The intrinsic discrepancies existing between the definition of fish stock units and the structure of biological populations emphasize the need for integrating genetic data of population structure into fishery management strategies in the perspective of improving the assessment and management of valuable target species. Population samples of Pagellus bogaraveo (Brunnich; 1768), a commercially valuable deep-water fish ineffectively exploited in the past decade, were considered in the present work. A total of 320 individuals were collected from different fishing grounds in the Atlantic Ocean and the Mediterranean Sea during surveys from the EU-funded MEDITS project and with traditional fishery along the European and African coasts. Samples were analyzed through the use of 21 microsatellite markers to estimate both genetic variability and differentiation. In general, no signal of population differentiation was detected since low levels of variation between groups were observed across multiple approaches. As a matter of fact, AMOVA revealed the highest percentage of total variation ‘within populations”. Moreover, no correlation with geographical distance was found using FST estimates. Analyses conducted using individual-based methods such as Bayesian clustering (STRUCTURE) and geometric approach (DAPC) agreed in showing a lack of structured population along the study areas. In all, the high homogeneity revealed using the molecular markers assessed suggested the absence of physical barriers between the geographical areas considered in this study. Hence, high connectivity spreads across the whole Mediterranean Sea and especially between the Atlantic and Mediterranean areas.

Spiga Martina, F.A. (2022). Limitless connectivity: panmixia of Pagellus bogaraveo (Brünnich, 1768) over large distances.

Limitless connectivity: panmixia of Pagellus bogaraveo (Brünnich, 1768) over large distances

Spiga Martina
Primo
;
Ferrari Alice;Cariani Alessia
Ultimo
2022

Abstract

The intrinsic discrepancies existing between the definition of fish stock units and the structure of biological populations emphasize the need for integrating genetic data of population structure into fishery management strategies in the perspective of improving the assessment and management of valuable target species. Population samples of Pagellus bogaraveo (Brunnich; 1768), a commercially valuable deep-water fish ineffectively exploited in the past decade, were considered in the present work. A total of 320 individuals were collected from different fishing grounds in the Atlantic Ocean and the Mediterranean Sea during surveys from the EU-funded MEDITS project and with traditional fishery along the European and African coasts. Samples were analyzed through the use of 21 microsatellite markers to estimate both genetic variability and differentiation. In general, no signal of population differentiation was detected since low levels of variation between groups were observed across multiple approaches. As a matter of fact, AMOVA revealed the highest percentage of total variation ‘within populations”. Moreover, no correlation with geographical distance was found using FST estimates. Analyses conducted using individual-based methods such as Bayesian clustering (STRUCTURE) and geometric approach (DAPC) agreed in showing a lack of structured population along the study areas. In all, the high homogeneity revealed using the molecular markers assessed suggested the absence of physical barriers between the geographical areas considered in this study. Hence, high connectivity spreads across the whole Mediterranean Sea and especially between the Atlantic and Mediterranean areas.
2022
Biodiversity Genomics 2022
17
17
Spiga Martina, F.A. (2022). Limitless connectivity: panmixia of Pagellus bogaraveo (Brünnich, 1768) over large distances.
Spiga Martina, Ferrari Alice, Mokhtar-Jamaï Kenza, Johnstone Carolina, Pérez Rodríguez Montse, Hidalgo Manuel, Hernandez Pilar, Cariani Alessia...espandi
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/906406
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