印度洋长鳍金枪鱼栖息地指数模型的构建与验证
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S934

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国家自然科学基金浙江两化融合联合基金(U1609202);国家重点研发计划(2016YFC1400903,2019YFD0901404)


Construction and verification of a habitat suitability index model for the Indian Ocean albacore tuna
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    摘要:

    长鳍金枪鱼(Thunnus alalunga)因其经济价值、分布广泛,成为世界各国海洋渔业的主要捕捞对象之一。对长鳍金枪鱼进行渔场预报研究,可以提高捕捞效率和渔获产量,为渔业生产提供科学依据。选取了2006—2014年印度洋长鳍金枪鱼的生产数据,结合海洋表层的温度、盐度和叶绿素a浓度等3个环境因子,运用一元非线性指数模型按月份建立了各环境因子的印度洋长鳍金枪鱼单因子栖息地适应性指数(suitability index, SI)后,采用算术平均法获得综合栖息地适应性指数模型(habitat suitability index, HSI),并根据2016年印度洋渔业生产数据及相应海洋环境资料,基于地理信息系统(geographic information system,GIS)软件——ArcGIS对栖息地指数模型进行验证。研究表明该模型对渔场预报准确率约为90.56%,各HSI等级下平均预报准确率为87.46%,对于HSI等级4和5(IHSI>0.5)等较高HSI值渔区所代表的中心渔场,其平均准确率为71.82%,考虑到IHSI>0.5的产量平均比重达69.35%这一事实,说明所建立的HSI模型对印度洋长鳍金枪鱼具有较好的预报效果。

    Abstract:

    Because of its economic value and wide distribution, albacore tuna (Thunnus alalonga) has become one of the main fishing targets in the world’s marine fisheries. Prediction of albacore tuna can improve fishing efficiency and yield, and provide scientific basis for fishery production.The production data of albacore tuna in the Indian Ocean from 2006 to 2014 and three environmental factors of temperature, salinity and chlorophyll a concentration in the surface layer of the ocean were used in this study. The single-factor Suitability Index (SI) of Indian Ocean albacore tuna with various environmental factors was established monthly by using the single-variable non-linear index model. Then the arithmetic average method was used to obtain the comprehensive Habitat Suitability Index (HSI) model. Using the 2016 Indian ocean albacore tuna production data and the corresponding marine environment data, furthermore, the HSI model was verified based on the ArcGIS platform. The results show that the accuracy of the monthly fishing ground forecast is about 90.56% and the overall forecast accuracy for each HSI grade is 87.46%. Moreover, for the central fishing ground with IHSI>0.5, the average accuracy rate is 71.82%. Considering that the average yield ratio of IHSI>0.5 is 69.35%, it can be concluded that the established HSI model had a promising forecast effect for the Indian Ocean albacore tuna.

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张亚男,官文江,李阳东.印度洋长鳍金枪鱼栖息地指数模型的构建与验证[J].上海海洋大学学报,2020,29(2):268-279.
ZHANG Yanan, GUAN Wenjiang, LI Yangdong. Construction and verification of a habitat suitability index model for the Indian Ocean albacore tuna[J]. Journal of Shanghai Ocean University,2020,29(2):268-279.

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  • 收稿日期:2019-02-22
  • 最后修改日期:2019-07-18
  • 录用日期:2019-07-26
  • 在线发布日期: 2020-04-14
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