Spatiotemporal Variation in Carbon and Water Use Efficiency and Their Influencing Variables Based on Remote Sensing Data in the Nanling Mountains Region
A comprehensive evaluation of the variations in carbon use efficiency (CUE) and water use efficiency (WUE) in the Nanling Mountains Region (NMR) is crucial for gaining insights into the intricate relationships between climate change and ecosystem processes. This study evaluates the spatiotemporal ra...
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MDPI AG
2025-02-01
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| author | Sha Lei Ping Zhou Jiaying Lin Zhaowei Tan Junxiang Huang Ping Yan Hui Chen |
| author_facet | Sha Lei Ping Zhou Jiaying Lin Zhaowei Tan Junxiang Huang Ping Yan Hui Chen |
| author_sort | Sha Lei |
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| description | A comprehensive evaluation of the variations in carbon use efficiency (CUE) and water use efficiency (WUE) in the Nanling Mountains Region (NMR) is crucial for gaining insights into the intricate relationships between climate change and ecosystem processes. This study evaluates the spatiotemporal rates of dynamics in CUE, WUE, gross primary productivity (GPP), net primary productivity (NPP), and evapotranspiration (ET) over the period from 2001 to 2023, using remote sensing data and linear regression analysis. Trend analysis, Hurst exponent analysis, and stability analysis were applied to examine the long-term patterns of CUE and WUE, while partial correlation analysis was employed to explore the spatial relationships between these efficiencies and climatic factors. The main findings of the study are as follows: (1) The CUE and WUE of the NMR decreased geographically from 2001 to 2023, and both the CUE and WUE of NMR showed a significant declining trend (<i>p</i> < 0.05) with the CUE decreasing at a rate of 0.0014/a (a: year) and the WUE falling at a rate of 0.0022/a. (2) The average values of the CUE and WUE of the NMR from 2001 to 2023 were 0.47 and 0.82 g C·m<sup>−2</sup>·mm<sup>−1</sup>, respectively, with a clear geographical difference. (3) The CUE and WUE in the NMR showed widespread degradation trends with some localized improvements, yet sustainability analysis indicates a likely continued decline across most areas, particularly for forests, while grasslands exhibit the greatest resilience. (4) Precipitation had a significantly stronger impact on WUE, while temperature appeared to exert a more substantial effect on CUE, with vegetation types responding differently; notably, shrubland displayed a direct association between CUE and temperature. In summary, multi-source data were employed to comprehensively analyze the spatiotemporal dynamics of CUE and WUE in the NMR over the past 23 years. We also examined the features of their responses to global warming, offering valuable theoretical insights into the carbon and water dynamics within the terrestrial ecosystems of the NMR. |
| format | Article |
| id | doaj-art-eb3cbe3ee22e4d7ca6e027e86b816601 |
| institution | OA Journals |
| issn | 2072-4292 |
| language | English |
| publishDate | 2025-02-01 |
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| series | Remote Sensing |
| spelling | doaj-art-eb3cbe3ee22e4d7ca6e027e86b8166012025-08-20T02:03:42ZengMDPI AGRemote Sensing2072-42922025-02-0117464810.3390/rs17040648Spatiotemporal Variation in Carbon and Water Use Efficiency and Their Influencing Variables Based on Remote Sensing Data in the Nanling Mountains RegionSha Lei0Ping Zhou1Jiaying Lin2Zhaowei Tan3Junxiang Huang4Ping Yan5Hui Chen6Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, ChinaGuangdong Nanling Forest Ecosystem National Field Scientific Observation and Research Station, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, ChinaGuangdong Nanling Forest Ecosystem National Field Scientific Observation and Research Station, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, ChinaGuangdong Nanling Forest Ecosystem National Field Scientific Observation and Research Station, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, ChinaGuangdong Nanling Forest Ecosystem National Field Scientific Observation and Research Station, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, ChinaGuangdong Nanling Forest Ecosystem National Field Scientific Observation and Research Station, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, ChinaGuangdong Nanling Forest Ecosystem National Field Scientific Observation and Research Station, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, ChinaA comprehensive evaluation of the variations in carbon use efficiency (CUE) and water use efficiency (WUE) in the Nanling Mountains Region (NMR) is crucial for gaining insights into the intricate relationships between climate change and ecosystem processes. This study evaluates the spatiotemporal rates of dynamics in CUE, WUE, gross primary productivity (GPP), net primary productivity (NPP), and evapotranspiration (ET) over the period from 2001 to 2023, using remote sensing data and linear regression analysis. Trend analysis, Hurst exponent analysis, and stability analysis were applied to examine the long-term patterns of CUE and WUE, while partial correlation analysis was employed to explore the spatial relationships between these efficiencies and climatic factors. The main findings of the study are as follows: (1) The CUE and WUE of the NMR decreased geographically from 2001 to 2023, and both the CUE and WUE of NMR showed a significant declining trend (<i>p</i> < 0.05) with the CUE decreasing at a rate of 0.0014/a (a: year) and the WUE falling at a rate of 0.0022/a. (2) The average values of the CUE and WUE of the NMR from 2001 to 2023 were 0.47 and 0.82 g C·m<sup>−2</sup>·mm<sup>−1</sup>, respectively, with a clear geographical difference. (3) The CUE and WUE in the NMR showed widespread degradation trends with some localized improvements, yet sustainability analysis indicates a likely continued decline across most areas, particularly for forests, while grasslands exhibit the greatest resilience. (4) Precipitation had a significantly stronger impact on WUE, while temperature appeared to exert a more substantial effect on CUE, with vegetation types responding differently; notably, shrubland displayed a direct association between CUE and temperature. In summary, multi-source data were employed to comprehensively analyze the spatiotemporal dynamics of CUE and WUE in the NMR over the past 23 years. We also examined the features of their responses to global warming, offering valuable theoretical insights into the carbon and water dynamics within the terrestrial ecosystems of the NMR.https://www.mdpi.com/2072-4292/17/4/648Nanling mountains region (NMR)carbon use efficiency (CUE)water use efficiency (WUE)climate change |
| spellingShingle | Sha Lei Ping Zhou Jiaying Lin Zhaowei Tan Junxiang Huang Ping Yan Hui Chen Spatiotemporal Variation in Carbon and Water Use Efficiency and Their Influencing Variables Based on Remote Sensing Data in the Nanling Mountains Region Remote Sensing Nanling mountains region (NMR) carbon use efficiency (CUE) water use efficiency (WUE) climate change |
| title | Spatiotemporal Variation in Carbon and Water Use Efficiency and Their Influencing Variables Based on Remote Sensing Data in the Nanling Mountains Region |
| title_full | Spatiotemporal Variation in Carbon and Water Use Efficiency and Their Influencing Variables Based on Remote Sensing Data in the Nanling Mountains Region |
| title_fullStr | Spatiotemporal Variation in Carbon and Water Use Efficiency and Their Influencing Variables Based on Remote Sensing Data in the Nanling Mountains Region |
| title_full_unstemmed | Spatiotemporal Variation in Carbon and Water Use Efficiency and Their Influencing Variables Based on Remote Sensing Data in the Nanling Mountains Region |
| title_short | Spatiotemporal Variation in Carbon and Water Use Efficiency and Their Influencing Variables Based on Remote Sensing Data in the Nanling Mountains Region |
| title_sort | spatiotemporal variation in carbon and water use efficiency and their influencing variables based on remote sensing data in the nanling mountains region |
| topic | Nanling mountains region (NMR) carbon use efficiency (CUE) water use efficiency (WUE) climate change |
| url | https://www.mdpi.com/2072-4292/17/4/648 |
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