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

Molecular Characterization of Cryptosporidium spp. in Cultivated and Wild Marine Fishes from Western Mediterranean with the First Detection of Zoonotic Cryptosporidium ubiquitum

Fish not only harbor host-specific species/genotypes of Cryptosporidium, but also species like zoonotic C. parvum or anthroponotic C. hominis, which can pose a risk for fish consumers. This study aims to investigate fish cryptosporidiosis in an important aquaculture and fishery area of the Western Mediterranean (Comunidad Valenciana, Spain). We analyzed 404 specimens belonging to the following three groups: cultivated fish (N = 147), wild synanthropic fish (N = 147) and wild fish from extractive fisheries (N = 110). Nested PCR targeting the 18S rRNA gene, followed by sequencing and phylogenetic analysis, were performed. Positive isolates were also amplified at the actin gene locus. An overall prevalence of 4.2% was detected, with the highest prevalence in the synanthropic group (6.1%). C. molnari was identified in thirteen specimens from seven different host species. Zoonotic C. ubiquitum was detected in two European sea bass (Dicentrarchus labrax). One isolate similar to C. scophthalmi was detected in a cultivated meagre (Argyrosomus regius), and one isolate, highly divergent from all the Cryptosporidium species/genotypes described, was identified from a synanthropic round sardinella (Sardinella aurita). This study contributes to increasing the molecular data on fish cryptosporidiosis, expanding the range of known hosts for C. molnari and identifying, for the first time, zoonotic C. ubiquitum in edible marine fishes, pointing out a potential health risk.

Parasitic copepod (Lernanthropus kroyeri) on caged sea bass (Dicentrarchus labrax): An estimation of abundance and internal infestation pressure

Infestation by parasitic copepods is a substantial problem in the cage culture of European sea bass (Dicentrarchus labrax). The Copepoda parasite, Lernanthropus kroyeri (Lernanthropidae), is one of the threats to the mariculture of sea bass. In the present study, we evaluated the data of abundance for L. kroyeri pre-adults and adult males (PAAM) and ovigerous adult females (AF_o ) to estimate the internal infection pressure (IIP) in the same cage environment. The sea bass infested by L. kroyeri was collected from grow-out sea cages located in Gulluk Bay (Turkey) in September and October 2019. Mean fish weight and length of sea bass were 75.79 ± 1.66 g and 21.40 ± 0.56 cm, respectively. The fixed lag method was used to predict the abundance of L. kroyeri adult females. The overall prevalence of L. kroyeri was 60%. The mean abundance of PAAM and AF_o varied from 0.8 ± 0.24 to 2.5 ± 0.67 and 2.9 ± 0.40 to 4.3 ± 0.55, respectively. The abundance of AF was strongly correlated with PAAM. The pattern of AF_o and PAAM was interpreted as an indication of the continuous infestation of L. kroyeri on sea bass. Our results showed that the correlation of AF_o abundance for five consecutive weeks was significant, representing the main determinative factor for the continuity of the parasitic load. In our approach, internal infestation pressure is the quantitative estimation of the potential infective copepodids, which are mainly characterized by AF abundance and the prevalence. We predicted that the internal infestation pressure could be high, even exceeding the 50.000 × 10⁶ potential infective copepodids for one sea cage with the fish density of 20 sea bass/m³ .

The effect of temperature on ability of Lepeophtheirus salmonis to infect and persist on Atlantic salmon

The salmon louse (Lepeophtheirus salmonis) is an ecologically and economically important parasite of salmonid fish. Temperature is a strong influencer of biological processes in salmon lice, with development rate increased at higher temperatures. The successful attachment of lice onto a host is also predicted to be influenced by temperature; however, the correlation of temperature with parasite survival is unknown. This study describes the effects of temperature on infection success, and survival on the host during development to the adult stage. To accurately describe infection dynamics with varying temperatures, infection success was recorded on Atlantic salmon (Salmo salar) between 2 and 10°C. Infection success ranged from 20% to 50% and was strongly correlated with temperature, with the highest success at 10°C. Parasite loss was monitored during development at eight temperatures with high loss of lice at 3 and 24°C, whilst no loss was recorded in the temperature range from 6 to 21°C. Sea temperatures thus have large effects on the outcome of salmon louse infections and should be taken into account in the management and risk assessment of this parasite. Improving understanding of the infection dynamics of salmon lice will facilitate epidemiological modelling efforts and efficiency of pest management strategies.

