Spatiotemporal evolutionary and mechanism analysis of grassland GPP in China
At the ecosystem level, Gross Primary Productivity (GPP) was defined as the organic compounds formed by plants that absorb atmospheric CO2 through photosynthesis and sequester carbon in plant bodies. How to accurately assess the spatiotemporal evolution of ecosystem carbon indicators has become a cr...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-10-01
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| Series: | Ecological Indicators |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1470160X22007956 |
| _version_ | 1828145821102637056 |
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| author | Panxing He Xiaoliang Ma Xiaoyu Meng Zhiming Han Huixia Liu Zongjiu Sun |
| author_facet | Panxing He Xiaoliang Ma Xiaoyu Meng Zhiming Han Huixia Liu Zongjiu Sun |
| author_sort | Panxing He |
| collection | DOAJ |
| description | At the ecosystem level, Gross Primary Productivity (GPP) was defined as the organic compounds formed by plants that absorb atmospheric CO2 through photosynthesis and sequester carbon in plant bodies. How to accurately assess the spatiotemporal evolution of ecosystem carbon indicators has become a critical issue to be addressed. Chinese grasslands are located in a typical arid and semi-arid climate zone and are sensitive to global changes, which will inevitably have serious impacts on the function and structure of Chinese grasslands. Based on this, our paper takes Chinese grassland ecosystems as the research area, and used multi-source GPP dataset from terrestrial ecosystem model simulations and remote sensing satellite observations to quantitatively analyze the spatiotemporal evolution patterns of GPP in Chinese grasslands over the past 40 years. We combined trend analysis and breakpoint test, and then to analyze the mechanism components of GPP space–time variability. The main results are as follows: (1) The model and remote sensing estimated GPP results showed that more than 80% of Chinese grasslands show a significant increasing trend over the past 40 years, with growth rates ranging from 0.68 to 3.13 g C/m−2 year−1. (2) GPPmax also shows that more than 80% of Chinese grasslands are growing rapidly, with an overall growth rate of more than 0.1 g C/m−2 year−1 in each region. The overall long-term trends and interannual variability of multi-source GPP and GPPmax are generally consistent, yet vegetation dynamics in local areas are still uncertain. (3) The breakpoint test showed that ‘monotonically increasing’ was the largest breakpoint type of GPP in Chinese grasslands (33.09%), and the direction of change of GPP in Chinese grasslands before and after the breakpoint was also increasing. (4) GPPmax × CUP explained 91% of the temporal variability of annual-scale GPP in Chinese grasslands from a mechanistic view, and we found that the peak photosynthetic growth and the length of the phenological period synergistically controlled the interannual variability of GPP in Chinese grasslands. Under the scenario of rapid global change, our study accurately assessed the long-term dynamics of GPP and its mechanism-driven of grassland ecosystems in China, which is helpful for estimating and predicting the carbon budget of grassland ecosystems in China, and has important guiding significance for policy formulation to mitigate climate change. |
| first_indexed | 2024-04-11T20:37:13Z |
| format | Article |
| id | doaj.art-a84e7e2fd173466f80b3eaeec689e16e |
| institution | Directory Open Access Journal |
| issn | 1470-160X |
| language | English |
| last_indexed | 2024-04-11T20:37:13Z |
| publishDate | 2022-10-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ecological Indicators |
