title: Modelling the northern stock of European Sea Bass (Dicentrarchus labrax): an individual based approach
Creators: name: Watson, Joseph William
Publisher: name: University of Reading
Year: 2021

description: Capture fisheries provide nutrition, jobs, and recreation across the world. However, the aquatic ecosystems in which they operate are under increasing pressures from climate change, fishing pressure and other anthropogenic stressors. It is the difficult role of fisheries management to consider all the needs of fisheries and threats to these aquatic resources and find an appropriate balance. In this thesis, I focus on what happens to individuals in capture fisheries and build a series of models to analyse both the fish and the fishers that catch them. I have specifically focused on the northern stock of the important commercially and recreationally targeted European sea bass (Dicentrachus labrax). By focusing on the individuals, I obtain mechanistic insights into different aspects of this fishery and make suggestions on how this could be used in future management. Following the theme of the individual, I start by considering sublethal impacts of anthropogenic stressors on individual fish. Stressors caused by human activities can cause a range of sublethal impacts such as detrimental behavioural changes or injury that could result in reduced growth and reproduction. In chapter two I develop an energy budget approach to investigate how these sublethal stressors can influence life processes of fish. The method developed partitions impact into the initial energetic cost of attempts to escape from the stressor, followed by the energetic impacts of any injury or behavioural change, and their consequent effects on life processes. As a case study, I assess the sublethal effects of catch and release angling for the European sea bass. Chapter three moves on from fish and focuses on the fishing pressure caused by the fishers, where I analyse fisher decisions with the aim of gaining a mechanistic insight into fishing pressure. As in chapter two the study focuses on the northern UK stock of sea bass, specifically the under 10m fleet that target them. This study makes use of a vessel logbook scheme alongside environmental and economic data sets to investigate daily decisions made by commercial sea bass fishers. The primary result is the important effect of wave height on fisher behaviour, where I found that fewer vessels left UK ports during rough weather to go fishing and vessels that did were less successful. The findings from this study have implications for management as increases of extreme weather events during the key fishing seasons may impact on the ability of the small inshore vessels to land catch limits within allowed time periods, which may affect their profitability. In chapters four and five, consistent with the individual theme, I present a spatially explicit individual based model (IBM) of the northern stock of European sea bass. The IBM is developed from an existing IBM published by Walker et al., 2020. The key updates are the addition of a realistic energy budget driven by dynamic maps of phytoplankton density and the inclusion of all life stages. The energy budget additions now link population dynamics to environmental drivers which ultimately produce emergent population dynamics, including key fisheries management metrics. I present some encouraging fits to the ICES stock assessment data and suggest the IBM could be an additional tool in stock assessment. This research can be used to inform future management of the northern stock of sea bass, especially in the context of spatial management. Future works should focus on using the IBM to test a range of management scenarios and responses to environmental change and has additional scope to add the findings from chapters two and three as sub models related to fisher behaviour and sublethal stressors. The approach developed for sea bass could be applied to other species and fisheries, which would allow spatial management measures to be tested more effectively.