Farms In Norway Research Articles

Opportunities and challenges in new production systems for salmon farming in Norway—Industry perspective

The Norwegian salmon farming industry is characterized by an increasing technological diversity with new production systems emerging. The objective of this paper is to provide knowledge about challenges and opportunities with new production systems as perceived by industry representatives with hands-on experience. Interviews and workshops with fish farmers and suppliers illustrate that even though environmental issues concerning salmon lice, escapes, and diseases can be reduced, and in some cases solved, new challenges might arise. Semi-closed containment and land-based system concerns pertained to water quality and fish welfare, while exposed and offshore systems were more concerned about harsh conditions and their effects on fish, structures, and work operations. However, possibilities for beneficial new production strategies, the potential for a more stable production environment, and increased biosecurity are seen as important advantages. These findings provide valuable perspectives for industry, technology suppliers, and regulators moving forward.

Conventional or organic cattle farming? Trade-offs between crop yield, livestock capacity, organic premiums, and government payments

CONTEXTAn important question for farmers is whether to run their farm conventionally or organically. This choice can significantly affect the farm's financial performance and its impact on the environment. OBJECTIVEThe primary objective of this study is to compare the profitability of conventional and organic cattle systems and investigate how it is associated with individual farm characteristics, like forage production capacity, forage quality, milk quota, animal housing capacity, and their relative presences. METHODWe employ a whole farm optimization model, customized for Norwegian cattle farming. The primary goal of this model is to maximize the gross margin by optimizing decisions related to land usage and animal inventory while adhering to a set of constraints. We systematically solve more than 200,000 model instances, with varying farm characteristics. RESULTS AND CONCLUSIONSThe results can be distilled to the following key points: If forage of good quality is readily available, but the livestock operation cannot be expanded due to animal housing and milk quota restrictions, organic may outcompete conventional farming. Otherwise, gross margin is maximized with conventional farming. These findings emphasize the crucial role of forage production capacity and quality in relation to available milk quota and infrastructure when considering the transition from conventional to organic farming. Extensive sensitivity analyses affirm the robustness of these conclusions. Regional regulatory factors, such as government farm payments, also play a significant role, and influence the optimal farming approach. Additionally, we show that increases in organic price premiums can markedly impact the competitiveness of organic farming, even in a system where government payments make out a significant part of the farm revenue. SIGNIFICANCEThe model can support farmers to make informed decisions about converting to organic or conventional farming. It can also be used by policymakers to determine the level of support required to make it worthwhile for different types of farms to convert. We also show that existing government payment schemes give rise to regional differences in the incentives for organic farming in Norway. To ensure equal incentives for organic farming across the country, the organic payments would have to be regionally adjusted, in line with the other already regionally dependent government payments. This insight may be of significant interest to policymakers and other stakeholders.

Energy (in)justice in the green energy transition. The case of Fosen wind farms in Norway

In 2021, the Norwegian Supreme Court ruled that wind power licences issued in 2010 for two wind farms in the Fosen area near Trondheim violated the cultural rights of the local Sámi herders. The Fosen case is of interest as it demonstrates how policy intervention to honour the human rights of citizens to a healthy environment came into conflict with the indigenous human rights. Our study explores why this wind power project became a policy failure and what the Sámi achieved in terms of green energy justice through their legal and political struggles as well as settlement agreements. The green energy justice framework fails to address longstanding indigenous injustices and inequalities. Hence, it needs to recognise traditional knowledge, assess the historical context of the intervention, and include a veto right to indigenous minorities to ensure that their rights protected by Article 27 of the ICCPR are respected. The policy failure involved opposition among the Sámi herders to the intervention. The failure occurred as politics shaped the decision and decision-making process underestimated the impact on reindeer husbandry and ignored the objections raised by the Sámi herders. The Supreme Court ruling addressed the reasons for the policy failure and strengthened the indigenous dimensions of the green energy justice. The Sámi herders and their supports were unable to mobilise public media support for the removal of the windmills to undo the human rights violation. Hence, the settlement agreements included distributional justice in the form of monetary compensation and the recognition of their need for new land for winter grazing as well as strengthening of their procedural justice with granting of a veto right on future licenses of the two wind farms.

