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Marine spatial planning (MSP) is a management tool that could help mitigate the conflict that exists between the American lobster (Homarus americanus) fishery and the net-pen salmon aquaculture industry in the Canadian Maritime provinces. We developed adult American lobster species distribution models (SDMs) for use in MSP in Liverpool, Nova Scotia, through remote sensing data collection methods. A single-beam echo sounder was used to collect bathymetry and seafloor substrate data, and an aerial drone collected lobster presence data through the georeferenced photography of lobster trap buoys. The SDMs display trends in lobster presence likelihood that correspond with established patterns of habitat selection in adult lobsters. The areas where lobsters are predicted to have the highest likelihood of presence are sections of hard and rocky substrate, though that association is confounded by depth. The uncertainty of the SDMs was quantitatively assessed and the importance of explicitly analysing the effects of scale and resolution of spatial data are highlighted.

Sea lice are one of the most economically costly and ecologically concerning problems facing the salmon farming industry. Here, we validated a coupled biological and physical model that simulated sea lice larvae dispersal from salmon farms in the Broughton Archipelago (BA), British Columbia, Canada. We employed a concept from ecological agent-based modeling known as ‘pattern matching’, which identifies similar emergent properties in both the simulated and observed data to confirm that the simulation contained sufficient complexity to recreate the emergent properties of the system. One emergent property from the biophysical simulations was the existence of sub-networks of farms. These were also identified in the observed sea lice count data in this study using a space-time scan statistic (SaTScan) to identify significant spatio-temporal clusters of farms. Despite finding support for our simulation in the observed data, which consisted of over a decade’s worth of monthly sea lice abundance counts from salmon farms in the BA, the validation was not entirely straightforward. The complexities associated with validating this biophysical dispersal simulation highlight the need to further develop validation techniques for agent-based models in general, and biophysical simulations in particular, which often result in patchiness in their dispersal fields. The methods utilised in this validation could be adopted as a template for other epidemiological dispersal models, particularly those related to aquaculture, which typically have robust disease monitoring data collection plans in place.

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

The health and welfare of farmed fish are highly dependent on environmental conditions. Under suboptimal conditions, the negative impact on welfare can cause changes in fish behaviour. Acoustic tags can provide high resolution and high frequency data to monitor fish positioning within the cage, which can be used to infer swimming behaviour. In this study, implanted acoustic tags were used to monitor the three-dimensional positioning of Atlantic salmon (Salmo salar) at a commercial farm in Nova Scotia, Canada. The one-month study period allowed the characterisation of background behaviour and changes in behaviour in relation to different environmental conditions, namely, water characteristics in terms of dissolved oxygen and temperature caused by the fall overturn, storm conditions, and feeding activity. The three-dimensional position of 15 fish was recorded using high temporal resolution (3 s). Fish movement was characterised by calculating four fish variables: distance from the centre of the cage [m], depth [m], velocity [ms−1], and turning angle [°]. The population swam in a counterclockwise swimming direction around 4 ± 2 m depth at an average speed of 0.61 ± 0.38 ms−1. After the fall overturn, the population moved significantly towards cage centre while decreasing velocity, and non-significant differences in depth and turning angle were observed. During feeding periods, a significant increase in depth and velocity, as well as a reduction in turning angle were observed. The storm event did not cause any significant change in the four fish variables. While some of the behavioural changes were difficult to assess with respect to causation, the high resolution, high frequency data provide unique detailed positioning information to further our understanding of the swimming behaviour of farmed fish.

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

Wild lobster (Homarus americanus) abundance was monitored before, during, and after salmon (Salmo salar) aquaculture production in a bay on Grand Manan Island, New Brunswick, Canada, in an 8-year survey, 2008 to 2015. Diver transects and free-area spot-dives were used to measure the carapace length and determine sex (including berried state) of each lobster encountered both inside (farm) and outside (reference) the lease boundaries. In pairwise comparisons of each sampling date, there was no significant difference between the number of lobsters inside the salmon farming area versus a nearby reference site and no significant difference in the number of berried females inside or out of the farm lease area. Combining data from all lobster surveys (farm and reference sites) indicated an increase over 8 years, similar in slope to the increase of the trap fishery in Lobster Fishing Area (LFA) 38. These results indicate that the fish farm had no obvious impact on lobster density at any point in the salmon production cycle and that inshore lobster abundance followed trends similar to those of the general fishery of LFA 38.

