Knock knock, who's there? Identifying wild species‐specific fish sounds with passive acoustic localization and random forest models

Passive acoustic monitoring (PAM) is a useful non-destructive tool for evaluating species presence, diversity and abundance. However, in marine environments, a dearth of tools and methods for identifying wild, species-specific fish calls makes quantitative PAM assessments for specific fish species challenging. We tested a novel passive acoustic localization array with paired audio/video for identifying wild, species-specific fish sounds in a high-diversity region of British Columbia, Canada. We then used random forest models incorporating 47 sound features to test the feasibility of differentiating species-specific fish calls. We identified calls for eight soniferous fish species, five of which had never been documented or described, including vermillion (Sebastes miniatus), canary (S. pinniger), and black rockfish (S. melanops). Random forest models were able to differentiate fish knocks and grunts to the species level with high accuracy (80% for knocks, 88% for grunts). The models struggled to differentiate species knocks when sample sizes were low. The Gini impurity index and partial dependence probability plots showed species-specific differences in call features that measure low frequencies and central frequencies. We also provide a comprehensive set of species-specific call characteristics for 47 sound features which can be used to parameterize fish sound detectors. Our study outlines a robust method for collecting and differentiating wild species-specific fish sounds from a high-diversity region with many closely related soniferous fish species. This research can be used to design a species-specific fish sound detector for quantitative estimates of species presence, diversity and range. These adaptable methods can also be applied elsewhere using the same 47 sound features and random forest models to identify species-specific fish sound parameters.