Publication - Research and analysis

The interactions and effects of sea lice on wild salmon

Contents
The interactions and effects of sea lice on wild salmon
Modelling Infection Dynamics

Modelling Infection Dynamics

A second aspect of the Scottish Government project on understanding sea lice interactions with wild salmon is to look at ways to improve sea lice control through management practices. 

Area connectivity matrices

Currently a sea lice dispersal model has been developed and assessed by Scottish Government scientists for Loch Linnhe, on the west coast of Scotland. This dispersal model has been used to estimate the proportion of lice transported between farms. This allows the relative importance of different farms in contributing to infection dynamics at the loch scale to be identified, and may help with prioritisation of e.g. treatments to reduce overall burden. In the future it is intended to couple the biological and particle tracking part of the existing model (using the principles from Loch Linnhe) to the newly-developed Scottish Shelf Model (SSM) to develop a connectivity matrix at the coastal scale between Farm Management Areas (FMA). FMAs are areas within which the Scottish aquaculture industry co-ordinates stocking, fallowing and treatments, to generate more effective disease/sea lice control.

A connectivity matrix for management areas may identify key management areas contributing to lice burden elsewhere and where changes to management effort or strategies may have wider benefits. It may also identify potential modifications to FMA boundaries which might reduce further the connectivity between areas, the transfer of lice, and the maintenance of infection cycles.

Models to inform on efficacy of farm management areas and management practices on sea lice control

One of the elements determining the efficacy of designated FMAs with respect to sea lice control is how well isolated they are from neighbouring FMAs in terms of sea lice transfer. A model is being developed to inform on the efficacy of management areas in reducing lice burdens when “leakage” between FMAs varies to different extents. The benefits of synchronised versus non-synchronised treatments, stocking and fallowing within FMAs will also be modelled. This will provide advice, in conjunction with the connectivity modelling above, on the efficacy of current management structure, and cost-benefit of any changes to the structure.

Treatments are a key component in the control of sea lice on farms. However, they are expensive to administer, and the total amount of treatment allowed to be used per farm is restricted under environmental regulations. Therefore treatment strategies need to be carefully considered. It is also known that treatments can reduce in efficacy overtime. To help improve decisions on treatments, a model is being developed to determine level of sea lice control provided by treatments of different efficacy. The model can also be used to determine how many treatments/treatment rate is required to control sea lice for a treatment with a given efficacy.

In the image below, model outputs for lice per fish (black) and treatment rate per month (grey) are shown for treatment efficacies of 0 to 1, under two management (synchronous: solid line, asynchronous: dash line) and two dispersal scenarios (local mixing: thick line, dispersive mixing: thin line).

treatment efficiency graph