bioRxivEvolutionary Biology
Evidence of stock connectivity, hybridization and misidentification in white anglerfish support the need for adopting a genetics-informed fisheries management approach
I. Aguirre-Sarabia, N. Diaz-Arce, I. Pereda-Agirre, I. Mendibil, A. Urtizberea, H. D. Gerritsen, F. Burns, I. Holmes, J. Landa, I. Coscia, I. Quincoces, M. Santurtun, A. Zanzi, J. T. Martinsohn, N. Rodriguez-Ezpeleta
Abstract
Understanding population connectivity within a species as well as potential interactions with its close relatives is crucial to define management units and to derive efficient management actions. However, although genetics can reveal mismatches between biological and management units and other relevant but hidden information such as species misidentification or hybridization, the uptake of genetic methods by the fisheries management process is far from having been consolidated. Here, we have assessed the power of genetics to better understand the population connectivity of white angelfish (Lophius piscatorius) and its interaction with its sister species, the black anglerfish (L. budegassa). Our analyses, based on thousands of genome-wide single nucleotide polymorphisms, show three findings that are crucial for white anglerfish management. We found i) that white anglerfish is likely composed of a single panmictic population throughout the Northeast Atlantic, challenging the three-stock based management, ii) that a fraction of specimens classified as white anglerfish using morphological characteristics are genetically identified as black anglerfish (L. budegassa) and iii) that the two Lophius species naturally hybridize leading to a population of hybrids of up to 20% in certain areas. Our results set the basics for a genetics-informed white anglerfish assessment framework that accounts for stock connectivity, revises and establishes new diagnostic characters for Lophius species identification and evaluates the effect of hybrids in the current and future assessments of the white anglerfish. Furthermore, our study contributes to provide additional evidence of the potentially negative consequences of ignoring genetic data for assessing fisheries resources.
- organism: multiple species
- assay: DNA methylation
- research focus: host-pathogen & immune response
- approach: statistical model
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