Understanding sources of sea lice for salmon farms in Chile

On the prediction of SAV transmission among Norwegian aquaculture sites

Pancreas Disease (PD) is a viral disease that affects Atlantic salmon (Salmo salar) in Norwegian, Scottish and Irish aquaculture. It is caused by salmonid alphavirus (SAV) and represents a significant problem in salmonid farming. Infection with SAV leads to reduced growth, mortality, product downgrading, and has a significant financial impact for the farms. The overall aim of this study is to evaluate the effect of various factors on the transmission of SAV and to create a predictive model capable of providing an early warning system for salmon farms within the Norwegian waters. Using a combination of publicly available databases, specifically BarentsWatch, and privately held PCR analyses a feature set consisting of 11 unique features was created based on the input parameters of the databases. An ensemble model was developed based on this feature set using XG-Boost, Ada-Boost, Random Forest and a Multilayer Perceptron. It was possible to successfully predict SAV transmission with 94.4% accuracy. Moreover, it was possible to predict SAV transmission 8 weeks in advance of a 'PD registration' at individual aquaculture salmon farming sites. Important predictors included well boat movement, environmental factors, proximity to sites with a 'PD registration' and seasonality.

Timing and probability of arrival for sea lice dispersing between salmon farms

Sea lice are a threat to the health of both wild and farmed salmon and an economic burden for salmon farms. With a free-living larval stage, sea lice can disperse tens of kilometres in the ocean between salmon farms, leading to connected sea louse populations that are difficult to control in isolation. In this paper, we develop a simple analytical model for the dispersal of sea lice (Lepeophtheirus salmonis) between two salmon farms. From the model, we calculate the arrival time distribution of sea lice dispersing between farms, as well as the level of cross-infection of sea lice. We also use numerical flows from a hydrodynamic model, coupled with a particle tracking model, to directly calculate the arrival time of sea lice dispersing between two farms in the Broughton Archipelago, British Columbia, in order to fit our analytical model and find realistic parameter estimates. Using the parametrized analytical model, we show that there is often an intermediate interfarm spacing that maximizes the level of cross-infection between farms, and that increased temperatures will lead to increased levels of cross-infection.

Estimating the dispersal of Lepeophtheirus salmonis sea lice within and among Atlantic salmon sites of the Bay of Fundy, New Brunswick

The objective of this study was to estimate the impact of infestation pressures on the abundance of the parasitic sea louse, Lepeophtheirus salmonis, in the Bay of Fundy, New Brunswick (NB), Canada, using the Fish-iTrends database for the years 2009-2018. Infestation pressures were calculated as time-lagged weighted averages of the abundance of adult female (AF) sea lice within a site (internal infestation pressure: IIP) and among sites (external infestation pressure: EIP). The EIP weights were calculated from seaway distances among sites and a Gaussian kernel density for bandwidths of 5 to 60 km. The EIP with a bandwidth of 10 km had the best fit, as determined with Akaike's information criterion, and historical AF sea lice abundance. This estimated dispersal distance of 10 km was similar to previous studies in Norway, Scotland and in New Brunswick. The infestation pressures estimated from empirical AF sea lice abundance within and among sites significantly increased the abundance of AF sea lice (p < .001). This study concludes that sea lice burdens within Atlantic salmon farms in the Bay of Fundy, NB, are affected by within site management and could be improved by synchronizing treatments between sites.

Epidemiological Factors Associated With Caligus rogercresseyi Infection, Abundance, and Spatial Distribution in Southern Chile

Sea lice (Caligus rogercresseyi) are external parasites that affect farmed salmonids in Chile, and the scale of their sanitary and economic impact cannot be overstated. Even though space–time patterns suppose parasite aggregation, specific locations related to different infestation levels, as well as their associated factors across the geographic range involved, had not been investigated as of the writing of the present article. The understanding of the effects and factors entailed by the presence of C. rogercresseyi may be deemed a key element of Integrated Pest Management (IPM). In the present study, the multivariate spatial scan statistic was used to identify geographic areas and times of C. rogercresseyi infestation and to estimate the factors associated with such patterns. We used official C. rogercresseyi monitoring data at the farm level, with a set of 13 covariates, to provide adjustment within the analyses. The analyses were carried out for a period of 5 years (2012–2016), and they included three fish species (Salmo salar, Oncorhynchus mykiss, and Oncorhynchus kisutch) in order to assess the consistency of the identified clusters. A retrospective multinomial, spatial, and temporal scan test was implemented to identify farm clusters of either of the different categories of C. rogercresseyi infested farms: baseline, medium, and high, based on the control chemical threshold established by the health authority. The baseline represents adequate farm performance against C. rogercresseyi infestation. Then, production and environmental factors of the medium and high infestation farms were compared with the baseline using regression techniques. The results revealed a total of 26 clusters (p < 0.001), of which 12 correspond to baseline, 1 to medium, and the remaining 13 to high infestation clusters. In general, baseline clusters are detected in a latitudinal gradient on estuarine areas, with increasing relative risks to complex island water systems. There is a spatial structure in specific sites, north of Los Lagos Region and central Aysén Region, with high infestation clusters and epidemic peaks during 2013. In addition, average weight, salmon species, chemotherapeutants, latitude, temperature, salinity, and year category are factors associated with these C. rogercresseyi patterns. Recommendations for an IPM plan are provided, along with a discussion that considers the involvement of stock density thresholds by salmon species and the spatial structure of the efficacy of chemical control, both intended to avoid the advance of resistance and to minimize environmental residues.

