TY - JOUR
T1 - Predictive biophysical models of bivalve larvae dispersal in Scotland
AU - Corrochano-Fraile, Ana
AU - Adams, Thomas
AU - Aleynik, Dmitry
N1 - © 2022 Corrochano-Fraile, Adams, Aleynik, Bekaert and Carboni. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY).
PY - 2022/9/12
Y1 - 2022/9/12
N2 - 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.
AB - 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.
KW - bivalve
KW - larval disposal
KW - particle tracking
KW - Scotland
KW - Aquaculture
KW - finite volume coastal ocean model
U2 - https://doi.org/10.3389/fmars.2022.985748
DO - https://doi.org/10.3389/fmars.2022.985748
M3 - Article
SN - 2296-7745
JO - Frontiers in Marine Science
JF - Frontiers in Marine Science
IS - 9
M1 - 985748
ER -