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Quantifying the impacts of land cover change on gross primary productivity globally
Historically, humans have cleared many forests for agriculture. While this substantially reduced ecosystem carbon storage, the impacts of these land cover changes on terrestrial gross primary productivity (GPP) have not been adequately resolved yet. Here, we combine high-resolution datasets of satel...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9626452/ https://www.ncbi.nlm.nih.gov/pubmed/36319733 http://dx.doi.org/10.1038/s41598-022-23120-0 |
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author | Krause, Andreas Papastefanou, Phillip Gregor, Konstantin Layritz, Lucia S. Zang, Christian S. Buras, Allan Li, Xing Xiao, Jingfeng Rammig, Anja |
author_facet | Krause, Andreas Papastefanou, Phillip Gregor, Konstantin Layritz, Lucia S. Zang, Christian S. Buras, Allan Li, Xing Xiao, Jingfeng Rammig, Anja |
author_sort | Krause, Andreas |
collection | PubMed |
description | Historically, humans have cleared many forests for agriculture. While this substantially reduced ecosystem carbon storage, the impacts of these land cover changes on terrestrial gross primary productivity (GPP) have not been adequately resolved yet. Here, we combine high-resolution datasets of satellite-derived GPP and environmental predictor variables to estimate the potential GPP of forests, grasslands, and croplands around the globe. With a mean GPP of 2.0 kg C m(−2) yr(−1) forests represent the most productive land cover on two thirds of the total area suitable for any of these land cover types, while grasslands and croplands on average reach 1.5 and 1.8 kg C m(−2) yr(−1), respectively. Combining our potential GPP maps with a historical land-use reconstruction indicates a 4.4% reduction in global GPP from agricultural expansion. This land-use-induced GPP reduction is amplified in some future scenarios as a result of ongoing deforestation (e.g., the large-scale bioenergy scenario SSP4-3.4) but partly reversed in other scenarios (e.g., the sustainability scenario SSP1-1.9) due to agricultural abandonment. Comparing our results to simulations from state-of-the-art Earth System Models, we find that all investigated models deviate substantially from our estimates and from each other. Our maps could be used as a benchmark to reduce this inconsistency, thereby improving projections of land-based climate mitigation potentials. |
format | Online Article Text |
id | pubmed-9626452 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-96264522022-11-03 Quantifying the impacts of land cover change on gross primary productivity globally Krause, Andreas Papastefanou, Phillip Gregor, Konstantin Layritz, Lucia S. Zang, Christian S. Buras, Allan Li, Xing Xiao, Jingfeng Rammig, Anja Sci Rep Article Historically, humans have cleared many forests for agriculture. While this substantially reduced ecosystem carbon storage, the impacts of these land cover changes on terrestrial gross primary productivity (GPP) have not been adequately resolved yet. Here, we combine high-resolution datasets of satellite-derived GPP and environmental predictor variables to estimate the potential GPP of forests, grasslands, and croplands around the globe. With a mean GPP of 2.0 kg C m(−2) yr(−1) forests represent the most productive land cover on two thirds of the total area suitable for any of these land cover types, while grasslands and croplands on average reach 1.5 and 1.8 kg C m(−2) yr(−1), respectively. Combining our potential GPP maps with a historical land-use reconstruction indicates a 4.4% reduction in global GPP from agricultural expansion. This land-use-induced GPP reduction is amplified in some future scenarios as a result of ongoing deforestation (e.g., the large-scale bioenergy scenario SSP4-3.4) but partly reversed in other scenarios (e.g., the sustainability scenario SSP1-1.9) due to agricultural abandonment. Comparing our results to simulations from state-of-the-art Earth System Models, we find that all investigated models deviate substantially from our estimates and from each other. Our maps could be used as a benchmark to reduce this inconsistency, thereby improving projections of land-based climate mitigation potentials. Nature Publishing Group UK 2022-11-01 /pmc/articles/PMC9626452/ /pubmed/36319733 http://dx.doi.org/10.1038/s41598-022-23120-0 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Krause, Andreas Papastefanou, Phillip Gregor, Konstantin Layritz, Lucia S. Zang, Christian S. Buras, Allan Li, Xing Xiao, Jingfeng Rammig, Anja Quantifying the impacts of land cover change on gross primary productivity globally |
title | Quantifying the impacts of land cover change on gross primary productivity globally |
title_full | Quantifying the impacts of land cover change on gross primary productivity globally |
title_fullStr | Quantifying the impacts of land cover change on gross primary productivity globally |
title_full_unstemmed | Quantifying the impacts of land cover change on gross primary productivity globally |
title_short | Quantifying the impacts of land cover change on gross primary productivity globally |
title_sort | quantifying the impacts of land cover change on gross primary productivity globally |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9626452/ https://www.ncbi.nlm.nih.gov/pubmed/36319733 http://dx.doi.org/10.1038/s41598-022-23120-0 |
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