TANG Feng, GE Zhongxi, TANG Bohui, FANG Liuyang, ZHANG Zhen, FAN Dong, CHEN Junyi, ZHU Xinming. 2026: Mapping vegetation phenology and its response to climate change in Southwest China using solar-induced chlorophyll fluorescence. Journal of Mountain Science, 23(1): 97-117. DOI: 10.1007/s11629-025-9700-6
Citation: TANG Feng, GE Zhongxi, TANG Bohui, FANG Liuyang, ZHANG Zhen, FAN Dong, CHEN Junyi, ZHU Xinming. 2026: Mapping vegetation phenology and its response to climate change in Southwest China using solar-induced chlorophyll fluorescence. Journal of Mountain Science, 23(1): 97-117. DOI: 10.1007/s11629-025-9700-6

Mapping vegetation phenology and its response to climate change in Southwest China using solar-induced chlorophyll fluorescence

  • Accurate phenological information is essential for measuring ecosystem dynamics and carbon uptake. Southwest China is one of the country's largest terrestrial carbon sink regions and plays a crucial role in carbon peaking and neutrality. However, its complex terrain, fragile ecosystem, and variable climate challenge carbon sink stability. Vegetation phenology significantly impacts carbon absorption and release, making accurate phenological data essential for understanding carbon sequestration dynamics. The widespread distribution of evergreen forests and their weak seasonal variation in canopy introduce significant uncertainties in extracting phenology using traditional remote sensing information in this region. These limitations can lead to inaccurate assessments of carbon sink dynamics. Therefore, precise phenology extraction and analysis are vital for improving ecosystem dynamics and the carbon cycle in Southwest China. Firstly, we employed different ways to evaluate the ability of solar-induced chlorophyll fluorescence (SIF) and traditional remote sensing information to extract phenology. Secondly, based on SIF, we analyzed the spatial and temporal changes in the start of the growing season (SOS), the end of the growing season (EOS), and the length of the growing season (LOS) from 2001 to 2020. Finally, we systematically analyzed the response of SOS and EOS to five preseason climatic factors. The results showed that (1) SIF outperformed traditional remote sensing information in extracting phenology. (2) Vegetation phenology exhibited significant spatial heterogeneity. Moreover, SOS, EOS, and LOS showed trends of advancement, delay, and extension both overall and across all vegetation types. (3) Precipitation was the main factor influencing SOS, while surface downward solar radiation and mean temperature were the main factors affecting EOS, and the phenology of different vegetation types showed a great difference in response to preseason climate factors. These findings improve our understanding of vegetation phenology and its dynamics over Southwest China.
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