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Discrimination of the phenotypic sardine <i>Sardina pilchardus</i> stocks off the Moroccan Atlantic coast using a morphometric analysis


A. Mounir
A. Ewague
M. Znari
H. Elmghazli

Abstract

Morphometric variation can be very useful for discriminating ‘phenotypic stocks’ as groups with similar life-history traits. Such groups are of great importance for accurate population-dynamics modelling for purposes of fishery stock assessment and management, independent of their genetic differences or similarities. This study is a contribution to the stock identification of the sardine Sardina pilchardus off the Moroccan Atlantic coast. The objectives were to (i) assess whether specimens from stocks defined by the FAO correspond to different morphotypes, and (ii) compare the obtained results with those recently published on the genetic variability of the studied populations. Morphometric analyses, using truss variables and landmarks data from sardine sampled from four widely spaced ports of landing along the Moroccan Atlantic coast (from north to south: Larache, Safi, Tantan and Dakhla), were carried out using multivariate and geometric approaches. Principal components analysis of truss variables and cluster analysis of the average shape of the sardine revealed the existence of three distinct morphotypes: ‘Larache,’ ‘Safi–Tantan’ and ‘Dakhla.’ These correspond well with the FAO’s stock subdivision. The morphometric variation might be related to the mesoscale hydrodynamic characteristics of the study area. However, these morphometric results do not fully accord with recently published data on genetic variability of the species. Those data indicated the genetic singularity of the Safi population, which could have led to the historical collapse of that sardine stock in the 1970s. Additional work is needed to validate the obtained results by taking into account seasonal variations and transitional areas between stocks.

Keywords: European pilchard, geometric approach, morphometrics, multivariate analysis, small pelagics, stock identification


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eISSN: 1814-2338
print ISSN: 1814-232X