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The relevance of using in situ carbon and nitrogen data and satellite images to assess aboveground carbon and nitrogen stocks for supporting national REDD + programmes in Africa

BACKGROUND: To reduce the uncertainty in estimates of carbon emissions resulting from deforestation and forest degradation, better information on the carbon density per land use/land cover (LULC) class and in situ carbon and nitrogen data is needed. This allows a better representation of the spatial...

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Autores principales: Chabi, Adéyèmi, Lautenbach, Sven, Tondoh, Jérôme Ebagnerin, Orekan, Vincent Oladokoun Agnila, Adu-Bredu, Stephen, Kyei-Baffour, Nicholas, Mama, Vincent Joseph, Fonweban, John
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7227328/
https://www.ncbi.nlm.nih.gov/pubmed/31506725
http://dx.doi.org/10.1186/s13021-019-0127-7
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author Chabi, Adéyèmi
Lautenbach, Sven
Tondoh, Jérôme Ebagnerin
Orekan, Vincent Oladokoun Agnila
Adu-Bredu, Stephen
Kyei-Baffour, Nicholas
Mama, Vincent Joseph
Fonweban, John
author_facet Chabi, Adéyèmi
Lautenbach, Sven
Tondoh, Jérôme Ebagnerin
Orekan, Vincent Oladokoun Agnila
Adu-Bredu, Stephen
Kyei-Baffour, Nicholas
Mama, Vincent Joseph
Fonweban, John
author_sort Chabi, Adéyèmi
collection PubMed
description BACKGROUND: To reduce the uncertainty in estimates of carbon emissions resulting from deforestation and forest degradation, better information on the carbon density per land use/land cover (LULC) class and in situ carbon and nitrogen data is needed. This allows a better representation of the spatial distribution of carbon and nitrogen stocks across LULC. The aim of this study was to emphasize the relevance of using in situ carbon and nitrogen content of the main tree species of the site when quantifying the aboveground carbon and nitrogen stocks in the context of carbon accounting. This paper contributes to that, by combining satellite images with in situ carbon and nitrogen content in dry matter of stem woods together with locally derived and published allometric models to estimate aboveground carbon and nitrogen stocks at the Dassari Basin in the Sudan Savannah zone in the Republic of Benin. RESULTS: The estimated mean carbon content per tree species varied from 44.28 ± 0.21% to 49.43 ± 0.27%. The overall mean carbon content in dry matter for the 277 wood samples of the 18 main tree species of the region was 47.01 ± 0.28%—which is close to the Tier 1 coefficient of 47% default value suggested by the Intergovernmental Panel on Climate Change (IPCC). The overall mean fraction of nitrogen in dry matter was estimated as 0.229 ± 0.016%. The estimated mean carbon density varied from 1.52 ± 0.14 Mg C ha(−1) (for Cropland and Fallow) to 97.83 ± 27.55 Mg C ha(−1) (for Eucalyptus grandis Plantation). In the same order the estimated mean nitrogen density varied from 0.008 ± 0.007 Mg ha(−1) of N (for Cropland and Fallow) to 0.321 ± 0.088 Mg ha(−1) of N (for Eucalyptus grandis Plantation). CONCLUSION: The results show the relevance of using the in situ carbon and nitrogen content of the main tree species for estimating aboveground carbon and nitrogen stocks in the Sudan Savannah environment. The results provide crucial information for carbon accounting programmes related to the implementation of the REDD + initiatives in developing countries.
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spelling pubmed-72273282020-05-27 The relevance of using in situ carbon and nitrogen data and satellite images to assess aboveground carbon and nitrogen stocks for supporting national REDD + programmes in Africa Chabi, Adéyèmi Lautenbach, Sven Tondoh, Jérôme Ebagnerin Orekan, Vincent Oladokoun Agnila Adu-Bredu, Stephen Kyei-Baffour, Nicholas Mama, Vincent Joseph Fonweban, John Carbon Balance Manag Research BACKGROUND: To reduce the uncertainty in estimates of carbon emissions resulting from deforestation and forest degradation, better information on the carbon density per land use/land cover (LULC) class and in situ carbon and nitrogen data is needed. This allows a better representation of the spatial distribution of carbon and nitrogen stocks across LULC. The aim of this study was to emphasize the relevance of using in situ carbon and nitrogen content of the main tree species of the site when quantifying the aboveground carbon and nitrogen stocks in the context of carbon accounting. This paper contributes to that, by combining satellite images with in situ carbon and nitrogen content in dry matter of stem woods together with locally derived and published allometric models to estimate aboveground carbon and nitrogen stocks at the Dassari Basin in the Sudan Savannah zone in the Republic of Benin. RESULTS: The estimated mean carbon content per tree species varied from 44.28 ± 0.21% to 49.43 ± 0.27%. The overall mean carbon content in dry matter for the 277 wood samples of the 18 main tree species of the region was 47.01 ± 0.28%—which is close to the Tier 1 coefficient of 47% default value suggested by the Intergovernmental Panel on Climate Change (IPCC). The overall mean fraction of nitrogen in dry matter was estimated as 0.229 ± 0.016%. The estimated mean carbon density varied from 1.52 ± 0.14 Mg C ha(−1) (for Cropland and Fallow) to 97.83 ± 27.55 Mg C ha(−1) (for Eucalyptus grandis Plantation). In the same order the estimated mean nitrogen density varied from 0.008 ± 0.007 Mg ha(−1) of N (for Cropland and Fallow) to 0.321 ± 0.088 Mg ha(−1) of N (for Eucalyptus grandis Plantation). CONCLUSION: The results show the relevance of using the in situ carbon and nitrogen content of the main tree species for estimating aboveground carbon and nitrogen stocks in the Sudan Savannah environment. The results provide crucial information for carbon accounting programmes related to the implementation of the REDD + initiatives in developing countries. Springer International Publishing 2019-09-10 /pmc/articles/PMC7227328/ /pubmed/31506725 http://dx.doi.org/10.1186/s13021-019-0127-7 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
Chabi, Adéyèmi
Lautenbach, Sven
Tondoh, Jérôme Ebagnerin
Orekan, Vincent Oladokoun Agnila
Adu-Bredu, Stephen
Kyei-Baffour, Nicholas
Mama, Vincent Joseph
Fonweban, John
The relevance of using in situ carbon and nitrogen data and satellite images to assess aboveground carbon and nitrogen stocks for supporting national REDD + programmes in Africa
title The relevance of using in situ carbon and nitrogen data and satellite images to assess aboveground carbon and nitrogen stocks for supporting national REDD + programmes in Africa
title_full The relevance of using in situ carbon and nitrogen data and satellite images to assess aboveground carbon and nitrogen stocks for supporting national REDD + programmes in Africa
title_fullStr The relevance of using in situ carbon and nitrogen data and satellite images to assess aboveground carbon and nitrogen stocks for supporting national REDD + programmes in Africa
title_full_unstemmed The relevance of using in situ carbon and nitrogen data and satellite images to assess aboveground carbon and nitrogen stocks for supporting national REDD + programmes in Africa
title_short The relevance of using in situ carbon and nitrogen data and satellite images to assess aboveground carbon and nitrogen stocks for supporting national REDD + programmes in Africa
title_sort relevance of using in situ carbon and nitrogen data and satellite images to assess aboveground carbon and nitrogen stocks for supporting national redd + programmes in africa
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7227328/
https://www.ncbi.nlm.nih.gov/pubmed/31506725
http://dx.doi.org/10.1186/s13021-019-0127-7
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