Chang et al.: The Antarctic Oscillation index as an environmental parameter for predicting catches of lllex argentinus 
209 
Table 3 
List of environmental variables in the predictive generalized linear models used in analyses 
of the influence of environmental factors on catch per unit of effort for Argentine Shortfin 
squid ( lllex argentinus) in the southwest Atlantic, when progressive analysis was performed 
with data from 1998 through 2007. The symbol in a cell denotes that a variable was in- 
cluded in the model with either positive (+) or negative (-) loading. All coefficients in models 
were significant at P-value <0.05. Note that PPANov, PPADec, and PPAMar represent 2-year- 
lagged Antarctic Oscillation indices in November, December, and March, respectively, before 
the fishing season; PS_5m_Mar and S_5m_Mar represent subsurface seawater temperatures 
at a depth of 5 m at the southern Patagonian shelf in the previous and concurrent March, 
respectively; and R 2 represents the coefficient of multiple determination. 
Environmental variables 
Year 
PPANov 
PPADec 
PPAMar 
PS_5m_Mar S_5m_Mar 
R 2 (%) 
1998 
- 
+ 
- 
91.3 
1999 
- 
+ 
- 
93.9 
2000 
- 
+ 
- 
90.2 
2001 
- 
+ 
- 
90.6 
2002 
- 
+ 
- 
90 
2003 
- 
+ 
- 
87 
2004 
- 
+ 
- 
84.5 
2005 
- 
+ 
- 
78.7 
2006 
- 
+ 
+ 
- 
82.2 
2007 
- 
+ 
- 
83 
Another hypothesis is indicated by the significant 
negative correlation of squid logC7 with the previous 
year’s subsurface seawater temperature in March in 
the southern Patagonian shelf. The lag of SST effect 
on abundances of Argentine shortfin squid has been 
reported previously; colder temperatures in the hatch- 
ing area of the northern Patagonian shelf indicated in- 
creased catches in the following fishing year (Waluda et 
ah, 1999). Because of the positive correlation between 
fecundity and mantle length and between fecundity 
and weight for Argentine shortfin squid (Haimovici 
et ah, 1998), individual growth and fecundity that re- 
sults from cold seawater temperatures in the previous 
year would be greater than growth and fecundity that 
results from warmer temperatures in previous years. 
These time-lag effects of seawater temperature would 
affect squid abundance in the following year. 
Effect of atmospheric forcing 
Atmospheric forcing may also influence variation in the 
abundance of squids. Our results show that the AAO 
affects catch of Argentine shortfin squid and revealed a 
2-year lag in that effect. Because the Argentine short- 
fin squid has an annual life cycle, environmental fac- 
tors should affect its abundance within one reproduc- 
tive cycle or pass that effect on to the following re- 
productive cycle by affecting recruitment (Waluda et 
ah, 1999, 2004). The 2-year lag in our results indicates 
that the AAO may not directly affect squid abundance 
and that indirect biotic or abiotic linkages exist be- 
tween atmospheric circulation patterns and stock fluc- 
tuations. Similarly, studies of the common octopus ( Oc- 
topus vulgaris ) in the Canary Islands suggested that 
fluctuations in octopus catches were the result of SST 
fluctuations but were in synergy with other unknown 
environmental variables that were affected by North 
Atlantic Oscillation patterns with a few months lag 
(Caballero-Alfonso et ah, 2010; Polanco et ah, 2011). 
Waluda et ah (1999; 2004) reported that the SOI had 
a teleconnection of SST anomalies between the Pacific 
and Atlantic Oceans and that the SOI, therefore, had 
a time-lag effect on the catch of Argentine shortfin 
squid around Falkland Islands. Those results indicate 
the potential for connection between atmospheric forc- 
ing anomalies and abundance variation of cephalopods 
through SST with a time lag. 
In the southwest Atlantic, the AAO was positively 
correlated with SST anomalies in the South Brazil 
Large Marine Ecosystems between 20°S and 35°S (Gh- 
erardi et ah, 2010), the inferred hatching zone of Ar- 
gentine shortfin squid (Waluda et ah, 2001a) and where 
paralarvae have been found between July and Decem- 
ber (Haimovici et ah, 1998). The correlations between 
the AAO and SST anomalies became stronger with a 
lag of 15-24 months; the strongest correlation had a 
lag time of 24 months (Gherardi et ah, 2010). That 
correlation indicates that a lower AAO in November 2 
years before that time would lead to a lower than aver- 
age SST in the inferred hatching area during the pe- 
riod of hatching. Because SST in the hatching grounds 
of the northern Patagonian shelf during the period of 
