Shifts in Plant Phenology and Its Responses to Climate Warming in Three Temperate Cities of China during 1963–2020

The advance of spring phenology and the delay of autumn phenology caused by global warming have been documented by many studies. However, most research has focused on natural areas, with limited studies conducted on phenological observations in urban environments. Here, we selected the first flowering date (FFD), first leaf date (FLD), and leaf coloring date (LCD) at three sites (Beijing, Harbin, and Mudanjiang) from the China Phenological Observation Network. We analyzed the phenological changes of 84 species between 1963–1991 and 1992–2020 to examine their response to urban warming. We then quantified the correlations and regressions between phenological events and preseason temperature. The results show the following: (1) Among the three sites, the mean FFD and FLD were earliest in Beijing, while the mean LCD occurred earliest in Harbin and latest in Beijing. (2) FFD and FLD exhibited a significant trend towards earlier occurrences at all three sites, while LCD showed a significant delay trend except for the Mudanjiang site. Specifically, at the Beijing, Harbin, and Mudanjiang sites, the mean FFD advanced by 8.32 days, 6.11 days, and 2.60 days in the latter period (p < 0.05), whereas the mean FLD advanced by 11.30 days, 7.21 days, and 5.02 days (p < 0.05), respectively. (3) In Beijing, Harbin, and Mudanjiang, both FFD and FLD were significantly negatively correlated with preseason temperature. However, no consistent relationship was observed between LCD and preseason temperature. These results enhance our understanding of the response of plant phenology to urban warming.

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Journal
Forests
Published
2024-09-27
DOI
https://doi.org/10.3390/f15101712
Citations
1
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
0.46
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article

Shifts in Plant Phenology and Its Responses to Climate Warming in Three Temperate Cities of China during 1963–2020

Lijuan Cao, Shaozhi Lin, Junhu Dai, Wenrui Bai et al.
1 citations
Forests
Remote Sensing in Agriculture
0.46
article

Shifts in Plant Phenology and Its Responses to Climate Warming in Three Temperate Cities of China during 1963–2020

Lijuan Cao, Shaozhi Lin, Junhu Dai, Wenrui Bai, Mengyao Zhu, Chengxi Gao, Xingming Hao, Yulong Hao, Wei Liu
article en
1 citations

Abstract

The advance of spring phenology and the delay of autumn phenology caused by global warming have been documented by many studies. However, most research has focused on natural areas, with limited studies conducted on phenological observations in urban environments. Here, we selected the first flowering date (FFD), first leaf date (FLD), and leaf coloring date (LCD) at three sites (Beijing, Harbin, and Mudanjiang) from the China Phenological Observation Network. We analyzed the phenological changes of 84 species between 1963–1991 and 1992–2020 to examine their response to urban warming. We then quantified the correlations and regressions between phenological events and preseason temperature. The results show the following: (1) Among the three sites, the mean FFD and FLD were earliest in Beijing, while the mean LCD occurred earliest in Harbin and latest in Beijing. (2) FFD and FLD exhibited a significant trend towards earlier occurrences at all three sites, while LCD showed a significant delay trend except for the Mudanjiang site. Specifically, at the Beijing, Harbin, and Mudanjiang sites, the mean FFD advanced by 8.32 days, 6.11 days, and 2.60 days in the latter period (p < 0.05), whereas the mean FLD advanced by 11.30 days, 7.21 days, and 5.02 days (p < 0.05), respectively. (3) In Beijing, Harbin, and Mudanjiang, both FFD and FLD were significantly negatively correlated with preseason temperature. However, no consistent relationship was observed between LCD and preseason temperature. These results enhance our understanding of the response of plant phenology to urban warming.

ForestsVol. 15(10)
Chinese Academy of Sciences (CN), Higher Education Commission (PK), Xinjiang Institute of Ecology and Geography (CN), Institute of Geographic Sciences and Natural Resources Research (CN), University of Chinese Academy of Sciences (CN)
Sustainable cities and communities
Openalex Percentile: Top 29%
Remote Sensing in Agriculture
0.46
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