Understanding the Dynamics of Ancillary Pelagic Species in the Adriatic Sea
The status of fishery resources in the Mediterranean Sea is critical: most of the fish and shellfish stocks are in overexploitation and only half of them are routinely assessed. This manuscript presents the use of Surplus Production Models (SPMs) as a valid option to increase the number of assessed...
Guardado en:
| Autores principales: | , , , , , , , , , , |
|---|---|
| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Frontiers Media S.A.
2021
|
| Materias: | |
| Acceso en línea: | https://doaj.org/article/433f561a91c14aa5829acd6f6d886250 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| Sumario: | The status of fishery resources in the Mediterranean Sea is critical: most of the fish and shellfish stocks are in overexploitation and only half of them are routinely assessed. This manuscript presents the use of Surplus Production Models (SPMs) as a valid option to increase the number of assessed stocks, with specific attention to the Adriatic basin. Particularly, the stock of European sprat (Sprattus sprattus), Mediterranean horse mackerel (Trachurus mediterraneus), and Atlantic horse mackerel (Trachurus trachurus) living in the Adriatic Sea have been evaluated comparing three SPMs: Catch Maximum Sustainable Yields (CMSY), Stochastic surplus Production model in Continuous Time (SPiCT), and Abundance Maximum Sustainable Yields (AMSY). The different approaches present some variations; however, they generally agree on describing all the stocks close to the reference values for both biomass and fishing mortality in the most recent year. For the European sprat, AMSY results are the most robust model for this species’ survey data allow depicting a clearer picture of the history of this stock. Indeed, for the horse mackerel species, CMSY or SPiCT results are the preferred models, since for these species landings are not negligible. Notwithstanding, age-structured assessments remain the most powerful approach for evaluating the status of resources, but SPMs have proved to be a powerful tool in a data-limited context. |
|---|