Projecting distributions of Argentine shortfin squid(Illex argentinus)in the Southwest Atlantic using a complex integrated model

We developed an approach that integrates generalized additive model（GAM） and neural network model（NNM）for projecting the distribution of Argentine shortfin squid（Illex argentinus）. The data for this paper was based on commercial fishery data and relevant remote sensing environmental data including sea surface temperature（SST）, sea surface height（SSH） and chlorophyll a（Chl a） from January to June during 2003 to 2011. The GAM was used to identify the significant oceanographic variables and establish their relationships with the fishery catch per unit effort（CPUE）. The NNM with the GAM identified significant variables as input vectors was used for predicting spatial distribution of CPUE. The GAM was found to explain 53.8% variances for CPUE. The spatial variables（longitude and latitude） and environmental variables（SST, SSH and Chl a） were significant. The CPUE had nonlinear relationship with SST and SSH but a linear relationship with Chl a. The NNM was found to be effective and robust in the projection with low mean square errors（MSE） and average relative variances（ARV）.The integrated approach can predict the spatial distribution and explain the migration pattern of Illex argentinus in the Southwest Atlantic Ocean.

A stock assessment for Illex argentinus in Southwest Atlantic using an environmentally dependent surplus production model

The southern Patagonian stock（SPS） of Argentinian shortfin squid, Illex argentinus, is an economically important squid fishery in the Southwest Atlantic. Environmental conditions in the region play an important role in regulating the population dynamics of the I. argentinus population. This study develops an environmentally dependent surplus production（EDSP） model to evaluate the stock abundance of I. argentines during the period of 2000 to 2010. The environmental factors（favorable spawning habitat areas with sea surface temperature of 16–18°C） were assumed to be closely associated with carrying capacity（K） in the EDSP model. Deviance Information Criterion（DIC） values suggest that the estimated EDSP model with environmental factors fits the data better than a Schaefer surplus model without environmental factors under uniform and normal scenarios.The EDSP model estimated a maximum sustainable yield（MSY） from 351 600 t to 685 100 t and a biomass from 1 322 400 t to1 803 000 t. The fishing mortality coefficient of I. argentinus from 2000 to 2010 was smaller than the values of F（0.1） and F（MSY）. Furthermore, the time series biomass plot of I. argentinus from 2000 to 2010 shows that the biomass of I.argentinus and this fishery were in a good state and not presently experiencing overfishing. This study suggests that the environmental conditions of the habitat should be considered within squid stock assessment and management.