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Effect of oceanographic barriers and overfishing on the population genetic structure of the European spiny lobster (Palinurus elephas)
Palero, F.; Abelló, P.; MacPherson, E.; Beaumont, M.; Pascual, M. (2011). Effect of oceanographic barriers and overfishing on the population genetic structure of the European spiny lobster (Palinurus elephas). Biol. J. Linn. Soc. 104(2): 407-418. dx.doi.org/10.1111/j.1095-8312.2011.01728.x
In: Biological Journal of the Linnean Society. Academic Press: London. ISSN 0024-4066, more
Peer reviewed article

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Keyword
    Marine
Author keywords
    Bayesian; coalescence; DAPC; diversity; long-lived species; microsatellites; phyllosoma; phylogeography

Authors  Top 
  • Palero, F.
  • Abelló, P.
  • MacPherson, E.
  • Beaumont, M.
  • Pascual, M.

Abstract
    Defining population structure and genetic diversity levels is of the utmost importance for developing efficient conservation strategies. Overfishing has caused mean annual catches of the European spiny lobster (Palinurus elephas) to decrease alarmingly along its distribution area. In this context, there is a need for comprehensive studies aiming to evaluate the genetic health of the exploited populations. The present study is based on a set of ten nuclear markers amplified in 331 individuals from ten different localities covering most of P. elephas distribution area. Samples from Atlantic and Mediterranean basins showed small but significant differences, indicating that P. elephas populations do not behave as a single panmictic unit but form two partially-overlapping groups. Despite intense overfishing, our dataset did not recover a recent bottleneck signal, and instead showed a large and stable historical effective size. This result could be accounted for by specific life-history traits (reproduction and longevity) and the limitations of molecular markers in covering recent timescales for nontemporal samples. The findings of the present study emphasize the need to integrate information on effective population sizes and life-history parameters when evaluating population connectivity levels from genetic data

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