Assessing the Present and Future Habitat Suitability of Caligus rogercresseyi (Boxshall and Bravo, 2000) for Salmon Farming in Southern Chile

The sea louse (Caligus rogercresseyi) is the most relevant parasite for the farmed salmon industry in Chile, the second largest producer worldwide. Although spatial patterns of C. rogercresseyi have been addressed from data obtained from established monitoring and surveillance programs, studies on its spatial ecology are limited. A wide geographic distribution of C. rogercresseyi is presumed in Chile; however, how this species could potentially be distributed in space is unknown. Our study presents an analysis of the habitat suitability for C. rogercresseyi in the entire area occupied by marine sites of salmon farms in Chile. Habitat suitability modeling was used to explore the likelihood of species spatial occurrence based on environmental characteristics. Due to the expanding salmon industry in southern Chile, we studied C. rogercresseyi habitat suitability models for present (average of 2005-2010) and two future projections (2050 and 2100) under different climate change scenarios. Models were constructed with the maxent algorithm using a large database of spatial C. rogercresseyi occurrences from the Chilean fisheries health authority and included 23 environmental variables obtained from the Ocean Rasters for Analysis of Climate and Environment (Bio-ORACLE). Habitat suitability models indicated that water temperature, water salinity, and current velocity of waters were the most important characteristics limiting C. rogercresseyi distribution in southern Chile. Habitat suitability models for current climate indicated a heterogeneous pattern with C. rogercresseyi being present in waters with temperature range 12.12-7.08°C (sd = 0.65), salinity range 33.7-25.5 pss (sd = 1.73), and current water velocity range 0.23-0.01 m-1 (sd = 0.02). Predictions for future projections in year 2050 and year 2100 suggest new clumped dispersion of the environmental conditions for C. rogercresseyi establishment. Our results suggest complexity and a wide dispersion of the biogeographic distribution of the C. rogercresseyi habitat suitability with potential implications for control strategies and environmental issues for salmon farming in Chile. Further investigations are required into C. rogercresseyi distribution in southern Chile considering the possible effect of climate change.

Spatial modeling of individual-level infectious disease transmission: Tuberculosis data in Manitoba, Canada

Geographically dependent individual level models (GD-ILMs) are a class of statistical models that can be used to study the spread of infectious disease through a population in discrete-time in which covariates can be measured both at individual and area levels. The typical ILMs to illustrate spatial data are based on the distance between susceptible and infectious individuals. A key feature of GD-ILMs is that they take into account the spatial location of the individuals in addition to the distance between susceptible and infectious individuals. As a motivation of this article, we consider tuberculosis (TB) data which is an infectious disease which can be transmitted through individuals. It is also known that certain areas/demographics/communities have higher prevalent of TB (see Section 4 for more details). It is also of interest of policy makers to identify those areas with higher infectivity rate of TB for possible preventions. Therefore, we need to analyze this data properly to address those concerns. In this article, the expectation conditional maximization algorithm is proposed for estimating the parameters of GD-ILMs to be able to predict the areas with the highest average infectivity rates of TB. We also evaluate the performance of our proposed approach through some simulations. Our simulation results indicate that the proposed method provides reliable estimates of parameters which confirms accuracy of the infectivity rates.

Estimating sea lice infestation pressure on salmon farms: Comparing different methods using multivariate state-space models

Sea lice are ectoparasites of salmonids, and are considered to be one of the main threats to Atlantic salmon farming. Sea lice infestation on a farm is usually initiated by attachment of the free-living copepodid stage derived from the surrounding water, frequently originating from adult lice on the same farm or from neighboring salmonid farms, referred to as internal and external sources, respectively. Various approaches have been proposed to quantify sea lice infestation pressure on farms to improve the management of this pest. Here, we review and compare five of these methods based on sea lice data from 20 farms located near Grand Manan island in the Bay of Fundy, New Brunswick, Canada. Internal and external infestation pressures (IIP and EIP, respectively) were estimated using different approaches, and their effects were modeled either by a unique parameter for all production cycles or by different parameters for each production cycle, using a multivariate state-space model. Predictive variables, such as water temperature and sea lice treatments, were included in the model, and their effects across production cycles were estimated along with those of other model parameters. Results showed that models with only EIP explained the variation in the data better than models with only IIP, and that models with unique IIP and unique EIP for all cycles were generally associated with the best model fit. The simplest, fixed lag method for calculating infestation pressure had the best predictive performance in our models among the methods studied.

