Evidence map›Paper›PMID 42503029›Full record

ArticleMolecular ecology2026

Distance-Limited Larval Replenishment in the Deep-Sea Mussel Gigantidas platifrons Challenges Connectivity-Based Conservation Planning.

Zhaoshan Zhong, Li Zhou, Hao Chen, Chaofeng Cai, Yujie Yan, Ziyun Ye, Mengna Li, Jiacheng Wang, Huan Zhang, Hao Wang and 7 more

Abstract read
In one paragraph

Article in Molecular ecology, 2026. 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

17 authors.

Zhaoshan ZhongChinese Academy of Sciences, Institute of Oceanology, Qingdao, China.ORCID https://orcid.org/0000-0003-1643-5407
Li ZhouChinese Academy of Sciences, Institute of Oceanology, Qingdao, China.
Hao ChenChinese Academy of Sciences, Institute of Oceanology, Qingdao, China.ORCID https://orcid.org/0000-0001-6697-0809
Chaofeng CaiSouthern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou, China.
Yujie YanChinese Academy of Sciences, Institute of Oceanology, Qingdao, China.
Ziyun YeChinese Academy of Sciences, Institute of Oceanology, Qingdao, China.
Mengna LiNational Deep Sea Center, Qingdao, China.
Jiacheng WangChinese Academy of Sciences, Institute of Oceanology, Qingdao, China.
Huan ZhangChinese Academy of Sciences, Institute of Oceanology, Qingdao, China.
Hao WangChinese Academy of Sciences, Institute of Oceanology, Qingdao, China.ORCID https://orcid.org/0000-0003-3272-2350
Lei CaoChinese Academy of Sciences, Institute of Oceanology, Qingdao, China.
Yan SunChinese Academy of Sciences, Institute of Oceanology, Qingdao, China.ORCID https://orcid.org/0000-0001-7911-0963
Chao LianChinese Academy of Sciences, Institute of Oceanology, Qingdao, China.
Yang GuoChinese Academy of Sciences, Institute of Oceanology, Qingdao, China.ORCID https://orcid.org/0000-0001-7837-7279
Jingchun FengSouthern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou, China.ORCID https://orcid.org/0000-0002-6819-8645
Minxiao WangChinese Academy of Sciences, Institute of Oceanology, Qingdao, China.ORCID https://orcid.org/0000-0002-6567-3295
Chaolun LiUniversity of Chinese Academy of Sciences, Beijing, China.

Funding

Marine S&T Fund of Shandong Province for Pilot National Laboratory for Marine Science and Technology (Qingdao) 2022QNLM030004National Natural Science Foundation of China 42221005National Natural Science Foundation of China 42476101National Natural Science Foundation of China U2544219Science & Technology Fundamental Resources Investigation Program 2024FY101000Science & Technology Fundamental Resources Investigation Program 2024YFC2816000Shandong Provincial Key Research and Development Program (Competitive Innovation Platform) 2026CXPT225Shandong Provincial Natural Science Foundation ZR2024MD026Shandong Provincial Natural Science Foundation ZR2025MS657
6 · The paper itself

Abstract

Deep-sea chemosynthetic ecosystems, critical for global methane and sulphur cycling, require accurate connectivity data for effective conservation planning amid increasing anthropogenic threats. Because hosts and their environmentally acquired symbionts operate at fundamentally different spatial and temporal scales, we analysed each at the scale appropriate to its biology: host Gigantidas platifrons population structure was assessed both regionally (across 11 Northwest Pacific chemosynthetic sites) and within a single cold seep (Site F, South China Sea) across six shell-length cohorts spanning < 1 year to > 100 years, while the methanotrophic endosymbiont Methyloprofundus sp. was profiled across the same cohorts at Site F to test whether its genetic composition tracks host age or is environmentally homogenized. We found that although the overall host population at Site F is panmictic (ADMIXTURE K = 1; max F

Indexed as

BivalviaConservation of Natural ResourcesGenetics, PopulationAnimalsEcosystemLarvaSymbiosischemosynthetic ecosystems protectiondeep‐sea musselsholobiont temporal dynamicspopulation genomicssymbiont recruitment

Identifiers

PMID42503029
PMCPMC13401863

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Registered trials

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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.