  Warming oceans due to climate change are leading to increased numbers of
ectoparasitic copepods, also known as sea lice, which can cause significant
ecological loss to wild salmon populations and major economic loss to
aquaculture sites. The main transport mechanism driving the spread of sea lice
populations are near-surface ocean currents. Present strategies to estimate the
distribution of sea lice larvae are computationally complex and limit
full-scale analysis. Motivated to address this challenge, we propose SALT: Sea
lice Adaptive Lattice Tracking approach for efficient estimation of sea lice
dispersion and distribution in space and time. Specifically, an adaptive
spatial mesh is generated by merging nodes in the lattice graph of the Ocean
Model based on local ocean properties, thus enabling highly efficient graph
representation. SALT demonstrates improved efficiency while maintaining
consistent results with the standard method, using near-surface current data
for Hardangerfjord, Norway. The proposed SALT technique shows promise for
enhancing proactive aquaculture management through predictive modelling of sea
lice infestation pressure maps in a changing climate.