Chilean aquaculture and the new challenges: Pathogens, immune response, vaccination and fish diversification

In Chile, the salmon and trout farmed fishing industries have rapidly grown during the last years, becoming one of the most important economic sources for the country. However, infectious diseases caused by bacteria, virus, mycoses and parasites, result in losses of up to 700 million dollars per year for the Chilean aquaculture production with the consequent increase of antibiotic and antiparasitic usage. After 30 years of its first appearance, the main salmon health problem is still the salmonid rickettsial septicaemia (SRS), which together with other disease outbreaks, reveal that vaccines do not provide acceptable levels of long-lasting immune protection in the field. On the other hand, due to the large dependence of the industry on salmonids production, the Chilean government promoted the Aquaculture diversification program by 2009, which includes new species such as Merluccius australis, Cilus gilberti and Genypterus chilensis, however, specific research regarding the immune system and vaccine development are issues that still need to be addressed and must be considered as important as the farm production technologies for new fish species. Based on the experience acquired from the salmonid fish farming, should be mandatory an effort to study the immune system of the new species to develop knowledge for vaccination approaches, aiming to protect these aquaculture species before diseases outbreaks may occur. This review focuses on the current status of the Chilean aquaculture industry, the challenges related to emerging and re-emerging microbial pathogens on salmonid fish farming, and the resulting needs in the development of immune protection by rational designed vaccines. We also discussed about what we have learn from 25 years of salmonid researches and what can be applied to the new Chilean farmed species on immunology and vaccinology.

Sea lice exposure to non-lethal levels of emamectin benzoate after treatments: a potential risk factor for drug resistance

The avermectin derivative emamectin benzoate (EMB) has been widely used by salmon industries around the world to control sea lice infestations. Resistance to this anti-parasitic drug is also commonly reported in these industries. The objective of this study was to quantify the number of sea lice potentially exposed to sub-lethal concentrations of EMB while fish clear the drug after treatments. We assessed juvenile sea lice abundance after 38 EMB treatments on six Atlantic salmon farms, in a small archipelago in British Colombia, Canada, between 2007 and 2018. We fitted a standard EMB pharmacokinetic curve to determine the time when fish treated with this product would have EMB tissue concentrations below the recommended target therapeutic level. During the study, we estimated that for each sea lice treatment there was, on average, an abundance of 0.12 juvenile sea lice per fish during the time period when the concentrations of EMB would have been lower than 60ppb, the recommended therapeutic treatment level for sea lice. The findings from this study on metaphylactic anti-parasitic treatments identify a potential driver for drug resistance in sea lice that should be further explored.

Dynamics of Caligus rogercresseyi (Boxshall & Bravo, 2000) in farmed Atlantic salmon (Salmo salar) in southern Chile: Are we controlling sea lice?

Caligus rogercresseyi generates the greatest losses in the salmon industry in Chile. The relationship between salmon farming and sea lice is made up of various components: the parasite, host, environment and farming practices, which make it difficult to identify patterns in parasite population dynamics to define prevention and control strategies. The objectives of this study were to analyse and compare the effect of farming, sanitary practices and environmental variables on the abundance of gravid females (GF) and juveniles (JUV) of C. rogercresseyi on Salmo salar in three Salmon Neighborhood Areas (SNAs) in Region 10, south of Chile. Linear mixed-effects models of the negative binomial distribution were used to evaluate the effect of the different explanatory variables on GF and JUV. Productive variables were the key drivers explaining the abundance of GF and JUV. Results suggest that C. rogercresseyi is not controlled and JUV are persistent in the three SNAs, and sanitary practices do not control the dissemination of the parasite among sites. Environmental variables had a low impact on sea lice abundance. There is a need to perform analysis for modelling of parasite population dynamics to improve Integrated Pest Management, including changes in the governance to achieve an effective prevention and control.

The Use of Kernel Density Estimation With a Bio-Physical Model Provides a Method to Quantify Connectivity Among Salmon Farms: Spatial Planning and Management With Epidemiological Relevance

Connectivity in an aquatic setting is determined by a combination of hydrodynamic circulation and the biology of the organisms driving linkages. These complex processes can be simulated in coupled biological-physical models. The physical model refers to an underlying circulation model defined by spatially-explicit nodes, often incorporating a particle-tracking model. The particles can then be given biological parameters or behaviors (such as maturity and/or survivability rates, diel vertical migrations, avoidance, or seeking behaviors). The output of the bio-physical models can then be used to quantify connectivity among the nodes emitting and/or receiving the particles. Here we propose a method that makes use of kernel density estimation (KDE) on the output of a particle-tracking model, to quantify the infection or infestation pressure (IP) that each node causes on the surrounding area. Because IP is the product of both exposure time and the concentration of infectious agent particles, using KDE (which also combine elements of time and space), more accurately captures IP. This method is especially useful for those interested in infectious agent networks, a situation where IP is a superior measure of connectivity than the probability of particles from each node reaching other nodes. Here we illustrate the method by modeling the connectivity of salmon farms via sea lice larvae in the Broughton Archipelago, British Columbia, Canada. Analysis revealed evidence of two sub-networks of farms connected via a single farm, and evidence that the highest IP from a given emitting farm was often tens of kilometers or more away from that farm. We also classified farms as net emitters, receivers, or balanced, based on their structural role within the network. By better understanding how these salmon farms are connected to each other via their sea lice larvae, we can effectively focus management efforts to minimize the spread of sea lice between farms, advise on future site locations and coordinated treatment efforts, and minimize any impact of farms on juvenile wild salmon. The method has wide applicability for any system where capturing infectious agent networks can provide useful guidance for management or preventative planning decisions.

