Abstract
In this dissertation, the author adopted the normalized difference vegetation index (NDVI) and meteorological data from 1982 to 2016 of the typical climate zones in coastal areas of China to analyze the influence of daytime and nighttime warming asymmetric changes in different seasons on vegetation activities during the growing season period according to the copula function theory optimized based on Markov chain Monte Carlo (MCMC). The main conclusions are as follows: (1) The seasonal daytime and nighttime warming trends of Guangdong, Jiangsu and Liaoning over the past 35 years were significant, and the daytime and nighttime warming rates were asymmetric. In spring and summer of Guangdong province, the warming rate in the daytime was higher than that at night, while, in autumn, the opposite law was observed. However, the warming rate in the daytime was lower than that at night in Jiangsu and Liaoning provinces. There were latitude differences in diurnal and nocturnal warming rate. (2) The daytime and nighttime warming influences on vegetation showed significant seasonal differences in these three regions. In Guangdong, the influence of nighttime warming on vegetation growth in spring is greater than that in summer, and the influences of daytime warming on vegetation growth from strong to weak were spring, summer and autumn. In Jiangsu, both the influences of daytime and nighttime warming on vegetation growth in summer were less than that in autumn. In Liaoning, both the influences of daytime and nighttime warming on vegetation growth from strong to weak were autumn, spring and summer. (3) In Guangdong, Jiangsu and Liaoning provinces, their maximum temperature (Tmax) and minimum temperature (Tmin) and the joint probability distribution functions of NDVI, all had little effect on NDVI when Tmax and Tmin respectively reached their minimum values, but their influences on NDVI were obvious when Tmax and Tmin respectively reached their maximum values. (4) The smaller the return period, the larger the range of climate factor and NDVI, which has indicated that when the climate factor is certain, the NDVI is more likely to have a smaller return period, and the frequency of NDVI over a certain period is higher. In addition, the larger the climate factor, the greater the return period is and NDVI is less frequent over a certain period of time. This research can help with deep understanding of the dynamic influence of seasonal daytime and nighttime asymmetric warming on the vegetation in typical coastal temperature zones of China under the background of global climate change.
Highlights
As an important component of the terrestrial ecosystem, vegetation is a key medium for the flow of matter and energy in the atmosphere, hydrosphere, biosphere and soil [1] and plays an important role in surface radiation balance [2,3], estimation of biogeophysical and biochemical parameters [4,5,6], carbon–nitrogen cycle [7,8,9], slowing the increase of greenhouse gas concentrations [10], maintaining the ecosystem stability [11] and other aspects
This research can help with deep understanding of the dynamic influence of seasonal daytime and nighttime asymmetric warming on the vegetation in typical coastal temperature zones of China under the background of global climate change
The typical temperature zones along the eastern coast of China presented the asymmetry of daytime and nighttime warming in different seasons, showing a significant rising trend, and the geographical distribution of the temperature increase trend was obviously different in respective seasons
Summary
As an important component of the terrestrial ecosystem, vegetation is a key medium for the flow of matter and energy in the atmosphere, hydrosphere, biosphere and soil [1] and plays an important role in surface radiation balance [2,3], estimation of biogeophysical and biochemical parameters [4,5,6], carbon–nitrogen cycle [7,8,9], slowing the increase of greenhouse gas concentrations [10], maintaining the ecosystem stability [11] and other aspects It is affected by climate change and actively responds to climate change [12,13]. The response of vegetation activities to temperature changes shows uncertainty [27,28], and a further study about how temperature changes affect the physiological activities of plants is urgently needed
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
