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The effects of air temperature and precipitation on the net primary productivity in China during the early 21st century

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Abstract

Research on how terrestrial ecosystems respond to climate change can reveal the complex interactions between vegetation and climate. net primary productivity (NPP), an important vegetation parameter and ecological indicator, fluctuates within any given ecological environment or regional carbon budget. In this study, spatial interpolation was used to generate a spatial dataset, with 1-km spatial resolution, with meteorological data from 736 observation stations across China. An improved CASA model was used to simulate NPP over the period of 2001–2013 by taking into account land-cover change in every year during the same period. We propose the gridbased spatial patterns and dynamics of annual NPP, annual average temperature, and annual total precipitation based on the model. We also used the model to demonstrate the spatial correlation between NPP, temperature, and precipitation in the study area with special focus on the impact of climate change in the early 21st century. Results showed that the spatial pattern of NPP over all of China is characterized by higher values in the southeast and lower values in the northwest. The spatial pattern of temperature indicates substantial latitudinal differences across the country, and the spatial pattern of precipitation shows a ribbon of decline from the southeast coast to the northwest inland. Most areas show an upward trend in NPP. Temperatures appear to decrease across the country during the global warming hiatus (1998–2008), and are accompanied by an increase in precipitation over most regions. The correlation between NPP and annual average temperature is weak. Alternatively, NPP and annual total precipitation are positively correlated in northern and central China at a coefficient above 0.64 (p<0.01) yet negatively correlated in the eastern parts of the Qinghai- Tibet Plateau and Sichuan Basin. Results can provide useful information for improving parameters for calibration of the terrestrial ecosystem process model.

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Acknowledgements

This research received financial support from the National Basic Research Program of China (No. 2016YFC0502900), the National Natural Science Foundation of China (Nos. 41601562, 41401643, and 41401050), the Research Project for Young Teachers of Fujian Province (No. JAT160085), and the Scientific Research Foundation of Fuzhou University (No. XRC-1536). We would like to thank the editors and reviewers for providing helpful suggestions and support.

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Authors and Affiliations

  1. College of Environment and Resource, Fuzhou University, Fuzhou, 350116, China

    Qianfeng Wang, Jingyu Zeng, Bingxiong Fan, Jia Tang, Yi Huang, Wulin Wang & Wei Shui

  2. Key Laboratory of Spatial Data Mining & Information Sharing, Ministry of Education of China, Fuzhou, 350116, China

    Qianfeng Wang, Jingyu Zeng, Bingxiong Fan, Jia Tang, Yi Huang, Wulin Wang & Wei Shui

  3. Fujian Provincial Key Laboratory of Remote Sensing of Soil Erosion and Disaster Protection, Fuzhou, 350116, China

    Qianfeng Wang, Jingyu Zeng, Bingxiong Fan, Jia Tang, Yi Huang, Wulin Wang & Wei Shui

  4. Climate Change Cluster, University of Technology Sydney, Broadway, New South Wales, 2007, Australia

    Song Leng

  5. College of Biological Science and Engineering, Fuzhou University, Fuzhou, 350116, China

    Cong Jiang

  6. Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, 100094, China

    Qing Zhang

  7. China Institute of Water Resources and Hydropower Research, Beijing, 100038, China

    Yanping Qu

  8. Research Center on Flood and Drought Disaster Reduction, Beijing, 100038, China

    Yanping Qu

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  1. Qianfeng Wang
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  2. Jingyu Zeng
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  3. Song Leng
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  10. Wulin Wang
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  11. Wei Shui
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Correspondence to Wei Shui.

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Wang, Q., Zeng, J., Leng, S. et al. The effects of air temperature and precipitation on the net primary productivity in China during the early 21st century. Front. Earth Sci. 12, 818–833 (2018). https://doi.org/10.1007/s11707-018-0697-9

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  • DOI: https://doi.org/10.1007/s11707-018-0697-9

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