory plots combined with airborne LiDAR data and satellite images will likely reduce the uncertainty of the AGB distribution of the Brazilian Amazon. Springer International Publishing 2019-09-03 /pmc/articles/PMC7226941/ /pubmed/31482475 http://dx.doi.org/10.1186/s13021-019-0126-8 Text en © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Tejada, Graciela
Görgens, Eric Bastos
Espírito-Santo, Fernando Del Bon
Cantinho, Roberta Zecchini
Ometto, Jean Pierre
Evaluating spatial coverage of data on the aboveground biomass in undisturbed forests in the Brazilian Amazon
title Evaluating spatial coverage of data on the aboveground biomass in undisturbed forests in the Brazilian Amazon
title_full Evaluating spatial coverage of data on the aboveground biomass in undisturbed forests in the Brazilian Amazon
title_fullStr Evaluating spatial coverage of data on the aboveground biomass in undisturbed forests in the Brazilian Amazon
title_full_unstemmed Evaluating spatial coverage of data on the aboveground biomass in undisturbed forests in the Brazilian Amazon
title_short Evaluating spatial coverage of data on the aboveground biomass in undisturbed forests in the Brazilian Amazon
title_sort evaluating spatial coverage of data on the aboveground biomass in undisturbed forests in the brazilian amazon
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7226941/
https://www.ncbi.nlm.nih.gov/pubmed/31482475
http://dx.doi.org/10.1186/s13021-019-0126-8
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