Fig 1.
The study region on the Discovery Islands, British Columbia, Canada.
The map displays eight salmon farms (F1-F8) represented as black squares. Juvenile sockeye salmon are simulated to migrate from the Start Point to the End Point. Infestation pressure refers to the local concentration of Caligus clemensi copepodid larvae per 100m x 100m grid cell. The maps in the insets were created using R with public domain Natural Earth base maps (http://www.naturalearthdata.com/), and the main map was created using R with public domain British Columbia Data Catalogue base maps (https://catalogue.data.gov.bc.ca/).
Fig 2.
Two examples of stochastic migration paths of juvenile sockeye salmon.
These paths demonstrate their journeys along Route 3, near farm F1 (as detailed in Fig 1). The sample salmon travelled from east to west, with closed and open circles indicating the pixels they traversed. Each pixel in the grid measures 100m x 100m. The salmon spent approximately 4.63 minutes in each cell, maintaining an equal duration across all cells.
Fig 3.
Example of five juvenile sockeye salmon stochastic migration paths for each route in the Discovery Islands, British Columbia, Canada.
The map marks eight salmon farms with black squares and delineates each migration route from the start (bottom-right black circle) to the end (upper-left black circle). In every simulation, Route 1 deterministically adheres to the shortest path, resulting in an identical route marked by straight lines and right angles across all simulations. Conversely, Routes 2 and 3 show meandering salmon migration patterns, attributable to the stochastic nature of their path selection. Infestation pressure is applied in a manner identical to that shown in Fig 1. These maps were created using R with public domain British Columbia Data Catalogue base maps (https://catalogue.data.gov.bc.ca/).
Fig 4.
Migration metrics distribution across simulations.
For 3000 simulations of an agent-based model, the distributions of (A) migration distance, (B) progression rate, and (C) total infestation pressure are presented. In all simulations, Route 1 showed consistent results, marked by vertical dashed red lines.
Table 1.
Mean migration distance, migration duration, swimming speed, progression rate and total infestation pressure for each route.
These values were derived from the averages of 3000 simulations per route.
Fig 5.
Pixel-wise infestation pressure during juvenile sockeye salmon migration.
This figure illustrates the cumulative infestation pressures encountered in five representative simulations across three different migration routes. The five simulations in each route are signified by a distinct colour. Route 1 simulations display uniformity, reflecting deterministic migration patterns, while Routes 2 and 3 exhibit variations due to stochastic influences.
Fig 6.
Sea lice abundance variation across three migration routes.
Histograms represent the distribution of sea lice infestations for juvenile sockeye salmon across three different migration routes, based on 3000 simulations. The upper panels were generated using the logarithmic model, whereas the lower panels were produced using the proportional model.
Fig 7.
Sensitivity analysis of parameters affecting salmon infestation using Pearson correlation coefficients.
(A) Comparative impact assessment of various parameters and route selection; Route 2 and Route 3 denote the relative impact of selecting these routes as opposed to Route 1. (B-D) Detailed impacts of parameters on infestation rates for individual routes: (B) depicts Route 1 where the progression rate is constant; thus, it is excluded from analysis, (C) and (D) show the variable influences on Routes 2 and 3, respectively. The numbers 1 and 2 in the headings correspond to the results from the logarithmic model and the proportional model, respectively. Bars oriented to the right signify a direct correlation between parameter value and model output. Conversely, bars to the left represent an inverse correlation. The length of the bar indicates the strength of the correlation, with parameters organized in descending order of influence.