What affects the level of local social acceptance of salmon farming in Norway?

The concept of a social licence to operate (SLO) that first emerged related to mining has been developed into several strands of theoretical models and used to study the social acceptance of industries in different contexts. There is an emerging literature on SLO for salmon-farming, but very few quantitative analyses are done to identify and assess factors that affect the level of social acceptance. Models that explain social acceptance levels from people's trust in an industry or company, their confidence in governance, and views on procedural and distributional fairness (trust models) are designed for quantitative analysis, and they have been successful in explaining social acceptance levels for mining. In this paper, we use survey data to test whether the factors in trust models can also explain the level of local social acceptance for salmon farming in Norway. From the structural equation modelling analysis, we conclude that these models at best have limited explanatory power in our case. We then develop an alternative model to analyse social acceptance, where factors of perception and attitudes and respondents' individual characteristics are tested as direct regression paths to influence level of acceptance. This model explains the variation in the data well. The factors that most strongly affect the level of acceptance, and which industry or authorities also can influence, are the perception of to what degree aquaculture is environmentally sustainable, whether the industry acts according to society's expectations, and if the industry is trustworthy. Practical implications for the industry and governance are discussed.

Consequences of reduced effectiveness of salmon lice treatments for lice control

The effective control of ectoparasitic salmon lice, Lepeophtheirus salmonis, in fish farms is challenged by the salmon lice having developed resistance towards several antiparasitic drugs and by the effectiveness of non-medicinal treatments being limited by considerations of fish welfare. When new antiparasitics are introduced to the market, these should be used sparingly to slow resistance development. Using a population model for salmon lice parameterised for salmonid fish farms in Norway, we quantified how reduced treatment effectiveness influences treatment frequency and lice abundance. Furthermore, we investigated when in the production cycle a highly effective lice treatment leads to the largest reduction in the total number of treatments, mean lice abundance and lice larvae production. Results showed that reductions in treatment effectiveness to lower than 50% led to the steepest increases in treatment frequency and mean lice abundance, as well as to increased risk that lice abundance increased beyond control. The timing of the most effective treatment had only moderate effects on the total treatment need and the mean number of adult female lice through the production cycle, but large effect on the production of lice larvae in spring. These findings imply that farmers can optimise the timing of the most effective treatment to reduce the release of lice larvae in the period of year when wild salmonids are in coastal waters, without compromising total treatment need or mean lice levels.

A Billion‐Euro Industry? (De‐)territorialisation Processes of Norway's Seaweed Farming Assemblage

AbstractSeaweed farming is a rising sector in European policy narratives and is increasingly integrated in coastal countries' bioeconomy strategies. Norway aims to lead this European ‘Seaweed Revolution’. Envisioned as a ‘billion‐euro industry’, its development is in its infancy yet contains ambitions for upscaling and socio‐economic credentials that promote it as a sector for sustainable finance and investments. Through assemblage conceptualisation, the paper unfolds the relations that connect the fluid materialities of seaweed with ambitious business plans, coastal localities, calls for upscaling, complex markets and assesses the trajectories potentials for sector development. Instead of forecasting the future of seaweed farming in Norway, it displays how the sociospatial complexities of the Norwegian seaweed farming assemblages' components enable or disperse currently dominant and optimistic sectoral narratives, providing a critical window to highlight the underlying and partially contradictory processes that shape the development trajectories of a sector promoted as a beacon of sustainable transformation.

