| Illex argentinus is one of the most important species of cephalopods in the world.The Malvinas,Islas(Falkland Is.)Sea is one of the most important fishing grounds for the Illex argentinus,with an average annual catch of more than 200,000 tonnes.Currently,research on Illex argentinus fishing forecasting is mostly concentrated in Argentina’s exclusive economic zone and the high seas,while less research is conducted on fishing forecasting related to the Malvinas area.To this end,this study uses more than 20 years of production statistics and marine environmental data,Illex argentinus in the Malvinas Sea area,the use of gray system and other theories and methods,to carry out studies on the prediction of the abundance of the Illex argentinus resources in the Malvinas Sea area,The results of this study will be beneficial to the rational exploitation of the resources of Illex argentinus in the Malvinas Sea area and provide a theoretical basis for the sustainable utilization of the resources of Illex argentinus in this area.The specific findings are as follows:(1)Annual and seasonal variations of sea surface temperature in the fishing grounds of Illex argentinus in the southwest Atlantic Ocean.From 1995 to 2019,the sea surface temperature ranges from 57°W-69°W and 33°S-53°S in the southwest Atlantic Ocean were 4-27 ℃,with a significant variation,The range of standard deviation of surface temperature is 1.34-4.95°C,and the sea area with standard deviation above4.4°C is 57°W-58°W,34°S-37°S,58°W-59°W,35°S-36°S,This area,which happens to be the mouth of the South n Río de la Plata,is one of the main spawning grounds of the Illex argentinus.The annual variation coefficients of surface temperature range from 0.14 to 0.31 in the 57°W-69°W and 33°S-53°S waters of the south-west Atlantic Ocean.The variation coefficients above 0.3 are mainly distributed in the 57°W-58°W and 39°S-43°S,58°W-59°W,44°S-47°S and 59°W-60°W,45°S-46°S,These areas are the southern migration zone of the Illex argentinus,as well as the distribution of the main fishing grounds.Therefore,it is inferred that the significant year-to-year changes of surface temperature in these areas may have an impact on the stock replenishment and fisheries formation of Illex argentinus.The months with a variation coefficient of sea surface temperature above 0.10 in the sea areas of 57 ° W-69 ° W and 33 ° S-53 ° S in the southwest Atlantic Ocean are mainly distributed in June to August,These times coincide with the spawning season for the main population of Illex argentinus.The sea area with the largest variation of SST from June to August was mainly distributed in 57°W-59°W,35°S-36°S,57°W-58°W,41°S-49°S,58°W-59°W,46°S-48°S,67°W-69°W,51°S-53°S,These waters are closely related to the spawning grounds,migration routes,and so on of Illex argentinus.Therefore,changes in sea surface temperature during spawning will affect the spawning and larval growth and death of Illex argentinus,further affecting the resource replenishment of squid.The variation coefficients of sea surface temperature of 57°W-69°W and33°S-53°S in the southwest Atlantic Ocean were 0.07-0.08.The relatively large variation coefficients were mainly distributed from January to April,January to April is the main operating season for Illex argentinus.The stations with large sea surface temperature variation coefficients from January to April are mainly distributed in the sea areas of 57°W-58°W,41°S-47°S,57°W-60°W,46°S-50°S,66°W-68°W,and48°S-50°S,These waters are closely related to squid feeding migration channels and the distribution of fishing grounds.Therefore,the changes in sea surface temperature from January to April are relatively small compared to the spawning period,but these small changes will have an impact on the spatial and temporal distribution of the fishing grounds of Illex argentinus.The SST variation coefficients of 57°W-69°W and33°S-53°S in the south-west Atlantic were in the top 10 and occurred 7 times or more,mainly 57°W-58°W,47°S-50°S,57°W-59°W,46°S-49°S,and 58°W-59°W,46°S-48°S,The spatial distribution is relatively concentrated,These areas are mainly in the area where the Illex argentinus migrates southward to feed and grow,In terms of time,it is mainly concentrated in January to August and October to December,which is the spawning period of Illex argentinus from June to August,and the fishing season from December to May of the next year.It is inferred that the significant changes in the annual resource replenishment and fishing grounds of Illex argentinus are highly correlated with the spatiotemporal changes in surface temperature in the above sea areas.The research results provide a basis for future research on the fishing situation prediction of Illex argentinus.