基于栖息地指数的阿拉伯海鲐鱼渔情预报模型构建

Forecasting fishing ground of mackerel (Scomber australasicus) in Arabian Sea based on habitat suitability index

为了更好地了解和可持续开发利用阿拉伯海澳洲鲐(Scomber australasicus)资源,采用2016—2017年1、2、11和12月主渔汛期间我国公海围网渔船在阿拉伯海的鲐鱼生产数据,结合海表温度(Sea surface temperature,SST)、混合层厚度(Mixed-layer thickness, MLT)、海面高度异常(Sea level anomaly, SLA)、叶绿素a浓度(Chlorophyll-a concentration, CHL)环境数据,分别构建了以渔获量(Fish catch, FC)和作业次数(Fishing times, FT)为基础的栖息地指数(Habitat suitability index, HSI)模型:FC-HSI和FT-HSI模型。在HIS>0.6的海域,2016和2017年实际渔获量占比分别为76.25%和80.03%。利用2018年的实际生产数据对模型进行预报准确度验证,得出在HIS>0.6的海域,实际渔获量占比分别为45.68%和50.15%,FT-HSI模型的预报结果优于FC-HSI模型。结果表明,基于SST、MLT、SLA、CHL的FT-HSI模型能够较好地预测阿拉伯海鲐鱼的中心渔场。

In order to better understand and sustainably develop and utilize the mackerel(Scomber australasicus)resources in the Arabian Sea,according to the Chinese light purse seine production data of mackerel in the high sea of the Arabian Sea during the main fishing seasons(January,February,October and November)from 2016 to 2017,combining with the environmental data of sea surface temperature(SST),sea level anomaly(SLA),mixed-layer thickness(MLT),chlorophyll-a concentration(CHL),we established the habitat suitability index(HSI)models,which were based on catch(FC)and fishing times(FT),FC-HSI model and FT-HSI mo-del.In the sea area with HSI greater than 0.6,the actual catches in 2016 and 2017 accounted for 76.25%and 80.03%,respectively.Using the actual production data in 2018 to verify the prediction accuracy of FC-HSI and FT-HSI models,it is found that in the sea area with HSI greater than 0.6,the actual catches accounted for 45.68%and 50.15%,respectively,which indicates that the prediction result of FT-HSI model was slightly better than that of FC-HSI model.This study shows that the FT-HSI model based on SST,MLT,SLA and CHL can better predict the central fishing ground of mackerel in the Arabian Sea.