Redefining seasons: Dynamic meteorological delineation unveils novel patterns in vegetation phenology responses to climate change
Vegetation phenology is a sensitive indicator of climate change, and the impact of large-scale meteorological seasonal variations on phenological patterns remains understudied because traditional seasonal divisions fail to capture the dynamics of rapid phenological change. Utilizing CN05 gridded tem...
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Elsevier
2025-02-01
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| Series: | Ecological Indicators |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1470160X25001438 |
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| author | Xinyi Fan Zhixin Hao Yang Liu |
| author_facet | Xinyi Fan Zhixin Hao Yang Liu |
| author_sort | Xinyi Fan |
| collection | DOAJ |
| description | Vegetation phenology is a sensitive indicator of climate change, and the impact of large-scale meteorological seasonal variations on phenological patterns remains understudied because traditional seasonal divisions fail to capture the dynamics of rapid phenological change. Utilizing CN05 gridded temperature data, we applied a dynamic meteorological model to analyze the spatial distribution and trends of spring and autumn, revealing their influence on regional vegetation phenology. We revealed that the start of spring and end of spring advanced at rates of −0.19 d·yr−1 and −0.15 d·yr−1, respectively, affecting 92.57 % and 82.85 % of the study area. Conversely, the start and end of autumn were delayed by + 0.06 d·yr−1 and + 0.10 d·yr−1, impacting 54.05 % and 89.96 % of the region. The length of spring and length of autumn increased at rates of + 0.05 d·yr−1 and + 0.02 d·yr−1, respectively, across 55.93 % and 53.97 % of the area. These changes exhibited a clear latitudinal gradient, with a decreasing duration from south to north. Significant correlations were observed between seasonal variations and vegetation phenology; earlier spring onset corresponded to an earlier start of the growing season in 71.58 % of the study area, while a later end of autumn correlated with a delayed end of the growing season in 59.72 % of the region. This study systematically demonstrates, for the first time, the extensive influence of climate-driven seasonal changes on vegetation phenology, offering valuable insights for weather forecasting, climate zoning, and phenology management. |
| format | Article |
| id | doaj-art-4041cf400e5348f9af55717c589875cd |
| institution | Kabale University |
| issn | 1470-160X |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ecological Indicators |
| spelling | doaj-art-4041cf400e5348f9af55717c589875cd2025-02-11T04:33:41ZengElsevierEcological Indicators1470-160X2025-02-01171113214Redefining seasons: Dynamic meteorological delineation unveils novel patterns in vegetation phenology responses to climate changeXinyi Fan0Zhixin Hao1Yang Liu2Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; University of Chinese Academy of Sciences, Beijing, 100049, ChinaCorresponding author.; Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; University of Chinese Academy of Sciences, Beijing, 100049, ChinaKey Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; University of Chinese Academy of Sciences, Beijing, 100049, ChinaVegetation phenology is a sensitive indicator of climate change, and the impact of large-scale meteorological seasonal variations on phenological patterns remains understudied because traditional seasonal divisions fail to capture the dynamics of rapid phenological change. Utilizing CN05 gridded temperature data, we applied a dynamic meteorological model to analyze the spatial distribution and trends of spring and autumn, revealing their influence on regional vegetation phenology. We revealed that the start of spring and end of spring advanced at rates of −0.19 d·yr−1 and −0.15 d·yr−1, respectively, affecting 92.57 % and 82.85 % of the study area. Conversely, the start and end of autumn were delayed by + 0.06 d·yr−1 and + 0.10 d·yr−1, impacting 54.05 % and 89.96 % of the region. The length of spring and length of autumn increased at rates of + 0.05 d·yr−1 and + 0.02 d·yr−1, respectively, across 55.93 % and 53.97 % of the area. These changes exhibited a clear latitudinal gradient, with a decreasing duration from south to north. Significant correlations were observed between seasonal variations and vegetation phenology; earlier spring onset corresponded to an earlier start of the growing season in 71.58 % of the study area, while a later end of autumn correlated with a delayed end of the growing season in 59.72 % of the region. This study systematically demonstrates, for the first time, the extensive influence of climate-driven seasonal changes on vegetation phenology, offering valuable insights for weather forecasting, climate zoning, and phenology management.http://www.sciencedirect.com/science/article/pii/S1470160X25001438Vegetation phenologyClimate changeSeasonal variationsDynamic meteorological model |
| spellingShingle | Xinyi Fan Zhixin Hao Yang Liu Redefining seasons: Dynamic meteorological delineation unveils novel patterns in vegetation phenology responses to climate change Ecological Indicators Vegetation phenology Climate change Seasonal variations Dynamic meteorological model |
| title | Redefining seasons: Dynamic meteorological delineation unveils novel patterns in vegetation phenology responses to climate change |
| title_full | Redefining seasons: Dynamic meteorological delineation unveils novel patterns in vegetation phenology responses to climate change |
| title_fullStr | Redefining seasons: Dynamic meteorological delineation unveils novel patterns in vegetation phenology responses to climate change |
| title_full_unstemmed | Redefining seasons: Dynamic meteorological delineation unveils novel patterns in vegetation phenology responses to climate change |
| title_short | Redefining seasons: Dynamic meteorological delineation unveils novel patterns in vegetation phenology responses to climate change |
| title_sort | redefining seasons dynamic meteorological delineation unveils novel patterns in vegetation phenology responses to climate change |
| topic | Vegetation phenology Climate change Seasonal variations Dynamic meteorological model |
| url | http://www.sciencedirect.com/science/article/pii/S1470160X25001438 |
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