Research on the abundance prediction model of Illex argentinus based on sea surface temperature of spawning ground
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摘要: 阿根廷滑柔鱼(Illex argentinus)为短生命周期种,其资源丰度易受海洋环境变化的影响,尤其是在产卵场的早期生活史阶段。根据2003−2016年我国鱿钓船队在西南大西洋的生产统计数据,以及产卵场海洋表面温度(SST)卫星遥感数据,用相关性分析方法筛选出阿根廷滑柔鱼产卵旺季期间(6月份)表征产卵场SST变化的特征海域;基于阿根廷滑柔鱼产卵场最适SST范围占总面积之比(Ps)与资源丰度单位捕捞努力渔获量(CPUE,t/船)呈正相关性的假设,回溯阿根廷滑柔鱼最适的产卵场及水温环境条件,并据此建立多种基于表征产卵场SST环境因子的资源丰度多元线性预测模型。相关性分析结果表明:6月份有两片连续海域(Area 1、Area 2)的SST与CPUE之间存在显著相关性,分别为42.5°~44°S、57.5°~59°W(Area 1)和39°~39.5°S、45°~46°W(Area 2);回溯的阿根廷滑柔鱼产卵场范围为37.5°~44°S、41.5°~51.5°W,产卵场最适SST范围为16~17.5℃。利用2个特征海域(Area 1、Area 2)SST以及回溯的产卵场Ps建立4种的多元线性资源丰度指数(ICPUE)预测模型,结果表明,包含表征寒暖流的特征海域和回溯产卵场Ps的方案4模型优于其他3种模型,其资源丰度指数预测模型为ICPUE=1.390 4×Ps+0.261 9×SSTArea 1+0.096 2×SSTArea 2−3.248 0。Abstract: Illex argentinus was a short life cycle species. Its resource abundance is susceptible to changes in the marine environment, especially in its early life history stage. According to the production statistics of the Chinese squid jigging fleet during 2003−2016 in the Southwest Atlantic and the sea surface temperature (SST) of the spawning ground from satellite remote sensing, the correlation analysis method was used to select the featured area representing SST changes during the spawning season (June) of I. argentinus. Based on the assumption that the ratio of optimum SST range to the total area (Ps) of the spawning ground of I. argentinus is positively correlated with the abundance index (catch per fishing unit, CPUE, t/ship), the optimum spawning area and suitable sea water temperature range of I. argentinus were traced back, and a variety of multivariate linear prediction models of abundance index based on the environmental factors were established. The correlation analysis shows that there are significant correlations between SST and CPUE in two consecutive sea areas (Area 1, Area 2) in June. They are 42.5°−44°S, 57.5°−59°W (Area 1) and 39°−39.5°S, 45°−46°W (Area 2) respectively. The inferred spawning area of I. argentinus ranges from 37.5°S to 44°S and 41.5°W to 51.5°W, and the optimum SST in the spawning area is 16°C to 17.5°C. The SSTs of two featured areas (Area 1, Area 2) and Ps in the inferred spawning area are used to establish four types of multivariate linear prediction models of abundance index (ICPUE), the results show that the fourth model containing the featured areas and Ps in the inferred spawning area is superior to the other 3 models, and its prediction model of abundance index is ICPUE=1.390 4×Ps+0.261 9×SSTArea 1+0.096 2×SSTArea 2−3.248 0.
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表 1 产卵场特征海域SST与次年CPUE相关性分析结果
Tab. 1 The result of correlation analysis parameters between SST in key area and CPUE of next year
Area 1 Area 2 经纬度范围 42.5°~44°S,57.5°~59°W 39°~39.5°S,45°~46°W R 0.618 7 0.609 2 p 0.024 2 0.027 1 表 2 推测产卵场(37.5°~44°S,41.5°~51.5°W)不同最适SST范围的Ps与CPUE相关性分析结果
Tab. 2 The result of correlation analysis parameters between Ps of different optimal SST ranges and CPUE in forecasted spawning ground (37.5°−44°S,41.5°−51.5°W)
产卵场最适SST范围 R p 15.5~17℃ 0.470 2 0.104 9 16~17.5℃ 0.654 5 0.015 2 16.5~18℃ 0.205 0 0.501 6 17~18.5℃ −0.083 2 0.787 0 15.5~17.5℃ 0.544 3 0.054 4 16~18℃ 0.524 2 0.065 9 16.5~18.5℃ 0.113 4 0.712 1 15.5~18℃ 0.502 7 0.080 0 16~18.5℃ 0.381 1 0.198 8 表 3 多元线性模型方程以及预报结果
Tab. 3 Multiple linear model equations and forecast results
方案 多元线性预测模型方程 R p MSE 1 ICPUE=2.570 1×Ps+0.253 6×SSTArea 1−1.928 2 0.732 1 0.021 5 0.037 9 2 ICPUE=2.581 6×Ps+0.092 6×SSTArea 2−1.602 0 0.720 6 0.025 7 0.039 2 3 ICPUE=0.328 0×SSTArea 1+0.124 2×SSTArea 2−3.868 5 0.774 7 0.010 2 0.032 6 4 ICPUE=1.390 4×Ps+0.261 9×SSTArea 1+0.096 2×SSTArea 2−3.248 0 0.796 2 0.023 5 0.029 9 表 4 多元线性模型方程自变量t检验结果
Tab. 4 Multivariate linear model equation variable t test result
方案 t(Ps) t(SST 1) t(SST 2) 1 1.816 2.522 2 1.956 2.375 3 2.394 2.332 4 1.910 2.678 2.552 -
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