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Liu X, Lai Q, Yin S, Bao Y, Tong S, Adiya Z, Sanjjav A, Gao R. Spatio-temporal patterns and control mechanism of the ecosystem carbon use efficiency across the Mongolian Plateau. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 907:167883. [PMID: 37863235 DOI: 10.1016/j.scitotenv.2023.167883] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 10/10/2023] [Accepted: 10/14/2023] [Indexed: 10/22/2023]
Abstract
Carbon use efficiency (CUE) is a crucial parameter that reflects the carbon storage within ecosystems, providing insight into the potential for carbon sequestration at the ecosystem scale and its feedback on climate change. The Mongolian Plateau exemplifies an arid and semi-arid region with a delicate ecological environment that displays heightened sensitivity to global climate change. Understanding the variation and control of CUE is critical for assessing regional carbon. However, few studies have focused on the interaction of factors influencing CUE; furthermore, how CUE responds to climate change and anthropogenic activities remains unclear. Here, we aimed to investigate spatiotemporal patterns and their control mechanisms by generating CUE data based on multi-source remote sensing data. CUE demonstrated a slow downward trend from 2000 to 2018, with higher values in relatively dry-cool regions and lower values in relatively humid-warm regions. Furthermore, CUE values were ranked by biome as follows: grassland > sandy vegetation > cropland > shrubs > forest, driven by climate characteristics, vegetation coverage, water stress, stand age, and management practices. Additionally, climatic factors affected CUE more than the soil variables, except for alpine meadows. The climate factors of precipitation (PPT), index of water availability (IWA) (QPPT = 0.487, QIWA = 0.444), and soil factors, e.g., pH and soil organic content (SOC) (QPH = 0.397, QSOC = 0.372), had the greatest influence on CUE. Finally, most two explanatory factors interacted to effectively enhance the explanation of CUE; the synergy of the IWA and PPT contributed the most to CUE (QIWA∩PPT = 0.604). Moreover, the joint effect of climate change and anthropogenic activities was identified as the major contributor (68 %) to the decline in CUE within this region. This study presents compelling evidence highlighting the importance of considering climate change and anthropogenic disturbances in ecosystem management and conservation efforts in arid and semi-arid regions.
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Affiliation(s)
- Xinyi Liu
- College of Geographical Science, Inner Mongolia Normal University, Hohhot 010022, China
| | - Quan Lai
- College of Geographical Science, Inner Mongolia Normal University, Hohhot 010022, China; Inner Mongolia Key Laboratory of Remote Sensing and Geographic Information Systems, Inner Mongolia, Normal University, Hohhot 010022, China.
| | - Shan Yin
- College of Geographical Science, Inner Mongolia Normal University, Hohhot 010022, China; Inner Mongolia Key Laboratory of Remote Sensing and Geographic Information Systems, Inner Mongolia, Normal University, Hohhot 010022, China
| | - Yuhai Bao
- College of Geographical Science, Inner Mongolia Normal University, Hohhot 010022, China; Inner Mongolia Key Laboratory of Remote Sensing and Geographic Information Systems, Inner Mongolia, Normal University, Hohhot 010022, China
| | - Siqin Tong
- College of Geographical Science, Inner Mongolia Normal University, Hohhot 010022, China; Inner Mongolia Key Laboratory of Remote Sensing and Geographic Information Systems, Inner Mongolia, Normal University, Hohhot 010022, China
| | - Zolzaya Adiya
- Institute of Geography and Geoecology, Mongolian Academy of Sciences, Ulaanbaatar 14201, Mongolia
| | - Amarjargal Sanjjav
- Institute of Geography and Geoecology, Mongolian Academy of Sciences, Ulaanbaatar 14201, Mongolia
| | - Rihe Gao
- College of Geography and Environmental Sciences, Tianjin Normal University, Tianjin 300382, China
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Spatial and Temporal Drought Characteristics in the Huanghuaihai Plain and Its Influence on Cropland Water Use Efficiency. REMOTE SENSING 2022. [DOI: 10.3390/rs14102381] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/04/2022]
Abstract
Understanding the relationship between drought and the water use efficiency (WUE) in terrestrial ecosystems can help reduce drought risk. It remains unclear what the correlation between the cropland water use efficiency (CWUE) and drought during drought events. We aim to identify the spatiotemporal relationship between drought and the CWUE and to ensure the service capacity of cultivated land ecosystems. In this study, the cubist algorithm was used to establish a monthly integrated surface drought index (mISDI) dataset for the Huang–Huai–Hai Plain (HHHP), and the run theory was used to identify drought events. We assessed the spatio-temporal variations of drought in the HHHP during 2000–2020 and its influence on the CWUE. The research results were as follows: from the overall perspective of the HHHP, the mISDI showed a downward trend. Drought had an enhanced effect on the CWUE of the HHHP, and the enhancement of the CWUE in the eastern hilly area was more significant. The CWUE response to drought had a three-month lag period and a significant positive correlation, and it was shown that the cultivated land ecosystems in this area had strong drought resistance ability. This study provides a new framework for understanding the response of the CWUE to drought and formulating reasonable vegetation management strategies for the HHHP.
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