In this study, environmental and fishery data are used to examine links between the oceanography of the Southwest Atlantic, and the distribution and abundance of the ommastrephid squid <I>Illex argentinus</I>. Spatial and temporal patterns in squid distribution and abundance are examined using Geographic Information Systems (GIS), remotely-sensed satellite-derived environmental data and statistical techniques. Inter-annual variability in the recruitment of <I>I. argentinus</I> was shown to be influenced by both large and mesoscale oceanographic processes operating during the early life history stages at the Brazil-Falkland (Malvinas) confluence. During the fishery period, in Falkland Islands (Malvinas) waters, variability in large scale sea surface temperature (SST) was not found to influence the abundance of <I>I. argentinus</I>, but the distribution of squid within the fishery was found to be associated with mesoscale oceanographic features occurring in this region. Indices describing oceanographic variability during the early life-stages were found to be of value in predicting the recruitment of squid to the fishery in Falkland Islands (Malvinas) waters. Teleconnections were shown to exist between SST anomalies in the Pacific (related to El Nino-Southern Oscillation (ENSO) events) and the Atlantic, and it is possible that environmentally-driven recruitment variability in squid populations such as <I>I. argentinus </I>may prove to be a useful biological indicator of global phenomena such as ENSO. Oceanographic variability was found to be an important factor in influencing both the distribution and abundance of <I>I. argentinus </I>in the Southwest Atlantic. The techniques used in this study are readily transferable to the study of other ommastrephid squid species.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:368533 |
| Date | January 2000 |
| Creators | Waluda, Claire Marie |
| Publisher | University of Aberdeen |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
Page generated in 0.0023 seconds