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Evaluating the Environmental Conditions Required for the Development of Offshore Aquaculture: Impact on Farmed Atlantic Salmon Health and Welfare

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Abstract

Scottish salmon is worth over £2 billion to the country’s economy. It is Scotland’s top food export and a particularly valuable product, at about 10% above the world price. Recently, the Scottish Government developed a plan that aims at doubling this production of salmon by 2030. However, a number of factors limit the progress of the industry in its current form, which is based primarily on sea cages in sheltered, fjordic sea lochs where water exchange is restricted. These limitations include the impact of sea lice infestations on fish health (Black 2001), the cost and environmental impact of chemical treatments against the parasite (Costello 2009, SARF 2016, Van Geest 2014), their development of resistance to these treatments (Aaen et al. 2015), planning issues (James & Davies 2010), the (regulatory) Scottish Environment Protection Agency (SEPA) biomass limit of 2500t/site, and the increasing impact of harmful algal blooms (HABs), which can be particularly acute in restricted water exchange environments (Gowen et al. 2012). Moreover, the industry also faces opposition from environmental campaigners who fear that farming in sea lochs might damage wild stocks and the ecosystem. Development of aquaculture in more dispersive “offshore” environments offers a potential solution to some of these problems. Improved, science-based evidence with direct relevance to the complex environment of the west coast of Scotland will permit planning and informed regulation of this offshore transition. The project will address a number of the issues, specifically offshore developments, algal blooms, [sea lice/AGD] host-pathogen interactions and fish health and welfare. These will be addressed through four interconnected work packages: 1) Physical Oceanography, 2) Wave modelling and risk, 3) Hydrodynamic and sea lice/HAB modelling, and 4) Fish health and welfare implications. The latter addresses the particular issue of moving cages offshore and the impact on Atlantic Salmon health and welfare (Kirchhoff et al 2011, Ashley, 2007). Materials and methods Health historical data will be supplied by the partner salmon company regarding mortalities, condition, growth, health blood parameters, sea lice counts, and gross gill scores (e.g. amoebic gill disease (AGD) and proliferative gill disease (PGD)). Data on detailed morphometrics and welfare scoring indices (external appearance and fin and tissue damage) will be supplemented by ‘in situ’ sampling data in the same periods and at the same sites where the physical oceanography samplings take place. Environmental and physical data will also be provided by the company to complete the database from the sampling sites. There will be 3 main sampling points per treatment (offshore vs inshore farms), at which a total of 45 fish will be sampled per site (15 fish per cage, 3 cages per site, and 2 sites). Historical and newly-collected fish heath data will be analysed, through both univariate and multivariate statistics, in relation to physical oceanographic parameters, waves, sea lice, and HAB data, as well as by elaborating model predictions. Initial sampling was already performed in winter 2019. Fish were weighted and measured, sea lice, AGD and PGD scored and skin mucous, blood and tissue sampled and stored for posterior analysis. The next sampling will take place in spring 2019 and at harvest (August-September 2019). By the time of the conference, more data will be available. Results and Discussion Because this is an ongoing project and the current results are only preliminary, more data to support the claim of an offshore site’s potential in improving welfare in Atlantic salmon is needed. However, current results indicate that offshore environments presented significantly lower incidence of parasites (AGD, Caligus sp. and adult male sea lice) and had better welfare indicator scores, such as fin damage and cataracts. The decreased incidence of parasites could be the result of increased water velocities, improved aeration and net cleanliness in offshore sites. This increased water velocity could also explain the lower number of sea lice due to the increased difficulty in attachment to the fish (Revie et al., 2004). However, results indicate that fish were smaller in the offshore site. Later samplings will show whether this weight and length difference is maintained. Additional work and analysis of historical data is required to confidently validate the hypothesis that high energy offshore sites improve welfare and overall health of Atlantic salmon. However, current results are promising.
1: Physical Oceanography
Detailed physical
observations.
2: Wave Modelling and
Risk Analysis
Long-term (25-year) high
resolution hindcast wave
model simulations.
3: Hydrodynamic and Sea
Lice/HAB Modelling
Models used to evaluate
sea lice connectivity and
HAB development.
4: Fish Health and welfare
Offshore conditions are likely to have health and welfare implications.
Evaluating the Environmental Conditions Required for
the Development of OffshoreAquaculture: Impact on Farmed
Atlantic Salmon Health and Welfare
Four inter-connected
work packages
Offshore Inshore
Higher O2
concentration
Higher salinity levels
Higher energy (waves,
currents, tides…)
Sonia Rey · Aimee Wilford · Bernat Morro
38.20 m
8 m
8 m
assessed in
February
(winter) and
July (summer)
2019.
15 fish/pen,
3 pens/site
Weight
3.35 kg/m3
Summer
Winter Length Fulton index
Summer Summer
Winter
Winter
AGD score Cortisol
Summer Haematocrit
Winter
Chalimus Adult Adult Caligus sp.
Sea Lice Incidence
Summer
Summer Winter SummerSummer
****
**
*
*
*
*
Slower growth and lower Fulton index
Higher overall sea lice counts
Lower incidence of deformities/cataracts
Lower AGD incidence (not significant)
Lower stress levels
Lower O2
concentration
Lower salinity
levels
Lower energy
Winter Winter
Winter Winter Winter
Results
Conclusions: Effects of offshore conditions
Lepeophtheirus salmonis
Offshore Inshore
Morphometrics data, blood parameters and operational welfare indicators were
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