西北太平洋柔鱼洄游重心年际变化及预测

柔鱼(Ommastrephes bartramii)是西北太平洋海域重要的经济头足类,海洋环境决定其资源的空间分布,通过研究其洄游路径的时空变化趋势与海洋环境之间的关系,来推测柔鱼资源的空间分布是当前渔业资源学研究重点,对于实际生产也有重大意义。利用系统聚类分析和神经网络,根据2004年—2015年我国西北太平洋鱿钓生产统计数据和环境数据,包括海表面温度(Sea Surface Temperature,SST)、海表面盐度(Sea Surface Salinity,SSS)和叶绿素浓度(chlorophyll concentration,Chl-a)数据,结合尼诺转化指数(Trans-Ni1o index TNI),分析柔鱼洄游路径的时空变化和海洋环境之间的关系,预测柔鱼在海洋环境的影响下,洄游路径可能发生的变化。结果表明:柔鱼洄游重心的产量占比与洄游重心的离散度在10月和11月呈现出显著的负相关;洄游重心的纬度变化和TNI之间有着显著的正相关,而经度上并未呈现这一关系;研究利用神经网络模型建立了基于海表面温度、盐度和叶绿素浓度的柔鱼洄游路径时空变化的预测模型,预测结果显示,时间跨度在8—11月内,柔鱼洄游重心纬度上呈现南-北-南,经度上呈现出西-东-西的变化趋势,8月和9月预测洄游重心海域的产量占比为64%和68%,10月和11月,柔鱼种群进行产卵洄游。预测产量占比明显提高,预测海域产量占比为83%和89%。

Interannual variation and forecasting of Ommastrephes bartramii migration gravity in the northwest Pacific Ocean

Ommastrephes bartramii is a commercially important cephalopod in the northwest Pacific Ocean, and as ecological opportunist, the spatial distribution of its stock is determined by marine environment. Using the relationship between the spatio-temporal variation of the migratory path and the oceanic environment to predict the spatial distribution of the squid resources is the research emphasis of fishery resources. It has great significance to practical production. According to the fishing production data from Chinese fishing fleet, combined with sea surface temperature (SST), sea surface salinity (SSS), chlorophyll-a concentration (chl-a) and Trans-Niño index (TNI) in the northwest Pacific Ocean during August to November in 2004 to 2015, We used hierarchical cluster analysis and neural network to analyze the relationship between the spatio-temporal variation of the migratory path and the oceanic environment to predict the change of the migratory path of the squid under the influence of the oceanic environment.The results showed that the proportion of production of the migratory gravity of the squid is significantly negatively correlated with the dispersion degree in October and November. There is a significant positive correlation between the change of the migratory gravity in the latitude and the TNI, which does not appear in the longitude.The model of predicting the spatio-temporal variation of the migratory path of the squid was established by using the neural network combined with sea surface temperature, salinity and chlorophyll concentration. The results of forecasting showed that during August to November, the migration gravity of squid shows the change trend of south-north-south in the latitude, and the change trend of west-east-west in the longitude.In August and September, the estimated proportion of production of the migratory gravity area was 64% and 68% respectively. In October and November, the prediction accuracy rate has obviously improved, and the estimated proportion of production of the migratory gravity area was 83% and 89% respectively.