Carrying Capacity (CC) has emerged as a potential tool to sustainably manage human activities such as aquaculture. However, interdisciplinary and integrated frameworks for holistic CC assessments are still missing. The goal of this study was to generate expert consensus on best evaluative practices for holistic CC assessments of ocean-based salmon aquaculture. To achieve this goal, a 3-round Delphi study was conducted with 21 aquaculture and carrying capacity experts from around the world. Experts emphasized that the holistic CC process should i) engage all stakeholders in the process, ii) consider the combination of social, political, ecological, and economic aspects, iii) respond to changes over time, iv) consider multiple spatial and temporal scales, and v) be understandable and clear to all stakeholders involved. Furthermore, the expert panel emphasized the need for a cyclical and dynamic process that allows for the incorporation of feedback in the planning stages, embracing adaptive management. Due to the early stages of truly holistic assessments, the experts recognized challenges related to knowledge uncertainties and lack of approaches to integrate socio-economic data with ecological and physical data, potential conflicts arising from a multi-stakeholder process, and ill-equipped governance structures. The proposed guidelines and framework could help address some of the conceptual and procedural barriers to implementing holistic assessments into decision-making and may position CC as a useful decision-support tool for governments seeking sustainable aquaculture management.

This paper focuses on the availability of economic indicators and metrics to assess effects of marine aquaculture production in the North Atlantic area (the EU, Norway, Canada and USA), including also social and environmental effects. We consider how aquaculture planning and management is organised in the different countries and the usefulness of economic information to address different aquaculture‐related policies. We find that the most relevant economic data for aquaculture management should be at the local and regional levels rather than nationally. The availability of such economic data is mapped for national, regional and local level. The focus is on data that are publicly available from authorities or research institutions. The availability of data is generally fairly good for national and regional data on the direct economic effects of aquaculture. Data on how aquaculture‐related products or input markets are affected are however poorly available, as are economic data on external effects from aquaculture. Countries with a larger aquaculture sector tend to have better availability of aquaculture‐related economic data than those with a smaller sector. An index is developed and calculated to show more specifically where the countries have relatively good or poor data availability compared to their needs. While it will not always be cost‐effective or meaningful to collect economic data on the effects of aquaculture, our study indicates that several countries could benefit from expanding such data collection. It can make trade‐off decisions more consistent and easier to perform, and aquaculture policies and measures can be better tailored to specific contexts This article is based upon work from COST Action OceansPast Platform (OPP – IS1403), supported by COST (Euro-pean Cooperation in Science and Technology). We gratefully acknowledge support also from the institutions of the authors, and discussions in the ICES Working Group onSocial and Economic Dimensions of Aquaculture. In particular, we thank Max Troell, Cecile Brugere and Max Ebeling for input. Lucia Fanning was supported by the Ocean Frontier Institute Large Research Project on Social Licenseand Planning in Coastal Communities SI

Until very recently, governments of many countries, as well as their supporting organizations, have primarily addressed the biological, technical and economic aspects of aquaculture. In contrast, social and cultural aspects of aquaculture production have taken a backseat. Drawing on the observation that aquaculture development in Western Societies has largely failed to address these social effects across different scales and contexts, this paper offers a new way of capturing and visualising the diverse social dimensions of aquaculture. It does so by testing the ability to operationalise a set of social dimensions based on categories and indicators put forward by the United Nations, using several case studies across the North Atlantic. Local/regional stakeholder knowledge realms are combined with scientific expert knowledge to assess aquaculture operations against these indicators. The approach indicates that one needs to have a minimum farm size in order to have an impact of a visible scale for the different social dimension categories. While finfish aquaculture seems to be more social impactful than rope mussel farming, the latter can hold important cultural values and contribute to place-based understanding, connecting people with place and identity, thus playing a vital role in maintaining the working waterfront identity. It could be shown that aquaculture boosts a potential significant pull-factor to incentivise people to remain in the area, keeping coastal communities viable. By visualising the social effects of aquaculture, a door may be opened for new narratives on the sustainability of aquaculture that render social license and social acceptability more positive.

