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

J. Wang, G. J. Pierce, M. Sacau, J. Portela, M. B. Santos, X. Cardoso, J. M. Bellido

Research output: Contribution to journalArticle

13 Citations (Scopus)

Abstract

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 degrees S and 47.0 degrees 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. (c) 2006 Elsevier B.V. All rights reserved.

Original languageEnglish
Pages (from-to)133-144
Number of pages12
JournalFisheries Research
Volume83
Issue number2-3
DOIs
Publication statusPublished - Feb 2007

Keywords

  • hake
  • SST
  • oceanography
  • remote sensing
  • SW Atlantic
  • upwelling system
  • Illex-Argentinus
  • English-Channel
  • South Atlantic
  • oceanographic variabiity
  • environmental-influences
  • interannual variability
  • mesoscale oceanography
  • Ommastrephid-squid
  • satellite imagery

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