Evidence map›Paper›PMID 40612617›Full record

ArticleFrontiers in plant science2025

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

Zhang Shikang, Zhang Wei, Li Xiaotong

Abstract read
In one paragraph

Article in Frontiers in plant science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Zhang ShikangCollege of Resources and Environment, Anhui Science and Technology University, Fengyang, China.
Zhang WeiCollege of Architecture, Anhui Science and Technology University, Bengbu, China.
Li XiaotongCollege of Management, Anhui Science and Technology University, Bengbu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

climate changegrowing seasonmiddle and lower reaches of the Yangtze Riverspatial and temporal analysisvegetation phenology

Identifiers

PMID40612617
PMCPMC12222279

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.