Zamora-Garcia et al.: Catch rate, length, and sex ratio of Merluccius productus in the Gulf of California 369 
Table 1 
Summary of variables in the generalized additive models used to standardize the natural 
logarithm of catch per unit of effort (logCPUE), the mean standard length (SL), and the nat- 
ural logarithm of the sex ratio (logSR) for Pacific hake (Merluccius productus) in the north- 
ern Gulf of California. The model with the lowest Akaike information criterion (AIC) was 
considered the best. Also provided are the differences in AIC values between the best model 
and each of the other models (AAICs). The explanatory variables used in the models include 
tow speed (in kilometers per hour), mesh size in the codend (in centimeters), average depth 
of trawl tow (in meters), hour of the beginning of the tow (with hours expressed as numerals 
between 1 and 24), month, year, and the interaction of month and year. Models were fit to 
data for Pacific hake caught in 2015-2019 during the fishing season from January through 
March. Asterisks (*) indicate variables that were excluded from the final models because 
their inclusion did not reduce AIC in at least 2 units along with a significant increase in the 
explained variance. The variable hour in the model for mean SL was excluded because it 
had high nonlinearity (effective degrees of freedom=8.59), considered difficult to interpret. 
Cummulative 
Response Explanatory Explained deviance 
variable variable deviance (%) explained (%) AIC 
logCPUE Null 0.00 0.00 2603.70 
Covariates 
+s(Speed) 2.43 2.43 2598.48 -5.22 
+s(Mesh) 3.69 6.12 2580.93 -17.55 
+s(Depth) 2.04 8.16 2571.97 -8.96 
+s(Hour) 1.05 9.21 2454.34 -117.63 
Factors 
+Month 1.09 10.30 2449.98 -4.36 
+Year 2.10 12.40 2439.75 -10.23 
Interactions 
+Month x Year 7.50 19.90 2380.46 -59.29 
Mean SL Null 0.00 0.00 3505.75 
Covariates 
+s(Mesh)* 0.17 3505.59 -0.15 
+s(Hour)* 4.35 3391.07 -114.68 
+s(Speed) 8.68 i 3473.78 -32.97 
+s(Depth)* 1.32 3472.30 -1.47 
Factors 
+Month 4.40 3460.61 -13.71 
+Year 4.60 3448.03 -12.53 
Interactions 
+ Month x year* 1.90 3449.56 +1.41 
Null 0.00 I 1042.23 
Covariates 
+s(Mesh)* 2.40 1042.15 
+s(Depth) 4.90 ‘ 1026.90 
+s(Speed)* 2.43 1026.00 
+s(Hour)* 0.40 985.29 
Factors 
+Month* -0.29 1030.00 
+Year 7.14 ; 1024.37 
Interactions 
+ Month x year 5.76 1013.30 
and 2019 (433 kg/h [95% CI: 321-590 kg/h]) (Fig. 4A). February (376 kg/h [95% CI: 305-454 kg/h]) and March 
In addition, a negative trend in CPUE was observed on (312 kg/h [95% CI: 253-385 kg/h]), respectively. However, 
a monthly basis (Fig. 4B). On average, January had the this pattern was not consistent across years, as indicated 
highest mean CPUE (719 kg/h [95% CI: 493-1057 kg/h]), by the relevance of the month and year interaction term 
followed by significant decreases of 48% and 52% in (Table 1). 
