Divergent leaf senescence changes in meadows, steppes, and cultivated vegetation on the Qinghai–Tibetan Plateau

Temporal changes in autumn leaf senescence dates and their drivers across meadows, steppes, and cultivated vegetation on the Qinghai–Tibetan Plateau (QTP) remain poorly understood. Using long-term ground observation data from 12 sites, we analyzed interannual change trends in leaf senescence date and quantified the influences of climatic factors (i.e., temperature, precipitation, and sunshine duration), soil moisture, and spring phenology on its shifts. Meadows showed a significant delaying trend (0.891 days/year), mainly driven by substantial increases in air temperature and precipitation during the growing season, particularly in the late season. Steppes exhibited an overall insignificant delaying trend (0.214 days/year), where the delaying effects of increased precipitation and reduced sunshine duration were partly offset by the late-season soil moisture decline. In cultivated vegetation, a slight advance in leaf senescence date (−0.108 days/year) was primarily caused by earlier spring green-up date, supplemented by increased temperature and precipitation during the growing season, which led plants to grow earlier and complete their life cycles sooner. Climatic influences were stronger in the late season for meadows but greater in the early season for steppes. Compared with meadows and steppes, spring phenology had the strongest effect on the timing of leaf senescence in cultivated vegetation. These findings advance our understanding of vegetation phenological shifts on the QTP and highlight the necessity of incorporating the notable differences across vegetation types into both phenological models and ecosystem management practices.

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Publication Details

Journal
Global Ecology and Conservation
Published
2025-11-28
DOI
https://doi.org/10.1016/j.gecco.2025.e03996
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
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article

Divergent leaf senescence changes in meadows, steppes, and cultivated vegetation on the Qinghai–Tibetan Plateau

Xuetong Zhao, Pin Wu, B. J. Li, Qiqi Li et al.
Global Ecology and Conservation
Remote Sensing in Agriculture
article

Divergent leaf senescence changes in meadows, steppes, and cultivated vegetation on the Qinghai–Tibetan Plateau

Xuetong Zhao, Pin Wu, B. J. Li, Qiqi Li, Qingling Sun, Siyu Zhu, Wei Liu, Jiang Zhu
article en

Abstract

Temporal changes in autumn leaf senescence dates and their drivers across meadows, steppes, and cultivated vegetation on the Qinghai–Tibetan Plateau (QTP) remain poorly understood. Using long-term ground observation data from 12 sites, we analyzed interannual change trends in leaf senescence date and quantified the influences of climatic factors (i.e., temperature, precipitation, and sunshine duration), soil moisture, and spring phenology on its shifts. Meadows showed a significant delaying trend (0.891 days/year), mainly driven by substantial increases in air temperature and precipitation during the growing season, particularly in the late season. Steppes exhibited an overall insignificant delaying trend (0.214 days/year), where the delaying effects of increased precipitation and reduced sunshine duration were partly offset by the late-season soil moisture decline. In cultivated vegetation, a slight advance in leaf senescence date (−0.108 days/year) was primarily caused by earlier spring green-up date, supplemented by increased temperature and precipitation during the growing season, which led plants to grow earlier and complete their life cycles sooner. Climatic influences were stronger in the late season for meadows but greater in the early season for steppes. Compared with meadows and steppes, spring phenology had the strongest effect on the timing of leaf senescence in cultivated vegetation. These findings advance our understanding of vegetation phenological shifts on the QTP and highlight the necessity of incorporating the notable differences across vegetation types into both phenological models and ecosystem management practices.

Global Ecology and ConservationVol. 64
Sun Yat-sen University (CN), Chinese Academy of Sciences (CN), State Forestry and Grassland Administration (CN), Institute of Geographic Sciences and Natural Resources Research (CN), University of Chinese Academy of Sciences (CN)
Openalex Percentile: Top 64%
Remote Sensing in Agriculture
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