Tool for predicting Caligus rogercresseyi abundance on salt water salmon farms in Chile

Caligus rogercresseyi is a host-dependent parasite that affects rainbow trout and Atlantic salmon in Chile. Numbers of sea lice on fish increase over time at relatively predictable rates when the environment is conducive to the parasite's survival and fish are not undergoing treatment. We developed a tool for the salmon industry in Chile that predicts the abundance of adult sea lice over time on farms that are relatively isolated. We used data on sea louse abundance collected through the SalmonChile INTESAL sea lice monitoring program to create series of weekly lice counts between lice treatment events on isolated farms. We defined isolated farms as those with no known neighbors within a 10 km seaway distance and no more than two neighbors within a 20 km seaway distance. We defined the time between sea lice treatments as starting the week immediately post treatment and ending the week before a subsequent treatment. Our final dataset of isolated farms consisted of 65 series from 32 farms, between 2009 and 2015. Given an observed abundance at time t = 0, we built a model that predicted 8 consecutive weekly sea louse abundance levels, based on the preceding week's lice prediction. We calibrated the parameters in our model on a randomly selected subset of training data, choosing the parameter combinations that minimized the absolute difference between the predicted and observed sea louse abundance values. We validated the parameters on the remaining, unseen, subset of data. We encoded our model and made it available as a Web-accessible applet for producers. We determined a threshold, based on the upper 97.5% predictive interval, as a guideline for producers using the tool. We hypothesize that if farms exceed this threshold, especially if the sea lice levels are above this threshold 2 and 4 weeks into the model predictions, the sea louse population on the farm is likely influenced by sources other than lice within the farm.

Using biological-physical modelling for informing sea lice dispersal in Loch Linnhe, Scotland

Sea lice are a constraint on the sustainable growth of Scottish marine salmonid aquaculture. As part of an integrated pest management approach, farms coordinate procedures within spatial units. We present observations of copepodids being at relatively greater density than nauplii in upper waters, which informs the development of surface layer sea lice transmission modelling of Loch Linnhe, Scotland, for informing farm parasite management. A hydrodynamic model is coupled with a biological particle-tracking model, with characteristics of plankton sea lice. Simulations are undertaken for May and October 2011-2013, forced by local wind data collected for those periods. Particles are continually released from positions representing farm locations, weighted by relative farm counts, over a 2-week period and tracked for a further 5 days. A comparison is made between modelled relative concentrations against physical and biological surveys to provide confidence in model outputs. Connectivity between farm locations is determined in order to propose potential coordination areas. Generally, connectivity depends on flow patterns in the loch and decreases with increased farm separation. The connectivity indices are used to estimate the origins of the sea lice population composition at each site, which may influence medicinal regimens to avoid loss of efficacy.

A multivariable assessment of the spatio-temporal distribution of pyrethroids performance on the sea lice Caligus rogercresseyi in Chile

Synthetic pyrethroids have been widely used in Chile to control the sea lice Caligus rogercresseyi, a major ectoparasite of farmed salmon. Although resistance of C. rogercresseyi to pyrethroids has been reported in Chile, there is no information regarding the geographic extent of this problem. In this study we explored the spatial and temporal variation of C. rogercresseyi's response to pyrethroids in Chile from 2012 to 2013. We modeled lice abundance one week after treatment with a linear mixed-effects regression, and then we performed spatial and spatio-temporal cluster analyses on farm-level effects and on treatment-level residuals, respectively. Results indicate there were two areas where the post-treatment lice counts were significantly higher than in the rest of the study area. These spatial clusters remained even once we adjusted for environmental and management predictors, suggesting unmeasured factors (e.g. resistance) were causing the clustering. Further investigation should be carried out to confirm this hypothesis.

