基于DIDSON双频识别声纳技术的青草沙水库鱼类资源量评估
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上海海洋大学,上海海洋大学,上海海洋大学,上海海洋大学,上海海洋大学,上海海洋大学,上海海洋大学

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国家自然科学基金青年科学基金(41606210);上海市浦江人才计划(16PJ1403900);中国博士后科学基金(2015M581586)


Evaluation of fish resources in Qingcaosha Reservoir based on dual-frequency identification sonar technology
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College of Marine Sciences,Shanghai Ocean University,Shanghai,China,Shanghai Ocean University,Shanghai,China,Shanghai Ocean University,Shanghai,China,Shanghai Ocean University,Shanghai,China,Shanghai Ocean University,Shanghai,China,Shanghai Ocean University,Shanghai,China,Shanghai Ocean University,Shanghai,China

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    摘要:

    2015年9月利用双频识别声纳DIDSON(Dual-Frequency Identification Sonar)对青草沙水库的主要鱼类资源进行了探测评估。利用渔业声学数据处理软件Echoview对DIDSON采集的数据进行处理分析,对图像中的鱼体进行跟踪计数,结合人工目视计数验证了软件计数的准确性。运用DIDSON统计鱼类数量,并结合渔获物的鱼类体长、体质量等信息进一步评估水库中主要鱼类的资源量。评估结果表明,运用平面密度法统计水库鱼类数量约为1.16×107~1.24×107尾,水库中小型鱼类(体长<20 cm)在数量上所占比例较多(78.3%),而中大型鱼类(体长>40 cm)所占比例较少(8.5%)。由库区鱼类的平均体长体质量关系可得出水库渔业资源量约为4 620~4 980 t。利用GIS分析了各航线内鱼体质量的空间分布状态,结果显示水库东南侧深水区资源量较多,而水库西北侧资源量较少。本文创新性地利用DIDSON声纳数据进行青草沙水库渔业资源的评估,获得了客观的结果,并提出了一些建议及展望。

    Abstract:

    The main fish resources of Qingcaosha Reservoir were detected and evaluated by dual-frequency identification sonar (DIDSON) in September, 2015. The data collected by DIDSON are analyzed and processed by Fishery Acoustic Data Processing Software Echoview. The fish in the image is counted and the accuracy of software counting is verified by the artificial visual counting. The amount of major fish stocks in the reservoir was further evaluated based on the number of fish collected by DIDSON and the information on the fish length and weight of fish collected by the catch. The results show that the number of reservoir fish is about 1.16×107~1.24 ×107, and the proportion of small fish (length <20 cm) is 78.3%, while the medium and large fish (length> 40 cm) accounted for a small proportion (8.5%). From the relationship between the average body weight and body weight in the reservoir area,it can be concluded that the reservoir fishery resource is about 4 620~4 980 t. The spatial distribution of fish body weight in reservoirs was given by GIS method. The spatial distribution of fish weight in the route was analyzed by GIS. The results showed that there were more resources in the deep-water region on the southeast side of the reservoir, while the resources on the northwest side of the reservoir were generally less. The innovative applicability of DIDSON in assessing fishery resources of Qingcaosha Reservoir is discussed, and some suggestions and prospects are put forward.

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张翔,沈蔚,童剑锋,章守宇,龚小玲,陈明,魏宪云.基于DIDSON双频识别声纳技术的青草沙水库鱼类资源量评估[J].上海海洋大学学报,2017,26(4):561-569.
ZHANG Xiang, SHEN Wei, TONG Jianfeng, ZHANG Shouyu, GONG Xiaoling, CHEN Ming, WEI Xianyun. Evaluation of fish resources in Qingcaosha Reservoir based on dual-frequency identification sonar technology[J]. Journal of Shanghai Ocean University,2017,26(4):561-569.

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  • 收稿日期:2016-12-06
  • 最后修改日期:2017-04-05
  • 录用日期:2017-04-27
  • 在线发布日期: 2017-07-25
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