Integrating molecular identification of pelagic eggs with geostatistical mapping to improve the delineation of North Sea fish spawning grounds
|Author(s)||Lelievre Stephanie2, Jerome Marc1, Maes Gregory E.3, Vaz Sandrine2, Calaivany Sachidhanandam1, Verrez-Bagnis Veronique1|
|Affiliation(s)||1 : IFREMER, Biotechnol & Marine Resources Unit, Nantes, France.
2 : IFREMER, Fisheries Resources Lab, Boulogne Sur Mer, France.
3 : Katholieke Univ Leuven, Fish Genet Grp, Lab Biodivers & Evolutionary Genom, Louvain, Belgium.
|Source||Marine Ecology-progress Series (0171-8630) (Inter-research), 2012 , Vol. 445 , P. 161-172|
|WOS© Times Cited||5|
|Keyword(s)||Fish eggs, PCR-RFLP, 16S rRNA, Geostatistical analyses, Distribution, Spawning grounds|
|Abstract||Maps of the spawning grounds of commercially important fishes are necessary when assessing the level of connectivity between life stages of fishes and for identifying ecologically valuable marine areas. A first step toward mapping the spawning grounds is a reliable and rapid species identification of pelagic fish eggs to assess the spatio-temporal distribution of spawning aggregations. As many species have similar egg sizes and morphology, the molecular validation of visually identified eggs is often essential for the use of such data in fisheries management. In the present study, we developed a rapid 16S rRNA PCR-restriction fragment length polymorphism (RFLP) assay to distinguish between formalin-fixed fish eggs of dab Limanda limanda, flounder Platichthys flesus and pout Trisopterus spp., which were collected during the 2008 International Bottom Trawl Survey in the Eastern English Channel and southern North Sea. A comparison of the rapid 16S rRNA PCR-RFLP method with initial visual identification revealed 93% of correct identifications for dab, 90% for pout, but only 64% for flounder, representing an overall error rate of 17%. Visual misidentification occurred mainly between dab and flounder and between flounder and pout. Egg abundance and the relative proportions of each species were subsequently analysed geostatistically. Molecular identifications were incorporated to obtain corrected interpolated distribution maps, taking into account the results from molecular identifications as a correction factor. This highlighted the distinct spawning grounds for the 3 studied taxa and facilitated the identification of regions of high conservation value for these species.|