(2)Relationship between abundance of Illex argentinus and sea surface temperature in the Malvinas Sea area.According to the research,in January,the stations with a significant correlation coefficient between CPUE and surface temperature of Illex argentinus(P<0.01)are concentrated in the sea areas of 55°W-65°W and 45°S-52°S.In February,the stations with a significant correlation coefficient between CPUE and sea surface temperature(P<0.01)were concentrated in the sea areas of 57°W-62°W and45°S-51°S.In January,the stations with extremely significant correlation coefficient between CPUE and sea surface temperature(P<0.05)were mainly distributed in the sea areas of 57°W-66°W and 36°S-53°S.In May,the stations with a significant correlation coefficient between CPUE and sea surface temperature(P<0.05)were mainly distributed in the sea areas of 57°W-59°W,39°S-41°S,and 63°W-66°W,45°S-47°S.The research shows that the correlation coefficient between sea surface temperature in March and CPUE in the following year is extremely significant(P<0.01),and the stations are concentrated in the 64°W-66°W,40°S-42°S sea areas.The stations with significant correlation coefficient between sea surface temperature in March and CPUE in the following year(P<0.05)are mainly distributed in the sea areas of 58°W-64°W,33°S-36°S,and 60°W-66°W,38°S-43°S.The stations with significant correlation coefficient between sea surface temperature in May and CPUE in the following year(P<0.05)are mainly distributed in the sea areas of 57°W-66°W and41°S-51°S.The stations with significant correlation coefficient between sea surface temperature in June and CPUE in the following year(P<0.05)are mainly distributed in the sea areas of 57°W-60°W,41°S-43°S,and 60°W-63°W,43°S-47°S.The stations with significant correlation coefficient between sea surface temperature in July and CPUE in the following year(P<0.05)are mainly distributed in the sea areas of 57°W-60°W and 41°S-43°S.According to the research,among 56 statistically significant stations,the grey correlation degree ranges from 0.6525 to 0.6851,The top five gray correlation stations are 61.5 ° W,51.5 ° S(January),64.5 ° W,50.5 ° S(January),62.5 ° W,51.5 ° S(January),63.5 ° W,50.5 ° S(January),61.5 ° W,50.5 ° S(January),that is,they are distributed in the range of 61°W-65°W,50°S-52°S.In January,within the sea areas of61°W-65°W and 50°S-52°S,the sea surface temperature can be used as a prediction index for the abundance of Illex argentinus resources in the Malvinas Sea area.The appropriate range is between 8.1-10.5℃.If the water temperature exceeds 11.0℃,it is not conducive to the formation of fishing grounds in the sea area.(3)Prediction for the abundance index of Illex angentinus in the waters near Malvinas Islands.Using CPUE data from 2015-2019,2014-2019,2013-2019,and2012-2019,GM(1,1)models for different time series were established.It is found that the GM(1,1)model based on the CPUE data from 2015 to 2019 is the best,and all the statistical parameters have passed the test,while other GM(1,N)models are not suitable for the CPUE prediction model.The results show that five linear models are established respectively by using the sea surface temperatures of 61.5°W,50.5°S,63.5°W,50.5°S,64.5°W,50.5°S,62.5°W,51.5°S and 61.5°W,51.5°S in January of that year,both were statistically significant(P<0.01),The CPUE prediction model based on the sea surface temperature of 61.5°W and 50.5°S has the lowest P value of 0.0054,which can be used for the scientific prediction of CPUE.The results show that five linear models are established respectively by using the sea surface temperatures of 63.5°W,41.5°S,65.5°W,41.5°S,64.5°W,41.5°S,64.5°W,40.5°S and 65.5°W,40.5°S in March of last year,both were statistically significant(P<0.05),The CPUE prediction model based on sea surface temperatures of 64.5°W and41.5°S has the lowest P-value,only 0.0047,and can be used for scientific prediction of CPUE.Taking 1615t/vessel at the upper limit and 784T/vessel at the lower limit as the index values,the prediction models of the disaster model in rich years and the disaster model in poor years are constructed respectively as follows:X(t)=33.689exp(0.234t)-28.689,X(t)=57.527exp(0.129t)-56.527.Theoretically,the average relative error of the disaster model in rich years is 8.284%,the value of level deviation is 0.165,and the average relative error of the disaster model in poor years is 8.182%,the value of level deviation is 0.107.The models can be used for the medium and long term prediction of CPUE. |