Risk factors for infectious pancreatic necrosis in farmed Chilean Atlantic salmon (Salmo salar L.) from 2010 to 2013

Infectious pancreatic necrosis (IPN) is a widespread and economically devastating fish disease caused by infection with a virus referred to as IPN virus (IPNv). In Chile, the disease is endemic and prevalent in both fresh- and salt-water farms affecting cultured salmonids, mainly Atlantic salmon. Here, we present the results of a retrospective cohort study of Atlantic salmon farms stocked between 2010 and 2013, aimed at quantifying the extent to which certain epidemiological factors influence the time interval between stocking and onset of IPN mortality (time to mortality, ttm) in marine farms. Six variables were retained in a final multivariable Cox proportional hazard model. Compared to the 2010 stocking year, ttm was shorter for salmon stocked in years 2012 (HR = 2.1; p = 0.005) and 2013 (HR = 4.3; p = 0.01). The number of salmon farms within a 10-km radius (HR = 1.07; p = 0.002), positive report of IPN in the previous production cycle (HR = 1.95; p = 0.006), three or more smolt batches (HR = 2.27; p < 0.001), and positive report of mortality attributable to BKD (HR = 2.02; p < 0.001) were also associated with low ttm; conversely, ttm was longer for farms that stocked heavier fish (HR = 0.94; p = 0.001). The results presented here were consistent with early studies of IPN epidemiology in Norway and Scotland. Some of the risk factors identified in this study also influenced the risk for other diseases, such as infectious salmon anemia, suggesting that implementation of selected management practices may help to mitigate the burden of important infectious diseases of salmon in Chile.

Using state-space models to predict the abundance of juvenile and adult sea lice on Atlantic salmon

Sea lice are marine parasites affecting salmon farms, and are considered one of the most costly pests of the salmon aquaculture industry. Infestations of sea lice on farms significantly increase opportunities for the parasite to spread in the surrounding ecosystem, making control of this pest a challenging issue for salmon producers. The complexity of controlling sea lice on salmon farms requires frequent monitoring of the abundance of different sea lice stages over time. Industry-based data sets of counts of lice are amenable to multivariate time-series data analyses. In this study, two sets of multivariate autoregressive state-space models were applied to Chilean sea lice data from six Atlantic salmon production cycles on five isolated farms (at least 20 km seaway distance away from other known active farms), to evaluate the utility of these models for predicting sea lice abundance over time on farms. The models were constructed with different parameter configurations, and the analysis demonstrated large heterogeneity between production cycles for the autoregressive parameter, the effects of chemotherapeutant bath treatments, and the process-error variance. A model allowing for different parameters across production cycles had the best fit and the smallest overall prediction errors. However, pooling information across cycles for the drift and observation error parameters did not substantially affect model performance, thus reducing the number of necessary parameters in the model. Bath treatments had strong but variable effects for reducing sea lice burdens, and these effects were stronger for adult lice than juvenile lice. Our multivariate state-space models were able to handle different sea lice stages and provide predictions for sea lice abundance with reasonable accuracy up to five weeks out.

Association between sea lice (Lepeophtheirus salmonis) infestation on Atlantic salmon farms and wild Pacific salmon in Muchalat Inlet, Canada

Growth in salmon aquaculture over the past two decades has raised concerns regarding the potential impacts of the industry on neighboring ecosystems and wild fish productivity. Despite limited evidence, sea lice have been identified as a major cause for the decline in some wild Pacific salmon populations on the west coast of Canada. We used sea lice count and management data from farmed and wild salmon, collected over 10 years (2007–2016) in the Muchalat Inlet region of Canada, to evaluate the association between sea lice recorded on salmon farms with the infestation levels on wild out-migrating Chum salmon. Our analyses indicated a significant positive association between the sea lice abundance on farms and the likelihood that wild fish would be infested. However, increased abundance of lice on farms was not significantly associated with the levels of infestation observed on the wild salmon. Our results suggest that Atlantic salmon farms may be an important source for the introduction of sea lice to wild Pacific salmon populations, but that the absence of a dose response relationship indicates that any estimate of farm impact requires more careful evaluation of causal inference than is typically seen in the extant scientific literature.

Quantitative risk assessment of salmon louse-induced mortality of seaward-migrating post-smolt Atlantic salmon

The Norwegian government recently implemented a new management system to regulate salmon farming in Norway, aiming to promote environmentally sustainable growth in the aquaculture industry. The Norwegian coast has been divided into 13 production zones and the volume of salmonid production in the zones will be regulated based on salmon lice effects on wild salmonids. Here we present a model for assessing salmon louse-induced mortality of seaward-migrating post-smolts of Atlantic salmon. The model quantifies expected salmon lice infestations and louse-induced mortality of migrating post-smolt salmon from 401 salmon rivers draining into Norwegian coastal waters. It is assumed that migrating post-smolts follow the shortest path from river outlets to the high seas, at constant progression rates. During this migration, fish are infested by salmon lice of farm origin according to an empirical infestation model. Furthermore, louse-induced mortality is estimated from the estimated louse infestations. Rivers draining into production zones on the West Coast of Norway were at the highest risk of adverse lice effects. In comparison, rivers draining into northerly production zones, along with the southernmost production zone, were at lower risk. After adjusting for standing stock biomass, estimates of louse-egg output varied by factors of up to 8 between production zones. Correlation between biomass adjusted output of louse infestation and densities of farmed salmon in the production zones suggests that a large-scale density-dependent host-parasite effect is a major driver of louse infestation rates and parasite-induced mortality. The estimates are sensitive to many of the processes in the chain of events in the model. Nevertheless, we argue that the model is suited to assess spatial and temporal risks associated with farm-origin salmon lice.

