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Clupeoid Population Variability, the Environment and Satellite Imagery in Coastal Upwelling Systems

Authors
  • Cole, James1
  • McGlade, Jacqueline2
  • 1 NOAA-NMFS, Pacific Fisheries Environmental Laboratory, 1352 Lighthouse Avenue, Pacific Grove, CA, 93950, USA , Pacific Grove
  • 2 Centre for Coastal and Marine Sciences (NERC), Plymouth Marine Laboratory, Prospect Place, Plymouth, PL1 3DH, United Kingdom , Prospect Place, Plymouth
Type
Published Article
Journal
Reviews in Fish Biology and Fisheries
Publisher
Springer-Verlag
Publication Date
Dec 01, 1998
Volume
8
Issue
4
Pages
445–471
Identifiers
DOI: 10.1023/A:1008861224731
Source
Springer Nature
Keywords
License
Yellow

Abstract

Sardine, pilchard and anchovy stocks form the basis of commercially important purse seine fisheries in eastern boundary upwelling regions. High levels of environmentally driven recruitment variability have, however, made them especially difficult to manage. Reliable forecasts of recruitment success would greatly help with the setting of catch quotas prior to each fishing season. Theories of how environmental conditions influence recruitment success, according to survival/mortality of the early life-history stages, can be divided into mechanistic and sythesis theories. Mechanistic theories are concerned with specific physical processes, whereas synthesis theories attempt to unite the various mechanistic processes within a single conceptual framework. Despite the successful testing of some theories, there has been little success in reliably predicting recruitment success from a knowledge of environmental conditions. Possible reasons include the following: non-linearity in the relationship between environmental parameters and recruitment; the poor spatial and temporal resolution of much oceanographic data; the wide range of different factors involved in determining recruitment success; and the choice of environmental index. The recent compilation of time series of satellite images for these regions offers a solution to some of these problems, and in doing so reopens the possibility of finding sufficiently good relationships between environmental conditions and recruitment success for management purposes. In particular, the high resolution of these time series allows for the construction of environmental indices across many different spatial and temporal scales. These time series also open up the possibility of quantifying the behaviour of upwelling systems according to the evolution of their spatial structure through time, using pattern analysis techniques.

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