Improving acoustic exposure estimate accuracy with georeferenced animal density information

The state of the art in marine animal acoustic exposure prediction modeling is agent-based movement models, such as JASMINE, where animats are programmed to move in realistic four-dimensional paths through a virtual ocean. Animats are typically seeded uniformly, perhaps with bathymetric constraints to approximate animal distribution patterns. Acoustic source and propagation models can be used to create sound fields representing the sounds of a proposed action in that virtual ocean. Model outputs are typically acoustic exposure histories and summary exposure metrics such as maximum SPL and cumulative SEL. The number of modeled exposures exceeding regulatory thresholds are then scaled by animal densities to predict the number of exposures. Animal density has been typically represented as a scalar value for an entire area. This began when density information was meager. Spatially and temporally specific density data have become available. JASMINE can now incorporate this information by reporting where an animat exceeds regulatory thresholds and use the localized animal density estimate rather than a mean value for the whole simulation area. Using spatially and temporally explicit density reduces model assumptions about animal distribution and produces more precise exposure estimates while allowing for the incorporation of future dynamic distribution prediction models.