Waves and currents decrease the available space in a salmon cage

Johannesen, Ása; Patursson, Øystein; Kristmundsson, Jóhannus; Dam, Signar Pætursonur; Mulelid, Mats; Klebert, Pascal

doi:10.1371/journal.pone.0263850

Cited by 12 publications

(9 citation statements)

References 48 publications

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“…Analysis was carried out in R [44] and tidyverse [45] using the packages lubridate [46] and circular [47] for data cleanup, lme4 [48] and lmerTest [49] for statistical inference, performance [50] for model fit assessment, and ggplot2 [51] with colorspace [52] was used for plotting. All data and code used for the analysis is available on Github [43].…”

Section: Discussionmentioning

confidence: 99%

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Waves and currents decrease the available space in a salmon cage

Johannesen¹,

Patursson²,

Kristmundsson³

et al. 2021

Preprint

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Due to increasing demand for salmon and environmental barriers preventing expansion in established sites, salmon farmers seek to move or expand their production to more exposed sites. In this study we investigate the effects of strong currents and waves on the behaviour of salmon and how they choose to use the space available to them. Using video cameras and echo sounders, we show that fish prefer to use the entire water column, narrowing their range only as a response to cage deformation, waves, or daylight. Conversely, fish show strong horizontal preference, mostly occupying the portions of the cage exposed to currents. Additionally, waves cause salmon to move away from the sides of the cage. Even when strong currents and waves decrease the amount of available space, salmon choose to occupy the more exposed part of the cage. This indicates that at least with good water exchange, the high biomass caused by limited vertical space is not so aversive that salmon choose to move to less desirable areas of the cage. However, the dispersal throughout the entire available water column indicates that keeping the cone portion of the cage available in strong currents would be beneficial to salmon welfare.

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Section: Discussionmentioning

confidence: 99%

“…Once data had been exported, the exported files were read into R, where the surface and the lowest 4.5 metres (below the cage bottom) were removed. The code for the echo sounder data processing can be found on Github [43].…”

Section: Data Processingmentioning

confidence: 99%

Waves and currents decrease the available space in a salmon cage

Johannesen¹,

Patursson²,

Kristmundsson³

et al. 2021

Preprint

Self Cite

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show abstract

“…These cages move around due to mooring flexibility and undergo significant deformation when subjected to strong forcing from currents or large waves. As wave height increases, fish dive deeper to avoid unsteady water at the surface and swim farther from the net, reducing the available volume inside the cage that the fish can occupy [4].…”

Section: Introductionmentioning

confidence: 99%

“…Welfare concerns may also arise due to low oxygen conditions [7], causing fish to seek swimming depths with more favourable oxygen levels [6]. Moreover, other factors such as temperature [8], time of day [9], currents [4], [9], and waves [4] can also influence fish diving depth. Each of these factors can serve as an indicator of potential welfare issues for salmon.…”

Section: Introductionmentioning

confidence: 99%

“…Among the various non-invasive monitoring tools available, acoustic observations are particularly promising. This is primarily because this technology has the range to capture information on the scale of fish farms [4], contrary to alternatives such as submerged camera-based systems where the maximum range varies between 0.5 -25m [10]. The simplest form of acoustic observation is the active singlebeam sonar which, by producing acoustic pulses and measuring the backscatter, can produce information about the range and target strength of objects in the field of view.…”

Section: Introductionmentioning

confidence: 99%

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Fish Monitoring in Aquaculture Using Multibeam Echosounders and Machine Learning

Kristmundsson,

Patursson,

Potter

et al. 2023

IEEE Access

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Offshore salmon aquaculture is a growing industry that faces challenges such as sea lice infestations and varying environmental conditions, necessitating the development of new monitoring systems to improve fish welfare and sustainability. In this paper, we propose and test a machine learning based method for underwater detection and localisation using multibeam echosounders (MBES) in fish farming applications. We demonstrate a three-stage process involving data acquisition, pre-processing, and object detection. We then compare the performance of four different vision based deep learning object detection algorithms in different signal-to-noise scenarios by artificially adding noise to the pre-beamformed signals. This method successfully detects fish in MBES images, which has potential applications in optimising feeding schedules, behaviour analysis, and fish health monitoring. Furthermore, this method holds potential for the detection and tracking of other objects within fish farms, such as cages and mooring lines. This study paves the way for further development of MBES data being used as a non-invasive and automated monitoring method in aquaculture.

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Effect of diel light cycles on vertical migration patterns of Lepeophtheirus salmonis (Krøyer, 1837) copepodids measured in an in situ mesocosm

Hagemann,

Kvæstad,

Venås

2024

Aquacult Int

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The ectoparasitic salmon louse (Lepeophtheirus salmonis Krøyer, 1837) persists as a major hindrance for continued growth of the Norwegian salmon industry. Shielding technologies or management strategies are being used to reduce the likelihood of contact in the net pens between the salmon and the sea lice’s infectious copepodid stage. Knowledge about the vertical distribution and diel migration patterns of the planktonic sea lice stages are inevitably a premise for such water-depth-dependent avoidance technologies to be efficient; however, not many studies have investigated diel vertical migration patterns of sea lice in situ or in relevant scales. In this work, we aimed to monitor the diel migration of L. salmonis copepodids in the vertical plane without the influence of hydrographical forces, using sufficient water column depth of 11 m, natural thermoclines, and natural exogenous light conditions. We followed a cohort of copepodids over the course of 4 days and measured their vertical distribution in the water column twice per hour in a custom made mesocosm, using automatic particle detection and machine learning to analyse position and migration patterns. The L. salmonis copepodid population displayed reverse diel migration, and we found a statistically significant interaction between depth and time. During the day, copepodids were found in the upper 1 m of the water column, before the majority of the population descended to 1–2 m depth during night-time. A small fraction of the population remained in the upper part of the water column also during night-time. A significantly higher fraction of the copepodid population resided in the upper metre during daylight hours compared to other depths. These results could be utilised as input in sea lice dispersal models which are important management tools in today’s sea lice prevention strategies and regulatory frameworks.

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Waves and currents decrease the available space in a salmon cage

Cited by 12 publications

References 48 publications

Waves and currents decrease the available space in a salmon cage

Waves and currents decrease the available space in a salmon cage

Fish Monitoring in Aquaculture Using Multibeam Echosounders and Machine Learning

Effect of diel light cycles on vertical migration patterns of Lepeophtheirus salmonis (Krøyer, 1837) copepodids measured in an in situ mesocosm

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