Safeguarding the welfare of Scottish farmed Atlantic salmon: current practices and future prospects

Abstract

Farmed fish welfare has become a growing priority as aquaculture continues to expand to meet global demand. The Scottish salmon farming industry is a prime example of this growth, reaching record highs in production and intensification over recent years. The compelling evidence for fish sentience highlights the ethical imperative of safeguarding the welfare of the millions of animals involved. Achieving appropriate levels of salmon welfare, however, presents considerable challenges. Animal welfare is a complex, multi-faceted concept, the intricacy of which is only further amplified when dealing with the anadromous life cycle of Atlantic salmon. The aim of this PhD was to provide industry-relevant contributions towards the monitoring and safeguarding of farmed salmon welfare. An additional aim was to validate or further refine a novel on-farm welfare assessment tool that provides the most benefits in this manner. Chapter 1 provides the context for this study, outlining key concepts of animal welfare, the importance of farmed salmon welfare, and various factors, indicators, and considerations that are important for farmed salmon welfare. Chapter 2 addresses the complexity of enhancing farmed salmon welfare by conducting a survey on the Scottish salmon farming sector, consulting industry professionals to better understand their current welfare concerns and research priorities. Chapter 3 investigates what role welfare standards can play in providing assurances for farmed salmon welfare, as well as how welfare practices within the industry have changed over the years, through examining changes in farm site compliance to these standards. Chapter 4 assessed the effectiveness of Qualitative Behavioural Assessment (QBA) in capturing changes in the behavioural expressions of Atlantic salmon following exposure to a stressful event. Chapter 5 summarises the findings from these studies, outlining how Chapters 2 and 3 informed the development of the QBA experiment conducted in Chapter 4 and the significance of QBA’s validation. Chapter 5 then develops on these findings, proposing a direction for future research regarding the potential for behavioural welfare assessment tools to utilise computer vision and machine learning technologies. The results from this thesis highlight the potential that non-intrusive, remote, animal-based welfare indicators have in improving the monitoring and management of farmed salmon welfare. In particular, QBA shows great potential as a unique welfare indicator within aquaculture. This is the first study to demonstrate QBA’s sensitivity to changes in the behavioural expressions of Atlantic salmon and highlight the unique insights it offers into salmon welfare.