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应用生态学报 ›› 2023, Vol. 34 ›› Issue (2): 519-526.doi: 10.13287/j.1001-9332.202302.034

• 研究论文 • 上一篇    下一篇

黄海南部及东海黄鮟鱇时空分布

袁兴伟, 姜亚洲, 高小迪, 杨林林, 刘尊雷, 程家骅*   

  1. 中国水产科学研究院东海水产研究所/农业部东海与远洋渔业资源开发利用重点实验室, 上海 200090
  • 收稿日期:2022-04-04 接受日期:2022-12-01 出版日期:2023-02-15 发布日期:2023-08-15
  • 通讯作者: *E-mail: dhsziyuan@163.com
  • 作者简介:袁兴伟, 男, 1982年生, 副研究员。主要从事渔业资源评估研究。E-mail: yuanxw@ecsf.ac.cn
  • 基金资助:
    农业农村部近海渔业资源调查项目和农业农村部中日暂定水域渔业资源调查项目(2018—2019)

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

YUAN Xingwei, JIANG Yazhou, GAO Xiaodi, YANG Linlin, LIU Zunlei, CHENG Jiahua*   

  1. East China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences/Key Laboratory of East China Sea Fishery Resources Exploitation, Ministry of Agriculture and Rural Affairs, Shanghai 200090, China
  • Received:2022-04-04 Accepted:2022-12-01 Online:2023-02-15 Published:2023-08-15

摘要: 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。

关键词: 黄鮟鱇, 栖息地适宜性指数, 环境因子, 提升回归树, 时空分布

Abstract: 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.

Key words: Lophius litulon, habitat suitability index, environmental factor, boosted regression tree, spatio-temporal distribution