Biological, environmental, economic and ethical issues become increasingly pertinent as the scale of the aquaculture industry expands. This study used acoustic telemetry data and wavelet analysis to investigate behavioural patterns of Atlantic salmon when exposed to artificial underwater lights in fully stocked production cages located on the Norwegian coast. Using acoustic depth sensor tags, time series of depth registrations were gathered from 21 individual salmon distributed over three cages during a five-month experimental period. Underwater lights, normally used to suppress pre-harvest sexual maturation amongst Atlantic salmon, were installed at eight-metre depth and switched on in the middle of the experimental period. Swimming depth registrations initially showed a typical diurnal swimming behaviour, manifested by registrations generally in deeper waters during day-time than during night-time. The diurnal swimming behaviour abruptly ceased after the onset of lights. The change in swimming behaviour was detected by wavelet analysis and coincided with the introduction of underwater lights. Results from this study demonstrate the utility of wavelet analysis as a timely surveillance tool when investigating behavioural patterns of a periodic nature in fish, and specifically the individual response of farmed salmon to artificial lighting in a genuine industrial setting.

随着水产养殖业规模的扩大，生物、环境、经济和伦理问题变得越来越重要。本研究使用声学遥测数据和小波分析来研究大西洋鲑鱼在位于挪威海岸的储备充足的生产网箱中暴露于人工水下灯时的行为模式。使用声学深度传感器标签，在五个月的实验期间从分布在三个网箱中的 21 条鲑鱼中收集了深度记录的时间序列。水下灯通常用于抑制大西洋鲑鱼收获前的性成熟，安装在 8 米深，并在实验期间打开。游泳深度记录最初显示出典型的昼夜游泳行为，通常在白天比夜间更深的水域中记录。光照开始后，昼夜游泳行为突然停止。游泳行为的变化是通过小波分析检测到的，与水下灯光的引入相吻合。这项研究的结果证明了小波分析在调查鱼类周期性行为模式时作为一种及时监测工具的效用，特别是在真正的工业环境中养殖鲑鱼对人工照明的个体反应。