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Towards Regional, Error-Bounded Landscape Carbon Storage Estimates for Data-Deficient Areas of the World

Monitoring landscape carbon storage is critical for supporting and validating climate change mitigation policies. These may be aimed at reducing deforestation and degradation, or increasing terrestrial carbon storage at local, regional and global levels. However, due to data-deficiencies, default gl...

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Autores principales: Willcock, Simon, Phillips, Oliver L., Platts, Philip J., Balmford, Andrew, Burgess, Neil D., Lovett, Jon C., Ahrends, Antje, Bayliss, Julian, Doggart, Nike, Doody, Kathryn, Fanning, Eibleis, Green, Jonathan, Hall, Jaclyn, Howell, Kim L., Marchant, Rob, Marshall, Andrew R., Mbilinyi, Boniface, Munishi, Pantaleon K. T., Owen, Nisha, Swetnam, Ruth D., Topp-Jorgensen, Elmer J., Lewis, Simon L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3443093/
https://www.ncbi.nlm.nih.gov/pubmed/23024764
http://dx.doi.org/10.1371/journal.pone.0044795
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author Willcock, Simon
Phillips, Oliver L.
Platts, Philip J.
Balmford, Andrew
Burgess, Neil D.
Lovett, Jon C.
Ahrends, Antje
Bayliss, Julian
Doggart, Nike
Doody, Kathryn
Fanning, Eibleis
Green, Jonathan
Hall, Jaclyn
Howell, Kim L.
Marchant, Rob
Marshall, Andrew R.
Mbilinyi, Boniface
Munishi, Pantaleon K. T.
Owen, Nisha
Swetnam, Ruth D.
Topp-Jorgensen, Elmer J.
Lewis, Simon L.
author_facet Willcock, Simon
Phillips, Oliver L.
Platts, Philip J.
Balmford, Andrew
Burgess, Neil D.
Lovett, Jon C.
Ahrends, Antje
Bayliss, Julian
Doggart, Nike
Doody, Kathryn
Fanning, Eibleis
Green, Jonathan
Hall, Jaclyn
Howell, Kim L.
Marchant, Rob
Marshall, Andrew R.
Mbilinyi, Boniface
Munishi, Pantaleon K. T.
Owen, Nisha
Swetnam, Ruth D.
Topp-Jorgensen, Elmer J.
Lewis, Simon L.
author_sort Willcock, Simon
collection PubMed
description Monitoring landscape carbon storage is critical for supporting and validating climate change mitigation policies. These may be aimed at reducing deforestation and degradation, or increasing terrestrial carbon storage at local, regional and global levels. However, due to data-deficiencies, default global carbon storage values for given land cover types such as ‘lowland tropical forest’ are often used, termed ‘Tier 1 type’ analyses by the Intergovernmental Panel on Climate Change (IPCC). Such estimates may be erroneous when used at regional scales. Furthermore uncertainty assessments are rarely provided leading to estimates of land cover change carbon fluxes of unknown precision which may undermine efforts to properly evaluate land cover policies aimed at altering land cover dynamics. Here, we present a repeatable method to estimate carbon storage values and associated 95% confidence intervals (CI) for all five IPCC carbon pools (aboveground live carbon, litter, coarse woody debris, belowground live carbon and soil carbon) for data-deficient regions, using a combination of existing inventory data and systematic literature searches, weighted to ensure the final values are regionally specific. The method meets the IPCC ‘Tier 2’ reporting standard. We use this method to estimate carbon storage over an area of33.9 million hectares of eastern Tanzania, reporting values for 30 land cover types. We estimate that this area stored 6.33 (5.92–6.74) Pg C in the year 2000. Carbon storage estimates for the same study area extracted from five published Africa-wide or global studies show a mean carbon storage value of ∼50% of that reported using our regional values, with four of the five studies reporting lower carbon storage values. This suggests that carbon storage may have been underestimated for this region of Africa. Our study demonstrates the importance of obtaining regionally appropriate carbon storage estimates, and shows how such values can be produced for a relatively low investment.