Warming waters are changing marine pathogen dispersal patterns and infectivity worldwide. Coupled biological–physical modelling has been used in many systems to determine the connectivity of metapopulations via infectious disease particles. Here we model the connectivity of sea lice larvae (Lepeophtheirus salmonis) among salmon farms in the Broughton Archipelago, British Columbia, Canada, using a coupled biological–physical model. The physical model simulated pathogen dispersal, while the biological component influenced the survival and developmental rates of the sea lice. Model results predicted high temporal variability in connectivity strength among farms, an emergent effect from the interacting parts of the simulation (dispersion versus survival and development). Drivers of temporal variability were disentangled using generalized additive modeling, which revealed the variability was most strongly impacted by the spring freshet, which can act as a natural aid for sea lice control in the Broughton Archipelago. Our results suggest that farm management strategies can benefit by accounting for short-term spikes in regional pathogen connectivity among farms. Additionally, future scenarios of a warming climate with reduced snowpack can make sea lice control more challenging.

We sought to understand factors associated with refusal of adjuvant radiotherapy in endometrial cancer and its impact on outcomes.Data from the National Cancer Database for patients who underwent surgery for nonmetastatic endometrial cancer between 2004 and 2015 were pooled. The Pearson χ test and multivariate logistic regression analyses were used to assess demographic, clinical, and treatment factors. Inverse probability of treatment weighting was used to account for differences in baseline characteristics. Kaplan-Meier analyses and doubly-robust estimation with multivariate Cox proportional hazards modeling were used to analyze overall survival (OS).We identified 4739 of 80,803 patients (5.9%) who refused radiotherapy. Factors associated with refusal were: no insurance (relative risk [RR]=1.66, P0.01), Medicare (RR=1.42, P0.01), living50 miles from treatment (RR=1.34, P0.01), Charlson-Deyo Comorbidity Scores of 1 (RR=1.16, P0.01) or ≥2 RR=1.38, P0.01), age above 60 years (RR=1.28, P0.01), International Federation of Gynecology and Obstetrics (FIGO) stages IIIA (RR=1.63, P0.01) and IIIC (RR=1.65, P0.01) disease, papillary (RR=1.69, P0.01) and clear cell histology (RR=1.64, P0.01). Factors associated with radiation therapy receipt included: Hispanic race (RR=0.61, P0.01), income$63,000 (RR=0.89, P=0.044), undergoing chemotherapy (RR=0.17, P0.01), FIGO stages IB (RR=0.81, P0.01) and II (RR=0.70, P0.01) disease, and lymphadenectomy (RR=0.79, P0.01). After weighting, 5-year OS was significantly lower with refusal (74.3% vs. 79.7%, P0.01). This survival decrement was maintained across FIGO stages.We identified characteristics associated with radiation refusal, including socioeconomic barriers, advanced disease stage, and histology. Refusal of radiotherapy conferred decreased OS across FIGO stages.

Precision aquaculture is founded on a set of disparate, interconnected sensors deployed within the marine environment to monitor, analyze, interpret, and provide decision support for farm operations. Recent technological innovations facilitate aquaculture becoming part of the Internet of Things (IoT) -- modern farms are characterized by hundreds of interconnected sensors that store and serve data, interact with other sensors and devices, and connect with a fog and cloud ecosystem. We describe the implementation of the precision aquaculture concept to a number of farms in eastern Canada. The work combines partners from industry, technology, and academia to provide data-driven insight and decision that promotes ecologically sustainable intensification of aquaculture. The article presents a first case study on how IoT can instrument, inform, and impact the aquaculture industry. Challenges related to connectivity, interoperability, and standardization are discussed, and we elucidate how our experiences can inform future activities.

