作　　者： ; ;

机构地区： 中国水产科学研究院南海水产研究所

出　　处： 《大连海洋大学学报》 2020年第3期439-446,共8页

摘　　要： 为了利用单位捕捞努力量渔获量(CPUE)更好地评估南海鸢乌贼Sthenoteuthis oualaniensis资源的丰度情况,掌握鸢乌贼的资源分布与时空因子及海洋环境因子之间的关系,采用R语言中广义线性模型(GLM)和广义加性模型(GAM),结合时空因子及海洋环境因子对2013—2017年南海鸢乌贼的CPUE进行标准化研究,并评价各因子对CPUE的影响。结果表明:GLM模型分析显示,有7个变量对CPUE有重要影响,依次为月份、海表温度、海面高度、叶绿素a浓度、经度、年份和纬度;包含这7个因子的GAM模型的AIC值最小且模型最优,对CPUE偏差的解释率为36.68%,其中,高CPUE分别出现在3—5月份海表温度为26.0~30.5℃、海表面高度为0.60~0.75 m、叶绿素a浓度为0.06~0.13 mg/m3的海域内。研究表明,基于GLM模型和GAM模型对南海外海鸢乌贼灯光罩网渔业CPUE标准化研究,能够较好地反映鸢乌贼资源的丰度变化情况。 Catch per unit effort(CPUE)of purpleback flying squid Sthenoteuthis oualaniensis were standardized based on the data of large-scale lighting net fishing vessels from 2013 to 2017 by generalized linear model(GLM)and generalized additive model(GAM)in R language combining with spatial-temporal factors and marine environmental factors to use the CPUE to assess the abundance of purpleback flying squid resources fully,and understand the relationship between the resource distribution and spatial-temporal factors and marine environmental factors.The results showed that there were 7 important variables including month,sea surface temperature,sea surface height,chlorophyll a,longitude,year and latitude impacting on CPUE through GLM model.The GAM model containing these seven factors as the best model had the minimal AIC value,with CPUE deviation interpretation rate of 36.68%,the high CPUE in the sea surface temperature of 26.0-30.5℃from March to May,the sea surface level of 0.60-0.75 m,and the chlorophyll concentration of 0.06-0.13 mg/m3.The findings indicate that the CPUE standardization on large-scale lighting nets of purpleback flying squid on the open sea of South China Sea based on the GLM model and the GAM model better reflect the abundance changes in the squid resources.

关 键 词： 南海鸢乌贼 标准化 大型灯光罩网 广义线性模型 广义加性模型

领　　域： []