Effects of regional coordination of salmon louse control in reducing negative impacts of salmonid aquaculture on wild salmonids.

Parasitic salmon lice (Lepeophtheirus salmonis) are a constraint to the sustainable growth of salmonids in open net pens, and this issue has caused production to level off in recent years in the most aquaculture-intensive areas of Norway. The maximum allowed biomass at a regional level is regulated by using the so-called "traffic light" system, where salmon louse-induced mortality of migrating wild salmon post-smolts is evaluated against set targets. As a case study, we have investigated how a specific aquaculture-intensive area can reduce its louse levels sufficiently to achieve a low impact on wild salmon. Analyses of the output from a virtual post-smolt model that uses data on the reported number of salmon lice in fish farms as key input data and estimates the salmon louse-induced mortality of wild out-migrating Atlantic salmon post-smolts, suggested that female louse abundance on the local farms must be halved in spring to reach the goal implied by the traffic light system. The outcome of a modelling scenario simulating a proposed new plan for coordinated production and fallowing proved beneficial, with an overall reduction in louse infestations and treatment efforts. The interannual variability in louse abundance in spring, however, increased for this scenario, implying unacceptably high louse abundance when many farms were in their second production year. We then combined the scenario with coordinated production with other louse control measures. Only measures that reduced the density of farmed salmonids in open cages in the study area resulted in reductions in salmon louse infestations to acceptable levels. This could be achieved either by stocking with larger fish to reduce exposure time or by reducing fish numbers, e.g. by producing in closed units.

Simulated effects of increasing salmonid production on sea lice populations in Norway.

Norway produces more than one million tonnes of salmonids every year, almost exclusively in open-water net pens. In 2014, the Norwegian government announced plans to increase salmonid production. However, increasing the number of farmed salmonids can have negative effects on the marine environment that threaten the industry's sustainability. In particular, production growth can lead to an increase in density-dependent diseases, including parasitic sea lice. The aim of this study was to simulate the effects of increased salmonid production on sea lice abundance using different scenarios for increasing the number of fish and for the management of sea lice. We used a previously developed, partly stage-structured model based on Norwegian production and environmental data to simulate the different scenarios. Our results show that increasing the marine farmed salmonid population at a national level by two or five times the current production leads to an increase in the sea lice abundance by 3.5% and 7.1%, respectively. We also found that by lowering the maximum allowable level of sea lice to an average of 0.049 adult females per fish, weekly treatments can be used to control sea lice population growth with a five times increase in production. However, this increases the number of farms treating per week by as much as 281.3%, which can lead to high costs and increased mortality among farmed salmonids. Overall, the results from our study shed light on the effects of increasing salmonid production in Norway with respect to the ongoing threat of sea lice infestations.

Surveillance of the Sensitivity towards Antiparasitic Bath-Treatments in the Salmon Louse (Lepeophtheirus salmonis).

The evolution of drug resistant parasitic sea lice is of major concern to the salmon farming industry worldwide and challenges sustainable growth of this enterprise. To assess current status and development of L. salmonis sensitivity towards different pesticides used for parasite control in Norwegian salmon farming, a national surveillance programme was implemented in 2013. The programme aims to summarize data on the use of different pesticides applied to control L. salmonis and to test L. salmonis sensitivity to different pesticides in farms along the Norwegian coast. Here we analyse two years of test-data from biological assays designed to detect sensitivity-levels towards the pesticides azamethiphos and deltamethrin, both among the most common pesticides used in bath-treatments of farmed salmon in Norway in later years. The focus of the analysis is on how different variables predict the binomial outcome of the bioassay tests, being whether L. salmonis are immobilized/die or survive pesticide exposure. We found that local kernel densities of bath treatments, along with a spatial geographic index of test-farm locations, were significant predictors of the binomial outcome of the tests. Furthermore, the probability of L. salmonis being immobilized/dead after test-exposure was reduced by odds-ratios of 0.60 (95% CI: 0.42-0.86) for 2014 compared to 2013 and 0.39 (95% CI: 0.36-0.42) for low concentration compared to high concentration exposure. There were also significant but more marginal effects of parasite gender and developmental stage, and a relatively large random effect of test-farm. We conclude that the present data support an association between local intensities of bath treatments along the coast and the outcome of bioassay tests where salmon lice are exposed to azamethiphos or deltamethrin. Furthermore, there is a predictable structure of L. salmonis phenotypes along the coast in the data, characterized by high susceptibility to pesticides in the far north and far south, but low susceptibility in mid Norway. The study emphasizes the need to address local susceptibility to pesticides and the need for restrictive use of pesticides to preserve treatment efficacy.