Marine aquaculture is the most promising industry for ensuring future provision of seafood. Yet, the worldwide growth and expansion of this industry have been slower than expected, calling for the identification of environmentally suitable sites while accounting for all factors that could constrain or benefit its establishment. Here, we determine the main obstacles and risks hindering the growth and expansion of marine aquaculture, as well as the needs and recommendations to overcome such constraints. Our analysis is based on results obtained from a consultation process held in 16 study sites located around the world with the participation of 614 stakeholders representing the research community, aquaculture industry, government, conservation groups, and education and fishermen associations. A high level of commonality exists in the main issues hindering aquaculture growth and expansion in coastal, off-the-coast and offshore aquaculture with most being attributed to interactions with other maritime activities, including conflicts with other users and administrative procedures, including licensing. Critical needs for improved management and expansion of the aquaculture industry are related to planning andmanagement of developments and technological advances, with economic and market needs featuring to a lesser extent. Key procedures recommended to assist further aquaculture growth are th standardisation and simplification of regulatory frameworks, improvement of governance, and the adoption of participatory processes to facilitate meaningful and productive stakeholder engagement. We strongly recommend stakeholder participation to enhance insights on the full environmental and human dimensions of marine management and for implementation of ecosystem-based marine spatial planning.

An aquaculture investor (AQI) index was developed in order to provide a broad view of the relative attractiveness of 29 different European countries to aquaculture investors. AQI is based on five complementary categories: Market, Production, Regulatory, Environment, and Social, with each category containing four indicators. The attraction of investment into aquaculture depends on the viability of developing aquaculture for each country, and these five categories account for the connectivity in the aquaculture industry. The index benchmarks and tracks countries' progress by producing a quantitative and scalable tool for stakeholders to assess and monitor aquaculture attractiveness, and is designed to rank aquaculture competitiveness for each country. Index scores calculated for Europe range from moderate to good, on a heuristic five-class scale. Countries in Northern Europe with well-established aquaculture sectors score better than countries in Southern Europe. Countries with developing aquaculture sectors tend to score moderately. While high scores within single categories can be achieved, the index rewards countries with high scores across the five categories, to provide a more useful tool for stakeholders. No countries within Europe rank below the middle of the moderate range. The index identifies several countries with high scores that do not have significant aquaculture industries (e.g. Sweden and Finland), and further research is warranted to identify why aquaculture has not been developed. It is expected that as AQI is expanded to lower income countries spanning other geographic regions, countries with lower quality indicator scores will have lower overall scores. The index provides a broad-scale approach across a wide range of categories, and should be interpreted in that context, since it is designed to provide high-level guidance of the general attractiveness for aquaculture in each country. Appropriate due diligence for specific circumstances is warranted by all stakeholders requiring further knowledge to assist decision-making. To ensure a wide dissemination and maximum visual appeal to both investors and the public, the AQI index was deployed as a smartphone application (AquaInvestor), freely available on the Google Play Store, together with a companion website, and to our knowledge provides the first country-wide comparative assessment of aquaculture potential, available to investors and the general public in eight European languages and Chinese.

Visually-based approaches using techniques such as sediment surface images as well as sediment profile imaging (SPI) have been applied previously in the assessment of benthic impacts of organic enrichment. New visually-based benthic health indices (VBH and Surface Index) that integrate various visual properties was developed for muddy and sandier sediments, respectively. Visual indices were compared to the existing sulfide-based thresholds often used in environmental monitoring programs (EMPs). We utilized both techniques as well as geochemical indicators of eutrophication to detect benthic impacts at shallow shellfish and finfish farms in Nova Scotia, Canada. The visual indices were able to capture a non-sulfidic anaerobic condition in the sediments missed by the current sulfide-based system. Our results indicate that as presently configured, the visual based index will provide a more stringent standard in the EMPs that currently rely on a sulfide-based classification system, and thus affect regulatory judgement.

