The application of a mathematical model to evaluate the effectiveness of control strategies against Ciona intestinalis in mussel production

The Prince Edward Island (PEI) mussel industry has faced challenges associated with invasive tunicate species over the past two decades. Field experiments to find suitable mitigation strategies require considerable time and are resource intensive. This study demonstrates the application of a mathematical model to assess several control strategies against Ciona intestinalis populations under different temperature conditions in a mussel production area in PEI. A temperature dependent compartmental model was used to model the total abundance of C. intestinalis. Each mitigation strategy was defined in terms of a combination of timing and frequency of treatments. Various strategies were explored to obtain the combination that maximized the difference in predicted abundances between the control (untreated) and the different mitigation strategies. Treatment frequency was allowed to vary between one and four times over a given production year. The model was assessed under baseline conditions, which mimicked water temperatures from Georgetown Harbor, PEI, in 2008; as well as under scenarios that reflected prolonged summer or warm spring temperatures. Furthermore, the sensitivity of the model to variations in presumed treatment efficacy was evaluated. The use of all four available treatments, starting around the first week of July and correctly timed thereafter, provided the most effective strategy, assuming the baseline temperature scenario. However, the effectiveness of this mitigation strategy depended on temperature conditions. The mathematical model developed in this study allows decision makers to explore different strategies to control the abundance of C. intestinalis in mussel production areas under different environmental conditions. In addition, the modeling framework developed could be adapted to simulate comparable ectoparasitic infestation in aquatic environments

Sea lice infestations on juvenile chum and pink salmon in the Broughton Archipelago, Canada, from 2003 to 2012

Juvenile pink salmon Oncorhynchus gorbuscha and chum salmon O. keta were sampled by beach or purse seine to assess levels of sea lice infestation in the Knight Inlet and Broughton Archipelago regions of coastal British Columbia, Canada, during the months of March to July from 2003 to 2012. Beach seine data were analyzed for sea lice infestation that was de - scribed in terms of prevalence, abundance, intensity, and intensity per unit length. The median annual prevalence for chum was 30%, ranging from 14% (in 2008 and 2009) to 73% (in 2004), while for pink salmon, the median was 27% and ranged from 10% (in 2011) to 68% (in 2004). Annual abundance varied from 0.2 to 5 sea lice per fish with a median of 0.47 for chum and from 0.1 to 3 lice (median 0.42) for pink salmon. Annual infestation followed broadly similar trends for both chum and pink salmon. However, the abundance and intensity of Lepeophtheirus salmonis and Caligus clemensi, the 2 main sea lice species of interest, were significantly greater on chum than on pink salmon in around half of the years studied. Logistic regression with random effect was used to model prevalence of sea lice infestation for the combined beach and purse seine data. The model suggested inter-annual variation as well as a spatial clustering effect on the prevalence of sea lice infestation in both chum and pink salmon. Fish length had an effect on prevalence, although the nature of this effect differed according to host species

Bayesian risk assessment model of human cryptosporidiosis cases following consumption of raw Eastern oysters (Crassostrea virginica) contaminated with Cryptosporidium oocysts in the Hillsborough River system in Prince Edward Island, Canada.

Cryptosporidium spp. has been associated with foodborne infectious disease outbreaks; however, it is unclear to what extent raw oyster consumption poses a risk to public health. Control of Cryptosporidium in shellfish harvest seawater in Canada is not mandatory and, despite relay/depuration processes, the parasite can remain viable in oysters for at least a month (depending on initial loads and seawater characteristics). Risks of human infection and illness from exposure to oysters contaminated with Cryptosporidium oocysts were assessed in a Bayesian framework. Two data sets were used: counts of oocysts in oysters harvested in Approved, Restricted, and Prohibited zones of the Hillsborough River system; and oocyst elimination rate from oysters exposed to oocysts in laboratory experiments. A total of 20 scenarios were assessed according to number of oysters consumed in a single serving (1, 10 and 30) and different relay times. The median probability of infection and developing cryptosporidiosis (e.g. illness) due to the consumption of raw oysters in Prince Edward Island was zero for all scenarios. However, the 95th percentiles ranged from 2% to 81% and from 1% to 59% for probability of infection and illness, respectively. When relay times were extended from 14 to 30 days and 10 oysters were consumed in one serving from the Restricted zones, these probabilities were reduced from 35% to 16% and from 15% to 7%, respectively. The 14-day relay period established by Canadian authorities for harvesting in Restricted zones seems prudent, though insufficient, as this relay period has been shown to be enough to eliminate fecal coliforms but not Cryptosporidium oocysts, which can remain viable in the oyster for over a month. Extending relay periods of 14 and 21 days for oysters harvested in Restricted zones to 30 days is likely insufficient to substantially decrease the probability of infection and illness. The highest risk was found for oysters that originated in Prohibited zones. Our findings suggest that Cryptosporidium oocysts are a potential cause of foodborne infection and illness when consuming raw oysters from Hillsborough River, one of the most important oyster production bays on Prince Edward Island. We discuss data gaps and limitations of this work in order to identify future research that can be used to reduce the uncertainties in predicted risks

Comparison of Remotely-Sensed Sea Surface Temperature and Salinity Products With in Situ Measurements From British Columbia, Canada

Sea surface temperature (SST) and salinity (SSS) are essential variables at the ocean and atmosphere interface when considering risk factors for disease in farmed and wild fish stocks. Ecological research has witnessed a recent trend in use of digital and satellite technologies, including remote-sensing tools. We explored spatial coverage of remotely-sensed SST and SSS data and compared them with in situ measurements of water temperatures and salinity, which led to suggested adjustments to the remotely-sensed data for its use in aquaculture research. The in situ data were from farms and wild surveillance sites in coastal British Columbia, Canada, from 2003 to 2016. Concurrent SST and SSS values were extracted from remotely-sensed products and compared with 20,513 and 20,038 in situ records for water temperature and salinity, respectively, from 232 different sites. Among nine SST products evaluated, the UKMO OSTIA SST (UK Meteorological Office) had the highest retrieval, and highest concordance correlation coefficient (0.86), highest index of agreement (0.93), fewest missing values, and smallest mean and SD values for bias, when compared to in situ measurements. A mixed linear regression model with UKMO OSTIA SST as the predictor for in situ measurements estimated an adjustment coefficient of 0.89°C for UKMO OSTIA SST. None of the three SSS products evaluated provided appropriate corresponding values for in situ sites, suggesting that spatial coverage for the study area is currently lacking. This study demonstrates that, among SST products, UKMO OSTIA SST is currently best suited for aquaculture studies in coastal BC. The near real-time availability of these data with the estimated adjustment would allow their use in forecast models, surveillance of pathogens, and the creation of risk maps

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

Abstract 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