Spatiotemporal Variations in Stable Vegetation Phenology Across China Over the Past Two Decades and Their Responses to Seasonal Climate Changes

27 Pages Posted: 17 May 2025

See all articles by Jian Luo

Jian Luo

affiliation not provided to SSRN

Xiaobo Wu

affiliation not provided to SSRN

Yisen Gao

affiliation not provided to SSRN

Yufei Cai

affiliation not provided to SSRN

Li Yang

affiliation not provided to SSRN

Yijun Xiong

affiliation not provided to SSRN

Qingchun Yang

affiliation not provided to SSRN

Jiaxin Liu

affiliation not provided to SSRN

Yijin Li

affiliation not provided to SSRN

Zhiyong Deng

affiliation not provided to SSRN

Bing Li

Sichuan Agricultural University

Abstract

Vegetation phenology (VP) is a crucial biological indicator for monitoring terrestrial ecosystems and global climate change. However, VP monitoring using traditional remote sensing vegetation indices has significant limitations in precise analysis. Furthermore, most studies have overlooked the distinction between stable and short-term VP in relation to climate change and have failed to clearly identify the seasonal variation in the impact of climatic factors on VP. This study estimates the stable VP periods in China using various remote sensing products, including Solar Induced Chlorophyll Fluorescence (SIF), Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and Leaf Area Index (LAI). Additionally, the study employs Sen’s slope, the Mann-Kendall (MK) test, and the Hurst index to reveal the spatiotemporal evolution of the Start of Season (SOS), End of Season (EOS), and Length of Growing Season (LOS). Using partial correlation analysis and random forest importance evaluation, this study accurately identifies the key climatic drivers of stable VP across different climate zones and assesses the seasonal contributions of climate to VP. The results indicate that: (1) In phenology monitoring, SIF data shows the highest correlation with ground station-observed phenology periods. (2) Over the past two decades, the spatial distribution of stable VP in China has revealed three primary spatial patterns: the Tibetan Plateau, and regions north and south of the Qinling-Huaihe Line. From arid and cold to warm and humid regions, the rate of SOS advancement gradually increases, EOS transitions from earlier to nearly unchanged, and the rate of LOS delay increases accordingly. (3) Spring climate primarily drives the advancement of SOS in stable vegetation across most climate zones, with temperature generally exerting a negative influence on SOS, while the regulation of EOS is more complex. The vapor pressure deficit plays a dual "limitation-promotion" role during summer and autumn. This study offers new insights into the climatic factors driving stable VP in China and provides a basis for vegetation adaptation to future climate change.

Keywords: Vegetation phenology, Solar-induced chlorophyll fluorescence, Seasonal climate, China, Spatiotemporal variation

Suggested Citation

Luo, Jian and Wu, Xiaobo and Gao, Yisen and Cai, Yufei and Yang, Li and Xiong, Yijun and Yang, Qingchun and Liu, Jiaxin and Li, Yijin and Deng, Zhiyong and Li, Bing, Spatiotemporal Variations in Stable Vegetation Phenology Across China Over the Past Two Decades and Their Responses to Seasonal Climate Changes. Available at SSRN: https://ssrn.com/abstract=5258632 or http://dx.doi.org/10.2139/ssrn.5258632

Jian Luo

affiliation not provided to SSRN ( email )

Xiaobo Wu (Contact Author)

affiliation not provided to SSRN ( email )

Yisen Gao

affiliation not provided to SSRN ( email )

Yufei Cai

affiliation not provided to SSRN ( email )

Li Yang

affiliation not provided to SSRN ( email )

Yijun Xiong

affiliation not provided to SSRN ( email )

Qingchun Yang

affiliation not provided to SSRN ( email )

Jiaxin Liu

affiliation not provided to SSRN ( email )

Yijin Li

affiliation not provided to SSRN ( email )

Zhiyong Deng

affiliation not provided to SSRN ( email )

Bing Li

Sichuan Agricultural University ( email )

46 Xinkang Rd, Yucheng Qu
Sichuan Sheng
China

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