Vertical distribution of Atlantic salmon (Salmo solar L.) in net pens: trade-off between surface light avoidance and food attraction

Fernö, Anders; Huse, Ingvar; Juell, Jon‐Erik; Bjordal, Åsmund

doi:10.1016/0044-8486(94)00384-z

Cited by 94 publications

(90 citation statements)

References 15 publications

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“…In aquaculture cages and tanks, this can be shown as a high concentration of fish near the feeding area and increased schooling activity (Juell et al 1994, Chen andPurser 2001). A good feed anticipatory response and feed intake can be signs of high feeding motivation and unstressed fish (Fernö et al 1995(Fernö et al , 2006. Experiments with salmon subjected to classical conditioning showed Fish Physiol Biochem (2012) 38:17-41 27 that the anticipatory response after giving a conditioned signal was affected by acute stress, and the time for recovery to normal baseline behaviours was longer than the period of elevated cortisol levels (Stien et al 2007, Bratland et al 2010.…”

Section: Group Swimming Behaviourmentioning

confidence: 99%

Behavioural indicators of welfare in farmed fish

Martins¹,

Galhardo²,

Noble³

et al. 2011

Current Views on Fish Welfare

120

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Behaviour represents a reaction to the environment as fish perceive it and is therefore a key element of fish welfare. This review summarises the main findings on how behavioural changes have been used to assess welfare in farmed fish, using both functional and feeling-based approaches. Changes in foraging behaviour, ventilatory activity, aggression, individual and group swimming behaviour, stereotypic and abnormal behaviour have been linked with acute and chronic stressors in aquaculture and can therefore be regarded as likely indicators of poor welfare. On the contrary, measurements of exploratory behaviour, feed anticipatory activity and rewardrelated operant behaviour are beginning to be considered as indicators of positive emotions and welfare in

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Section: Group Swimming Behaviourmentioning

confidence: 99%

Behavioural indicators of welfare in farmed fish

Martins¹,

Galhardo²,

Noble³

et al. 2011

Current Views on Fish Welfare

120

View full text Add to dashboard Cite

show abstract

“…Extending the period of fallowing could have a beneficial effect (Bron et al 1993, Grant & Treasurer 1993 More effective feeding and satiation of fish may reduce contact between host and parasite at the surface of the pens (Fernö et al 1995, Lyndon & Toovey 2000 Different stock types may be more or less susceptible to infestation by sea lice (MacKinnon 1998) quently, no consideration could be given to this factor. Following consideration of farm size, it was decided to split this variable into 2 related factors: (1) to reflect the historical situation, i.e.…”

Section: Justificationmentioning

confidence: 99%

“…Different levels of salinity seen across sites might be expected to affect the numbers of lice present (Heuch 1995) Sites are fallowed before each production cycle and fish are free of parasites. Presence and abundance of wild fish can impact on lice infestation patterns and levels (Tully et al 1999, Butler 2002 Diseased fish may be more susceptible to lice infestation (Wootten et al 1982) Given that sea lice appear to be photo-tactic alteration in the ambient light conditions may result in changes in lice abundance levels (Fernö et al 1995) Lice levels on sites in Norway may be affected by prevailing winds (Wallace 1998). As wind drives surface current, where lice are known to be present, it could have an effect on sea lice recruitment to specific sites Table 3 shows those factors found to be significant (p < 0.20) and therefore included in the multiple regression analysis.…”

Section: Justificationmentioning

confidence: 99%

Identifying epidemiological factors affecting sea lice Lepeophtheirus salmonis abundance on Scottish salmon farms using general linear models

Revie¹,

Gettinby²,

Treasurer³

et al. 2003

Dis. Aquat. Org.

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The variation in Lepeophtheirus salmonis sea lice numbers across 40 Scottish salmon farm sites during 1996 to 2000 was analysed using mean mobile abundance for 3 important 6 mo periods within the production cycle. Using statistical regression techniques, over 20 management and environmental variables suspected to have an effect on controlling lice populations were investigated as potential risk factors. The findings and models developed provide a picture of mobile L. salmonis infestation patterns on Scottish farm sites collectively. The results identified level of treatment, type of treatment, cage volume, current speed, loch flushing time and sea lice levels in the preceding 6 mo period to be key explanatory factors. Factors such as stocking density, site biomass, water temperature and the presence of neighbours, previously cited to be important correlates of sea lice risk from analysis of individual sites over time, were not found to be important. Variation in mobile abundance in the first half of the second year of production could be adequately explained (adjusted R 2 between 55 and 72%) by the recorded data, suggesting that there is scope for management to control L. salmonis abundance, though much of the variation remains unexplained.

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“…With regards to swimming depth, subgroups within the same sea cage are commonly observed, and may be explained by different hunger levels or unsynchronized feeding rhythms (Juell and Westerberg 1993;Juell et al 1994;Juell 1995;Fernö et al 1995). A positive correlation between hunger level and surface attraction has been showed at group level for caged salmon (Juell et al 1994), and could be a likely cause of small and thus potentially hungrier fish to maintain position close to surface.…”

Section: Competition and Feedingmentioning

confidence: 99%

“…Our observation of higher average weight at night-time compared to daytime at both 6 and 9 m depth is in support of this. Negatively buoyant salmon behaviorally counter by increased swimming speed to generate hydrodynamic lift Korsøen et al 2009), and at night-time, caged Atlantic salmon reduce their swimming speed and normally ascend towards the surface (Fernö et al 1995;Oppedal et al 2001;Korsøen et al 2009). Slower swimming speed during darkness may thus constrain their vertical distribution with regards to maintaining buoyancy.…”

Section: Size Stratificationmentioning

confidence: 99%

Sea caged Atlantic salmon display size-dependent swimming depth

Folkedal

Stien

Nilsson

et al. 2012

Aquat. Living Resour.

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-The present study investigates vertical distribution of fish size in three 12 m × 12 m wide and 14 m deep sea cages stocked with Atlantic salmon of average weight from 3.5 to 3.7 kg, at commercial densities between 15.6 to 16.2 kg m −3 , in Norway. For each cage, individual fish weight were estimated by three 0.6 m × 0.6 m measuring frames as fish swam through. The frames were positioned at 3, 6 and 9 m depth. Recordings were carried out over five days per cage in succession, and during relatively stable environmental conditions in late autumn 2010. In all cages, measured fish were 15−25% smaller at 3 m compared to the average weights at 6 and 9 m depth. Largest average weight difference between depths within one cage was 0.995 kg. The average weight at 6 and 9 m was higher at night-time compared to daytime. Fish at the lower end of the weight spectrum were predominantly registered at 3 m, while fish at the higher end of the spectrum were mostly registered at the greater depths. Fish of average size were well represented at all three depths. The fact that smaller fish swam shallower may be ascribed to natural behavioural traits and introduce an important consideration in representative sampling within commercial sea cages. In biomass estimations and sea lice counts size-dependent vertical stratification needs to be accounted for.

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Vertical distribution of Atlantic salmon (Salmo solar L.) in net pens: trade-off between surface light avoidance and food attraction

Cited by 94 publications

References 15 publications

Behavioural indicators of welfare in farmed fish

Behavioural indicators of welfare in farmed fish

Identifying epidemiological factors affecting sea lice Lepeophtheirus salmonis abundance on Scottish salmon farms using general linear models

Sea caged Atlantic salmon display size-dependent swimming depth

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