Lessons from sea louse and salmon epidemiology

Effective disease management can benefit from mathematical models that identify drivers of epidemiological change and guide decision-making. This is well illustrated in the host-parasite system of sea lice and salmon, which has been modelled extensively due to the economic costs associated with sea louse infections on salmon farms and the conservation concerns associated with sea louse infections on wild salmon. Consequently, a rich modelling literature devoted to sea louse and salmon epidemiology has been developed. We provide a synthesis of the mathematical and statistical models that have been used to study the epidemiology of sea lice and salmon. These studies span both conceptual and tactical models to quantify the effects of infections on host populations and communities, describe and predict patterns of transmission and dispersal, and guide evidence-based management of wild and farmed salmon. As aquaculture production continues to increase, advances made in modelling sea louse and salmon epidemiology should inform the sustainable management of marine resources.

Evaluating the effect of synchronized sea lice treatments in Chile

The sea louse is considered an important ectoparasite that affects farmed salmonids around the world. Sea lice control relies heavily on pharmacological treatments in several salmon-producing countries, including Chile. Among options for drug administration, immersion treatments represent the majority of antiparasitic control strategies used in Chile. As a topical procedure, immersion treatments do not induce a long lasting effect; therefore, re-infestation from neighbouring farms may undermine their efficacy. Synchronization of treatments has been proposed as a strategy to improve immersion treatment performance, but it has not been evaluated so far. Using a repeated-measures linear mixed-effect model, we evaluated the impact of treatment synchronization of neighbouring farms (within 10km seaway distance) on the adult lice mean abundance from weeks 2 to 8 post-treatment on rainbow trout and Atlantic salmon farms in Chile, while controlling for external and internal sources of lice before the treatments, and also for environmental and fish-related variables. Results indicate that treatment synchronization was significantly associated with lower adult lice levels from weeks 5 to 7 after treatment. This relationship appeared to be linear, suggesting that higher levels of synchronization may result in lower adult sea lice levels during these weeks. These findings suggest that synchronization can improve the performance of immersion delousing treatments by keeping sea lice levels low for a longer period of time. Our results may be applicable to other regions of the world where immersion treatments are widely used.

Simulated environmental transport distances of Lepeophtheirus salmonis in Loch Linnhe, Scotland, for informing aquaculture area management structures

In the majority of salmon farming countries, production occurs in zones where practices are coordinated to manage disease agents such as Lepeophtheirus salmonis. To inform the structure of zones in specific systems, models have been developed accounting for parasite biology and system hydrodynamics. These models provide individual system farm relationships, and as such, it may be beneficial to produce more generalized principles for informing structures. Here, we use six different forcing scenarios to provide simulations from a previously described model of the Loch Linnhe system, Scotland, to assess the maximum dispersal distance of lice particles released from 12 sites transported over 19 day. Results indicate that the median distance travelled is 6.1 km from release site with <2.5% transported beyond 15 km, which occurs from particles originating from half of the release sites, with an absolute simulated distance of 36 km observed. This provides information suggesting that the disease management areas developed for infectious salmon anaemia control may also have properties appropriate for salmon lice management in Scottish coastal waters. Additionally, general numerical descriptors of the simulated relative lice abundance reduction with increased distance from release location are proposed.

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.

Area contact networks and the spatio-temporal spread of infectious salmon anemia virus (ISAV) in Chile

Area management, the coordination of production and biosecurity practices across neighboring farms, is an important disease control strategy in aquaculture. Area management in aquaculture escalated in prominence in response to outbreaks of infectious salmon anemia (ISA) internationally. Successes in disease control have been attributed to the separation achieved through area-level synchronized stocking, fallowing, movement restrictions, and fomite or pest control. Area management, however, is costly; often demanding extra biosecurity, lengthy or inconveniently timed fallows, and localization of equipment, personnel, and services. Yet, this higher-order organizational structure has received limited epidemiologic attention. Chile's National Fisheries and Aquaculture Service instigated area management practices in response to the 2007 emergence of ISA virus (ISAV). Longitudinal data simultaneously collected allowed retrospective evaluation of the impact of component tenets on virus control. Spatiotemporal analyses identified hydrographic linkages, shared ports, and fish transfers from areas with recent occurrence of ISAV as the strongest predictors of virus spread between areas, though specifics varied by ISAV type (here categorized as HPR0 for the non-virulent genotypes, and HPRv otherwise). Hydrographic linkages were most predictive in the period before implementation of enhanced biosecurity and fallowing regulations, suggesting that viral load can impact spread dynamics. HPR0 arose late in the study period, so few HPRv events were available by which to explore the hypothesis of HPR0 as progenitor of outbreaks. However, spatiotemporal patterns in HPRv occurrence were predictive of subsequent patterns in HPR0 detection, suggesting a parallel, or dependent, means of spread. Better data precision, breadth and consistency, common challenges for retrospective studies, could improve model fit; and, for HPR0, specification of diagnostic test accuracy would improve interpretation.

