Salmon aquaculture can be a potential solution to bridge the gap between declining capture fisheries and increasing seafood demand. However, the environmental impacts it creates have generated criticism. The overall objectives of this dissertation are to examine the economic consequences of environmental issues associated with salmon aquaculture, and to explore policy implications and recommendations for reducing environmental impacts. These objectives are addressed in five main analyses. The growth of salmon aquaculture is analyzed based on farmed salmon production in the four leading producing countries and the sector as a whole. Analyses indicate that salmon aquaculture is unlikely to continue to grow at its current pace. A joint production function approach is used to estimate pollution abatement costs for the salmon aquaculture industry. Results reveal that pollution abatement costs vary among observations and models. On average, pollution abatement cost is estimated at 3.5% in terms of total farmed salmon production, and 6.5% in terms of total revenue of farmed salmon. The ecological and economic impacts of sea lice from salmon farms on wild salmon population and fisheries are also studied. Analyses suggest that these effects are minor when the sea lice induced mortality rate is below 20%, while they can be severe if the mortality is greater than 30%. Sea lice have greater ecological and economic impacts on pink salmon than on chum salmon. These effects are greater under a fixed exploitation rate than under a target escapement policy. The economic performance of open netcage and sea-bag production systems for salmon aquaculture is compared. Netcage systems appear to be more economically profitable than sea-bag systems when environmental costs are either not or only partially included. Sea-bag systems can be financially profitable only when the salmon they produce can achieve a price premium. Finally, policy implications are explored and recommendations are made for sustaining salmon aquaculture in a holistic manner based on the results from previous chapters. Technologies, economic-based instruments and more stringent environmental policies can be employed to reduce environmental impacts. However, there is no single solution to solve these environmental impacts, and a combination of policy options is needed.

Salmon aquaculture can be a potential solution to bridge the gap between declining capture fisheries and increasing seafood demand. However, the environmental impacts it creates have generated criticism. The overall objectives of this dissertation are to examine the economic consequences of environmental issues associated with salmon aquaculture, and to explore policy implications and recommendations for reducing environmental impacts. These objectives are addressed in five main analyses. The growth of salmon aquaculture is analyzed based on farmed salmon production in the four leading producing countries and the sector as a whole. Analyses indicate that salmon aquaculture is unlikely to continue to grow at its current pace. A joint production function approach is used to estimate pollution abatement costs for the salmon aquaculture industry. Results reveal that pollution abatement costs vary among observations and models. On average, pollution abatement cost is estimated at 3.5% in terms of total farmed salmon production, and 6.5% in terms of total revenue of farmed salmon. The ecological and economic impacts of sea lice from salmon farms on wild salmon population and fisheries are also studied. Analyses suggest that these effects are minor when the sea lice induced mortality rate is below 20%, while they can be severe if the mortality is greater than 30%. Sea lice have greater ecological and economic impacts on pink salmon than on chum salmon. These effects are greater under a fixed exploitation rate than under a target escapement policy. The economic performance of open netcage and sea-bag production systems for salmon aquaculture is compared. Netcage systems appear to be more economically profitable than sea-bag systems when environmental costs are either not or only partially included. Sea-bag systems can be financially profitable only when the salmon they produce can achieve a price premium. Finally, policy implications are explored and recommendations are made for sustaining salmon aquaculture in a holistic manner based on the results from previous chapters. Technologies, economic-based instruments and more stringent environmental policies can be employed to reduce environmental impacts. However, there is no single solution to solve these environmental impacts, and a combination of policy options is needed.

