Evidence map›Paper›PMID 41883998›Full record

ArticleiScience2026

Response of vegetation phenology to hydrothermal variables on the QTP using EVI and MSAVI.

Zhijian Zhao, Hui Lin, Li Wang, Min Huang, Lei Wu, Linling Tang, Tao Yang, Xin Xiao

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in iScience, 2026. 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

8 authors.

Zhijian ZhaoKey Laboratory of Poyang Lake Wetland and Watershed Research Ministry of Education/Postdoctoral Research Station of Chemistry, Jiangxi Normal University, Nanchang 330022, China.
Hui LinKey Laboratory of Poyang Lake Wetland and Watershed Research Ministry of Education/Postdoctoral Research Station of Chemistry, Jiangxi Normal University, Nanchang 330022, China.
Li WangKey Laboratory of Poyang Lake Wetland and Watershed Research Ministry of Education/Postdoctoral Research Station of Chemistry, Jiangxi Normal University, Nanchang 330022, China.
Min HuangKey Laboratory of Poyang Lake Wetland and Watershed Research Ministry of Education/Postdoctoral Research Station of Chemistry, Jiangxi Normal University, Nanchang 330022, China.
Lei WuCollege of Mathematics and Computer, Xinyu University, Xinyu 338004, China.
Linling TangKey Laboratory of Poyang Lake Wetland and Watershed Research Ministry of Education/Postdoctoral Research Station of Chemistry, Jiangxi Normal University, Nanchang 330022, China.
Tao YangKey Laboratory of Poyang Lake Wetland and Watershed Research Ministry of Education/Postdoctoral Research Station of Chemistry, Jiangxi Normal University, Nanchang 330022, China.
Xin XiaoKey Laboratory of Poyang Lake Wetland and Watershed Research Ministry of Education/Postdoctoral Research Station of Chemistry, Jiangxi Normal University, Nanchang 330022, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Vegetation phenology is a key indicator of how the Qinghai-Tibet plateau (QTP) ecosystem responds to changes in the hydrothermal environment. However, sparse QTP meteorological stations make observed traditional hydrothermal variables (air temperature and precipitation) insufficient for research needs. Building upon analyses of vegetation phenology using enhanced vegetation index and modified soil-adjusted vegetation index, this study adopts alternative hydrothermal variables (land surface temperature [LST], effective moisture and surface albedo). Geodetector and partial correlation analysis were employed to reveal the response mechanisms between vegetation phenology and hydrothermal variables. Results indicate that the length of the growing season (LOS) is primarily driven by the end of the growing season (EOS). From 2001 to 2020, EOS showed a significant positive correlation with LST. Compared to traditional variables, these variables demonstrated stronger explanatory power for vegetation changes. Hurst index analysis revealed vegetation recovery trends. This study provides scientific support for ecological management on the QTP.

Indexed as

BotanyEarth sciencesEnvironmental science

Identifiers

PMID41883998
PMCPMC13010112

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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.