Wild juvenile salmonids in Muchalat Inlet, British Columbia, Canada: factors associated with sea lice prevalence

The Muchalat Inlet, British Columbia, is among the most westerly points at which aquaculture is practiced in Canada. In this paper, we summarise data from over 18000 wild fish sampled at 16 sites over an 8 yr period, between 2004 and 2011. The most prevalent wild species was chum salmon Oncorhynchus keta (82.4%), followed by Chinook O. tshawytscha (10%) and coho O. kisutch (4.3%). However, inter-annual and seasonal variation was evident, and smaller numbers of other Pacific salmon and stickleback species were sporadically observed. A high percentage of wild salmon (~95%) had no sea lice parasites present, with less than 1% of the fish hosting a mobile-stage sea louse. Of the data for which sea lice species were recorded, just over 96% of samples were identified as Lepeophtheirus salmonis. Logistic regression models assessed the association between the presence of lice and a range of independent variables. These models indicated a significant degree of spatial variation, much of which could be explained in terms of salinity levels. There were also important variations through time, both over the season within a year and across years. In addition, coho salmon were significantly more likely (odds ratio = 1.65; 95% CI = 1.20-2.3) to be infected than chum salmon. The protective effect of low salinity was most clearly seen at values lower than 15 psu, although this was dependent on fish species.

Using Agent-Based Modelling to Predict the Role of Wild Refugia in the Evolution of Resistance of Sea Lice to Chemotherapeutants

A major challenge for Atlantic salmon farming in the northern hemisphere is infestation by the sea louse parasite Lepeophtheirus salmonis. The most frequent method of controlling these sea louse infestations is through the use of chemical treatments. However, most major salmon farming areas have observed resistance to common chemotherapeutants. In terrestrial environments, many strategies employed to manage the evolution of resistance involve the use of refugia, where a portion of the population is left untreated to maintain susceptibility. While refugia have not been deliberately used in Atlantic salmon farming, wild salmon populations that migrate close to salmon farms may act as natural refugia. In this paper we describe an agent-based model that explores the influence of different sizes of wild salmon populations on resistance evolution in sea lice on a salmon farm. Using the model, we demonstrate that wild salmon populations can act as refugia that limit the evolution of resistance in the sea louse populations. Additionally, we demonstrate that an increase in the size of the population of wild salmon results in an increased effect in slowing the evolution of resistance. We explore the effect of a population fitness cost associated with resistance, finding that in some cases it substantially reduces the speed of evolution to chemical treatments.

Sensitivity of Caligus rogercresseyi (Boxshall and Bravo 2000) to pyrethroids and azamethiphos measured using bioassay tests-A large scale spatial study

The variety of antiparasitics that can be used against caligid copepods is limited and efforts are needed to maintain their efficacies. The objective of this study was to monitor the sensitivity of Caligus rogercresseyi, populations towards antiparasitics based on deltamethrin, cypermethrin and azamethiphos within and across geographic regions. The bioassay design consisted of exposing parasites collected from 23 farms to the different chemotherapeutants at the concentration and exposure times recommended for field treatment, under laboratory conditions, and evaluating the number of dead and live parasites 48h after exposure. Parasites were collected from 23 farms distributed in four macrozones in the Los Lagos region and three macrozones in the Aysén region. Parasite sensitivity was evaluated using a Generalized Linear Mixed Model of the Binomial family (Logit) fit by the maximum likelihood, using the lme4 package in R. Parasite gender, macrozone, and antiparasitics were used as fixed factors and farm was the random factor. The model including all the factors proved to be a useful tool for predicting parasite sensitivity. This approach identified (i) those macrozones with a greater likelihood of finding parasite populations which are more or less sensitive to the three antiparasitics, (ii) cases in which parasite sensitivity to the different antiparasitics varied within a given macrozone, (iii) differences in sensitivity between females and males and (iv) an important random effect associated with farm. The results indicate a spatial variability of parasite sensitivity to antiparasitics which, added to the continuous treatments applied on farms, suggest it is necessary to regularly update the sensitivity status in the macrozones. This would allow managers to improve their decision making processes regarding the type of antiparasitic to be used in a given situation. The one-concentration type bioassay performed in this study allowed us to perform a large spatial study with replicated tests of the sensitivity of C. rogercresseyi to pyrethroids and azamethiphos. Further studies should focus on the farm effects, the relationship between the sensitivity of parasites and field efficacy, as well as parasite population structure and connectivity with regard to parasite transmission between farms.

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.