Salmon aquaculture can be a potential solution to bridge the gap between declining capture fisheries and increasing seafood demand. However, the environmental impacts it creates have generated criticism. The overall objectives of this dissertation are to examine the economic consequences of environmental issues associated with salmon aquaculture, and to explore policy implications and recommendations for reducing environmental impacts. These objectives are addressed in five main analyses. The growth of salmon aquaculture is analyzed based on farmed salmon production in the four leading producing countries and the sector as a whole. Analyses indicate that salmon aquaculture is unlikely to continue to grow at its current pace. A joint production function approach is used to estimate pollution abatement costs for the salmon aquaculture industry. Results reveal that pollution abatement costs vary among observations and models. On average, pollution abatement cost is estimated at 3.5% in terms of total farmed salmon production, and 6.5% in terms of total revenue of farmed salmon. The ecological and economic impacts of sea lice from salmon farms on wild salmon population and fisheries are also studied. Analyses suggest that these effects are minor when the sea lice induced mortality rate is below 20%, while they can be severe if the mortality is greater than 30%. Sea lice have greater ecological and economic impacts on pink salmon than on chum salmon. These effects are greater under a fixed exploitation rate than under a target escapement policy. The economic performance of open netcage and sea-bag production systems for salmon aquaculture is compared. Netcage systems appear to be more economically profitable than sea-bag systems when environmental costs are either not or only partially included. Sea-bag systems can be financially profitable only when the salmon they produce can achieve a price premium. Finally, policy implications are explored and recommendations are made for sustaining salmon aquaculture in a holistic manner based on the results from previous chapters. Technologies, economic-based instruments and more stringent environmental policies can be employed to reduce environmental impacts. However, there is no single solution to solve these environmental impacts, and a combination of policy options is needed. / Science, Faculty of / Resources, Environment and Sustainability (IRES), Institute for / Graduate

The intersection of the environment, the economy and society create a wicked problem in salmon aquaculture in Canada. To provide a unique insight into the challenges of the salmon aquaculture industry amongst key stakeholders, this thesis investigates the sentiment of several important stakeholder groups in the salmon aquaculture industry: academics, industry, ENGOs, Government, Indigenous peoples, and the media. By scraping data from Twitter from the years 2006 to 2021, it examines aquaculture sentiment from a global English-speaking view, as well as a subset of Canadian data. This thesis addresses the following questions: How does public sentiment towards salmon aquaculture differ over time? How does public sentiment towards salmon aquaculture differ among stakeholder groups? Data is analyzed through a stakeholder management theory framework using sentiment analysis. Data is collected from Twitter because users prefer it to other social media sites to share their unprompted thoughts, ideas, and opinions. The data is scrapable using the open-source Twitter scraper Twint. The data is processed using Google Colab notebooks: raw data is preprocessed into 273,319 tweets (rows) of clean data, which are analyzed using VADER’s natural language processing tool, yielding a sentiment score between -1 and +1 for each tweet. This thesis explores the dependent variable of sentiment and the independent variable of time. Findings are examined through the lens of overall sentiment, sentiment from year to year (2006-2021), sentiment per stakeholder category, and sentiment per stakeholder category per year. Sentiment from 2007 to 2021 is expected to be increasingly negative because of significant negative events in the salmon aquaculture industry from 2006 to 2021. There have been many policy changes, lawsuits, fish escapes and concerns from ENGOs, Indigenous groups, and researchers about salmon aquaculture during this time. However, the data contradicts this hypothesis by trending positively over time. The overall dataset is consistent and clusters around a mean of 0.3 (slightly positive), a median of 0.4 and a standard deviation of 0.4. The skewness of the general data is -0.994, meaning that the distribution has a moderate negative skew (most tweets have positive sentiment). The dataset has an R-squared value of 0.64, meaning that the data represents a moderate model, and an R-squared value of 0.79 (when removing outliers) shows an absolute strong model. All eight stakeholder group categories display a moderately negative skewness value and a positive mean sentiment. The Academic / Researcher Group and the Industry / Worker stakeholder groups show strong models, and the other stakeholder categories with lower R-squared values show weaker models. This thesis provides new insight into the growing and expanding salmon aquaculture industry. Further, understanding stakeholder sentiment can allow a government, individual, or group to be more proactive in its decision-making rather than reactive. The data allows for open dialogue with all stakeholders and promotes future research, analysis, and collaboration within the salmon aquaculture industry.

