Species identification of fish shoals using coupled split-beam and multibeam echosounders and two scuba-diving observational methods

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Viviane David , Anne Mouget , Pierre Thiriet , Corentin Minart , Yannick Perrot , Loïc Le Goff , Olivier Bianchimani , Solène Basthard-Bogain , Tristan Estaque , Justine Richaume , Jean-François Sys , Adrien Cheminée , Eric Feunteun , Anthony Acou , Patrice Brehmer
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引用次数: 2

Abstract

Species identification remains crucial for interpreting acoustic backscatter delivered by active acoustic methodologies. The study took place in a Marine Protected Area where highly restricted areas were present such as no take zones. We used an innovative methodology coupling split-beam and multibeam echosounders to detect and classify monospecific fish shoals (i.e. schools or aggregations). Species identifications were realised by underwater visual censuses made by scientific divers. Two experimental protocols, where the divers gave the identifications instantaneously thanks to a communication wireframe, were tested: three roving scuba divers locating the shoals or a towed scuba diver directly behind the vessel. Energy responses, 3-D morphological, shape indexes and spatial descriptive variables of multiple independent samples of 4 observed fish species shoals (Atherina sp., Boops boops, Chromis chromis and Spicara maena) were calculated from the acoustic data. According to their behaviour and feeding strategy, significant differences in the acoustic variables were found between species. The combined use of acoustic data from both echosounders significantly improved the fish species classification. They were well discriminated using a Linear Discriminant Analysis (LDA), including for B. boops, C. chromis and S. maena, which were all observed in aggregations. Finally, we used this LDA model to allocate species to unknown shoals monitored by acoustics methods in the studied site, highlighting the interest of our methodology to predict bentho-pelagic and pelagic fish distributions in shallow waters. We suggest that these acoustic methods to discriminate fish species could provide valuable insights for marine management and decision-making.

利用耦合分束和多束回声测深仪和两种水肺潜水观测方法识别鱼群
物种识别对于解释主动声学方法提供的声学反向散射仍然至关重要。这项研究是在一个海洋保护区进行的,那里有高度限制的区域,如禁渔区。我们使用了一种创新的方法,将分束和多束回声测深仪相结合,来检测和分类单特异性鱼群(即鱼群或集合体)。物种鉴定是通过科学潜水员进行的水下视觉普查来实现的。测试了两个实验方案,即潜水员通过通信线框即时进行识别:三名流动水肺潜水员定位浅滩,或一名拖曳水肺潜水员直接在船后。根据声学数据计算了4个观察到的鱼群(Atherina sp.、Boops Boops、Chromis Chromis和Spicara maena)的多个独立样本的能量响应、三维形态、形状指数和空间描述变量。根据它们的行为和进食策略,不同物种之间的声学变量存在显著差异。两种回声测深仪的声学数据的结合使用显著改善了鱼类的分类。使用线性判别分析(LDA)对它们进行了很好的判别,包括B.boops、C.chromis和S.maena,它们都在聚集中观察到。最后,我们使用该LDA模型将物种分配到研究地点通过声学方法监测的未知浅滩,突出了我们的方法对预测浅水区底栖中上层和中上层鱼类分布的兴趣。我们认为,这些识别鱼类物种的声学方法可以为海洋管理和决策提供有价值的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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