56 



Fishery Bulletin 104(1) 



Comparison of fishery data with physical data 



We found a correlation between CPUE of the largest 

 recruitment month with SST buoy data from 10 months 

 earlier in the SM area only. There may be physical 

 features specific to this area that increase the cor- 

 relation between spawning recruitment and SST. For 

 example, SM is a small area, it is close to the buoy, 

 most of the area is sandy bottom, and it contains the 

 Redondo Canyon. Thus if further attempts to match 

 physical oceanography to the biology of a pelagic species 

 were to occur, the Santa Monica Bay could be the most 

 ideal location. But this correlation between CPUE of the 

 largest recruitment month with SST in the SM area may 

 be a seasonal effect because the regression is significant 

 for SST only and not an SST anomaly. Furthermore, we 

 caution that the significance of the correlation between 

 CPUE and SST in SM may be a type-I error because it 

 was the only significant test of the 30 tests run with 

 an alpha level of 0.05. The size of the recruitment event 

 was not strongly related to small deviations from aver- 

 age monthly SST; thus the timing of squid recruitment 

 to spawning grounds in APR and OCT may be tied to 

 annual fluctuations of prey availability and correlations 

 with temperature may be coincidental. The 10-month 

 lag corresponds to the egg-laying date of 9-month-old 

 squid. The lack of a greater number of correlations may 

 be due to the small spatial resolution of the buoy data 

 and the enormous variability of SST data due to meso- 

 scale oceanographic features in the large fishery areas. 

 In some areas the nearest buoy was quite distant from 

 the fishery zone. 



To address the spatial distance of spawning grounds 

 from buoys, we compared SSTs derived from satel- 

 lite AVHRR images with CPUE. AVHRR data were 

 collected from just the shelves and slopes of the six 

 fishery areas because these are the most important 

 areas for the growth of hatchlings and juveniles. Cross- 

 correlation time series analyses were significant at 

 5-10 month lags (Table 3), but this significance did not 

 translate into any predictive capabilities with linear 

 regression. 



Similarly, cross-correlations of CPUE with SOI and 

 NIN03 were significant at a 10-month lag in Monterey 

 Bay and a 4-month lag in the Southern California 

 Bight. Thus the Monterey fishery (10% of landings) is 

 offset by six months (roughly one short cohort) from 

 the SCB fishery. The correlation coefficients for NIN03 

 were greater than those of SOI, corroborating the idea 

 that the direct influence of the coastal waves ("oceanic 

 teleconnection") is the main source of the changes in 

 the hydrographic and ecological features of the Califor- 

 nia Current system (Huyer and Smith, 1985; Rienecker 

 and Mooers, 1986; Lynn et al., 1995; Chavez, 1996; 

 Ramp et al., 1997) rather than the ENSO (El Niiio 

 Southern Oscillation)-related changes of atmospheric 

 circulation ("atmospheric teleconnection") (Simpson, 

 1983; Simpson, 1984a, 1984b; Mysak, 1986; Breaker 

 and Lewis, 1988; Breaker et al., 2001; Schwing et al., 

 2002). 



Loliginid life cycles and future management of squid fisheries 



The correlation between SST and CPUE in the following 

 season may have resulted from the unique development 

 pattern of teuthids. The use of CPUE as an index of 

 abundance of the population (Sakurai et al., 2000), in 

 combination with studies of squid growth in relation to 

 SST (Jackson and Domeier, 2003), could explain large 

 fluctuations in landings data from year to year. In terms 

 of bottom-up forcing, individual squid health and the 

 resulting population size result from a combination 

 of prey availability and metabolic rates. Squids grow 

 exponentially in the first two months of life and then 

 logarithmically until senescence. In rearing tanks and 

 given a constant food supply, loliginids also grow faster 

 in warmer temperatures (Yang et al., 1986; Forsythe 

 et al., 2001) as their metabolic rates increase (O'Dor, 

 1982). Grist and des Clers (1998) predicted that annual 

 fluctuations in SST that cause differential growth in 

 squids can lead to younger cohorts hatched in warm 

 temperatures and surpassing in size older cohorts born 

 in colder seasons. Thus in October, a large 6-month-old 

 squid that hatched in April and developed in warm 

 water may spawn with a smaller 9-month-old squid that 

 hatched in the cold waters of January. 



However, in the California system and possibly in 

 other upwelling systems the situation is more complex 

 than in rearing tanks. For example, Jackson and Do- 

 meier (2003) demonstrated that due to the influences of 

 El Nino and La Nifia cycles and upwelling. the mean 

 mantle length of Loligo opalescens is shortest when 

 larvae are hatched in the warmest temperatures and 

 longest when hatched in cold waters. Mantle length is 

 also positively correlated with the upwelling index. In 

 the ocean, squid do not have a constant food supply. 

 The high productivity and cold temperatures caused by 

 upwelling and La Nina combined to create a period of 

 rich food resources and lower metabolic rates for squid, 

 probably enhancing the recovery of the fishery in 1999. 

 During the El Nifio event the squids were small and less 

 abundant because they had a high metabolic rate due 

 to increased temperatures and were exposed to lower 

 levels of available prey due to decreased ocean produc- 

 tivity. Seasonal maxima of phytoplankton in Monterey 

 Bay occur in summer; but in the southern part of the 

 Southern California Bight productivity peaks in win- 

 ter (Nezlin et al., 2002). These differences may be an 

 indicator of why the fishery operates in Monterey Bay 

 from April to November, coinciding with the upwelling 

 season, and in the Southern California Bight from No- 

 vember to May, coinciding with less stratification of the 

 water column and more mixing due to winter storms 

 and colder air temperatures. 



Lowry and Carretta (1999) corroborated the tempera- 

 ture-induced plasticity of mantle length (ML) from beaks 

 of squid in California sea lion (Zalophus californianus) 

 scats and spewings. MLs of squid prey were half the 

 size during El Nino years on San Clemente and Santa 

 Barbara islands. However, at San Nicholas Island dur- 

 ing El Nino events, there were both small- and regular- 