The need to employ management strategies that recognize ecosystem services and their trade-offs is considered a cornerstone for the implementation of an Ecosystem Approach to Aquaculture (EAA), yet it is unclear how to operationalize these concepts. Here, the role of certification and sustainable seafood ranking programs (sustainability schemes) in maintaining ecosystem services and supporting an EAA was explored. The representation of ecosystem services within sustainability scheme criteria, as well as the attributes of those criteria, were assessed using marine salmon aquaculture as a case study. Criteria reflected a range of ecosystem services and support reducing pressure on those services. However, consideration of the resilience capacity of ecosystem services, recognition of enhancements to ecosystem services, and attributes that support cost-benefit analysis of salmon farming appear to be limited within sustainability scheme criteria. Overall, the farm-scale assessment approach of many sustainability schemes appears to be incongruent with the broader spatial perspective required to operationalize EAA.

Maximizing the mitigation potential of open-water finfish-shellfish integrated multi-trophic aquaculture (IMTA) farms is complex in terms of co-locating the trophic components. Both the dispersal of finfish aquaculture wastes and biological processes are highly influenced by water circulation. Consequently, the evaluation of shellfish-finfish synergy requires a combined study of biological and physical processes, which can be achieved by the implementation and coupling of mathematical models. A highly configurable mathematical model was developed that can be applied at the apparent spatial scale of IMTA sites. The model tracks different components of the seston, including feed wastes, fish faeces, shellfish faeces, natural detritus and phytoplankton. Based on the characterization of these fluxes, a hypothetical IMTA site was used to explore different spatial arrangements for evaluating finfish-shellfish farm mitigation efficiency. The site was modelled following a factorial design, which tested 2 levels of background seston concentrations, 3 farm designs, 2 hydrodynamic conditions and 2 levels of aquaculture intensity. The model predicts that mitigation efficiency is highly dependent on the background environmental conditions, obtaining maximum mitigation under oligotrophic conditions that stimulate shellfish filtration activity. The dominance of vertical fluxes of particulate matter triggered by the high settling velocity of finfish aquaculture wastes suggests that suspended shellfish aquaculture cannot significantly reduce organic loading of the seabed. Consequently, this suggests that waste mitigation at IMTA sites should be best achieved by placing organic extractive species (e.g. deposit feeders) on the seabed directly beneath finfish cages rather than in suspension in the water column.

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.

BACKGROUND: We compared injury incidence and mechanisms among youth, high school (HS), and National Collegiate Athletic Association (NCAA) boys’ and men’s lacrosse athletes for the 2014–2015 to 2016–2017 lacrosse seasons. METHODS: Multiple injury surveillance systems were used to capture 21 youth boys’, 22 HS boys’, and 20 NCAA men’s lacrosse team-seasons of data during the 2014–2015 to 2016–2017 seasons. Athletic trainers reported game and practice injuries and athlete exposures (AEs). Injuries included those occurring during a game and/or practice and requiring evaluation from an athletic trainer and/or physician. Injury counts, rates per 1000 AEs, and injury rate ratios (IRRs) with 95% confidence intervals (CIs) were calculated. RESULTS: The injury rate in youth was higher than those reported in HS (10.3 vs 5.3 per 1000 AEs; IRR = 2.0; 95% CI: 1.6–2.4) and the NCAA (10.3 vs 4.7 per 1000 AEs; IRR = 2.2; 95% CI: 1.9–2.5). When considering time loss injuries only (restricted participation of ≥24 hours), the injury rate in youth was lower than those reported in HS (2.0 vs 2.9 per 1000 AEs; IRR = 0.7; 95% CI: 0.5–0.95) and the NCAA (2.0 vs 3.3 per 1000 AEs; IRR = 0.6; 95% CI: 0.4–0.8). The concussion rate in youth was higher than those in HS (0.7 vs 0.3 per 1000 AEs; IRR = 2.4, 95% CI: 1.1–5.2) and the NCAA (0.7 vs 0.3 per 1000 AEs; IRR = 2.1, 95% CI: 1.2–3.7). Injuries at the youth, HS, and NCAA levels were most commonly associated with stick contact, inflammatory conditions (including bursitis, tendonitis, and other unspecified inflammation), and noncontact mechanisms, respectively. CONCLUSIONS: Although the time loss injury rate was lowest in youth boys’ lacrosse, the concussion rate was the highest. Injury prevention approaches should be specific to the mechanisms associated with each level of play (eg, equipment skill development in youth).