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spelling pubmed-34430932012-09-28 Towards Regional, Error-Bounded Landscape Carbon Storage Estimates for Data-Deficient Areas of the World Willcock, Simon Phillips, Oliver L. Platts, Philip J. Balmford, Andrew Burgess, Neil D. Lovett, Jon C. Ahrends, Antje Bayliss, Julian Doggart, Nike Doody, Kathryn Fanning, Eibleis Green, Jonathan Hall, Jaclyn Howell, Kim L. Marchant, Rob Marshall, Andrew R. Mbilinyi, Boniface Munishi, Pantaleon K. T. Owen, Nisha Swetnam, Ruth D. Topp-Jorgensen, Elmer J. Lewis, Simon L. PLoS One Research Article Monitoring landscape carbon storage is critical for supporting and validating climate change mitigation policies. These may be aimed at reducing deforestation and degradation, or increasing terrestrial carbon storage at local, regional and global levels. However, due to data-deficiencies, default global carbon storage values for given land cover types such as ‘lowland tropical forest’ are often used, termed ‘Tier 1 type’ analyses by the Intergovernmental Panel on Climate Change (IPCC). Such estimates may be erroneous when used at regional scales. Furthermore uncertainty assessments are rarely provided leading to estimates of land cover change carbon fluxes of unknown precision which may undermine efforts to properly evaluate land cover policies aimed at altering land cover dynamics. Here, we present a repeatable method to estimate carbon storage values and associated 95% confidence intervals (CI) for all five IPCC carbon pools (aboveground live carbon, litter, coarse woody debris, belowground live carbon and soil carbon) for data-deficient regions, using a combination of existing inventory data and systematic literature searches, weighted to ensure the final values are regionally specific. The method meets the IPCC ‘Tier 2’ reporting standard. We use this method to estimate carbon storage over an area of33.9 million hectares of eastern Tanzania, reporting values for 30 land cover types. We estimate that this area stored 6.33 (5.92–6.74) Pg C in the year 2000. Carbon storage estimates for the same study area extracted from five published Africa-wide or global studies show a mean carbon storage value of ∼50% of that reported using our regional values, with four of the five studies reporting lower carbon storage values. This suggests that carbon storage may have been underestimated for this region of Africa. Our study demonstrates the importance of obtaining regionally appropriate carbon storage estimates, and shows how such values can be produced for a relatively low investment. Public Library of Science 2012-09-14 /pmc/articles/PMC3443093/ /pubmed/23024764 http://dx.doi.org/10.1371/journal.pone.0044795 Text en © 2012 Willcock et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Willcock, Simon
Phillips, Oliver L.
Platts, Philip J.
Balmford, Andrew
Burgess, Neil D.
Lovett, Jon C.
Ahrends, Antje
Bayliss, Julian
Doggart, Nike
Doody, Kathryn
Fanning, Eibleis
Green, Jonathan
Hall, Jaclyn
Howell, Kim L.
Marchant, Rob
Marshall, Andrew R.
Mbilinyi, Boniface
Munishi, Pantaleon K. T.
Owen, Nisha
Swetnam, Ruth D.
Topp-Jorgensen, Elmer J.
Lewis, Simon L.
Towards Regional, Error-Bounded Landscape Carbon Storage Estimates for Data-Deficient Areas of the World
title Towards Regional, Error-Bounded Landscape Carbon Storage Estimates for Data-Deficient Areas of the World
title_full Towards Regional, Error-Bounded Landscape Carbon Storage Estimates for Data-Deficient Areas of the World
title_fullStr Towards Regional, Error-Bounded Landscape Carbon Storage Estimates for Data-Deficient Areas of the World
title_full_unstemmed Towards Regional, Error-Bounded Landscape Carbon Storage Estimates for Data-Deficient Areas of the World
title_short Towards Regional, Error-Bounded Landscape Carbon Storage Estimates for Data-Deficient Areas of the World
title_sort towards regional, error-bounded landscape carbon storage estimates for data-deficient areas of the world
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3443093/
https://www.ncbi.nlm.nih.gov/pubmed/23024764
http://dx.doi.org/10.1371/journal.pone.0044795
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