Large scale modelling of salmon lice (Lepeophtheirus salmonis) infection pressure based on lice monitoring data from Norwegian salmonid farms.

Infection by parasitic sea lice is a substantial problem in industrial scale salmon farming. To control the problem, Norwegian salmonid farms are not permitted to exceed a threshold level of infection on their fish, and farms are required to monitor and report lice levels on a weekly basis to ensure compliance with the regulation. In the present study, we combine the monitoring data with a deterministic model for salmon lice population dynamics to estimate farm production of infectious lice stages. Furthermore, we use an empirical estimate of the relative risk of salmon lice transmission between farms, that depend on inter-farm distances, to estimate the external infection pressure at a farm site, i.e. the infection pressure from infective salmon lice of neighbouring farm origin. Finally, we test whether our estimates of infection pressure from neighbouring farms as well as internal within farm infection pressure, predicts subsequent development of infection in cohorts of farmed salmonids in their initial phase of marine production. We find that estimated external infection pressure is a main predictor of salmon lice population dynamics in newly stocked cohorts of salmonids. Our results emphasize the importance of keeping the production of infectious lice stages at low levels within local networks of salmon farms. Our model can easily be implemented for real time estimation of infection pressure at the national scale, utilizing the masses of data generated through the compulsory lice monitoring in salmon farms. The implementation of such a system should give the salmon industry greater predictability with respect to salmon lice infection levels, and aid the decision making process when the development of new farm sites are planned.

Multivariate evaluation of the effectiveness of treatment efficacy of cypermethrin against sea lice (Lepeophtheirus salmonis) in Atlantic salmon (Salmo salar).

BACKGROUND: The sea louse Lepeophtheirus salmonis is the most important ectoparasite of farmed Atlantic salmon (Salmo salar) in Norwegian aquaculture. Control of sea lice is primarily dependent on the use of delousing chemotherapeutants, which are both expensive, and toxic to other wildlife. The method most commonly used for monitoring treatment effectiveness relies on measuring the percentage reduction in the mobile stages of Lepeophtheirus salmonis only. However, this does not account for changes in the other sea lice stages and may result in misleading or incomplete interpretation regarding the effectiveness of treatment. With the aim of improving the evaluation of delousing treatments, we explored multivariate analyses of bath treatments using the topical pyrethroid, cypermethrin, in salmon pens at five Norwegian production sites. RESULTS: Conventional univariate analysis indicated reductions of over 90% in mobile stages at all sites. In contrast, multivariate analyses indicated differing treatment effectiveness between sites (p-value < 0.01) based on changes in the proportion and abundance of the chalimus and PAAM (pre-adult and adult males) stages. Low water temperatures and shortened intervals between sampling after treatment may account for the differences in the composition of chalimus and PAAM stage groups following treatment. Using multivariate analysis, such factors could be separated from those which were attributable to inadequate treatment or chemotherapeutant failure. CONCLUSIONS: Multivariate analyses for evaluation of treatment effectiveness against multiple life cycle stages of L. salmonis yield additional information beyond that derivable from univariate methods. This can aid in the identification of causes of apparent treatment failure in salmon aquaculture.

Risk mapping of heart and skeletal muscle inflammation in salmon farming.

Heart and skeletal muscle inflammation (HSMI) is an infectious disease causing losses to the Norwegian salmon farming industry due to increased mortality and high morbidity in infected salmon. The disease is listed as a notifiable disease on list 3 (national list) by the Norwegian Food Safety Authority. HSMI is believed to be a viral disease, but the association to the recently discovered Piscine reovirus (PRV) remains unclear. Undoubtedly, other factors interact to determine whether PRV-infected fish develop disease or not. In this study, logistic regression was used to model the risk of an outbreak of HSMI at the cohort level, by including spatio-temporal risk factors. The data consisted of fish cohorts grown on geo-referenced farms from 2002 to 2010. The risk factors included were: infection pressure, cohort size (maximum number of fish), cohort index (smolt characteristics), cohort lifespan (months in sea) and a geo-index calculated as the position along a local polynomial regression line based on the longitude and latitude of each farm included in the study. The results showed that the risk of developing HSMI increased with increasing cohort lifespan, increasing infection pressure and increasing cohort size, and was mostly low for cohorts grown on farms in Southern-Norway, high for farms in Mid-Norway and variable for farms in Northern-Norway (based on the geo-index). The final model was used to explore three different scenarios with regards to the risk of developing HSMI, and to calculate the probability for each cohort of developing HSMI, independent of their actual disease-status. The model suggested that the probability of developing HSMI was much higher in Mid-Norway than in the rest of the country. Even though PRV seems to be widely distributed in the environment, the finding that infection pressure has a large influence on the probability of developing HSMI, suggests that it might be possible to reduce the number of clinical outbreaks, if measures are taken to reduce infection pressure. However, the prospects of controlling the spread of HSMI and reducing clinical outbreaks might be difficult because of indications of large distance spread of the disease.