Life cycle cost analysis of a floating wind farm in the Norwegian Sea

The offshore wind energy industry has witnessed rapid growth in the past decade. Still, there is a lack of commercial floating wind projects due to the relatively high development costs and other factors. To facilitate the holistic evaluation of floating wind farms in Norway, this article investigates the levelized cost of energy of a floating offshore wind farm and its economic feasibility. The Troll field west of Bergen, Norway, is assumed to be the target offshore site, and a farm size of 50 wind turbines with a lifespan of 25 years are considered. Each floating wind turbine has a 15-megawatt turbine mounted on a semi-submersible floater. Based on detailed analysis, the levelized cost of energy of the wind farm is estimated to be approximately 100.7 $/MWh. The capital expenditure is the most prominent cost and constitutes 63.1% of the total cost, and the operational expenditure constitutes the remaining 36.9%. Further, sensitivity analyses show the influence of the lifespan, capacity factor, and project discount rate on the levelized cost of energy. The present study contributes to techno-economic evaluation of floating wind projects at an early phase.

Occurrence of salmonid alphavirus and piscine orthoreovirus-1 infections in migrating salmon (Salmo salar L.) post-smolt in western Norway.

Viral diseases are a serious problem in Atlantic salmon (Salmo salar L.) farming in Norway, often leading to reduced fish welfare and increased mortality. Disease outbreaks in salmon farms may lead to spread of viruses to the surrounding environment. There is a public concern that viral diseases may negatively affect the wild salmon populations. Pancreas disease (PD) caused by salmonid alphavirus (SAV) and heart and skeletal muscle inflammation (HSMI) caused by piscine orthoreovirus-1 (PRV-1) are common viral diseases in salmon farms in western Norway. In the current study, we investigated the occurrence of SAV and PRV-1 infections in 651 migrating salmon post-smolt collected from three fjord systems (Sognefjorden, Osterfjorden and Hardangerfjorden) located in western Norway in 2013 and 2014 by real-time RT-PCR. Of the collected post-smolts, 303 were of wild origin and 348 were hatchery-released. SAV was not detected in any of the tested post-smolt, but PRV-1 was detected in 4.6% of them. The Ct values of PRV-1 positive fish were usually high (mean 32.0; range: 20.1-36.8). PRV-1 prevalence in post-smolts from the three fjords was 6.1% in Sognefjorden followed by 4.8% in Osterfjorden and 2.3% in Hardangerfjorden. The prevalence PRV-1 was significantly higher in wild (6.9%) compared to hatchery-released post-smolt (2.6%). The occurrence of PRV-1 infection in the fish was lowest in the Hardangerfjorden which has the highest fish farming intensity. Our results suggest that SAV infection are uncommon in migrating smolt while PRV-1 infection can be detected at low level. These findings suggest that migrating smolts were at low risk from SAV or PRV-1 released from salmon farms located in their migration routes in 2013 and 2014.

Comparing quantile regression spline analyses and supervised machine learning for environmental quality assessment at coastal marine aquaculture installations.

