栖息地指数模型在北太公海秋刀鱼渔情预报中的应用

Study on Fishery Forecast of Cololabis Saira in the Northen Pacific Based on Habitat Model

秋刀鱼(cololabis saira)作为高度洄游的大洋性鱼类,因其资源量大、分布广而成为我国远洋渔业重要的捕捞对象之一。本文根据2003～2015年我国大陆在北太平洋公海秋刀鱼的生产调查数据,结合所获得的环境数据,以秋刀鱼单位捕捞努力量渔获量(Catch Per Unit Effort,CPUE)为适应性指数(suitability index,SI),利用几何平均法、算术平均法、最大值法和最小值法分别建立基于海水海表面温度(sea surface temperature,SST)、海表面高度(sea surface height,SSH)和海表面叶绿素a浓度(sea surface chlorophyll,SSC)的综合栖息地指数(habitat suitability index,HSI)模型。并利用2015年5～11月生产数据用于HSI模型验证,T检验结果表明算术平均值法拟合效果最好(P<0.05),模型准确度达70%以上,确立最适的秋刀鱼渔情预报模型,可为秋刀鱼的生产提供参考。

As a highly migratory species with great economic value and abundant resources,Cololabis saira had become one of the main target species in the world's ocean fisheries.Using the saira production date from China's Mainland from June to November 2003--2015 in the Northen Pacific,we applied biomass combining environmental data from remote sensing as adaptive index to establish the habitat suitability index models (HSI)based on sea surface temperature (SST),sea surface height (SSH),sea surface salinity (SSS),and concentration of sea surface Chlorophyll a (SSC).The maximum value method,minimum value method,geometric mean value method and arithmetic mean value method are used.The habitat suitability index model was also verified based on production date and environmental data from May to November in 2015.The result,according to the t test (P<0.05),showed that the arithmetic mean value fits the best.The accuracy of the model was above 70%.The area of high biomass was mainly distributed in the area of high HSI which was more than 0.4.The other areas of high HSI might be potential fishing grounds.