Fin whale acoustic presence and song characteristics in seas to the southwest of Portugal

Cetaceans are the next frontier for vocal rhythm research

While rhythm can facilitate and enhance many aspects of behavior, its evolutionary trajectory in vocal communication systems remains enigmatic. We can trace evolutionary processes by investigating rhythmic abilities in different species, but research to date has largely focused on songbirds and primates. We present evidence that cetaceans-whales, dolphins, and porpoises-are a missing piece of the puzzle for understanding why rhythm evolved in vocal communication systems. Cetaceans not only produce rhythmic vocalizations but also exhibit behaviors known or thought to play a role in the evolution of different features of rhythm. These behaviors include vocal learning abilities, advanced breathing control, sexually selected vocal displays, prolonged mother-infant bonds, and behavioral synchronization. The untapped comparative potential of cetaceans is further enhanced by high interspecific diversity, which generates natural ranges of vocal and social complexity for investigating various evolutionary hypotheses. We show that rhythm (particularly isochronous rhythm, when sounds are equally spaced in time) is prevalent in cetacean vocalizations but is used in different contexts by baleen and toothed whales. We also highlight key questions and research areas that will enhance understanding of vocal rhythms across taxa. By coupling an infraorder-level taxonomic assessment of vocal rhythm production with comparisons to other species, we illustrate how broadly comparative research can contribute to a more nuanced understanding of the prevalence, evolution, and possible functions of rhythm in animal communication.

Fin whale song characteristics and potential subpopulation identity in the New York Bight

Fin whale (Balaenoptera physalus) song can follow a highly consistent pattern, and regional differences in song patterns can be a valuable indicator of subpopulation identity and distribution. In the Northwest Atlantic, endangered fin whales are currently managed as a single stock despite previous identification of different regional song patterns, which indicates potential subpopulation structuring and vulnerability to anthropogenic disturbance if not managed accordingly. Here we document fin whale song in the New York Bight (NYB) from 2017 to 2020 using passive acoustic data to identify monthly and yearly trends in song patterns and to explore potential subpopulation structuring. The predominant song pattern observed was highly consistent with the pattern documented almost a decade prior in the NYB, with short inter-note intervals (INI) from fall-winter and long-INIs in the spring. However, in one song year the majority of songs were composed of long-INIs. This change in song pattern could be due to a shift in fin whale behavior or possibly multiple fin whale subpopulations using the NYB. Fin whales in the NYB may be particularly vulnerable to disturbance given the increasing anthropogenic pressures in this region, and further research into subpopulation structuring is needed to ensure adequate management of these endangered whales.

Fin whale song evolution in the North Atlantic

Animal songs can change within and between populations as the result of different evolutionary processes. When these processes include cultural transmission, the social learning of information or behaviours from conspecifics, songs can undergo rapid evolutions because cultural novelties can emerge more frequently than genetic mutations. Understanding these song variations over large temporal and spatial scales can provide insights into the patterns, drivers and limits of song evolution that can ultimately inform on the species' capacity to adapt to rapidly changing acoustic environments. Here, we analysed changes in fin whale (Balaenoptera physalus) songs recorded over two decades across the central and eastern North Atlantic Ocean. We document a rapid replacement of song INIs (inter-note intervals) over just four singing seasons, that co-occurred with hybrid songs (with both INIs), and a clear geographic gradient in the occurrence of different song INIs during the transition period. We also found gradual changes in INIs and note frequencies over more than a decade with fin whales adopting song changes. These results provide evidence of vocal learning in fin whales and reveal patterns of song evolution that raise questions on the limits of song variation in this species.

Occurrence and patterns of fin whale songs reveal alternative migration strategies in Svalbard Islands, Norway

The Arctic marine environment is highly affected by global warming with notable changes in habitat conditions, which have great consequences on migrating species. For example, the timing of their migration can be altered leading to changes in their occurrence in suitable areas, which are critical for their survival. In this study, seven years of acoustic data were analysed in Svalbard Islands from 2014 to 2020, revealing that the occurrence of fin whales (Balaenoptera physalus) happened all year-round. The sea surface temperature recorded reveals conditions which could be favorable for these species to persist until the Polar Night. The occurrence of songs indicated that certain individuals did not undertake the migratory journey through the southern breeding grounds, possibly using the area for mating purposes. The analyses of the Inter-Note-Interval (INI) demonstrated that over the years songs with different patterns were found. This suggests that either the fin whales are able to switch their INI patterns or that populations with different INIs are visiting during the Winter. Therefore, this study unveils the undertaking of an alternative strategy to migration movements, and the possible potential origin of the fin whales overwintering in Svalbard.

Temporal evolution of the Mediterranean fin whale song

We present an analysis of fin whale (Balaenoptera physalus) songs on passive acoustic recordings from the Pelagos Sanctuary (Western Mediterranean Basin). The recordings were gathered between 2008 and 2018 using 2 different hydrophone stations. We show how 20 Hz fin whale pulses can be automatically detected using a low complexity convolutional neural network (CNN) despite data variability (different recording devices exposed to diverse noises). The pulses were further classified into the two categories described in past studies and inter pulse intervals (IPI) were measured. The results confirm previous observations on the local relationship between pulse type and IPI with substantially more data. Furthermore we show inter-annual shifts in IPI and an intra-annual trend in pulse center frequency. This study provides new elements of comparison for the understanding of long term fin whale song trends worldwide.