Organic enrichment associated with marine finfish aquaculture is a local stressor of marine coastal ecosystems. To maintain ecosystem services, the implementation of biomonitoring programs focusing on benthic diversity is required. Traditionally, impact-indices are determined by extracting and identifying benthic macroinvertebrates from samples. However, this is a time-consuming and expensive method with low upscaling potential. A more rapid, inexpensive, and robust method to infer the environmental quality of marine environments is eDNA metabarcoding of bacterial communities. To infer the environmental quality of coastal habitats from metabarcoding data, two taxonomy-free approaches have been successfully applied for different geographical regions and monitoring goals, namely quantile regression splines (QRS) and supervised machine learning (SML). However, their comparative performance remains untested for monitoring the impact of organic enrichment introduced by aquaculture on marine coastal environments. We compared the performance of QRS and SML using bacterial metabarcoding data to infer the environmental quality of 230 aquaculture samples collected from seven farms in Norway and seven farms in Scotland along an organic enrichment gradient. As a measure of environmental quality, we used the Infaunal Quality Index (IQI) calculated from benthic macrofauna data (reference index). The QRS analysis plotted the abundance of amplicon sequence variants (ASVs) as a function to the IQI from which the ASVs with a defined abundance peak were assigned to eco-groups and a molecular IQI was subsequently calculated. In contrast, the SML approach built a random forest model to directly predict the macrofauna-based IQI. Our results show that both QRS and SML perform well in inferring the environmental quality with 89% and 90% accuracy, respectively. For both geographic regions, there was high correspondence between the reference IQI and both the inferred molecular IQIs (p < 0.001), with the SML model showing a higher coefficient of determination compared to QRS. Among the 20 most important ASVs identified by the SML approach, 15 were congruent with the good quality spline ASV indicators identified via QRS for both Norwegian and Scottish salmon farms. More research on the response of the ASVs to organic enrichment and the co-influence of other environmental parameters is necessary to eventually select the most powerful stressor-specific indicators. Even though both approaches are promising to infer environmental quality based on metabarcoding data, SML showed to be more powerful in handling the natural variability. For the improvement of the SML model, addition of new samples is still required, as background noise introduced by high spatio-temporal variability can be reduced. Overall, we recommend the development of a powerful SML approach that will be onwards applied for monitoring the impact of aquaculture on marine ecosystems based on eDNA metabarcoding data.

Welfare and survival of lumpfish (Cyclopterus lumpus) in Norwegian commercial Atlantic salmon (Salmo salar) production

Lumpfish are currently used as a part of the overall strategy for the prevention and control of sea lice in Atlantic salmon farming in Norway. Their use as biological delousers is advantageous as it exposes salmon to very little stress and injuries. However, there is a growing concern and criticism about the welfare and survival of lumpfish in salmon farms. This study monitored the welfare and survival of lumpfish from four commercial salmon farms for 6 to 12 months in 2019–2021. Environmental and production conditions were also registered. Lumpfish welfare decreased during the study period, mainly related to eye and skin injuries. Mortality rate was low in the first few months after transfer to sea, but increased thereafter. Mechanical delousing affected the welfare and survival most negatively of all monitored external parameters. Even though diseases are often pointed out as the main factor for mortality of lumpfish in sea cages, it was not the case in the present study. However, there were indications that diseases are more likely to occur when lumpfish is already weakened by other factors such as mechanical delousing. One to two thirds of lumpfish were assessed as underweighted or emaciated at all time during the monitoring period, suggesting that the nutritional requirements of lumpfish are not fully met in sea cages.

IMPACT OF GLOBAL WARMING ON AQUACULTURE IN NORWAY

While aquaculture is predicted to play a significant role in addressing future global food demands, climate change is having a complex impact on aquaculture output. Climate change will have an effect on output levels, growth, feeding efficiency, and consequently farm productivity and profitability. The most significant challenges facing aquaculture are current and future climate change, which affects the viability of fish farming in Norway and around the world. Global warming and climate change have resulted in a decline in lake waters, an increase in sea level, changes in streams, and changes in precipitation models, all of which have begun to have a negative influence on all aquatic animals. According to the findings of this study, the yearly maximum temperature was 21.1 °C in July and the lowest was -2.8 °C in January, with the minimum temperature ranging from 13.5 °C in July to -7.5 °C in January. The highest average temperature was 17.4 °C in July, and the lowest was -5.1 °C in January. In terms of precipitation, the greatest was 118 mm in August, while the lowest was 56 mm in March. In terms of rainy days, the highest total was 11 mm in August, while the lowest total was 6 mm in March. In November, the humidity reached 90%, whereas in June, it was 66%. On bright days, the highest daylight hours were recorded in June at 12.1 hours, and the lowest hours were recorded in December at 2.5 hours. In this research, we explicitly investigated how these climate components may affect aquaculture in Norway. As a result, because it affects the stability of fish farming, this significant environmental issue must be addressed. It is critical to shed light on and thoroughly analyse the elements related to climate change in order to avoid the damages that result from them, as well as to identify strategies to adapt to these conditions and limit their effects on production and productivity. Corrective efforts should be implemented to reduce climate change and its consequences on fish output.

