Dataset Information

Rapid greening response of China's 2020 spring vegetation to COVID-19 restrictions: Implications for climate change.

ABSTRACT: The 2019 novel coronavirus pandemic (COVID-19) negatively affected global public health and socioeconomic development. Lockdowns and travel restrictions to contain COVID-19 resulted in reduced human activity and decreased anthropogenic emissions. However, the secondary effects of these restrictions on the biophysical environment are uncertain. Using remotely sensed big data, we investigated how lockdowns and traffic restrictions affected China's spring vegetation in 2020. Our analyses show that travel decreased by 58% in the first 18 days following implementation of the restrictions across China. Subsequently, atmospheric optical clarity increased and radiation levels on the vegetation canopy were augmented. Furthermore, the spring of 2020 arrived 8.4 days earlier and vegetation 17.45% greener compared to 2015-2019. Reduced human activity resulting from COVID-19 restrictions contributed to a brighter, earlier, and greener 2020 spring season in China. This study shows that short-term changes in human activity can have a relatively rapid ecological impact at the regional scale.

SUBMITTER: Su F

PROVIDER: S-EPMC8386938 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature

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Rapid greening response of China's 2020 spring vegetation to COVID-19 restrictions: Implications for climate change.

Su Fenzhen F Fu Dongjie D Yan Fengqin F Xiao Han H Pan Tingting T Xiao Yang Y Kang Lu L Zhou Chenghu C Meadows Michael M Lyne Vincent V Wilson John P JP Zhao Na N Yang Xiaomei X Liu Gaohuan G

Science advances 20210825 35

The 2019 novel coronavirus pandemic (COVID-19) negatively affected global public health and socioeconomic development. Lockdowns and travel restrictions to contain COVID-19 resulted in reduced human activity and decreased anthropogenic emissions. However, the secondary effects of these restrictions on the biophysical environment are uncertain. Using remotely sensed big data, we investigated how lockdowns and traffic restrictions affected China's spring vegetation in 2020. Our analyses show that ...[more]

PMID: 34433554

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Project description:Global warming has significantly altered plant phenology by advancing the timing of leaf emergence, impacting vegetation productivity and adaptability. Winter and spring temperatures have commonly been used to explain spring phenology shifts, but we still lack a solid understanding of the effects of interactions between conditions in different seasons. This study utilizes normalized difference vegetation index (NDVI) and meteorological data to examine the effects of changes in winter and spring temperatures and precipitation on the start of the vegetation growing season (SOS) at high latitudes in China from 1982 to 2015. We found that SOS in Northeast China, as a whole, showed a weak advancing trend (moving earlier in the year), but with obvious regional differences. Even within the same vegetation type, changes in SOS were faster in the cold north (1.9 days/decade) and the cold and dry northwest (1.6 days/decade) than the regional averages for deciduous needleleaf forests (DNF; 1.2 days/decade) and grasslands (0.6 days/decade). Increases in spring temperatures dominate forest SOS advancement, while grassland SOS is mainly influenced by winter and spring precipitation. Decreases in winter minimum temperature (Tmin) enhance the spring temperature sensitivity of SOS. The way that winter precipitation regulates the spring temperature sensitivity of SOS differs among vegetation types: increasing sensitivity in grasslands but suppressing it in DNF. The moderating effects of winter conditions account for the greatest part of the regional differences in the magnitude of change in SOS. Our findings highlight that, although rising spring temperatures significantly affect SOS, winter Tmin and precipitation are crucial for understanding spatial SOS differences, particularly in cold, arid high-latitude regions. Winter conditions play an essential role in regulating the response of vegetation SOS to spring climate at high latitudes. These results suggest that considering the moderating effect of winter climate can facilitate more accurate predictions of temperature-driven phenological changes under future climate change.

Dataset Information

Rapid greening response of China's 2020 spring vegetation to COVID-19 restrictions: Implications for climate change.

Publications

Rapid greening response of China's 2020 spring vegetation to COVID-19 restrictions: Implications for climate change.

Similar Datasets

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