Beaked whale echolocation signals are mostly frequency-modulated (FM) upsweep pulses and appear to be species specific. Evolutionary processes of niche separation may have driven differentiation of beaked whale signals used for spatial orientation and foraging. FM pulses of eight species of beaked whales were identified, as well as five distinct pulse types of unknown species, but presumed to be from beaked whales. Current evidence suggests these five distinct but unidentified FM pulse types are also species-specific and are each produced by a separate species. There may be a relationship between adult body length and center frequency with smaller whales producing higher frequency signals. This could be due to anatomical and physiological restraints or it could be an evolutionary adaption for detection of smaller prey for smaller whales with higher resolution using higher frequencies. The disadvantage of higher frequencies is a shorter detection range. Whales echolocating with the highest frequencies, or broadband, likely lower source level signals also use a higher repetition rate, which might compensate for the shorter detection range. Habitat modeling with acoustic detections should give further insights into how niches and prey may have shaped species-specific FM pulse types.
At least ten species of beaked whales inhabit the North Pacific, but little is known about their abundance, ecology, and behavior, as they are elusive and difficult to distinguish visually at sea. Six of these species produce known species-specific frequency modulated (FM) echolocation pulses: Baird’s, Blainville’s, Cuvier’s, Deraniyagala’s, Longman’s, and Stejneger’s beaked whales. Additionally, one described FM pulse (BWC) from Cross Seamount, Hawai’i, and three unknown FM pulse types (BW40, BW43, BW70) have been identified from almost 11 cumulative years of autonomous recordings at 24 sites throughout the North Pacific. Most sites had a dominant FM pulse type with other types being either absent or limited. There was not a strong seasonal influence on the occurrence of these signals at any site, but longer time series may reveal smaller, consistent fluctuations. Only the species producing BWC signals, detected throughout the Pacific Islands region, consistently showed a diel cycle with nocturnal foraging. By comparing stranding and sighting information with acoustic findings, we hypothesize that BWC signals are produced by ginkgo-toothed beaked whales. BW43 signal encounters were restricted to Southern California and may be produced by Perrin’s beaked whale, known only from Californian waters. BW70 signals were detected in the southern Gulf of California, which is prime habitat for Pygmy beaked whales. Hubb’s beaked whale may have produced the BW40 signals encountered off central and southern California; however, these signals were also recorded off Pearl and Hermes Reef and Wake Atoll, which are well south of their known range.
Passive acoustic monitoring has become an important data collection method, yielding massive datasets replete with biological, environmental and anthropogenic information. Automated signal detectors and classifiers are needed to identify events within these datasets, such as the presence of species-specific sounds or anthropogenic noise. These automated methods, however, are rarely a complete substitute for expert analyst review. The ability to visualize and annotate acoustic events efficiently can enhance scientific insights from large, previously intractable datasets. A MATLAB-based graphical user interface, called DetEdit, was developed to accelerate the editing and annotating of automated detections from extensive acoustic datasets. This tool is highly-configurable and multipurpose, with uses ranging from annotation and classification of individual signals or signal-clusters and evaluation of signal properties, to identification of false detections and false positive rate estimation. DetEdit allows users to step through acoustic events, displaying a range of signal features, including time series of received levels, long-term spectral averages, time intervals between detections, and scatter plots of peak frequency, RMS, and peak-to-peak received levels. Additionally, it displays either individual, or averaged sound pressure waveforms, and power spectra within each acoustic event. These views simultaneously provide analysts with signal-level detail and encounter-level context. DetEdit creates datasets of signal labels for further analyses, such as training classifiers and quantifying occurrence, abundances, or trends. Although designed for evaluating underwater-recorded odontocete echolocation click detections, DetEdit can be adapted to almost any stereotyped impulsive signal. Our software package complements available tools for the bioacoustic community and is provided open source at https://github.com/MarineBioAcousticsRC/DetEdit.
Sperm whales (Physeter macrocephalus) are a cosmopolitan species but are only found in ice‐free regions of the ocean. It is unknown how their distribution might change in regions undergoing rapid loss of sea ice and ocean warming like Baffin Bay in the eastern Canadian Arctic. In 2014 and 2018, sperm whales were sighted near Eclipse Sound, Baffin Bay: the first recorded uses of this region by sperm whales. In this study, we investigate the spatiotemporal distribution of sperm whales near Eclipse Sound using visual and acoustic data. We combine several published open‐source, data sets to create a map of historical sperm whale presence in the region. We use passive acoustic data from two recording sites between 2015 and 2019 to investigate more recent presence in the region. We also analyze regional trends in sea ice concentration (SIC) dating back to 1901 and relate acoustic presence of sperm whales to the mean SIC near the recording sites. We found no records of sperm whale sightings near Eclipse Sound outside of the 2014/2018 observations. Our acoustic data told a different story, with sperm whales recorded yearly from 2015 to 2019 with presence in the late summer and fall months. Sperm whale acoustic presence increased over the 5‐year study duration and was closely related to the minimum SIC each year. Sperm whales, like other cetaceans, are ecosystem sentinels, or indicators of ecosystem change. Increasing number of days with sperm whale presence in the Eclipse Sound region could indicate range expansion of sperm whales as a result of changes in sea ice. Monitoring climate change‐induced range expansion in this region is important to understand how increasing presence of a top‐predator might impact the Arctic food web.
Characterizing population structure and dynamics is critical for the conservation of endangered species. Monitoring sperm whales Physeter macrocephalus is especially difficult because it requires monitoring different latitudes to capture the dynamics of most populations. Since their remarkable sexual dimorphism in body size is reflected in their sounds, passive acoustic monitoring presents an opportunity to capture contiguous patterns in time, space, and over large scales. We show that the echolocation repetition rate (measured as inter‐click interval, ICI) as a proxy for body length is a suitable approach for large‐scale acoustic monitoring. Body length has previously been estimated from the time interval between pulses (IPI) within sperm whale echolocation clicks. These estimates can only be achieved when whales are oriented toward the recorder or directly facing away, resulting in sparse data. A representative subsample of data demonstrated that ICI and IPI are linearly correlated, allowing conversion of ICI distributions into likely body length categories. This approach was applied to three monitoring sites in the Gulf of Mexico (2010–2017), where sperm whale population structure and male movements were poorly understood. We identified three classes: large animals between 12–15 m (ICI between 0.72 and 1 sec), presumed to correspond to adult males, and small animals below 12 m (ICI between 0.44 and 0.64 sec) likely pertaining to social groups (mixed groups with adult females and their offspring), and the third class with mid‐sized animals (ICI between 0.64 and 0.83 sec) believed to contain adult females or sub‐adult males. Our results revealed spatial and seasonal variability of the population structure including possible male presence throughout the year and migratory patterns of the population. This approach provides a means to efficiently characterize the putative population structure of sperm whales to understand the population's geographical dynamics and population status, which is relevant under rapidly changing habitat conditions.
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