Life history traits for Ophryotrocha craigsmithi (Wiklund, Glover &amp; Dahlgren, 2009), a candidate species in integrated multitrophic aquaculture

Ophryotrocha craigsmithi (Wiklund, Glover &amp;amp; Dahlgren, 2009) has repeatedly been observed in high densities at salmonid fish farms in Norway and has been shown to feed on the organic waste released during fish production. This species has therefore been pointed out as a candidate for the benthic component of integrated multitrophic aquaculture (IMTA). Little is known about the life history traits of Ophryotrocha species found at greater depths in temperate waters. Insight into life traits is of key importance in evaluating the bio-mitigation and harvest potential of (benthic) species within IMTA systems. In this study, we aimed to describe key life history traits for O. craigsmithi, such as growth, reproductive pattern, and offset of reproduction. The main findings are as follows: (I) O. craigsmithi exhibits early sexual maturation and rapid growth, going from 5 to 16 mm in length in 8 weeks; (II) their estimated lifetime is approximately 15 weeks with a generation time of 4 weeks; (III) there are strong indications that they are gonochoric semicontinuous spawners; (IV) the majority of mature eggs ranged from 120 to 150 µm; and (V) the larvae developed into a free-swimming stage after approximately 1 week. To this end, we present a framework for assessing the suitability of deposit-feeding polychaetes as candidate species in IMTA, considering environmental adaptiveness, production potential, as well as carbon and nitrogen mitigation capacity. On the basis of this, O. craigsmithi shows a high suitability as an extractive farmed species in benthic IMTA.

Goats are able to adapt to virtual fencing; A field study in commercial goat herds on Norwegian farms

Virtual fencing technology has been developed over the last decades with the goal of giving farmers a flexible fence solution especially for remote rangeland. The latest technology is based on the use of Global Positioning System (GPS), mobile phone networks and internet applications. During the autumn of 2017 a field study was performed on eight commercial goat farms in Norway by using the Nofence virtual fencing technology. The main aim of the study was to describe the ability of goats to adapt to virtual fencing with three different sets of conditions. The first condition consisted of six groups with a total of 53 goats naïve to virtual fencing, that were introduced to and enclosed by a virtual fence. The second consisted of ten groups with a total of 92 goats already accustomed to virtual fencing being held on their regular pasture enclosed by a virtual fence. The third condition consisted of four groups with a total of 45 goats accustomed to virtual fencing that were moved to or given new rangeland areas enclosed by a virtual fence. All sets of conditions lasted for five days, and the number of audio cues and electric stimuli were automatically registered for all individual animals. A success ratio was calculated based on these measures. All variables were analyzed using a Generalized Linear Mixed Model with either a Poisson or Binomial distribution. The number of escapes were also registered. For the naïve goats, the mean number of audio cues and electric stimuli per goat were reduced from day one to day five, while the success ratio increased. On day one, 22 goats escaped whereas on day four and five no goats escaped. For the accustomed goats, the success ratio was significantly higher than that for the naïve goats, but not different from accustomed and moved. The total number of escapes in this condition was 7. For accustomed and moved, the success ratio was similar to the accustomed goats, but there was large variation across days, also in the number of audio cues. Escapes were only registered in one of the groups. We concluded that goats could adapt to and be confined by virtual fencing in commercial herds, but there were large individual variations as well as variation between groups regarding the number of audio cues and electric stimuli received.

