Literature DB >> 18410069

Integrating genetic and parasitological approaches in the frame of multidisciplinary fish stock analysis.

R Cimmaruta1, S Mattiucci, G Nascetti.   

Abstract

To assess fish stocks boundaries and state, the tools of population genetics have been widely used, contributing to the evaluation of relevant parameters such as the identification of stock boundaries, the assessment of gene flow and the estimation of effective population size. Also, increasing evidences show that the monitoring of the genetic diversity level is a reliable method to check the status of fish stocks. However, genetics cannot answer all the questions. For example, in high gene flow species the genetic approach could have not enough resolution to identify stock limits, while the use of parasites as biological tags could provide insights into stock structure. Even better, the so-called holistic approach, applying simultaneously a wide range of complementary techniques, is the only one considered able to provide a reliable and complete picture of fish stocks and to address a sustainable exploitation of marine resources. The work will present some examples from multidisciplinary studies concerning commercially relevant species with different biological features: the demersal European hake (Merluccius merluccius), the small pelagic horse mackerel (Trachurus trachurus) and the large pelagic swordfish (Xiphias gladius). In all these case studies merging genetic, parasitological and environmental data helped to reveal the real patterns of stocks structure.

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Year:  2007        PMID: 18410069

Source DB:  PubMed          Journal:  Parassitologia        ISSN: 0048-2951


  1 in total

1.  Metazoan parasite infection in the swordfish, Xiphias gladius, from the Mediterranean Sea and comparison with Atlantic populations: implications for its stock characterization.

Authors:  Simonetta Mattiucci; Alexandra Garcia; Paolo Cipriani; Miguel Neves Santos; Giuseppe Nascetti; Roberta Cimmaruta
Journal:  Parasite       Date:  2014-07-25       Impact factor: 3.000

  1 in total

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