Introduction
Sea lice remain a huge constraint for the sustainability of the aquaculture industry (Brooker et al., 2018; Moriarty et al., 2024). Their impact has driven the development of management tools, particularly models that can predict population dynamics, simulate dispersal between connected farms and wild populations of fish, and evaluate the efficacy of control strategies (Harrington et al., 2023; Revie et al., 2005). Particle-tracking models coupled with hydrodynamic components can simulate sea lice life cycles and transmission under variable environmental conditions. Sea lice dispersal models have become more readily integrated into management frameworks by determining appropriate treatment, stocking and fallowing periods of specific aquaculture zones (Vollset et al., 2018). However, model application and effectiveness remain inhibited by limited biological data. Knowledge gaps have been identified in previous reviews, highlighting the limitations arising from incomplete or outdated representations of louse biology (Brooker et al., 2018; Moriarty et al., 2024). Key processes influencing the planktonic larval stages require particular attention, as they remain poorly parameterized. We systematically evaluate the range of biological parameter values used in salmon lice dispersal models, with particular emphasis on planktonic larval stages, to distinguish empirically supported parameters from those that are assumed or weakly supported. By examining areas where empirical data are lacking, and assessing the extent to which generalised parameter values are applied across studies, we have identified priority areas where laboratory and field studies could improve parameterizations.
Methodology
To carry out a comprehensive search for papers that describe the development of dynamic sea lice models using biological data, keywords and Boolean logic were applied in Web of Science and Scopus. Articles went through an exclusion process resulting in 81 papers ultimately being assessed for biological parameterisation. Biological sea louse parameters were chosen for their importance to the infection process and modelling outcomes. These included data on ovigerous females, such as their abundance and source of data, as well as key fecundity-related parameters including egg number, egg replacement rate and egg viability. Additional parameters considered were hatching rates, larval development rates, mortality rates and swimming behaviour.
Results and Discussion
We determined that larval development rates are generally well characterised, however there is a reliance on outdated or limited data in other key areas including female reproduction, larval mortality, and larval swimming behaviour. These findings illustrate a need to better incorporate more scientifically rooted biological and environmental variability into models to improve the accuracy of their predictions and in turn strengthen sea lice management. Consequently, experiments aimed at strengthening these knowledge gaps have been developed. We will present preliminary data on the role of predation on influencing numbers of planktonic sea lice larvae including identifying the main planktonic predators. Additionally, experiments looking at how fecundity varies spatially and between lice from both wild and farmed fish has become a greater focus to eliminate uncertainties and will also be discussed.
Acknowledgment
This studentship has been funded under the NERC Scottish Universities Partnership for Environmental Research (SUPER) Doctoral Training Partnership (DTP) (Grant reference number NE/S007342/1 and website https://superdtp.st-andrews.ac.uk/), with additional CASE funding provided by MOWI Scotland Ltd., and Scottish Sea Farms.
References
Brooker, A.J., Skern-Mauritzen, R. and Bron, J.E. (2018) 'Production, mortality, and infectivity of planktonic larval sea lice, Lepeophtheirus salmonis (Kr��yer, 1837): current knowledge and implications for epidemiological modelling', ICES Journal of Marine Science, 75(4), pp. 1214–1234 Available at: https://doi.org/10.1093/icesjms/fsy015.
Harrington, P.D., Cantrell, D.L., Foreman, M.G.G., Guo, M. and Lewis, M.A. (2023a) 'Timing and probability of arrival for sea lice dispersing between salmon farms', Royal Society Open Science, 10(2), pp. 220853 Available at: https://doi.org/10.1098/rsos.220853.
Moriarty, M., Murphy, J.M., Brooker, A.J., Waites, W., Revie, C.W., Adams, T.P., Lewis, M., Reinardy, H.C., Phelan, J.P., Coyle, J.P., Rabe, B., Ives, S.C., Armstrong, J.D., Sandvik, A.D., Asplin, L.C., Karlsen, ��, Garnier, S., �� Nor��i, G., Gillibrand, P.A., Last, K.S. and Murray, A.G. (2024) 'A gap analysis on modelling of sea lice infection pressure from salmonid farms. I. A structured knowledge review', Aquaculture Environment Interactions, 16, pp. 1–25 Available at: https://doi.org/10.3354/aei00469.
Revie, C.W., Robbins, C., Gettinby, G., Kelly, L. and Treasurer, J.W. (2005) 'A mathematical model of the growth of sea lice, Lepeophtheirus salmonis, populations on farmed Atlantic salmon, Salmo salar L., in Scotland and its use in the assessment of treatment strategies', Journal of Fish Diseases, 28(10), pp. 603–613 Available at: https://doi.org/10.1111/j.1365-2761.2005.00665.x.
Vollset, K.W., Dohoo, I., Karlsen, ��, Halttunen, E., Kvamme, B.O., Finstad, B., Wennevik, V., Diserud, O.H., Bateman, A., Friedland, K.D., Mahlum, S., J��rgensen, C., Qviller, L., Krko��ek, M., ��tland, �� and Barlaup, B.T. (2018) 'Disentangling the role of sea lice on the marine survival of Atlantic salmon', ICES Journal of Marine Science, 75(1), pp. 50–60 Available at: https://doi.org/10.1093/icesjms/fsx104.