| Ommastrephid squid, such as Ommastrephes bartramii, Illex argentinus, and Disidicus gigas is important species for Chinese squid jigging fleets and of great economic value. In recent decades, the abundance of those species fluctuate sharply, however, the technology of fishery forecasting for ommastrephid squid, especially recruitment forecasting and stock assessment for squid is still in its infancy. Carrying out the research on fishery forecasting for oceanic squid, master their resource status and the changes of population are the key to realize the sustainable utilization and scientific management for ommastrephid squid.The scientific hypothesis of this research are,(1) squid is a short life-span sepeies, with the characteristics of “be dead immediately after spawning” and “no remaining group only recruitment”, so marine environment is the key factor affecting the fishing grounds distribution and recruitment for squid, that is the environmental factors in spawning grounds and feeding grounds play an important role for fishing grounds distribution and recruitment of squid;(2) environmental factors in spawning grounds and feeding grounds also have a major impact on the growth and recruitment of squid in surplus production models. Based on the above 2 scientific hypothesis, this paper focuses on how to choose the optimal temporal-spatial scale to construct fishing grounds forecasting models based on environmental factors; how to choose environmental factors in spawning grounds and feeding grounds to construct more robust and more accurate forecasting models of recruitment for squid; comparing stock assessment models based on environmental factors in spawning grounds or/and environmental factors in feeding grounds and comparing the degree of influence by environmental factors in stock assessment models for different squids. So, in this paper, according to the fishing production data from Chinese mainland and associate countries or regions, combined with sea surface temperature(SST), sea surface temperature anomaly(SSTA), sea surface height(SSH), and Chlorophyll-a concentration(Chl-a), research on fishing grounds forecasting, recruitment forecasting and making management strategy for Ommastrephes bartramii, Illex argentinus, and Disidicus gigas. The main conclusions are as follows.(1) fect of environmental factors on forming fishing grounds. The maximum contribution rate of fishing ground forecasting models was SST or SSTA, SST or SSTA has an important effect on the distribution of resources or fishing ground formation mechanism, the suitable ranges of SST for different squids are different. Other environmental factors, such as SSH, Chl-a also affected the distribution of squids. The existence of plankton is a basic condition for the formation of the squid fishing grounds. The Chl-a is a good indicator for food availability for squid. High Chl-a concentration yields good feeding environments, providing higher volumes of nutrients to the phytoplankton, zooplankton and dissolved organic materials, which links to the food density and availability for the squid. In Northwest Pacific Ocean, the first factor affecting fishing ground of Ommastrephes bartramii was SST, its contribution rate was 26%, the suitable range of SST was 11-18 oC, the contribution rate of Chl-a was 10%. In Southwest Atlantic Ocean, the first factor affecting fishing ground of Illex argentinus was SST, its contribution rate was 40%, the suitable range of SST was 7-15 oC. In Southeast Pacific Ocean, the first factor affecting fishing ground of Disidicus gigas was SSTA, its contribution rate was 29%, it was said that the fishing ground distribution of Disidicus gigas was easily affected by ENSO, the second factor was SST, and the suitable range of SST was 17-21 oC.(2) Effect of different temporal-spatial scale and different oceans on fishing grounds models. The suitable temporal-spatial scale obtained from one species was not fit other species, each species had its own unique optimal temporal-spatial scale. It was found that using different models would be got different temporal-spatial scale for fishing grounds compared with other models(HSI models, geostatistics models). The optimal temporal-spatial scale and environmental factors for fishing ground of Ommastrephes bartramii were “monthly”, “0.5o×0.5o”, and “SST, SSH” respectively; the optimal temporal-spatial scale and environmental factors for fishing ground of Illex argentinus were “weekly”, “1.0o×1.0o” and “SST” respectively; the optimal temporal-spatial scale and environmental factors for fishing ground of Disidicus gigas were “monthly”, “0.5o×0.5o”, “SST, SSH” respectively. Based on the optimal temporal-spatial scale and environmental factors of fishing grounds, using artificial neural network(ANN) models improved the forecasting accuracy of fishing grounds greatly. It could be explained from two aspects, a) the advantages of ANN, such as ANN has better ability of nonlinear fitting, b) using CPUE levels as fitting target instead of using CPUE reduced requirements of model performance. The fishing grounds forecasting models which using CPUE levels as fitting target could be more suited to the actual needs in the oceans. The forecasting accuracy of models for Ommastrephes bartramii, Illex argentinus, and Disidicus gigas were all above 80%, and the ARV values of models were all under 0.4.(3) Key environmental factors affected recruitment of squid. It was found that the key environmental factors were almost in contour-intensive areas or current intersection areas, the recruitment forecasting models for squid based on environmental factors were more accuracy and more robust. In Northwest Pacific Ocean, the environmental factors were significant at four key points, SST at point1(145o-146oE, 25o-26oN) in January, Chl-a at point2(168o- 169oE、27o- 28.5oN) in March, SST at point3(156.5o- 158oE、40o- 40.5oN) in November, Chl-a at point4(158o- 160oE、38o- 39oN) in August, these key points were almost in the path of Kuroshio or Oyashio. In the Southwest Atlantic Ocean, the environmental factors were significant at three key points, SST at point1(38o~39oS, 54o~55oW), point2(40.5o~41.5oS, 51o~52oW), and point3(39.9o~40.4oS,42.6o~43.1oW) in June, these key points were at the junction of Brazil current and Falkland current. In Southeast Pacific Ocean, the environmental factors were significant at six key points, SST at point1(13oN, 102oW) in July and point2(8oN,103.5oW) in June, SSH at point3(11oN, 102oW) in September and point4(12oN, 97.5oW) in February, Chl-a at point5(8oS, 107oW) in March and point6(10oS, 93.5oW) in October, these key points were in the path of Peru current and California current. The accuracy of fish recruitment forecasting models for Ommastrephes bartramii, Illex argentinus, and Disidicus gigas were all about 90%.(4) Comparison and analysis between Schaefer surplus production models based on key environmental factors in spawning grounds and feeding grounds. The Schaefer surplus production models based on key environmental factors in spawning grounds and feeding grounds using Bayesian statistical were constructed for the first time. It was found that, Ommastrephes bartramii, Illex argentinus, and Disidicus gigas were all in a better level, the fishing mortality of these three squids were all under Ftar、FMSY, the resources of Ommastrephes bartramii, Illex argentinus, and Disidicus gigas were not overfished currently. The stock assessment models based key environmental factors were fitted better than original models. In Northwest Pacific Ocean, the best fitted model was S-EDSP, the MSY of Ommastrephes bartramii was from 185 600 to 232 000 tons, and the BMSY of Ommastrephes bartramii was from 260 000-325 100 tons. In Southwest Atlantic Ocean, the best fitted model was S-F-EDSP, the MSY of Illex argentinus was from 335 700 to 518 600 tons,the BMSY of Illex argentinus was from 1 505 000 to 1 750 000 tons. In Southeast Pacific Ocean, the best fitted model was SF-EDSP, the MSY of Disidicus gigas was from 141 100 to 489 200 tons,the BMSY of Disidicus gigas was from 968 300 to 4 000 000 tons. Those results show that environmental factors are very important in stock assessment of short lifespan species like squid, environmental factors in the spawning and feeding grounds should be considered in squid stock assessment and management. |
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