Task 4c

Investigating cue-rate variability of deep-divers due to geographic region, behavioral state and group size and composition

Previous research on deep-diving cetacean species has shown that geographic differences in acoustic behavior must be considered when using acoustic cues for abundance estimation in a new region (Douglas et al. 2005, Warren et al. 2017). This task will focus on sperm whales and will utilize archived data from combined visual and acoustic surveys to assess cue rate variability in two LMR priority geographic regions. The data available include recordings from towed passive acoustic arrays, with concurrent visual sightings during daytime hours, as well as recordings from drifting passive acoustic buoys.

Team members

Erin Oleson
Karlina Merkens
Yvonne Barkley

Species considered

Sperm whale (Physeter macrocephalus)

Data available

Passive acoustic towed array data were collected as part of 5 years of visual/acoustic surveys in the Main Hawaiian Islands in the Central North Pacific Ocean. Continuous acoustic recordings were collected using custom-built hydrophone arrays (Figure 1) towed at approximately 4-10 m deep, 300 m behind the ship while traveling at 18.5 km/h (10 kt). The components of the towed hydrophone arrays and data acquisition systems varied between surveys (Table 1). During daylight hours, trained acousticians monitored the sounds aurally with headphones and visually using spectrographic software (ISHMAEL, Mellinger 2001; PAMGuard, Gillespie et al. 2008). When cetacean vocalizations were detected, a phone-pair bearing algorithm in ISHMAEL or PAMGuard was used to calculate the direction of the sound source relative to the bow of the ship. These bearings were plotted using a mapping software with a GPS interface (PAMGuard; Whaltrak, by Jay Barlow). Target motion analysis was used to estimate the perpendicular distance to the animals based on the convergence of plotted bearings with left/right ambiguity. In some cases, the ambiguity in perpendicular distances was resolved if the ship turned while the animals were still vocalizing. Acoustic encounters were linked to concurrent sightings when acoustic bearing estimates were consistent with the sighted location of the animal group (Rankin et al. 2008). When the ambiguity of the acoustic location estimate could not be resolved, the average perpendicular distance from both sides of the ship was recorded. A total of 327 acoustic encounters of sperm whales were detected. A total of 72 sperm whale encounters were concurrently detected by both visual and acoustic methods and 242 sperm whale encounters were detected by acoustic methods only, and only 13 sperm whale encounters were only detected by visual methods (Table 1, Figure 2).

Figure 1. Diagram of the linear hydrophone array towed 300 m behind the NOAA research vessels at approximately 10 m deep during a cetacean abundance line-transect survey. The line array consisted of two depth sensors (denoted with ‘D’) and two array nodes spaced 20 m apart, each housing three hydrophones (black dots) spaced approximately 1 m apart.

Table 1. Summary table with survey information, acoustic equipment, and total sperm whale encounters detected during PIFSC cetacean surveys within the Hawaiian Archipelago, excluding DASBR recordings.

Figure 2. Map of sperm whale encounters collected using towed hydrophone arrays within the Hawaiian Archipelago between 2010 and 2017. Concurrent sightings and acoustic encounters from towed arrays are shown as orange dots. Acoustic encounters from towed arrays without a concurrent visual sighting are shown as green stars, and visual sightings without acoustic data are shown as purple triangles.

Approach taken

Sperm whale echolocation clicks are identified based on their low frequency, long duration, and high amplitude characteristics. Four main click types exist, which are associated with different behaviors (Figure 3). When estimating sperm whale click rates for acoustic density estimation, it is important to consider different factors that may affect click production and detectability. Therefore, we are analyzing the data by considering the click type, the number of whales in a group, and their distance from the ship (Figure 4). Subsequently, the first set of acoustic encounters for analysis aims to minimize the impact of click detectability by only including groups of 1-2 animals producing regular and/or slow clicks located close enough to the ship where the effects of sound propagation are negligible (within 4 km). This initial subset of data will provide baseline results where we assume all clicks are detected to obtain accurate estimates of click rate, which can then be adjusted for sperm whale acoustic encounters with larger groups located farther away or in other cases where detectability may be influenced. Further analysis will also include comparing sperm whale group sizes obtained by visual observers with click rates measured from the towed array data to better understand the relationship between visual and acoustic group size estimates and between group size and click rate.

Figure 3. Spectrograms show four types of sperm whale echolocation clicks (dark gray vertical lines) present in the towed array data set that correspond to different behavioral states, including regular clicks (a), creaks (b), codas (c), and slow clicks (d). Each click type is differentiated by their inter-click interval, or time between clicks. Click types are also associated with different behaviors, such as foraging (a, b), socializing (c), and male communication (d).

Figure 4. Initial data set consisted of sperm whale acoustic encounters with less than 10 animals producing only foraging clicks (regular and creaks) and/or slow clicks within 4 km of the ship to support the assumption that every click is detected.

Progress

Initial data set of acoustic encounters 9 Dec 2021 - We are currently processing the initial data set of acoustic encounters, which contains regular and slow clicks. Since the towed array data contain variable noise levels (primarily due to noise from water flow and ship propellers), we are using a combination of automated click detectors with manual validation to annotate all echolocation clicks within each… Continue Reading