黄海南部及东海黄鮟鱇时空分布

Spatiotemporal distribution of Lophius litulon in the southern Yellow Sea and East China Sea

为探究黄鮟鱇栖息地时空分布特征,根据2018年11月(秋季)和2019年1月(冬季)、5月(春季)、8月(夏季)在黄海南部和东海开展的近海渔业资源大面定点底拖调查资料和同步采集的底层水温、底层盐度、底层溶解氧及水深数据,利用提升回归树(BRT)模型确定各环境因子的权重,分别选用算术平均法(AMM)和几何平均法(GMM)构建不同季节黄鮟鱇栖息地适宜性指数(HSI)模型,并通过交叉验证对模型输出结果进行比较分析。结果表明:2018—2019年黄鮟鱇最适栖息地存在季节差异。春季,黄鮟鱇最适栖息于49 m以浅的长江口及江苏近海浅水区;夏、秋季最适栖息于底层水温8.9~10.9℃的黄海东南部深水区;冬季最适栖息于9.2~12.7℃的黄海南部和东海北部深水区。BRT模型分析结果显示,春季对黄鮟鱇总偏差贡献率最大的是水深,其余3季贡献率最大的均为底层水温。交叉验证发现,除夏季外,运用AMM算法且赋予权重的HSI模型拟合效果更优。黄海南部和东海黄鮟鱇的时空分布特征与其生态习性及环境因子密切相关。

In order to investigate the temporal-spatial distribution of yellow goosefish in the open waters of the southern Yellow Sea(SYS) and East China Sea(ECS), according to the fishery data by bottom-trawl surveys and environmental data including sea bottom temperature(SBT), sea bottom salinity(SBS), bottom concentration of dissolved oxygen(BDO) and depth during 2018-2019, we established habitat suitability index(HSI) models by arithmetic mean(AMM) and geometric mean(GMM) methods, and compared the model outputs by cross validations. Especially, the weight of each environmental factor was evaluated by boosted regression tree(BRT). Results showed that the area with the highest habitat quality varied among seasons. The yellow goosefish mainly inhabited in the adjacent area of the Yangtze River Estuary and coastal waters of Jiangsu Province with depth ranged from 22 to 49 m in spring. The optimal inhabitation was located in the SYS, with the bottom temperature ranged from 8.9-10.9 ℃ in summer and autumn. Particularly, the optimal inhabitation extended from the SYS to the ECS with bottom temperature ranged from 9.2-12.7 ℃ in winter. Results of BRT models showed that depth was the most important environmental factor in spring and bottom temperature was the crucial one in the other three seasons. Results of cross validation showed that the weighted AMM-based HSI model performed better for yellow goosefish in spring, autumn and winter. The distribution of yellow goosefish was closely related to its biological traits and environmental factors in the SYS and ECS, China.