How effective are acoustic signals in territorial defence in the Lusitanian toadfish?

The function of fish sounds in territorial defence, in particular its influence on the intruder's behaviour during territorial invasions, is poorly known. Breeding Lusitanian toadfish males (Halobatrachus didactylus) use sounds (boatwhistles) to defend nests from intruders. Results from a previous study suggest that boatwhistles function as a 'keep-out signal' during territorial defence. To test this hypothesis we performed territorial intrusion experiments with muted Lusitanian toadfish. Males were muted by making a cut and deflating the swimbladder (the sound-producing apparatus) under anaesthesia. Toadfish nest-holder males reacted to intruders mainly by emitting sounds (sham-operated and control groups) and less frequently with escalated bouts of fighting. When the nest-holder produced a boatwhistle, the intruder fled more frequently than expected by chance alone. Muted males experienced a higher number of intrusions than the other groups, probably because of their inability to vocalise. Together, our results show that fish acoustic signals are effective deterrents in nest/territorial intrusions, similar to bird song.

Call recognition and individual identification of fish vocalizations based on automatic speech recognition: An example with the Lusitanian toadfish

The study of acoustic communication in animals often requires not only the recognition of species specific acoustic signals but also the identification of individual subjects, all in a complex acoustic background. Moreover, when very long recordings are to be analyzed, automatic recognition and identification processes are invaluable tools to extract the relevant biological information. A pattern recognition methodology based on hidden Markov models is presented inspired by successful results obtained in the most widely known and complex acoustical communication signal: human speech. This methodology was applied here for the first time to the detection and recognition of fish acoustic signals, specifically in a stream of round-the-clock recordings of Lusitanian toadfish (Halobatrachus didactylus) in their natural estuarine habitat. The results show that this methodology is able not only to detect the mating sounds (boatwhistles) but also to identify individual male toadfish, reaching an identification rate of ca. 95%. Moreover this method also proved to be a powerful tool to assess signal durations in large data sets. However, the system failed in recognizing other sound types.