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生物和非生物因子对秋季海州湾长蛇鲻栖息地适宜性的影响

朱承之 张云雷 赛可 韦雯钰 谢姝妤 夏铭璟 任一平 薛莹

朱承之,张云雷,赛可,等. 生物和非生物因子对秋季海州湾长蛇鲻栖息地适宜性的影响[J]. 海洋学报,2020,42(6):44–51 doi: 10.3969/j.issn.0253-4193.2020.06.006
引用本文: 朱承之,张云雷,赛可,等. 生物和非生物因子对秋季海州湾长蛇鲻栖息地适宜性的影响[J]. 海洋学报,2020,42(6):44–51 doi: 10.3969/j.issn.0253-4193.2020.06.006
Zhu Chengzhi,Zhang Yunlei,Sai Ke, et al. Impacts of biotic and abiotic factors on the habitat suitability of Saurida elongata during autumn in the Haizhou Bay, China[J]. Haiyang Xuebao,2020, 42(6):44–51 doi: 10.3969/j.issn.0253-4193.2020.06.006
Citation: Zhu Chengzhi,Zhang Yunlei,Sai Ke, et al. Impacts of biotic and abiotic factors on the habitat suitability of Saurida elongata during autumn in the Haizhou Bay, China[J]. Haiyang Xuebao,2020, 42(6):44–51 doi: 10.3969/j.issn.0253-4193.2020.06.006

生物和非生物因子对秋季海州湾长蛇鲻栖息地适宜性的影响

doi: 10.3969/j.issn.0253-4193.2020.06.006
基金项目: 山东省支持青岛海洋科学与技术试点国家实验室重大科技专项(2018SDKJ0501-2);国家自然科学基金项目(31772852,31802301)。
详细信息
    作者简介:

    朱承之(1998-),男,江西省上饶市人,主要研究方向为海洋渔业科学与技术。E-mail:1261903042@qq.com

    通讯作者:

    薛莹,教授,主要从事食物网营养动力学、鱼类栖息地和空间分布等领域的研究。E-mail:xueying@ouc.edu.cn

  • 中图分类号: P714+.5;S931.4

Impacts of biotic and abiotic factors on the habitat suitability of Saurida elongata during autumn in the Haizhou Bay, China

  • 摘要: 根据2011年和2013−2018年秋季在海州湾及邻近海域进行的底拖网调查数据,结合同步采集的底层水温、底层盐度、水深、资源密度、饵料生物等生物和非生物因子数据,开展长蛇鲻(Saurida elongata)栖息地适宜性的相关研究。利用提升回归树(Boosted Regression Tree, BRT)模型确定各环境因子的权重,分别采用算术平均法和几何平均法建立栖息地适宜性指数(Habitat Suitability Index, HSI)模型,并通过交叉验证确定最优模型。结果表明:海州湾长蛇鲻在秋季最适宜栖息的底层水温范围为17.5~18℃,最适底层盐度范围为31.3~32.0,最适水深范围为24~37 m;选择其3种主要饵料生物作为生物因子,即枪乌贼(Loligo spp.)、戴氏赤虾(Metapenaeopsis dalei)和六丝钝尾鰕虎鱼(Amblychaeturichthys hexanema),与底层水温、底层盐度和水深共同作为影响因子建立HSI模型。结果显示,对长蛇鲻空间分布总偏差贡献率最高的是饵料因子,其次是水深和底层水温。通过交叉验证发现,运用算术平均算法,且赋予权重的HSI模型具有较低的赤池信息准则值(Akaike Information Criterion, AIC)。研究发现,海州湾秋季长蛇鲻的最适栖息地(HSI≥0.7)主要分布在34.5°~36°N,119°~121°E之间,其中35°~36°N海域的最适栖息地分布范围大,而且从近岸至远海,HSI指数有增加的趋势。
  • 图  1  海州湾调查区域

    Fig.  1  Sampling areas in the Haizhou Bay

    图  2  海州湾长蛇鲻对底层水温、底层盐度、水深和饵料因子的适宜性指数曲线

    Fig.  2  Suitability index curves of bottom temperature, bottom salinity, water depth and prey factors for Saurida elongate in the Haizhou Bay

    图  3  各个非生物因子和生物因子对海州湾长蛇鲻提升回归树模型总偏差的相对贡献

    Fig.  3  Relative contribution of different abiotic and biotic factors to the total deviation explained by the boosted regression tree models of Saurida elongata in Haizhou Bay

    图  4  2011年和2013−2018年秋季海州湾长蛇鲻的HSI分布

    Fig.  4  Distribution of HSI for Saurida elongata during autumn of 2011 and 2013−2018 in the Haizhou Bay

    表  1  基于AMM算法和GMM算法的海州湾长蛇鲻HSI模型的交叉验证

    Tab.  1  Cross-validation of HSI model of the Haizhou Bay Saurida elongata based on AMM and GMM algorithm in mean confidence interval

    因子组合AMMGMM
    R2AICR2AIC
    A0.607 682.351 350.584 293.536 79
    B0.334 3415.573 710.316 7516.161 72
    C0.158 3719.380 210.059 7722.000 57
    D0.607 102.596 000.088 8222.215 53
    E0.879 06−24.771 300.751 92−14.411 00
    下载: 导出CSV

    表  2  AMM模型和GMM模型预测性能的比较

    Tab.  2  Comparison of prediction performance of AMM and GMM

    AMMGMM
    R2AICR2AIC
    0.879 06−24.771 30.751 92−14.411
    0.719 36−43.510 40.180 54−40.540 6
    0.956 35−5.062 30.951 215.563 29
    下载: 导出CSV
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出版历程
  • 收稿日期:  2019-10-19
  • 修回日期:  2019-12-17
  • 网络出版日期:  2020-11-18
  • 刊出日期:  2020-06-25

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