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

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.

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Publication Details

Journal
Scientific Data
Published
2025-10-13
DOI
https://doi.org/10.1038/s41597-025-05536-1
Primary Topic
Identification and Quantification in Food
Type
article
Field-Weighted Citation Impact
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article

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

Janet A. Nye, Brian S. Brookes, Rahmat Ali Khan, Mark A. Rubin et al.
Scientific Data
Identification and Quantification in Food
article

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

Janet A. Nye, Brian S. Brookes, Rahmat Ali Khan, Mark A. Rubin, Sarah J. Weisberg, Sally Hayes, Michael King, Hannah Karkout, Sky L. Hadjiargyrou, Ailyn A. Vasquez Taveras
article en

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.

Scientific DataVol. 12(1)
University of North Carolina at Chapel Hill (US), City College of New York (US), Gettysburg College (US), Hunter College (US), Stony Brook University (US)
Openalex Percentile: Top 74%
Identification and Quantification in Food
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