Food provisioning is a prominent feature of marine bivalve production, applicable worldwide since ancient times. Easy accessibility of this food source and high nutritional value make bivalves a possible driver in human evolution. In this section bivalve meat production is addressed, as well as other provisioning services including pearls and bio-active compounds. In both bivalve aquaculture and fisheries, harvest and production for meat provisioning must be balanced against carrying capacity and its implications for other services including water quality maintenance and habitat structure. Provisioning of meat through aquaculture can be improved via hatchery and breeding advances, a necessity in the changing ocean climate.

Bivalve aquaculture requires the alteration of natural populations of filter-feeders by artificially increasing their density. A bivalve farm could have negative consequences for the ecosystem if the filtration pressure of stocked biomass surpasses the capacity of the system to replenish the depleted resources. The concept of ecological carrying capacity, understood as the magnitude of aquaculture activity in a given area that can be supported without leading to unacceptable changes in the aquatic environment, is commonly used to inform management and regulatory decisions of bivalve aquaculture. In this study, a hydrodynamic model has been coupled to an ecological model that simulates the main dynamics of organic seston to evaluate the effects of bivalve aquaculture on seston supply and assess ecological carrying capacity. The spatially-explicit model allows the identification of areas where organic seston could be reduced beyond precautionary thresholds of ecosystem resilience. The model has been applied to three coastal embayments in Nova Scotia (Canada) that differ in water circulation and inlet/coastal complexity. The outcomes of the model suggest that the current aquaculture operations in Sober Island, Wine Harbour, and Whitehead are within the ecological carrying capacity of the ecosystem for bivalve aquaculture. The simulation of additional hypothetical stocking scenarios had demonstrated the relevance of local water circulation to the ecological carrying capacity of the system, and consequently for aquaculture operations. Accordingly, the placement of leases in areas with optimal circulation should be considered for planning purposes. The capability of the model to explore hypothetical scenarios could be used as a tool to guide management decisions in regard to site selection for new aquaculture sites.

Finfish aquaculture is a source of dissolved nutrients, which can impact water quality in the wider environment. Therefore, the potential effects of dissolved nutrient loading must be considered if management is to transition towards an Ecosystem Approach to Aquaculture. In this study, the dissolved nitrogen dispersion pattern from a rainbow trout farm in Port Mouton (Nova Scotia, Canada) was simulated and evaluated in the context of potential toxicity for a foundation seagrass species. A range of scenarios defined under a precautionary approach were simulated using a fully spatial hydrodynamic model. These worst-case scenarios predicted a maximum nitrogen concentration at any moment of the day of 7.5 μM, which is below the expected toxicity threshold for seagrass. Further scenarios demonstrated that the increased dispersion caused by the wind could drop these values by 45–50% in the vicinity of the farm, suggesting the relevant role of wind forcing in nitrogen dispersion. This outcome suggests that the decline of seagrass reported in some parts of Port Mouton bay are unlikely to have been triggered by dissolved nutrients discharged from the farm. This case-study demonstrates the value of ecosystem modelling to make science-based and transparent decisions to implement an ecosystem approach to aquaculture.

Open ocean fish farming involves containment of cultured animals under environmental conditions influenced by seasonal variation and water quality. Recently, an important area of research focus has been on water quality monitoring to improve aquaculture management. The development of novel sensors that report in real-time is critical to improve the monitoring capacity of farms, while increasing the understanding of the dynamics of environmental variables. In this study, commercially available, real-time dissolved oxygen and temperature sensors were distributed in the center of 19 cages at a commercial Atlantic salmon (Salmo salar) farm located within Shelburne Bay, Nova Scotia (Canada) and four reference sites. The site had an average depth of 15 m, while the cages consisted of nets 10 m deep. The dense deployment allowed for insight into the spatial and temporal variability of dissolved oxygen throughout the farm. Tide was determined to have the most significant impact on dissolved oxygen levels, with its influence varying depending on cage location within the farm. As waters flow from one end of the farm to the other, driven by tidal advection, fish behaviour and physiology, as well as flow restriction from cage infrastructure reduce oxygen levels in cages downstream. This results in oxygen concentrations out of phase on opposite ends of the farm, with higher oxygen levels at one end of the farm (i.e. 8.24 ± 0.29 mg L−1) and lower oxygen levels at the other (i.e. 5.38 ± 0.34 mg L−1) at any given phase of the tidal cycle. As Atlantic salmon become stressed and exhibit a reduced appetite at oxygen levels below 4–6 mg L−1, depending on temperature, it is important to accurately monitor the entirety of the farm. This study examined the patterns and drivers, specifically tide, of dissolved oxygen throughout a commercial salmon farm to understand the oxygen dynamics and make informed decisions that impact fish growth and welfare.

