Remotely sensed local oceanic thermal features and their influence on the distribution of hake (Merluccius hubbsi) at the Patagonian shelf edge in the SW Atlantic

We propose a new index based on sea surface temperature that can be used to locate local oceanic thermal features. The concept of relative spatial variability of local SST (SST RV), and the algorithm used to derive it, are introduced. The utility of this index is compared with that of SST gradient i...

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Detalles Bibliográficos
Autores: Wang, Jianjun, Pierce, Graham J., Sacau-Cuadrado, María del Mar, Portela, Julio, Santos, María Begoña, Cardoso, Xosé Antón, Bellido, José M.
Tipo de recurso: artículo
Fecha de publicación:2012
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/328844
Acceso en línea:http://hdl.handle.net/10261/328844
Access Level:acceso abierto
Palabra clave:Centro Oceanográfico de Vigo
Hake
Pesquerías
SST
Oceanography
Remote sensing
SW Atlantic
Descripción
Sumario:We propose a new index based on sea surface temperature that can be used to locate local oceanic thermal features. The concept of relative spatial variability of local SST (SST RV), and the algorithm used to derive it, are introduced. The utility of this index is compared with that of SST gradient in an analysis of environmental correlates of the distribution and abundance of the hake Merluccius hubbsi (Marini, 1933) on the Patagonian shelf edge between 44.5◦S and 47.0◦S and around the Falkland Islands (Islas Malvinas). The SST RV and SST gradient were calculated from AVHRR SST data. SST RV is suggested to be a more sensitive index than SST gradient for detecting local oceanic thermal features such as fronts. Local hake abundance varied between years and showed strong (albeit complex) relationships with depth and SST, as well as with parameters (SST RV and SST gradient) that indicate the presence of ocean surface thermal features. Although local hake abundance was positively correlated with both SST RV and SST gradient, the former correlation was stronger and in two out of three studied months SST RV was the better predictor of CPUE. Although CPUE tended to increase with SST RV, this relationship breaks down at the highest SST RV values, possibly because hake avoid the most turbulent waters.