Fin Whale (Balaenoptera physalus) in the Ligurian Sea: Preliminary Study on Acoustics Demonstrates Their Regular Occurrence in Autumn

The patterns of movement of the fin whale (Balaenoptera physalus (Linnaeus, 1758)) in the Mediterranean Sea are still a matter of debate. Feeding aggregations are well known in the Corso-Liguro-Provençal Basin from July to September, but little is known for the autumn and winter seasons. Passive acoustic monitoring (PAM) was implemented in the Ligurian Sea to overcome this gap and to investigate the temporal and spatial variation of fin whale acoustic presence. From July to December 2011, five autonomous recorders were deployed at between 700 and 900 m depths. Fin whale calls were automatically detected almost every day, with higher vocalization rates in October, November, and December. Furthermore, daily vocalization rates were higher during light hours, and closer to the coast. These outcomes suggest that not all the individuals migrate, staying in the area also during autumn for feeding or breeding purposes. The dial cycle of vocalization might be related to feeding activities and zooplankton vertical migration, whereas the proximity to the coast can be explained by the morphology of the area that promotes the upwelling system. Although this work only represents a six-month period, certainly it suggests the need for a larger spatial and temporal PAM effort, crucial for species management and for mitigating possible impact of anthropogenic activities at the basin level.

Improve automatic detection of animal call sequences with temporal context

Many animals rely on long-form communication, in the form of songs, for vital functions such as mate attraction and territorial defence. We explored the prospect of improving automatic recognition performance by using the temporal context inherent in song. The ability to accurately detect sequences of calls has implications for conservation and biological studies. We show that the performance of a convolutional neural network (CNN), designed to detect song notes (calls) in short-duration audio segments, can be improved by combining it with a recurrent network designed to process sequences of learned representations from the CNN on a longer time scale. The combined system of independently trained CNN and long short-term memory (LSTM) network models exploits the temporal patterns between song notes. We demonstrate the technique using recordings of fin whale (Balaenoptera physalus) songs, which comprise patterned sequences of characteristic notes. We evaluated several variants of the CNN + LSTM network. Relative to the baseline CNN model, the CNN + LSTM models reduced performance variance, offering a 9-17% increase in area under the precision-recall curve and a 9-18% increase in peak F1-scores. These results show that the inclusion of temporal information may offer a valuable pathway for improving the automatic recognition and transcription of wildlife recordings.

Acoustic tracking of fin whales: Habitat use and movement patterns within a Canadian Pacific fjord system

Fin whale 20 Hz calls were detected, localized, and tracked using a 10 km aperture network of three acoustic receivers deployed for 11 months in a Pacific Canadian fjord system. The area has been historically important for fin whales and is located along a route that tankers will begin using in 2024. A total of 6712 calls were localized, and trajectories were fitted for 55 acoustic tracks. Fin whale tracks occurred throughout the monitoring site. Call activity peaked in September and was low during winter months. Swimming characteristics varied significantly between day- and nighttime: at night, whales swam faster (7.1 vs 4.0 km/h median, +75.2%), which resulted in longer (+34.7%), less predictable (-70.6%) tracks as compared to daylight hours. Call frequencies varied between 16 and 32 Hz. Beside stereotypical song frequencies, fin whales also used irregular frequency components, which contributed the majority of calls in the summer but did not occur in the winter. The results suggest that the area is primarily used as a summer feeding ground, where fin whales follow a diel behavioral cycle. The observed activity patterns will aid in the assessment of strike risk and harassment mitigation and provide a baseline to document behavioral change.

On the use of the Lloyd's Mirror effect to infer the depth of vocalizing fin whales

The interference between the direct path and the sea surface reflection of a signal as measured by a receiver is called Lloyd's Mirror effect (LME). It results in a frequency-dependent interference pattern that can be observed in a spectrogram. LME depends on the receiver depth, signal source depth, signal frequency, and slant range between source and receiver. Knowing three of these parameters a priori, LME can be used to estimate the third parameter, such as source depth. Here, the work in Pereira et al. (2016) was expanded to estimate the depth of a vocalizing fin whale recorded by an ocean-bottom seismometer (OBS). In Pereira et al. (2016), the depth of a vocalizing fin whale was inferred by manually comparing spectrograms of LME transmission loss models with observed LME. This study developed an automated procedure to perform the same task using the LME interference pattern observed in the spectrograms of the hydrophone and the vertical channel of the OBS. The results show that the joint use of the two channels was the best approach to estimate a source depth using LME. LME provides a non-intrusive approach for estimating the depth at which a fin whale was vocalizing.

Autumn movements of fin whales (Balaenoptera physalus) from Svalbard, Norway, revealed by satellite tracking

Insight into animal movements is essential for understanding habitat use by individuals as well as population processes and species life-history strategies. In this study, we instrumented 25 fin whales with ARGOS satellite-transmitters in Svalbard, Norway, to study their movement patterns and behaviour (Area Restricted Search (ARS), transiting or unknown) during boreal autumn/early winter. Ten of the whales stayed in the tagging area (most northerly location: 81.68°N) for their entire tracking periods (max 45 days). The other 15 whales moved in a south-westerly direction; the longest track ended off the coast of northern Africa (> 5000 km from the tagging location) after 96 days. The whales engaged in ARS behaviour intermittently throughout their southward migrations. During transit phases the whales moved quickly; one individual maintained an average horizontal speed of 9.3 km/h (travelling 223 km per day) for a period of a week. This study documents that: (1) some fin whales might remain at high latitudes during winter; (2) the whales that do migrate probably feed along the way; (3) they can maintain high transiting speed for long periods and; (4) one breeding area for this species is likely located in deep, warm water some 100 km west of Morocco.