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Spatio-temporal evolution and prediction of carbon storage in Kunming based on PLUS and InVEST models
Carbon storage is a critical ecosystem service provided by terrestrial environmental systems that can effectively reduce regional carbon emissions and is critical for achieving carbon neutrality and carbon peak. We conducted a study in Kunming and analyzed the land utilization data for 2000, 2010, a...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10215775/ https://www.ncbi.nlm.nih.gov/pubmed/37250707 http://dx.doi.org/10.7717/peerj.15285 |
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author | Li, Yimin Yang, Xue Wu, Bowen Zhao, Juanzhen Jiang, Wenxue Feng, Xianjie Li, Yuanting |
author_facet | Li, Yimin Yang, Xue Wu, Bowen Zhao, Juanzhen Jiang, Wenxue Feng, Xianjie Li, Yuanting |
author_sort | Li, Yimin |
collection | PubMed |
description | Carbon storage is a critical ecosystem service provided by terrestrial environmental systems that can effectively reduce regional carbon emissions and is critical for achieving carbon neutrality and carbon peak. We conducted a study in Kunming and analyzed the land utilization data for 2000, 2010, and 2020. We assessed the features of land utilization conversion and forecasted land utilization under three development patterns in 2030 on the basis of the Patch-generating Land Use Simulation (PLUS) model. We used the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model to estimate changes in carbon storage trends under three development scenarios in 2000, 2010, 2020, and 2030 and the impact of socioeconomic and natural factors on carbon storage. The results of the study indicated that (1) carbon storage is intimately associated with land utilization practices. Carbon storage in Kunming in 2000, 2010, and 2020 was 1.146 × 108 t, 1.139 × 108 t, and 1.120 × 108 t, respectively. During the 20 years, forest land decreased by 142.28 km(2), and the decrease in forest land area caused a loss of carbon storage. (2) Carbon storage in 2030 was predicted to be 1.102 × 108 t, 1.136 × 108 t, and 1.105 × 108 t, respectively, under the trend continuation scenario, eco-friendly scenario, and comprehensive development scenario, indicating that implementing ecological protection and cultivated land protection measures can facilitate regional ecosystem carbon storage restoration. (3) Impervious surfaces and vegetation have the greatest influence on carbon storage for the study area. A spatial global and local negative correlation was found between impervious surface coverage and ecosystem carbon storage. A spatial global and local positive correlation was found between NDVI and ecosystem carbon storage. Therefore, ecological and farmland protection policies need to be strengthened, the expansion of impervious surfaces should be strictly controlled, and vegetation coverage should be improved. |
format | Online Article Text |
id | pubmed-10215775 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-102157752023-05-27 Spatio-temporal evolution and prediction of carbon storage in Kunming based on PLUS and InVEST models Li, Yimin Yang, Xue Wu, Bowen Zhao, Juanzhen Jiang, Wenxue Feng, Xianjie Li, Yuanting PeerJ Ecosystem Science Carbon storage is a critical ecosystem service provided by terrestrial environmental systems that can effectively reduce regional carbon emissions and is critical for achieving carbon neutrality and carbon peak. We conducted a study in Kunming and analyzed the land utilization data for 2000, 2010, and 2020. We assessed the features of land utilization conversion and forecasted land utilization under three development patterns in 2030 on the basis of the Patch-generating Land Use Simulation (PLUS) model. We used the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model to estimate changes in carbon storage trends under three development scenarios in 2000, 2010, 2020, and 2030 and the impact of socioeconomic and natural factors on carbon storage. The results of the study indicated that (1) carbon storage is intimately associated with land utilization practices. Carbon storage in Kunming in 2000, 2010, and 2020 was 1.146 × 108 t, 1.139 × 108 t, and 1.120 × 108 t, respectively. During the 20 years, forest land decreased by 142.28 km(2), and the decrease in forest land area caused a loss of carbon storage. (2) Carbon storage in 2030 was predicted to be 1.102 × 108 t, 1.136 × 108 t, and 1.105 × 108 t, respectively, under the trend continuation scenario, eco-friendly scenario, and comprehensive development scenario, indicating that implementing ecological protection and cultivated land protection measures can facilitate regional ecosystem carbon storage restoration. (3) Impervious surfaces and vegetation have the greatest influence on carbon storage for the study area. A spatial global and local negative correlation was found between impervious surface coverage and ecosystem carbon storage. A spatial global and local positive correlation was found between NDVI and ecosystem carbon storage. Therefore, ecological and farmland protection policies need to be strengthened, the expansion of impervious surfaces should be strictly controlled, and vegetation coverage should be improved. PeerJ Inc. 2023-05-23 /pmc/articles/PMC10215775/ /pubmed/37250707 http://dx.doi.org/10.7717/peerj.15285 Text en © 2023 Li et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Ecosystem Science Li, Yimin Yang, Xue Wu, Bowen Zhao, Juanzhen Jiang, Wenxue Feng, Xianjie Li, Yuanting Spatio-temporal evolution and prediction of carbon storage in Kunming based on PLUS and InVEST models |
title | Spatio-temporal evolution and prediction of carbon storage in Kunming based on PLUS and InVEST models |
title_full | Spatio-temporal evolution and prediction of carbon storage in Kunming based on PLUS and InVEST models |
title_fullStr | Spatio-temporal evolution and prediction of carbon storage in Kunming based on PLUS and InVEST models |
title_full_unstemmed | Spatio-temporal evolution and prediction of carbon storage in Kunming based on PLUS and InVEST models |
title_short | Spatio-temporal evolution and prediction of carbon storage in Kunming based on PLUS and InVEST models |
title_sort | spatio-temporal evolution and prediction of carbon storage in kunming based on plus and invest models |
topic | Ecosystem Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10215775/ https://www.ncbi.nlm.nih.gov/pubmed/37250707 http://dx.doi.org/10.7717/peerj.15285 |
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