Spatial and temporal characteristics of vegetation phenology in the middle and lower reaches of the Yangtze River and its response to climate

This study investigates the response mechanism of vegetation phenology to climate change in the middle and lower reaches of the Yangtze River from 2001 to 2022, aiming to reveal the spatial and temporal evolution patterns of vegetation SOS, EOS, and LOS and their driving factors, and to provide a scientific basis for regional ecological management. Based on the EVI dataset, climate parameters were extracted by S-G filtering and dynamic thresholding method and combined with one-way linear regression, stability analysis, and partial correlation analysis to assess the vegetation climate changes and their responses to air temperature, precipitation, sunshine hours, and surface temperature. The results showed that: (1) SOS advanced overall (0.29 d/a), EOS delayed (0.26 d/a), and LOS prolonged (0.56 d/a). (2) Significant trends of SOS advance and EOS postponement were observed in coniferous forests, agricultural fields, and natural vegetation, and EOS advance was significant in broadleaf forests. (3) In the future, SOS and EOS will continue to advance, and LOS of cropland will continue to extend. (4) Air temperature, precipitation, and sunshine hours have an advancing effect on SOS, surface temperature has a postponing effect on EOS, and precipitation and surface temperature have an extending effect on LOS. Vegetation climate change is affected by the complex interaction of climate factors, and the results of the study reveal its spatial and temporal evolution patterns and response mechanisms to climate change, providing an important reference for regional ecological assessment and management.

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Publication Details

Journal
Frontiers in Plant Science
Published
2025-06-19
DOI
https://doi.org/10.3389/fpls.2025.1589908
Citations
2
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
3.43
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article

Spatial and temporal characteristics of vegetation phenology in the middle and lower reaches of the Yangtze River and its response to climate

Shikang Zhang, Wei Zhang, Xiaotong Li
2 citations
Frontiers in Plant Science
Remote Sensing in Agriculture
3.43
article

Spatial and temporal characteristics of vegetation phenology in the middle and lower reaches of the Yangtze River and its response to climate

Shikang Zhang, Wei Zhang, Xiaotong Li
article en
2 citations

Abstract

This study investigates the response mechanism of vegetation phenology to climate change in the middle and lower reaches of the Yangtze River from 2001 to 2022, aiming to reveal the spatial and temporal evolution patterns of vegetation SOS, EOS, and LOS and their driving factors, and to provide a scientific basis for regional ecological management. Based on the EVI dataset, climate parameters were extracted by S-G filtering and dynamic thresholding method and combined with one-way linear regression, stability analysis, and partial correlation analysis to assess the vegetation climate changes and their responses to air temperature, precipitation, sunshine hours, and surface temperature. The results showed that: (1) SOS advanced overall (0.29 d/a), EOS delayed (0.26 d/a), and LOS prolonged (0.56 d/a). (2) Significant trends of SOS advance and EOS postponement were observed in coniferous forests, agricultural fields, and natural vegetation, and EOS advance was significant in broadleaf forests. (3) In the future, SOS and EOS will continue to advance, and LOS of cropland will continue to extend. (4) Air temperature, precipitation, and sunshine hours have an advancing effect on SOS, surface temperature has a postponing effect on EOS, and precipitation and surface temperature have an extending effect on LOS. Vegetation climate change is affected by the complex interaction of climate factors, and the results of the study reveal its spatial and temporal evolution patterns and response mechanisms to climate change, providing an important reference for regional ecological assessment and management.

Frontiers in Plant ScienceVol. 16
Anhui University of Science and Technology (CN), Anhui Science and Technology University (CN)
Climate action
Openalex Percentile: Top 9%
Remote Sensing in Agriculture
3.43
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