Loose housing-nothing to lose? Exploring the on-farm profitability, risk and agricultural policy consequences associated with a tie-stall ban on dairy farms

Due to stricter animal welfare regulations, in Norway tie-stalls for dairy cows are banned from 2034 onwards. The aim of this paper is to explore the profitability, risk and agricultural policy consequences associated with the transition from tie-stalls to loose housing. Data on farm economics and investments were collected from farm enterprise budgets on 66 farms that have built new cowsheds in recent years in Vestland county. Vestland was chosen because on average it has the smallest dairy farms in Norway, with 45 percent of the herds having less than 20 cows. To analyze profitability and risk we used net present value and stochastic simulation. The findings show that irrespective of herd size, to continue farming with an upgraded tie-stall is more profitable than to invest in new loose housing. For farms with less than 30 cows, investment in new loose housing is on average not profitable and involves a high risk. Unless the Governmental investment grant is significantly increased, the tie-stall ban will have large consequences for farm structure and conflict several agricultural policy goals. Farmland in less favored districts may go out of production, making it more difficult to reach the policy goals of increasing food production, agriculture across the country, biodiversity and rural viability. Our findings are of interest to politicians in countries where one considers stricter animal welfare regulations, as well as planners and farmers who consider investing in new loose housing dairies.

The Dynamics of Profitability among Salmon Farmers—A Highly Volatile and Highly Profitable Sector

Salmon farming stands out from many other industries with its very high profitability, but it is also highly volatile. The main question is whether the profit of individual firms is stable, or whether profitable firms change from year to year. The purpose of this article is to apply the theory of profit persistence to answer this question for salmon farming in Norway. By using panel data from 2010 to 2019, available from public statistics, we study the relative deviation from the average profits. We estimate the speed of adjustment to the profit norm by using a dynamic GMM estimator. We find a high degree of convergence to the average profit among salmon farmers. For companies belonging to the group with below-average profit, there is a positive correlation between growth and profitability and a negative link between debt ratio and deviation of profit rate. Our finding is that although the Norwegian aquaculture industry has large profits, there is large volatility in the profits of this industry. This is useful knowledge for investors, lenders, public authorities and others who need to know something about the risk in the aquaculture industry.

Associations among nutrient concentration, silage fermentation products, in vivo organic matter digestibility, rumen fermentation and in vitro methane yield in 78 grass silages

Grass-clover silage constitutes a large part of ruminant diets in Northern and Western Europe, but the impact of silage quality on methane (CH4) production is largely unknown. This study was conducted to identify the quality attributes of grass silage associated with variation in CH4 yield. We expected that silage nutrient concentrations and silage fermentation products would affect CH4 yield, and that these factors could be used to predict the methanogenic potential of the silages. Round bales (n = 78) of grass and grass-clover silage from 37 farms in Norway were sampled, incubated, and screened for in vitro CH4 yield, i.e. CH4 production expressed on the basis of incubated organic matter (CH4-OM) and digestible OM (CH4-dOM) using sheep. Concentration of indigestible neutral detergent fiber (iNDF) was quantified using the in situ technique. The data were subjected to correlation and principal component analyses. Stepwise multiple regression was used to model methanogenic potential of silages. Among all investigated silage composition variables, neutral detergent fiber (aNDFom) and water-soluble carbohydrate (WSC) concentrations obtained the greatest correlations to CH4-OM (r = −0.63 and r = 0.57, respectively, P < 0.001), while concentration of iNDF negatively correlated with CH4-OM (r = −0.48, P < 0.001). In vivo organic matter digestibility (OMD) and concentration of ammonia-N (NH3-N) in silages were also correlated to CH4-OM (r = 0.44 and r = −0.32, P < 0.001 and P < 0.01, respectively). The stepwise regression using CH4-OM as response variable included aNDFom, WSC, iNDF, silage propionic acid and pH in descending order. The stepwise regression using CH4-dOM as response variable included WSC, aNDFom and iNDF in descending order. Among in vitro rumen short chain fatty acids (SCFA), molar proportion of butyrate was the most prominent in increasing CH4-OM and CH4-dOM (r = 0.23 and r = 0.36, P < 0.05 and P < 0.01, respectively), while molar proportion of propionate was the most prominent SCFA in reducing CH4-OM and CH4-dOM (r = −0.23 and r = −0.26, respectively, P < 0.05). Regression models that account for silage quality attributes can be used to predict CH4 yield from silages with a coefficient of determination (R2) between 0.33 (CH4-dOM) and 0.65 (CH4-OM). In conclusion, concentration of WSC increased in vitro CH4-OM and CH4-dOM, while concentration of aNDFom and iNDF decreased CH4-OM and CH4-dOM in grass silages.

