The role of wind in controlling the connectivity of blue mussels (Mytilus edulis L.) populations

Abstract

Abstract Background Larval connectivity between distinct benthic populations is essential for their persistence. Although connectivity is difficult to measure in situ, it can be predicted via models that simulate biophysical interactions between larval behaviour and ocean currents. The blue mussel (Mytilus Edulis L.) is widespread throughout the northern hemisphere and extensively commercialised worldwide. In the Irish Sea, this industry represents ~ 50% of Welsh shellfisheries, where cultivation is mainly based on wild spat. However, the main sources and amount of spat varied interannually (1100 tonnes harvest in 2014 against zero in 2018). The aim of this study is to characterise the structure and dynamics of the blue mussel metapopulation within the northern part of the Irish Sea. Methods We develop a Lagrangian particle tracking model, driven by a high-resolution (from 30 to 5000 m) validated unstructured coastal hydrodynamic model of the Irish Sea, to simulate spatial and temporal variability of larval dispersal and connectivity between distinct mussel populations and potential settlement areas. Results Our results showed that: (1) larvae positioned near the surface were strongly influenced by wind-driven currents suggesting that connectivity networks had the potential to span hundreds of kilometres; (2) in contrast, larvae positioned deeper in the water column were driven by tidal currents, producing intricate spatial patterns of connectivity between mussel beds over tens of kilometres that were consistent over time. Conclusions Dispersal of mussel larvae in the tidally energetic Irish Sea during the April–May spawning season is potentially driven by wind-driven surface currents, as confirmed by fisherman observations of inter-annual variability in wild spat collection. These results have important implications for metapopulation dynamics within the context of climate change and sustainable shellfisheries management (i.e. gain and loss of populations and harvest areas according to wind conditions).