1. Comparison of three methods for identification of redfish (Sebastes mentella and S. norvegicus) from the Greenland east coast
- Author
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Marie Balslev Backe, Atal Saha, Helle Torp Christensen, Torild Johansen, Frank Rigét, and Rasmus Hedeholm
- Subjects
0106 biological sciences ,Redfish ,COD ,Aquatic Science ,Species separation ,Otolith ,010603 evolutionary biology ,01 natural sciences ,Life history theory ,AGE ,Fisheries management ,medicine ,Microsatellites ,East coast ,biology ,010604 marine biology & hydrobiology ,STOCK ,Linear discriminant analysis ,biology.organism_classification ,Shape analysis ,OTOLITH SHAPE-ANALYSIS ,NORTH-ATLANTIC ,Fishery ,R package ,SIZE ,medicine.anatomical_structure ,DISCRIMINATION ,SEPARATION ,MARINUS ,Sebastes ,Shape analysis (digital geometry) - Abstract
In management of fisheries, knowledge about the species is crucial due to differences in life history traits. The first step is therefore species identification. For many species this task is straightforward, however for some species e.g. the two species of Atlantic redfish Sebastes mentella and Sebastes norvegicus, it can be difficult for an untrained eye. With the goal to separate the two species, we analysed otolith shape variation of S. mentella and S. norvegicus caught on the continental slope of East Greenland using the R package “Shape R”. Results were evaluated against genetic analysis of the same fish, and compared to results of both a visual identification of the two species and a separation based on a linear discriminant analysis on standardised values of fish length, fish weight and otolith weight. It was concluded that the objective otolith shape analysis using the Shape R package analysis achieve a reasonable classification success, however with a clear bias towards S. mentella. Classification using the otolith weight achieved a slightly higher success than the shape analysis making it a promising method. Furthermore, the method is at the same time both objective, less time consuming than the otolith shape analysis and less expensive than genetic analysis. However, the visual classification method of the whole fish had the highest success rate of the three tested methods, which despite the need for trained technicians makes it the most successful method.
- Published
- 2018