Calculating the timing and probability of arrival for sea lice dispersing between salmon farms

TL;DR

This study develops an analytical and numerical model to predict sea lice dispersal timing and infection risk between salmon farms, highlighting the impact of farm spacing and temperature on cross-infection levels.

Contribution

The paper introduces a combined analytical and hydrodynamic modeling approach to quantify sea lice dispersal and infection probabilities between farms, incorporating environmental factors.

Findings

Intermediate farm spacing maximizes cross infection.

Higher temperatures increase infection levels.

Analytical model aligns with hydrodynamic simulations.

Abstract

Sea lice are a threat to the health of both wild and farmed salmon and an economic burden for salmon farms. With a free living larval stage, sea lice can disperse tens of kilometers in the ocean between salmon farms, leading to connected sea lice populations that are difficult to control in isolation. In this paper we develop a simple analytical model for the dispersal of sea lice between two salmon farms. From the model we calculate the arrival time distribution of sea lice dispersing between farms, as well as the level of cross-infection of sea lice. We also use numerical flows from a hydrodynamic model, coupled with a particle tracking model, to directly calculate the arrival time of sea lice dispersing between two farms in the Broughton Archipelago, BC, in order to fit our analytical model and find realistic parameter estimates. Using the parametrized analytical model we show that there is often an intermediate inter-farm spacing that maximizes the level of cross infection between farms, and that increased temperatures will lead to increased levels of cross infection.