Risk factors perceived predictive of ISA spread in Chile: applications to decision support

Aquaculture is anticipated to be a critical element in future solutions to global food shortage. However, diseases can impede industry efficiency and sustainability. Consequently, diseases can and have led to dramatic re-structuring in industry or regulatory practices. The emergence of infectious salmon anemia (ISA) in Chile is one such example. As in other countries, many mitigations were instituted universally, and many incurred considerable costs as they introduced a new layer of coordination of farming activities of marine sites within common geographic areas (termed 'neighborhoods' or 'barrios'). The aggregate response led to a strong reduction in ISA incidence and impact. However, the relative value of individual mitigations is less clear, especially where response policies were universally applied and retrospective analyses are missing 'controls' (i.e., areas where a mitigation was not applied). Further, re-focusing policies around disease prevention following resolution of an outbreak is important to renew sustainable production; though, again, field data to guide this shift in purpose are often lacking. Expert panels can offer timely decision support in the absence of empirical data. We convened a panel of fish health experts to weight risk factors predictive of ISA virus (ISAV) introduction or spread between Atlantic salmon barrios in Chile. Barrios, rather than sites, were the unit of interest because many of the new mitigations operate at this level and few available studies examine their efficacy. Panelists identified barrio processing plant biosecurity, fallowing strategies, adult live fish transfers, fish and site density, smolt quality, hydrographic connection with other neighborhoods, presence of sea lice (Caligus rogercresseyi), and harvest vessel biosecurity as factors with the greatest predictive strength for ISAV virulent genotype ('HPR-deleted') occurrence. Fewer factors were considered predictive of ISAV HPR0 genotype ('HPR0') occurrence, with greatest strengths assigned to fish and site density, adult live fish transfers, and smolt facility HPR0 status. Field validation based on ISAV and risk factor occurrence after panel completion generally supports expert estimates, and highlights a few factors (e.g., broodstock HPR0 status) less conclusive in the original study. Results inform legislation, industry best management practices and surveillance design.

RNA-Seq analysis using de novo transcriptome assembly as a reference for the salmon louse Caligus rogercresseyi

Despite the economic and environmental impacts that sea lice infestations have on salmon farming worldwide, genomic data generated by high-throughput transcriptome sequencing for different developmental stages, sexes, and strains of sea lice is still limited or unknown. In this study, RNA-seq analysis was performed using de novo transcriptome assembly as a reference for evidenced transcriptional changes from six developmental stages of the salmon louse Caligus rogercresseyi. EST-datasets were generated from the nauplius I, nauplius II, copepodid and chalimus stages and from female and male adults using MiSeq Illumina sequencing. A total of 151,788,682 transcripts were yielded, which were assembled into 83,444 high quality contigs and subsequently annotated into roughly 24,000 genes based on known proteins. To identify differential transcription patterns among salmon louse stages, cluster analyses were performed using normalized gene expression values. Herein, four clusters were differentially expressed between nauplius I–II and copepodid stages (604 transcripts), five clusters between copepodid and chalimus stages (2,426 transcripts), and six clusters between female and male adults (2,478 transcripts). Gene ontology analysis revealed that the nauplius I–II, copepodid and chalimus stages are mainly annotated to aminoacid transfer/repair/breakdown, metabolism, molting cycle, and nervous system development. Additionally, genes showing differential transcription in female and male adults were highly related to cytoskeletal and contractile elements, reproduction, cell development, morphogenesis, and transcription-translation processes. The data presented in this study provides the most comprehensive transcriptome resource available for C. rogercresseyi, which should be used for future genomic studies linked to host-parasite interactions.

Host demography influences the prevalence and severity of eelgrass wasting disease

Many marine pathogens are opportunists, present in the environment, but causing disease only under certain conditions such as immunosuppression due to environmental stress or host factors such as age. In the temperate eelgrass Zostera marina, the opportunistic labyrinthulomycete pathogen Labyrinthula zosterae is present in many populations and occasionally causes severe epidemics of wasting disease; however, risk factors associated with these epidemics are unknown. We conducted both field surveys and experimental manipulations to examine the effect of leaf age (inferred from leaf size) on wasting disease prevalence and severity in Z. marina across sites in the San Juan Archipelago, Washington, USA. We confirmed that lesions observed in the field were caused by active Labyrinthula infections both by identifying the etiologic agent through histology and by performing inoculations with cultures of Labyrinthula spp. isolated from observed lesions. We found that disease prevalence increased at shallower depths and with greater leaf size at all sites, and this effect was more pronounced at declining sites. Experimental inoculations with 2 strains of L. zosterae confirmed an increased susceptibility of older leaves to infection. Overall, this pattern suggests that mature beds and shallow beds of eelgrass may be especially susceptible to outbreaks of wasting disease. The study highlights the importance of considering host and environmental factors when evaluating risk of disease from opportunistic pathogens.

The analysis--hierarchical models: past, present and future

This paper discusses statistical modelling for data with a hierarchical structure, and distinguishes in this context between three different meanings of the term hierarchical model: to account for clustering, to investigate variability and separate predictive equations at different hierarchical levels (multi-level analysis), and in a Bayesian framework to involve multiple layers of data or prior information. Within each of these areas, the paper reviews both past developments and the present state, and offers indications of future directions. In a worked example, previously reported data on piglet lameness are reanalyzed with multi-level methodology for survival analysis, leading to new insights into the data structure and predictor effects. In our view, hierarchical models of all three types discussed have much to offer for data analysis in veterinary epidemiology and other disciplines.