Evidence map›Paper›PMID 41083475›Full record

ArticleScientific data2025

Novel species-level database of fish embryos and larvae in New York offshore waters, 2021-2023.

Sky L Hadjiargyrou, Molly Rubin, Hannah Karkout, Samara Hayes, Ailyn A Vasquez Taveras, Brianna J Brookes, Mariah K King, Raisa Khan, Janet A Nye, Sarah J Weisberg

Abstract readDataset
In one paragraph

Article in Scientific data, 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

10 authors.

Sky L HadjiargyrouSchool of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, NY, 11794, USA.
Molly RubinSchool of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, NY, 11794, USA.
Hannah KarkoutSchool of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, NY, 11794, USA.
Samara HayesSchool of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, NY, 11794, USA.
Ailyn A Vasquez TaverasSchool of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, NY, 11794, USA.
Brianna J BrookesThe City College of New York, New York, NY, 10031, USA.
Mariah K KingGettysburg College, Gettysburg, PA, 17325, USA.
Raisa KhanHunter College, New York, NY, 10065, USA.
Janet A NyeDepartment of Earth Marine and Environmental Sciences, Institute of Marine Sciences, University of North Carolina Chapel Hill, Morehead City, NC, 28557, USA.
Sarah J WeisbergSchool of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, NY, 11794, USA. sarah.weisberg@ices.dk.ORCID 0000-0003-4271-9534

Funding

New York State Department of Environmental Conservation (DEC) MOU #900286-0New York State Department of Environmental Conservation (DEC) MOU #900286-02
6 · The paper itself

Abstract

Understanding the population dynamics of fish is vital to maintaining healthy ocean ecosystems and the human communities that depend on them. However, most fish population models lack crucial information about early life stages. Even when fish embryos and larvae (collectively, ichthyoplankton) are sampled, similar morphological features make species-level visual identification difficult, especially for embryos. So, although the Northeast US continental shelf is well-studied, existing ichthyoplankton datasets generally lack species-level information on embryos. Unlike visual methods, DNA barcoding can readily discriminate between morphologically indistinguishable specimens. Thus, our dataset of 2,294 DNA barcoded fish embryos and larvae, collected near New York (USA), contributes valuable insight into local ichthyoplankton assemblages. This dataset contains 50 unique species. Most have previously been documented in our region, but one was novel: we identified an embryo of Bathyanthias mexicanus, a species not known to inhabit or spawn in the sampled area. More broadly, this dataset can be used to address questions about fish habitat across life stages and to help ensure that local fisheries are sustainably managed.

Indexed as

FishesAnimalsDNA Barcoding, TaxonomicEcosystemEmbryo, NonmammalianLarvaNew York

Identifiers

PMID41083475
PMCPMC12518518

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.