Long-term and longitudinal nutrient stoichiometry changes in oligotrophic cascade reservoirs with trout cage aquaculture

The potential nutrient stoichiometry changes caused by trout cage aquaculture is concerned especially in oligotrophic waters. Long-term total nitrogen (N), total phosphorus (P) and N:P ratio changes in 6 cascade reservoirs with rainbow trout cage aquaculture in the oligotrophic upstream Yellow River (UYR) were studied from 2013 to 2017 in this paper. The 5-year monitoring results showed that N, P and N:P ratio levels showed no obvious long-term changes in high-altitude oligotrophic waters with rainbow trout cage aquaculture. No obvious longitudinal N, P and N:P ratio level changes were observed in the 6 cascade reservoirs from upstream Longyangxia Reservoir (LYR) to downstream Jishixia Reservoir (JSR). The increased N and P resulting from the cage aquaculture accounted only for 1.74% and 5.2% of the natural N and P levels, respectively, with a fish production of 10,000 tonnes. The upstream Yellow River remained oligotrophic and phosphorus-limited. Results in this study proved that trout cage aquaculture do not necessarily cause nitrogen, phosphorus and N:P ratio changes even in oligotrophic waters. Phosphorus should be considered first when identifying priority nitrogen and phosphorus sources and the corresponding control measures in waters with high N:P ratio.

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.

Modeling Pathogen Dispersal in Marine Fish and Shellfish

In marine ecosystems, oceanographic processes often govern host contacts with infectious agents. Consequently, many approaches developed to quantify pathogen dispersal in terrestrial ecosystems have limited use in the marine context. Recent applications in marine disease modeling demonstrate that physical oceanographic models coupled with biological models of infectious agents can characterize dispersal networks of pathogens in marine ecosystems. Biophysical modeling has been used over the past two decades to model larval dispersion but has only recently been utilized in marine epidemiology. In this review, we describe how biophysical models function and how they can be used to measure connectivity of infectious agents between sites, test hypotheses regarding pathogen dispersal, and quantify patterns of pathogen spread, focusing on fish and shellfish pathogens.

Detection and Assessment of the Distribution of Infectious Agents in Juvenile Fraser River Sockeye Salmon, Canada, in 2012 and 2013

Infectious diseases may contribute to declines in Fraser River Sockeye salmon (Oncorhynchus nerka) stocks, but a clear knowledge gap exists around which infectious agents and diseases are important. This study was conducted to: (1) determine the presence and prevalence of 46 infectious agents in juvenile Fraser River Sockeye salmon, and (2) evaluate spatial patterns in prevalence and burden over initial seaward migration, contrasting patterns between 2 years of average and poor productivity. In total, 2,006 out-migrating Sockeye salmon were collected from four regions along their migration trajectory in British Columbia, in 2012 and 2013. High-throughput microfluidics quantitative PCR was employed for simultaneous quantitation of 46 different infectious agents. Twenty-six agents were detected at least once, including nine with prevalence >5%. Candidatus Brachiomonas cysticola, Myxobolus arcticus, and Pacific salmon parvovirus were the most prevalent agents. Infectious agent diversity and burden increased consistently upon smolts entry into the ocean, but they did not substantially change afterwards. Notably, both freshwater- and saltwater-transmitted agents were more prevalent in 2013 than in 2012, leading to an overall higher infection burden in the first two sampling regions. A reduction in the prevalence of two agents, erythrocytic necrosis virus and Paraneuclospora theridion, was observed between regions 2 and 3, which was speculated to be associated with mortality during the 1st month at sea. The most prevalent infectious agents were all naturally occurring. In a small number of samples (0.9%), seven agents were only detected around and after salmon farming regions, including four important pathogens: piscine orthoreovirus, Piscirickettsia salmonis, Tenacibaculum maritimum, and Moritella viscosa. As the first synoptic survey of infectious agents in juvenile Sockeye salmon in British Columbia, this study provides the necessary baseline for further research on the most prevalent infectious agents and their potential pathogenicity, which may adversely affect the productivity of valuable Sockeye salmon stocks. In addition, our findings are informative to the decision makers involved in conservation programs.

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.