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Predictive biophysical models of bivalve larvae dispersal in Scotland

  • Ana Corrochano-Fraile
  • , Thomas P. Adams
  • , Dmitry Aleynik
  • , Michael Bekaert
  • , Stefano Carboni

Research output: Contribution to journal › Article › peer-review

7 Citations (Scopus)
129 Downloads (Pure)

Abstract

In Scotland, bivalves are widely distributed. However, their larvae dispersion is still largely unknown and difficult to assess in situ. And, while Mytilus spp. dominate shellfish production, it is mostly dependent on natural spat recruitment from wild populations. Understanding the larval distribution pattern would safeguard natural resources while also ensuring sustainable farming practises. The feasibility of a model that simulates biophysical interactions between larval behaviour and ocean motions was investigated. We employed an unstructured tri-dimensional hydrodynamic model (finite volume coastal ocean model) to drive a particle tracking model, where prediction of larval movement and dispersal at defined locations might aid in population monitoring and spat recruitment. Our findings reveal a strong link between larval distribution and meteorological factors such as wind forces and currents velocity. The model, also, depicts a fast and considerable larval movement, resulting in a substantial mix of plankton and bivalve larvae, forming a large connection between the southern and northern regions of Scotland’s West coast. This enables us to forecast the breeding grounds of any area of interest, potentially charting connectivity between cultivated and wild populations. These results have significant implications for the dynamics of ecologically and economically important species, such as population growth and loss, harvesting and agricultural management in the context of climate change, and sustainable shellfish fisheries management. Furthermore, the observations on Scottish water flow suggest that tracking particles with similar behaviour to bivalve larvae, such as other pelagic larval stages of keystone species and potential pathogens such as sea lice, may have policy and farming implications, as well as disease control amid global warming issues.
Original languageEnglish
Article number985748
Number of pages11
JournalFrontiers in Marine Science
Volume9
Issue number9
DOIs
Publication statusPublished - 12 Sept 2022

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 2 - Zero Hunger
    SDG 2 Zero Hunger
  2. SDG 8 - Decent Work and Economic Growth
    SDG 8 Decent Work and Economic Growth
  3. SDG 12 - Responsible Consumption and Production
    SDG 12 Responsible Consumption and Production
  4. SDG 13 - Climate Action
    SDG 13 Climate Action
  5. SDG 14 - Life Below Water
    SDG 14 Life Below Water
  6. SDG 17 - Partnerships for the Goals
    SDG 17 Partnerships for the Goals

Keywords

  • bivalve
  • larval disposal
  • particle tracking
  • Scotland
  • Aquaculture
  • finite volume coastal ocean model

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