Spatio-temporal genetic tagging of a cosmopolitan planktivorous shark provides insight to gene flow, temporal variation and site-specific re-encounters
Date
2020-02-03Author
Lieber, Lilian
Hall, Graham
Hall, Jackie
Berrow, Simon
Johnston, Emmett
Gubili, Chrysoula
Sarginson, Jane
Francis, Malcolm
Duffy, Clinton
Wintner, Sabine P.
Doherty, Philip D.
Godley, Brendan J.
Hawkes, Lucy A.
Witt, Matthew J.
Henderson, Suzanne M.
De Sabata, Eleonora
Shivji, Mahmood S.
Dawson, Deborah A.
Sims, David W.
Jones, Catherine S.
Noble, Leslie R.
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Migratory movements in response to seasonal resources often influence population structure and dynamics. Yet in mobile marine predators, population genetic consequences of such repetitious behaviour remain inaccessible without comprehensive sampling strategies. Temporal genetic sampling of seasonally recurring aggregations of planktivorous basking sharks, Cetorhinus maximus, in the Northeast Atlantic (NEA) affords an opportunity to resolve individual re-encounters at key sites with population connectivity and patterns of relatedness. Genetic tagging (19 microsatellites) revealed 18% of re-sampled individuals in the NEA demonstrated inter/multi-annual site-specific re-encounters. High genetic connectivity and migration between aggregation sites indicate the Irish Sea as an important movement corridor, with a contemporary effective population estimate (Ne) of 382 (CI = 241–830). We contrast the prevailing view of high gene flow across oceanic regions with evidence of population structure within the NEA, with early-season sharks off southwest Ireland possibly representing genetically distinct migrants. Finally, we found basking sharks surfacing together in the NEA are on average more related than expected by chance, suggesting a genetic consequence of, or a potential mechanism maintaining, site-specific re-encounters. Long-term temporal genetic monitoring is paramount in determining future viability of cosmopolitan marine species, identifying genetic units for conservation management, and for understanding aggregation structure and dynamics.
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