Quantifying the impacts of land cover change on gross primary productivity globally
Abstract 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...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2022-11-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-022-23120-0 |
| _version_ | 1811328724479508480 |
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| author | Andreas Krause Phillip Papastefanou Konstantin Gregor Lucia S. Layritz Christian S. Zang Allan Buras Xing Li Jingfeng Xiao Anja Rammig |
| author_facet | Andreas Krause Phillip Papastefanou Konstantin Gregor Lucia S. Layritz Christian S. Zang Allan Buras Xing Li Jingfeng Xiao Anja Rammig |
| author_sort | Andreas Krause |
| collection | DOAJ |
| description | Abstract 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. |
| first_indexed | 2024-04-13T15:30:11Z |
| format | Article |
| id | doaj.art-7be760b8ee414f4d9c9b80d34b3eac65 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-04-13T15:30:11Z |
| publishDate | 2022-11-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-7be760b8ee414f4d9c9b80d34b3eac652022-12-22T02:41:24ZengNature PortfolioScientific Reports2045-23222022-11-0112111010.1038/s41598-022-23120-0Quantifying the impacts of land cover change on gross primary productivity globallyAndreas Krause0Phillip Papastefanou1Konstantin Gregor2Lucia S. Layritz3Christian S. Zang4Allan Buras5Xing Li6Jingfeng Xiao7Anja Rammig8TUM School of Life Sciences Weihenstephan, Technical University of MunichTUM School of Life Sciences Weihenstephan, Technical University of MunichTUM School of Life Sciences Weihenstephan, Technical University of MunichTUM School of Life Sciences Weihenstephan, Technical University of MunichWeihenstephan-Triesdorf University of Applied SciencesTUM School of Life Sciences Weihenstephan, Technical University of MunichResearch Institute of Agriculture and Life Sciences, Seoul National UniversityEarth Systems Research Center, Institute for the Study of Earth, Oceans, and Space, University of New HampshireTUM School of Life Sciences Weihenstephan, Technical University of MunichAbstract 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.https://doi.org/10.1038/s41598-022-23120-0 |
| spellingShingle | Andreas Krause Phillip Papastefanou Konstantin Gregor Lucia S. Layritz Christian S. Zang Allan Buras Xing Li Jingfeng Xiao Anja Rammig Quantifying the impacts of land cover change on gross primary productivity globally Scientific Reports |
| 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 |
| url | https://doi.org/10.1038/s41598-022-23120-0 |
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