Evidence map›Paper›PMID 27661983›Full record

ArticlePloS one

Predicting the Potential Distribution of Polygala tenuifolia Willd. under Climate Change in China.

Hongjun Jiang, Ting Liu, Lin Li, Yao Zhao, Lin Pei, Jiancheng Zhao

Open access · goldAbstract read
In one paragraph

Article in PloS one. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
5.2field-weighted citation impact, top 5% of its field
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

21 citing papers in PubMed, 52 citations in OpenAlex.

  1. Article
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  14. Review
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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

6 authors at 1 institution in 1 country.

Hongjun JiangCollege of Life Science, Hebei Normal University, Shijiazhuang, Hebei, China.
Ting LiuCollege of Life Science, Hebei Normal University, Shijiazhuang, Hebei, China.
Lin LiCollege of Life Science, Hebei Normal University, Shijiazhuang, Hebei, China.
Yao ZhaoCollege of Life Science, Hebei Normal University, Shijiazhuang, Hebei, China.
Lin PeiHebei Province Academy of Chinese Medicine Sciences, Shijiazhuang, Hebei, China.
Jiancheng ZhaoCollege of Life Science, Hebei Normal University, Shijiazhuang, Hebei, China.
Hebei Normal University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Global warming has created opportunities and challenges for the survival and development of species. Determining how climate change may impact multiple ecosystem levels and lead to various species adaptations is necessary for both biodiversity conservation and sustainable biological resource utilization. In this study, we employed Maxent to predict changes in the habitat range and altitude of Polygala tenuifolia Willd. under current and future climate scenarios in China. Four representative concentration pathways (RCP2.6, RCP4.5, RCP6.0, and RCP8.5) were modeled for two time periods (2050 and 2070). The model inputs included 732 presence points and nine sets of environmental variables under the current conditions and the four RCPs in 2050 and 2070. The area under the receiver-operating characteristic (ROC) curve (AUC) was used to evaluate model performance. All of the AUCs were greater than 0.80, thereby placing these models in the "very good" category. Using a jackknife analysis, the precipitation in the warmest quarter, annual mean temperature, and altitude were found to be the top three variables that affect the range of P. tenuifolia. Additionally, we found that the predicted highly suitable habitat was in reasonable agreement with its actual distribution. Furthermore, the highly suitable habitat area was slowly reduced over time.

Identifiers

PMID27661983
PMCPMC5035090
OpenAlexW2523250961

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.