Sea lice as a density-dependent constraint to salmonid farming.

Fisheries catches worldwide have shown no increase over the last two decades, while aquaculture has been booming. To cover the demand for fish in the growing human population, continued high growth rates in aquaculture are needed. A potential constraint to such growth is infectious diseases, as disease transmission rates are expected to increase with increasing densities of farmed fish. Using an extensive dataset from all farms growing salmonids along the Norwegian coast, we document that densities of farmed salmonids surrounding individual farms have a strong effect on farm levels of parasitic sea lice and efforts to control sea lice infections. Furthermore, increased intervention efforts have been unsuccessful in controlling elevated infection levels in high salmonid density areas in 2009-2010. Our results emphasize host density effects of farmed salmonids on the population dynamics of sea lice and suggest that parasitic sea lice represent a potent negative feedback mechanism that may limit sustainable spatial densities of farmed salmonids.

Low virulent infectious salmon anaemia virus (ISAV-HPR0) is prevalent and geographically structured in Norwegian salmon farming.

Infectious salmon anaemia (ISA) is a severe disease in farmed Atlantic salmon Salmo salar that has caused epidemic outbreaks in most salmon-producing countries worldwide. The disease is caused by virulent ISA virus (ISAV). Low virulent variants of the virus, characterised by a full-length sequence in the highly polymorphic region of segment 6 in the virus genome, have been reported with increasing frequencies. These variants of the virus, termed HPR0, have been proposed to be ancestors of virulent ISAV. We examined this idea through studies of the phylogeographic and environmental distribution of ISAV-HPR0, as well as phylogeographic associations between virulent ISAV and ISAV-HPR0. Samples from 232 fish groups were screened for ISAV. Real-time RT-PCR was used for detection of ISAV, and the ISAV haemagglutinin esterase (HE) gene was characterised for positive samples. A Mantel test was used to test phylogeographic associations between pairs of ISAV-HPR0 HE gene sequences. A rank test was used to test associations between HE gene sequences from virulent ISAV and ISAV-HPR0. ISAV-HPR0 was detected in fish groups both in freshwater and marine environments, and in juveniles, on-grown marine salmon and broodstock salmon. Genetic and geographic distances between pairs of ISAV-HPR0 HE gene sequences were positively correlated, suggesting that the population of ISAV-HPR0 is geographically structured. Finally, we found a spatial association between fish groups with virulent ISAV (n = 21) and fish groups with ISAV-HPR0 (n = 27), supporting the hypothesis that ISAV-HPR0 may undergo a transition to virulent ISAV.

A stochastic model for the assessment of the transmission pathways of heart and skeleton muscle inflammation, pancreas disease and infectious salmon anaemia in marine fish farms in Norway.

Salmon farming is threatened, economically and ecologically, by infectious diseases. To reduce the risk of epidemics, authorities have developed regulations. These are based on quantitative understanding of pathways of infection, representing disease specific risks. A stochastic model was fitted to historical data, to estimate risk factors associated with competing spread mechanisms. Three infectious diseases were compared, heart and skeletal muscle inflammation (HSMI), pancreas disease (PD) and infectious salmon anaemia (ISA). This study was based on space-time data, from Norway from 2003 to 2007, describing the susceptible fish cohorts and the reported infections. Particular interest was given to seaway distances between farms and their local management organisation. The parameter measuring the effect of distance to an infectious fish farm was positive and significant for all diseases, implying that the risk involved with proximate infectious fish farms increased with decreasing distance. For HSMI and PD there was a significant effect of sharing a contact network with an infectious farm. For HSMI, but not for PD or ISA, there was a significant effect of previous infected cohorts on the same farm. The relative contribution of each transmission pathway was dominated by seaway distance for PD and HSMI, while other non-defined pathways dominated for ISA. This comparative study highlights that the three diseases have different patterns of spread, with important consequences for disease prevention and management.