Increasing the amount of food produced while simultaneously reducing the environmental impacts of agriculture is one of the most pressing challenges facing humanity. A promising approach through which this could be achieved is ‘sustainable intensification’. This thesis contributes to the exploration of sustainable intensification using two complementary modes of investigation. First through the development of a conceptual framework that analyzes agricultural systems through the lens of ecosystem services and the trade-offs associated with using external inputs (e.g. fertilizer, pesticides, fossil fuels) as substitutes for them. Then by quantifying the life cycle environmental impacts of a novel aquaculture technology developed as a means for minimizing local ecological impacts. These modes of investigation are linked by using the conceptual framework to analyze trade-offs associated with waste capture in the aquaculture system. This research provides a potentially valuable method for conceptualizing agricultural systems and contributes to the knowledge of the environmental trade-offs associated with aquaculture.

There is considerable opportunity to develop new modelling techniques within a Geographic Information Systems (GIS) framework for the development of sustainable marine cage culture. However, the spatial data sets are often uncertain and incomplete, therefore new spatial models employing “soft computing” methods such as fuzzy logic may be more suitable. The aim of this study is to develop a model using Neuro-fuzzy techniques in a 3D GIS (Arc View 3.2) to predict coastal environmental vulnerability for Atlantic salmon cage aquaculture. A 3D hydrodynamic model (3DMOHID) coupled to a particle-tracking model is applied to study the circulation patterns, dispersion processes and residence time in Mulroy Bay, Co. Donegal Ireland, an Irish fjard (shallow fjordic system), an area of restricted exchange, geometrically complicated with important aquaculture activities. The hydrodynamic model was calibrated and validated by comparison with sea surface and water flow measurements. The model provided spatial and temporal information on circulation, renewal time, helping to determine the influence of winds on circulation patterns and in particular the assessment of the hydrographic conditions with a strong influence on the management of fish cage culture. The particle-tracking model was used to study the transport and flushing processes. Instantaneous massive releases of particles from key boxes are modelled to analyse the ocean-fjord exchange characteristics and, by emulating discharge from finfish cages, to show the behaviour of waste in terms of water circulation and water exchange. In this study the results from the hydrodynamic model have been incorporated into GIS to provide an easy-to-use graphical user interface for 2D (maps), 3D and temporal visualization (animations), for interrogation of results. v Data on the physical environment and aquaculture suitability were derived from a 3- dimensional hydrodynamic model and GIS for incorporation into the final model framework and included mean and maximum current velocities, current flow quiescence time, water column stratification, sediment granulometry, particulate waste dispersion distance, oxygen depletion, water depth, coastal protection zones, and slope. The Neuro-fuzzy classification model NEFCLASS–J, was used to develop learning algorithms to create the structure (rule base) and the parameters (fuzzy sets) of a fuzzy classifier from a set of classified training data. A total of 42 training sites were sampled using stratified random sampling from the GIS raster data layers, and the vulnerability categories for each were manually classified into four categories based on the opinions of experts with field experience and specific knowledge of the environmental problems investigated. The final products, GIS/based Neuro Fuzzy maps were achieved by combining modeled and real environmental parameters relevant to marine fin fish Aquaculture. Environmental vulnerability models, based on Neuro-fuzzy techniques, showed sensitivity to the membership shapes of the fuzzy sets, the nature of the weightings applied to the model rules, and validation techniques used during the learning and validation process. The accuracy of the final classifier selected was R=85.71%, (estimated error value of ±16.5% from Cross Validation, N=10) with a Kappa coefficient of agreement of 81%. Unclassified cells in the whole spatial domain (of 1623 GIS cells) ranged from 0% to 24.18 %. A statistical comparison between vulnerability scores and a significant product of aquaculture waste (nitrogen concentrations in sediment under the salmon cages) showed that the final model gave a good correlation between predicted environmental vi vulnerability and sediment nitrogen levels, highlighting a number of areas with variable sensitivity to aquaculture. Further evaluation and analysis of the quality of the classification was achieved and the applicability of separability indexes was also studied. The inter-class separability estimations were performed on two different training data sets to assess the difficulty of the class separation problem under investigation. The Neuro-fuzzy classifier for a supervised and hard classification of coastal environmental vulnerability has demonstrated an ability to derive an accurate and reliable classification into areas of different levels of environmental vulnerability using a minimal number of training sets. The output will be an environmental spatial model for application in coastal areas intended to facilitate policy decision and to allow input into wider ranging spatial modelling projects, such as coastal zone management systems and effective environmental management of fish cage aquaculture.