Evidence map›Paper›PMID 41312409›Full record

ArticleForestry research2025

Genomic vulnerability assessment reveals the potential benefits of adaptive introgression by mitigating the maladaptive risk of admixed populations.

Wen-Hao Li, Han-Yang Lin, Chen Chen, Chen-Feng Lin, Xing-Xing Shen, Yun-Peng Zhao

Abstract read
In one paragraph

Article in Forestry research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Wen-Hao Li *State Key Laboratory for Vegetation Structure, Function and Construction (VegLab), MOE Key Laboratory of Biosystem Homeostasis and Protection, College of Life Sciences, Zhejiang University, Hangzhou 310058, China.ORCID 0000-0002-2550-1069
Han-Yang Lin *State Key Laboratory for Vegetation Structure, Function and Construction (VegLab), MOE Key Laboratory of Biosystem Homeostasis and Protection, College of Life Sciences, Zhejiang University, Hangzhou 310058, China.ORCID 0000-0002-5259-060X
Chen ChenState Key Laboratory for Vegetation Structure, Function and Construction (VegLab), MOE Key Laboratory of Biosystem Homeostasis and Protection, College of Life Sciences, Zhejiang University, Hangzhou 310058, China.ORCID 0009-0006-4590-7775
Chen-Feng LinState Key Laboratory for Vegetation Structure, Function and Construction (VegLab), MOE Key Laboratory of Biosystem Homeostasis and Protection, College of Life Sciences, Zhejiang University, Hangzhou 310058, China.ORCID 0000-0002-8997-2644
Xing-Xing ShenCollege of Agriculture and Biotechnology, Zhejiang University, Hangzhou 310058, China.ORCID 0000-0001-5765-1419
Yun-Peng ZhaoState Key Laboratory for Vegetation Structure, Function and Construction (VegLab), MOE Key Laboratory of Biosystem Homeostasis and Protection, College of Life Sciences, Zhejiang University, Hangzhou 310058, China.ORCID 0000-0003-4393-8472

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As climate change accelerates, plant species largely rely on genetic variation to adapt and survive when they fail to track their ecological niches through range shifts. Predicted genomic vulnerability is able to identify populations lacking the necessary genetic variation for climate change adaptation. However, the role of introgression in genomic vulnerability remains poorly explored. Here, we used the dove tree (

Indexed as

Climate changeDavidia involucrataGenomic offsetGradient forestIntraspecific introgression

Identifiers

PMID41312409
PMCPMC12648016

What OpenQuestion holds

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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.