Evidence map›Paper›PMID 31024763›Full record

ArticlePeerJ2019

Simulating the effects of climate change across the geographical distribution of two medicinal plants in the genus

Junjun Li, Jie Wu, Kezhong Peng, Gang Fan, Haiqing Yu, Wenguo Wang, Yang He

Abstract read
In one paragraph

Article in PeerJ, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

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  12. The efficacy of machine learning algorithm for raw drug authentication inPhysiology and molecular biology of plants : an international journal of functional plant biology · 2021
    Article
  13. Review
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

7 authors.

Junjun LiCollege of Medical Technology, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Jie WuGanzi Prefecture Forest Research Institute, Kangding, China.
Kezhong PengGanzi Prefecture Forest Research Institute, Kangding, China.
Gang FanCollege of Medical Technology, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Haiqing YuGanzi Prefecture Forest Research Institute, Kangding, China.
Wenguo WangBiogas Institute of Ministry of Agriculture, Chengdu, China.
Yang HeCollege of Medical Technology, Chengdu University of Traditional Chinese Medicine, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe medicinal plants of

methodsThe Maxent model was used to predict the potential geographical distributions of the genus

resultsThe results show that the potential distribution of the two species will increase, thus more suitable habitats will be present in China. The suitable habitat for

Indexed as

Climate changeMaxentNardostachysNardostachys chinensisNardostachys jatamansiPotential distribution

Identifiers

PMID31024763
PMCPMC6474333

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.