Context Recent injury-surveillance data for collegiate-level cross-country athletes are limited. Objective To describe the epidemiology of National Collegiate Athletic Association (NCAA) men's and women's cross-country injuries during the 2009–2010 through 2013–2014 academic years. Design Descriptive epidemiology study. Setting Aggregate injury and exposure data collected from 25 men's and 22 women's cross-country programs, providing 47 and 43 seasons of data, respectively. Patients or Other Participants Collegiate student-athletes participating in men's and women's cross-country during the 2009–2010 through 2013–2014 academic years. Main Outcome Measure(s) Injury rates; injury rate ratios (RRs); injury proportions by body site, diagnosis, and apparatus; and injury proportion ratios were reported with 95% confidence intervals (CIs). Results The Injury Surveillance Program captured 216 injuries from men's cross-country and 260 injuries from women's cross-country, leading to injury rates of 4.66/1000 athlete-exposures (AEs) for men (95% CI = 4.04, 5.28) and 5.85/1000 AEs for women (95% CI = 5.14, 6.56). The injury rate in women's cross-country was 1.25 times that of men's cross-country (95% CI = 1.05, 1.50). Most injuries affected the lower extremity (men = 90.3%, women = 81.9%). The hip/groin-injury rate in women (0.65/1000 AEs) was higher than that in men (0.15/1000 AEs; RR = 4.32; 95% CI = 1.89, 9.85). The ankle-injury rate in men (0.60/1000 AEs) was higher than that in women (0.29/1000 AEs; RR = 2.07; 95% CI = 1.07, 3.99). Common diagnoses were strains (men = 19.9%, women = 20.4%) and inflammation (men = 18.1%, women = 23.8%). The majority of injuries were classified as overuse (men = 57.6%, women = 53.3%). Conclusions Consistent with prior research, injury distributions varied between male and female athletes, and the injury rate among females was higher. Understanding the epidemiology of these cross-country injuries may be important for developing appropriate preventive interventions.

Coastal embayments are dynamic open systems characterized by multiple sedimentary environments with specific biogeochemical properties, which instead are influenced by physicochemical and biological processes (e.g., hydrodynamics, carbon deposition, abiotic-chemical reactions, macrofaunal and microbial activity). In this study, a novel approach that combines benthic habitat mapping, empirical measurements, and multivariate analysis was used 1) to determine the variability of benthic primary production, respiration, and denitrification in different sediment types; and 2) to examine how sediment nutrient fluxes are influenced by organic content, porosity, salinity, temperature, depth, light availability, habitat, and sediment type. Of the total observed variance in benthic metabolic activity, 12.6%–66.5% was accounted for by these variables. Results highlight the important role of benthic diversity and their contribution to energy and matter cycling in coastal sediments. Consideration of these factors is key for the prediction of benthic processes at scales relevant for coastal management and valuation of associated ecosystem services.

In this paper we focus on the role of ecosystem models in improving our understanding of the complex relationships between bivalve farming and the dynamics of lower trophic levels. To this aim, we review spatially explicit models of phytoplankton impacted by bivalve grazing and discuss the results of three case studies concerning an estuary (Baie des Veys, France), a bay, (Tracadie Bay, Prince Edward Island, Canada) and an open coastal area (Adriatic Sea, Emilia-Romagna coastal area, Italy). These models are intended to provide insight for aquaculture management, but their results also shed light on the spatial distribution of phytoplankton and environmental forcings of primary production. Even though new remote sensing technologies and remotely operated in situ sensors are likely to provide relevant data for assessing some the impacts of bivalve farming at an ecosystem scale, the results here summarized indicate that ecosystem modelling will remain the main tool for assessing ecological carrying capacity and providing management scenarios in the context of global drivers, such as climate change.

