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基于DIDSON双频识别声纳技术的青草沙水库鱼类资源量评估

发布时间:2018-11-02 20:49
【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1.16×10~7~1.24×10~7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]:In September 2015, the main fish resources of Qingcaosha Reservoir were evaluated by using dual frequency recognition sonar DIDSON (Dual-Frequency Identification Sonar). The data collected by DIDSON were processed and analyzed by using fishery acoustics data processing software Echoview, and the accuracy of the software was verified by tracking and counting the fish body in the image. DIDSON was used to calculate the fish quantity and the fish body length and body mass were used to evaluate the resources of the main fish in the reservoir. The results show that the number of fish in the reservoir is about 1.16 脳 10 ~ (7) ~ 1.24 脳 10 ~ (7) by using the plane density method, and the proportion of small and medium-sized fish (20 cm) in the reservoir is more (78.3%). The proportion of medium and large fish (40 cm body length) was less (8.5%). According to the average body length mass relationship of fish in the reservoir area, it can be concluded that the fishery resources of the reservoir is about 4 620 ~ 4 980 t. The spatial distribution of fish mass in each route was analyzed by GIS. The results showed that there were more resources in the southeastern side of the reservoir and less in the west and north side of the reservoir. This paper creatively uses DIDSON sonar data to evaluate fishery resources of Qingcaosha Reservoir, obtains objective results, and puts forward some suggestions and prospects.
【作者单位】: 上海海洋大学海洋科学学院;上海市海洋局河口海洋测绘工程技术研究中心;上海海洋大学海洋生态与环境学院;上海海洋大学水产与生命学院;
【基金】: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)
【分类号】:S932.4

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