Quantification of free-living Gyrodactylus salaris in an infested river and consequences for inter-river dispersal.

Gyrodactylus salaris is a major threat to wild populations of Atlantic salmon Salmo salar in Norway. Inter-river dispersal of this parasite is considered to be mainly linked to infested fish. Dispersal through movement of contaminated water is considered possible but has not been quantitatively evaluated. To approach this problem, we built a simple model to estimate (1) the water concentration of free-living G. salaris and (2) the probability that given water volumes would contain free-living parasites. The concentration was back-estimated from reported experimental observations on the number of salmon juveniles found to be infected after being caged in a heavily infested river in Norway, protected from direct contact with the substrate or fish. Monte Carlo simulation was used to account for uncertainty and variability. The average concentration of G. salaris in the water column during the experiment was estimated to be 0.12 m(-3) (95% CI = 0.05 to 0.24). The probability that a given volume would contain at least 1 parasite was 1.2 x 10(-4) (95% CI = 5 x 10(-5) to 2.4 x 10(-4)) for 1 l, increasing to 0.67 (95% CI = 0.39 to 0.91) for 10,000 l. Thus, only high volumes were likely to represent a significant risk. Since we used data from a heavily infested spot, and despite the fact that time and space variations in water concentration of G. salaris may occur, we conclude that the risk of inter-river dispersal due to transfer of infested water through common river activities by humans is probably low.

Geographic risk factors for inter-river dispersal of Gyrodactylus salaris in fjord systems in Norway.

Gyrodactylus salaris has been recorded in 46 Norwegian rivers since 1975 and is considered a threat to Atlantic salmon stocks. The primary introductions of G. salaris (primary infected rivers) have been accounted for by specific events, as reported in the literature. The parasite has subsequently dispersed to adjacent localities (secondary infected rivers). The objective of this paper is to address the occurrence of secondary infections by examining the hypothesis of inter-river dispersal of G. salaris. A dispersal model for the secondary river infections via migrating infected fish is proposed. Due to the limited tolerance of G. salaris to salinity, both freshwater inflow to dispersal pathways and dispersal distance were expected to influence the probability of inter-river dispersal. Eighteen rivers were categorised as primary infected rivers, 28 as secondary infected rivers, and 54 as rivers at risk. Four risk factors: the log10 freshwater inflow; the dispersal distance; the time at risk; and the salmon harvest were combined in a multi-variable logistic regression model of the probability of secondary infection. The final multi-variable model included log10 freshwater inflow (Wald chi-square = 9.93) and dispersal distance (Wald chi-square = 6.48). Receiver operating characteristic analyses of the final model supported freshwater inflow as a strong predictor of G. salaris infection status. The strong influence of the freshwater inflow on the probability of secondary infection adds further support to the hypothesis of inter-river dispersal of G. salaris through fjords.

A stochastic model for infectious salmon anemia (ISA) in Atlantic salmon farming.

Infectious salmon anemia (ISA) is one of the main infectious diseases in Atlantic salmon farming with major economical implications. Despite the strong regulatory interventions, the ISA epidemic is not under control, worldwide. We study the data covering salmon farming in Norway from 2002 to 2005 and propose a stochastic space-time model for the transmission of the virus. We model seaway transmission between farm sites, transmission through shared management and infrastructure, biomass effects and other potential pathways within the farming industry. We find that biomass has an effect on infectiousness, the local contact network and seaway distance of 5 km represent similar risks, but a large component of risk originates from other sources, among which are possibly infected salmon smolt and boat traffic.

Crabs, leeches and trypanosomes: an unholy trinity?

The red king crab Paralithodes camtschaticus was deliberately introduced to the Barents Sea in the 1960s and 1970s from its native area in the North Pacific. The carapace of these crabs is a favoured substrate for the leech Johanssonia arctica to deposit its eggs, and the leech is a vector for a trypanosome blood parasite of marine fish, including cod. We examined cod for trypanosome infections during annual cruises along the coast of Finnmark in North Norway over three successive years from stations along a gradient of over 1000 km. In every year the level of trypanosome infection in cod was significantly highest in the area with the greatest density of king crabs. We propose the hypothesis that the burgeoning population of red king crabs in this area is indirectly responsible for increased transmission of trypanosomes to cod by promoting an increase in the population of the leech vector.