Many species rely on acoustic communication to fulfil several functions such as advertisement and mediation of social interactions (e.g., agonistic, mating). Therefore, fish calls can be an important source of information, e.g., to recognize reproductive periods or to assess fish welfare, and should be considered a potential non-intrusive tool in aquaculture management. Assessing fish acoustic activity, however, often requires long sound recordings. To analyse these long recordings automatic methods are invaluable tools to detect and extract the relevant biological information. Here we present a study to characterize meagre (Argyrosomus regius) acoustic activity during social contexts in captivity using an automatic pattern-recognition methodology based on the Hidden Markov Model. Calls produced by meagre during the breading season showed a richer repertoire than previously reported. Besides the dense choruses composed by grunts already known for this species, meagre emitted successive series of isolated pulses, audible as ‘knocks’. Grunts with a variable number of pulses were also registered. The overall acoustic activity was concurrent with the number of spawning events. A diel call rhythms exhibit peak of calling activity from 15:00 to midnight. In addition, grunt acoustic parameters varied significantly along the reproduction season. These results open the possibility to use the meagre vocal activity to predict breeding and approaching spawning periods in aquaculture management.

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.

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Males of several fish species aggregate and vocalize together, increasing the detection range of the sounds and their chances of mating. In the Lusitanian toadfish (Halobatrachus didactylus), breeding males build nests under rocks in close proximity and produce hundreds of boatwhistles (BW) an hour to attract females to lay their demersal eggs on their nests. Chorusing behaviour includes fine-scale interactions between individuals, a behavioural dynamic worth investigating in this highly vocal fish. Here we present a study to further investigate this species' vocal temporal patterns on a fine (individual rhythms and male-male interactions) and large (chorus daily patterns) scales. Several datasets recorded in the Tagus estuary were labelled with the support of an automatic recognition system based on hidden Markov models. Fine-scale vocal temporal patterns exhibit high variability between and within individuals, varying from an almost isochronous to an apparent aperiodic pattern. When in a chorus, males exhibited alternation or synchrony calling patterns, possibly depending on motivation and social context (mating or male-male competition). When engaged in sustained calling, males usually alternated vocalizations with their close neighbours thus avoiding superposition of calls. Synchrony was observed mostly in fish with lower mean calling rate. Interaction patterns were less obvious in more distanced males. Daily choruses showed periods with several active calling males and periods of low activity with no significant diel patterns in shallower intertidal waters. Here, chorusing activity was mainly affected by tide level.In contrast, at a deeper location, although tidal currents causes a decrease in calling rate, tide level did not significantly influence calling, and there was a higher calling rate at night. These data show that photoperiod and tide levels can influence broad patterns of Lusitanian toadfish calling activity as in other shallow-water fishes, but fine temporal patterns in acoustic interactions among nesting males is more complex than previously known for fishes.