Technoeconomic Optimization of Grid-Connected Hybrid Pv-System for Model Farms in Norway with Electric Tractors

Technoeconomic Optimization of Grid-Connected Hybrid Pv-System for Model Farms in Norway with Electric Tractors

Description of ISAV-HPRΔ-positive salmon farms in Norway in 2020.

Description of ISAV-HPRΔ-positive salmon farms in Norway in 2020.

Data Driven Insight Into Fish Behaviour and Their Use for Precision Aquaculture

Aquaculture, or the farmed production of fish and shellfish, has grown rapidly, from supplying just 7% of fish for human consumption in 1974 to more than half in 2016. This rapid expansion has led to the growth of Precision Aquaculture concept that aims to exploit data-driven management of fish production, thereby improving the farmer's ability to monitor, control, and document biological processes in farms. Fundamental to this paradigm is monitoring of environmental and animal processes within a cage, and processing those data toward farm insight using models and analytics. This paper presents an analysis of environmental and fish behaviour datasets collected at three salmon farms in Norway, Scotland, and Canada. Information on fish behaviour were collected using hydroacoustic sensors that sampled the vertical distribution of fish in a cage at high spatial and temporal resolution, while a network of environmental sensors characterised local site conditions. We present an analysis of the hydroacoustic datasets using AutoML (or automatic machine learning) tools that enables developers with limited data science expertise to train high-quality models specific to the data at hand. We demonstrate how AutoML pipelines can be readily applied to aquaculture datasets to interrogate the data and quantify the primary features that explains data variance. Results demonstrate that variables such as temperature, wind conditions, and hour-of-day were important drivers of fish motion at all sites. Further, there were distinct differences in factors that influenced in-cage variations driven by local variables such as water depth and ambient environmental conditions (particularly dissolved oxygen). The framework offers a transferable approach to interrogate fish behaviour within farm systems, and quantify differences between sites.

Development of cod farming in Norway: Past and current biological and market status and future prospects and directions

AbstractAtlantic cod is a historically abundant species in the North Atlantic region and has contributed to the prosperity of many nations. But a decline in stocks in the last century has prompted to initiate commercial farming of cod in captive conditions. Several approaches have been employed ranging from stock enhancement, capture‐based aquaculture and intensive cod farming. However, except for the enhancement efforts which were carried out for almost a century, efforts on other methods were intermittent coinciding with lower quotas. Intensive farming was attempted in Norway, Scotland, Ireland, Canada, Iceland and Faroe Islands in the 2000s. But it was carried out hastily to cash in the demand for cod in the market even though there were many biological knowledge gaps that are required for a successful aquaculture venture. The reasons for the failure of commercial farming in Norway during the 2000s were not only because of limited knowledge of the biology of cod but also the economic meltdown in Europe in 2008. Cod farming came to a halt; however, the Norwegian National Cod Breeding Program (NCBP) initiated in 2003 continued to operate and produced a fifth generation of a domesticated cod in 2019. Efforts to fill the gaps and the selective breeding for better growth and disease resistance within NCBP have improved the quality of the juveniles produced. We will discuss the past efforts and reasons for failure in farming of cod, how the current situation looks and the future direction in terms of cod biology, political atmosphere and market.