Correction to: A. C. Smaal et al. (eds.), Goods and Services of Marine Bivalves, https://doi.org/10.1007/978-3-319-96776-9. This book was inadvertently published with an incorrect copyright year '2018' within the book references. This has now been amended throughout the book to the correct copyright year '2019'.

Accurate maps representing seagrass spatial distribution are essential components for effective monitoring and management of coastal vegetated habitats. Satellite and acoustic remote sensing provide valuable spatial data for seagrass mapping, though few studies have evaluated the complementarity of these methods. In this study, the complementarity of seagrass mapping was assessed through comparison of acoustic and satellite remote-sensing data sets. QuickBird® satellite imagery representing the seagrass landscape of the Richibucto estuary, New Brunswick, Canada, was classified through an object-based procedure and evaluated against a single-beam sonar data set. Acoustic percentage cover values were classified into binary presence/absence format through the application of a decision threshold, allowing comparison with satellite data using the error matrix and derived metrics. Though the binary satellite classification resulted in relatively high accuracy compared with independent ground reference data, agreement between satellite and acoustic data sets was limited. Local differences in seagrass prevalence and patchiness affected classification accuracy, highlighting the potential for under-or overestimating seagrass cover when applying bay-scale classification to areas with different landscape structure. These results emphasize the importance of landscape context in seagrass mapping. Satellite and acoustic remote sensing were seen to fundamentally differ in their depiction of the landscape. Comparison of multiple remote-sensing methods allowed for assessment of complementarity as well as ecologically relevant insight to seagrass spatial dynamics, with implications for mapping and monitoring of seagrass habitats.

Intertidal landscapes are highly complex and dynamic habitats that exhibit variability over a range of spatial and temporal scales. The spatial arrangement of structure-forming biogenic features such as seagrasses and bivalves influences ecosystem function and the provision of important ecosystem services, though quantification and monitoring of intertidal landscape structure has been hindered by challenges collecting spatial data in the coastal zone. In this study, an intertidal landscape mosaic of eelgrass ( Zostera marina) and blue mussels ( Mytilus edulis) was observed using low-altitude aerial photography from a balloon-mounted digital camera platform. Imagery representing seagrass-bivalve landscape structure was classified and analysed using multiple metrics of landscape composition and configuration at the patch scale and the landscape scale. Patch-scale imagery was compared to a previously collected dataset in order to track temporal changes in seagrass patch metrics over a 26-month period. Seagrass and bivalve patches exhibited distinct spatial patterning at different spatial scales. At the patch scale, the change in seagrass metrics was consistent with patch border expansion at the expense of patch density and integrity. These methods demonstrate a novel approach for collecting high-resolution spatial data that could also be valuable to physical geographers dealing with similar fine-scale landscapes. The application of spatial metrics at multiple spatial scales quantified elements of the configuration and composition of a seagrass-bivalve habitat mosaic and allowed for the tracking of patch metrics through time to depict landscape change. Continued development of landscape metrics within intertidal habitats will increase understanding of the ecological function of these areas with benefits to management and monitoring of ecosystem health.

Temperature affects nearly all biological rates and consequently is fundamental to individual development time and timing of phenological events. One example is the duration of the pelagic larval stage of mussels, which is crucial for determining the magnitude and timing of recruitment, as well as population dispersal patterns. Understanding the impact of temperature on the rate of larval development is key to predicting the timing of settlement and optimizing mussel seed collection. Advising mussel farmers on Prince Edward Island about the ideal timing for collector deployment is one of the goals of the Mussel Monitoring Program (MMP). In this study we examine the relationship between the phenology of larval development based on MMP data, and satellite measurements of sea surface temperature. The analyses indicated that the first day of the year on which 10 –20% of the pool of mussel larvae reached 250 mm could be predicted using the thermal integral measure growing degree-days. While this finding confirmed the importance of temperature for mussel larval phenology, the effect of other environmental variables such as phytoplankton quantity and quality cannot be dismissed.