大亚湾核电临近海域中国毛虾声学探测分析

于2019年1月11―14日在大亚湾核电基地临近海域尝试采用声学探测技术,同时辅以拖网调查与水下视频观测的方法,对该海域中国毛虾(Acetes chinensis)的空间分布特征、定向迁移聚集规律和种群资源评估方法进行了研究分析,以期为大亚湾核电基地典型冷源致灾生物中国毛虾的监测预警与应急防控提供新的思路。调查发现,拖网渔获物中中国毛虾所占比重在99%以上,仅有数量极少的水母和鱼类。19:00―07:00的声学原位观测结果显示,不同时段中国毛虾海里面积反向散射系数(NASC)波动较大(0.56～170.30m~2/nmile~2),整体呈先增后减的变化趋势,最高值出现在22:30―22:40时段。垂直空间分布上,中国毛虾主要集群分布于水深5.2～7.2m的中下层水域,在22:50―00:10期间有明显向底层迁移的趋势。水平空间分布上,中国毛虾生物量密度由湾内至湾口断面逐渐增大。结合不同时段中国毛虾资源动态规律与水下视频观测结果,调查海域中国毛虾很可能在19:00―23:00期间向湾内迁移,23:00之后向湾口迁移。综上分析可知,声学评估方法较传统的渔业调查手段具有生态、高效、时空分辨率高、能提供实时监测数据等诸多优点,更能满足大亚湾核电站冷源生物安全预警与应急防控的现实需求。

Acoustic detection and analysis of Acetes chinensis in the adjacent waters of the Daya Bay Nuclear Power Plant

To provide a new option for the early warning, prevention, and control of the typical disaster-causing organism Acetes chinensis in the adjacent waters of Daya Bay Nuclear Power Station, an acoustic method, supplemented by a trawl survey and underwater video observation methods, was used to study the dynamics, spatial distribution characteristics, and migration trend of A. chinensis in the survey area from January 11 to 14, 2019. As a result, A. chinensis accounted for more than 99% of the captures collected by trawl samples, along with only a very few jellyfish and fish. Biomass density of A. chinensis estimated by the traditional sweeping area method was significantly higher than that derived from acoustic assessment. They showed a linear regression relationship:Y=2.3419X-3640.3 (Y depicts the result estimated by the traditional sweeping area method and X depicts the result derived from the acoustic assessment). According to in situ acoustic detection, the density of A. chinensis resources fluctuated greatly in different periods (0.56-170.30 m²/n mile²). This showed a general trend of first increasing and then decreasing, with the highest value during 22:30-22:40. In the vertical direction, A. chinensis was mainly distributed in the middle and lower waters at 5.2-7.2 m, and there was a clear downward migration trend from 22:50 to 00:10. In the horizontal direction, the biomass densities of A. chinensis in different transects increased gradually from the inside to the mouth of Daya Bay. Combined with dynamic regulation and the underwater video observations of A. chinensis resources in different time periods, it was likely that the A. chinensis would migrate into Daya Bay during 19:00-23:00, and then move back to the mouth of Daya Bay after 23:00. To further confirm this inference, in situ acoustic detection experiments should be conducted simultaneously in the adjacent waters of the Daya Bay Nuclear Power Plant and the mouth of Daya Bay, and the biotic and abiotic environmental factors, such as feed organisms, water temperature, salinity, and current among other factors should be considered comprehensively to further explore the driving mechanism of the horizontal migration of A. chinensis. In conclusion, compared with traditional investigation methods, the acoustic method has many advantages, such as scientific, efficient, and real-time monitoring. Therefore, it can better meet the practical needs of early warning, prevention, and control of cold source biosafety in the Daya Bay Nuclear Power Plant.