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<p>Frequent extreme weather events in the context of global climate change are significantly impacting vegetation phenology, with significant implications for the stability of terrestrial ecosystems and the global carbon cycle. However, the effects of extreme events such as freezing rain remain less explored compared to those of droughts and heatwaves. Focusing on two severe freezing rain events in southern China in February 2024, we extracted the start of the growing season (SOS) based on the time series constructed from TROPOMI solar-induced chlorophyll fluorescence (SIF), and compared the SOS between the freezing rain year and non-freezing rain years. Using structural equation modeling (SEM), pathways were assessed through which freezing rain intensity influences SOS shifts, physiological and structural vegetation components of vegetation to identify mechanisms underlying freezing rain impacts on forest phenology. The results indicate that the two extreme freezing rain events affected an area exceeding 1.07 × 10<sup>8</sup>&#xa0;ha, including Hunan, central-eastern Hubei, eastern Guizhou, and western Anhui. This resulted in an average SOS delay of 4.0 d in the region’s forests, with evergreen broadleaf forests having the most delay (8.6 d), followed by mixed coniferous-broadleaf forests, evergreen needleleaf forests, and deciduous broadleaf forests. In addition, freezing rain intensity correlated with more pronounced SOS delays, primarily driven by structural damage. In contrast, evergreen broadleaf forests showed a distinct impact pathway compared to the other three vegetation types, demonstrating greater susceptibility to physiological damage. This study reveals the impact of extreme freezing rain on the spring phenology of forests in southern China and the divergent mechanisms underlying its effects across forest types, providing a scientific basis for risk assessment, protection, and restoration.</p>

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Divergent mechanisms regulating freezing rain-induced spring phenology delays in forests in southern China

  • 期刊论文

  • 发表日期：

    2026年5月27日

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  • Yating Zhang,
  • Jinghua Chen,
  • Shaoqiang Wang,
  • Miaomiao Wang,
  • Ziqi Zhao,
  • Zehan Zhou,
  • Zhuoying Deng,
  • Haoyu Peng,
  • Jiageng Ma,
  • Xueqing Wang,
  • Yuhan Xiao

摘要

Frequent extreme weather events in the context of global climate change are significantly impacting vegetation phenology, with significant implications for the stability of terrestrial ecosystems and the global carbon cycle. However, the effects of extreme events such as freezing rain remain less explored compared to those of droughts and heatwaves. Focusing on two severe freezing rain events in southern China in February 2024, we extracted the start of the growing season (SOS) based on the time series constructed from TROPOMI solar-induced chlorophyll fluorescence (SIF), and compared the SOS between the freezing rain year and non-freezing rain years. Using structural equation modeling (SEM), pathways were assessed through which freezing rain intensity influences SOS shifts, physiological and structural vegetation components of vegetation to identify mechanisms underlying freezing rain impacts on forest phenology. The results indicate that the two extreme freezing rain events affected an area exceeding 1.07 × 108 ha, including Hunan, central-eastern Hubei, eastern Guizhou, and western Anhui. This resulted in an average SOS delay of 4.0 d in the region’s forests, with evergreen broadleaf forests having the most delay (8.6 d), followed by mixed coniferous-broadleaf forests, evergreen needleleaf forests, and deciduous broadleaf forests. In addition, freezing rain intensity correlated with more pronounced SOS delays, primarily driven by structural damage. In contrast, evergreen broadleaf forests showed a distinct impact pathway compared to the other three vegetation types, demonstrating greater susceptibility to physiological damage. This study reveals the impact of extreme freezing rain on the spring phenology of forests in southern China and the divergent mechanisms underlying its effects across forest types, providing a scientific basis for risk assessment, protection, and restoration.