Larsson Matz
Clinical Health Promotion Centre, Lund University, 22100 Lund, Sweden.
School of Health and Medical Sciences, Örebro University, 70182 Örebro, Sweden.
Animals (Basel). 2024 Jul 5;14(13):1984. doi: 10.3390/ani14131984.
The suggests that schooling can result in several benefits. (1) The acoustic pattern (AP) (pressure waves and other water movements) produced by swimming are likely to serve as signals within fish shoals, communicating useful spatial and temporal information between school members, enabling synchronized locomotion and influencing join, stay or leave decisions and shoal assortment. (2) Schooling is likely to reduce the masking of environmental signals, e.g., by auditory grouping, and fish may achieve windows of silence by simultaneously stopping their movements. (3) A solitary swimming fish produces an uncomplicated AP that will give a nearby predator's lateral line organ (LLO) excellent information, but, if extra fish join, they will produce increasingly complex and indecipherable APs. (4) Fishes swimming close to one another will also blur the electrosensory system (ESS) of predators. Since predators use multimodal information, and since information from the LLO and the ESS is more important than vision in many situations, schooling fish may acquire increased survival by confusing these sensory systems. The combined effects of such predator confusion and other acoustical benefits may contribute to why schooling became an adaptive success. A model encompassing the complex effects of synchronized group locomotion on LLO and ESS perception might increase the understanding of schooling behavior.
研究表明,集群行为能带来诸多益处。(1)鱼类游动产生的声学模式(AP)(压力波和其他水体运动)很可能在鱼群中充当信号,在鱼群成员之间传递有用的空间和时间信息,实现同步游动,并影响加入、停留或离开的决策以及鱼群的分类。(2)集群行为可能会减少环境信号的掩蔽,例如通过听觉分组,并且鱼类可能通过同时停止游动来获得安静的时段。(3)单独游动的鱼产生的声学模式简单,会给附近捕食者的侧线器官(LLO)提供很好的信息,但是,如果有额外的鱼加入,它们会产生越来越复杂且难以解读的声学模式。(4)彼此靠近游动的鱼也会模糊捕食者的电感应系统(ESS)。由于捕食者使用多模态信息,并且在许多情况下,来自侧线器官和电感应系统的信息比视觉信息更重要,集群的鱼可能通过混淆这些感官系统而提高生存率。这种捕食者混淆效应和其他声学益处的综合作用可能有助于解释为什么集群行为成为一种适应性成功。一个包含同步群体游动对侧线器官和电感应系统感知的复杂影响的模型,可能会增进对集群行为的理解。