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A three-dimensional approach to school typology using vertical scanning multibeam sonar

机译:垂直扫描多束声纳的三维学校类型学方法

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Fish school typology is usually based on vertical echosounding images. These images provide little objective information on school structure (internal characteristics) or morphology (external characteristics). This paper considers the possibility of using multibeam sonar for 3D recording of the external morphology and internal structure of schools, to enhance the identification of typological criteria. We used recordings of 668 schools obtained from three different regions (Senegal, 68; Venezuela, 343; Mexico, 257) on two different Clupeids (Venezuela and Senegal: Sardinella aurita; Mexico: Sardinops sagax). We extracted 26 parameters (4 geographical; 6 morphological; 16 structural) from each school in the data base, using geostatistics and 3D image- reconstruction software. The schools were very homogeneous in most of their characteristics, presenting unimodal distributions of most parameters. Structural variables presented a higher power of discrimination (significant differences among zones, species and positions in the water column) than morphological ones. Multivariate statistics (principal component analysis followed by mixed hierarchical classification) allowed the definition of four main classes of schools. The conclusion is that the structural data provided by multibeam sonar improves the possibility of obtaining a consistent typology.
机译:鱼类学校的类型学通常基于垂直回波图像。这些图像几乎没有提供有关学校结构(内部特征)或形态(外部特征)的客观信息。本文考虑了使用多束声纳对学校的外部形态和内部结构进行3D记录的可能性,以增强对类型学标准的识别。我们使用了来自三个不同地区(塞内加尔68,委内瑞拉343,墨西哥257)的668所学校的录音,记录了两个不同的克鲁皮犬(委内瑞拉和塞内加尔:Sardinella aurita;墨西哥:Sardinops sagax)。我们使用地统计学和3D图像重建软件从数据库中的每个学校提取了26个参数(4个地理; 6个形态学; 16个结构)。这些学校的大多数特征都是非常同质的,呈现出大多数参数的单峰分布。结构变量比形态变量具有更高的判别力(水柱中区域,物种和位置之间的显着差异)。多元统计(主要成分分析,然后进行混合层次分类)允许定义四个主要班级的学校。结论是,多束声纳提供的结构数据提高了获得一致类型学的可能性。

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