Evidence map›Paper›PMID 34601687›Full record

ArticleEnvironmental science and pollution research international2022

Spatiotemporal dynamics of vegetation in China from 1981 to 2100 from the perspective of hydrothermal factor analysis.

Guangchao Li, Wei Chen, Xuepeng Zhang, Pengshuai Bi, Zhen Yang, Xinyu Shi, Zhe Wang

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Article in Environmental science and pollution research international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Measuring the Effects of Climate Change on Wheat Production: Evidence from Northern China.International journal of environmental research and public health · 2022
    Article
4 · The record

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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

7 authors.

Guangchao LiCollege of Geoscience and Surveying Engineering, China University of Mining & Technology, Beijing, 100083, China.
Wei ChenCollege of Geoscience and Surveying Engineering, China University of Mining & Technology, Beijing, 100083, China. chenw@cumtb.edu.cn.ORCID http://orcid.org/0000-0002-2585-9984
Xuepeng ZhangCollege of Geoscience and Surveying Engineering, China University of Mining & Technology, Beijing, 100083, China.
Pengshuai BiCollege of Geoscience and Surveying Engineering, China University of Mining & Technology, Beijing, 100083, China.
Zhen YangCollege of Information Science and Engineering, Henan University of Technology, Zhengzhou, 450001, China.
Xinyu ShiCollege of Geoscience and Surveying Engineering, China University of Mining & Technology, Beijing, 100083, China.
Zhe WangCollege of Geoscience and Surveying Engineering, China University of Mining & Technology, Beijing, 100083, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The increased growth of vegetation has the potential to slow global climate warming. Therefore, analyzing and predicting the response assessment of Chinese vegetation to climate change is of great significance to studies of global warming. In this paper, we examine the spatiotemporal dynamics of vegetation leaf area index (LAI) values in China from 1981 to 2017 and their correlations with meteorological (hydrothermal) factors based on trend analysis and correlation analysis. We further construct an LAI prediction model based on hydrothermal conditions. The climate data obtained under different scenarios in the CMIP5 and CMIP6 climate models were used to predict the dynamic change trend of vegetation LAI from 2021 to 2100. The results show that most areas of China (72.82%) showed an improving trend in vegetation LAI from 1981 to 2017, during which the annual average LAI value increased at a rate of 0.0029 year

Indexed as

Climate ChangeEcosystemChinaFactor Analysis, StatisticalPlantsSpatio-Temporal AnalysisTemperatureClimate changeCMIP5CMIP6PredictionVegetation dynamics

Identifiers

PMID34601687

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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.