| spelling | doaj.art-a84e7e2fd173466f80b3eaeec689e16e2022-12-22T04:04:20ZengElsevierEcological Indicators1470-160X2022-10-01143109323Spatiotemporal evolutionary and mechanism analysis of grassland GPP in ChinaPanxing He0Xiaoliang Ma1Xiaoyu Meng2Zhiming Han3Huixia Liu4Zongjiu Sun5Ministry of Education Key Laboratory for Western Arid Region Grassland Resources and Ecology, College of Grassland Science, Xinjiang Agricultural University, Urumqi 830000, ChinaState Key Laboratory of Grassland Agro-ecosystems, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou 730020, ChinaKey Research Insititute of Yellow River Civilization and Sustainable Development, Collaborative Innovation Center on Yellow River Civilization, Henan University, Kaifeng 475000, ChinaCollege of Resources and Environment, Northwest A&F University, Yangling 712100, ChinaMinistry of Education Key Laboratory for Western Arid Region Grassland Resources and Ecology, College of Grassland Science, Xinjiang Agricultural University, Urumqi 830000, ChinaMinistry of Education Key Laboratory for Western Arid Region Grassland Resources and Ecology, College of Grassland Science, Xinjiang Agricultural University, Urumqi 830000, China; Corresponding author.At the ecosystem level, Gross Primary Productivity (GPP) was defined as the organic compounds formed by plants that absorb atmospheric CO2 through photosynthesis and sequester carbon in plant bodies. How to accurately assess the spatiotemporal evolution of ecosystem carbon indicators has become a critical issue to be addressed. Chinese grasslands are located in a typical arid and semi-arid climate zone and are sensitive to global changes, which will inevitably have serious impacts on the function and structure of Chinese grasslands. Based on this, our paper takes Chinese grassland ecosystems as the research area, and used multi-source GPP dataset from terrestrial ecosystem model simulations and remote sensing satellite observations to quantitatively analyze the spatiotemporal evolution patterns of GPP in Chinese grasslands over the past 40 years. We combined trend analysis and breakpoint test, and then to analyze the mechanism components of GPP space–time variability. The main results are as follows: (1) The model and remote sensing estimated GPP results showed that more than 80% of Chinese grasslands show a significant increasing trend over the past 40 years, with growth rates ranging from 0.68 to 3.13 g C/m−2 year−1. (2) GPPmax also shows that more than 80% of Chinese grasslands are growing rapidly, with an overall growth rate of more than 0.1 g C/m−2 year−1 in each region. The overall long-term trends and interannual variability of multi-source GPP and GPPmax are generally consistent, yet vegetation dynamics in local areas are still uncertain. (3) The breakpoint test showed that ‘monotonically increasing’ was the largest breakpoint type of GPP in Chinese grasslands (33.09%), and the direction of change of GPP in Chinese grasslands before and after the breakpoint was also increasing. (4) GPPmax × CUP explained 91% of the temporal variability of annual-scale GPP in Chinese grasslands from a mechanistic view, and we found that the peak photosynthetic growth and the length of the phenological period synergistically controlled the interannual variability of GPP in Chinese grasslands. Under the scenario of rapid global change, our study accurately assessed the long-term dynamics of GPP and its mechanism-driven of grassland ecosystems in China, which is helpful for estimating and predicting the carbon budget of grassland ecosystems in China, and has important guiding significance for policy formulation to mitigate climate change.http://www.sciencedirect.com/science/article/pii/S1470160X22007956Gross primary productivitySpatiotemporal evolutionaryInterannual variabilityGPPmax × CUPChinese grasslands |
| spellingShingle | Panxing He Xiaoliang Ma Xiaoyu Meng Zhiming Han Huixia Liu Zongjiu Sun Spatiotemporal evolutionary and mechanism analysis of grassland GPP in China Ecological Indicators Gross primary productivity Spatiotemporal evolutionary Interannual variability GPPmax × CUP Chinese grasslands |
| title | Spatiotemporal evolutionary and mechanism analysis of grassland GPP in China |
| title_full | Spatiotemporal evolutionary and mechanism analysis of grassland GPP in China |
| title_fullStr | Spatiotemporal evolutionary and mechanism analysis of grassland GPP in China |
| title_full_unstemmed | Spatiotemporal evolutionary and mechanism analysis of grassland GPP in China |
| title_short | Spatiotemporal evolutionary and mechanism analysis of grassland GPP in China |
| title_sort | spatiotemporal evolutionary and mechanism analysis of grassland gpp in china |
| topic | Gross primary productivity Spatiotemporal evolutionary Interannual variability GPPmax × CUP Chinese grasslands |
| url | http://www.sciencedirect.com/science/article/pii/S1470160X22007956 |
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