1. Monthly series of abundance indexes for the English Channel squid stock, based on fishery statistics of the United Kingdom (1980–93) and France (1986–96), were compared with water temperature data. The two objectives of the study were to test empirical predictive models and to analyse the stock–environment relationship at various time scales; both correlation and time-series statistical techniques were applied. Sea surface temperature (SST) showed inter-annual fluctuations and month-to-month auto-correlation in addition to the annual cycle.
2. Trends in squid landings and temperature at the annual scale were found to be related, whatever the statistical method used (moving averages, cumulative functions or regression using averaged data).
3. Variable selection applied in a ‘multi-month’ model suggested that fishing season indexes could be predicted from temperatures observed in the previous winter. The link between mild winter conditions and cohort success in winter/spring spawning species suggested that early life survival (and/or growth) was involved. This empirical model is a first step in the development of environment-predicted recruitment indexes useful for management advice.
4. Seasonal decomposition was performed on both the squid resource data and SST data in search of short-term relationships. In spite of the flexibility of the loliginid life-cycle, no significant relationship was found between squid seasonally adjusted indexes and temperature anomalies in the previous months. This underlined the conclusion that temperature effect on cohort success was not constant throughout the year.