Behavior Of Humpback Whales Research Articles

The Hunt Fellowship: Inspiring acoustics professionals of the future

Students may exit a Ph.D. program feeling fatigued, and sometimes a bit directionless professionally. These feelings combined with the challenging academic job market could be part of the reason for this time period being one of the biggest “leaks in the pipeline,” for women scientists in particular. The flexibility and generosity of the Hunt Fellowship can be inspiring at this crossroads of a young scientist’s career. As the 2009–2010 Hunt Postdoctoral Research Fellowship recipient, I studied the acoustic behavior of humpback whales on their Antarctic feeding grounds, working under the mentorship of Dr. Whitlow Au (University of Hawaii) and Dr. Douglas Nowacek (Duke University). This project followed seamlessly from my dissertation, yet brought me to new ecosystems and reinvigorated my research questions with surprising data. The signal processing skills I gained in acoustic and animal movement analysis solidified my interest in quantitative acoustic behavior research and I made strong connections with several interdisciplinary research groups. This all fueled my career path toward my current Research Faculty position at Moss Landing Marine Laboratories, using similar sound and movement tags to study the effects of anthropogenic noise on cetaceans in general.

A hybrid WOA-CBO algorithm for construction site layout planning problem

The whale optimization algorithm (WOA) is a recently developed swarm-based optimization algorithm inspired by the hunting behavior of humpback whales. This study attempts to enhance the original formulation of the WOA by hybridizing it with some concepts of the colliding bodies optimization (CBO) in order to improve solution accuracy, reliability and convergence speed. The new method, called WOA-CBO algorithm, is applied to construction site layout planning problem. To show the efficiency and performance of the WOA and WOA-CBO in construction site layout problems, three case studies are selected. First case is a discrete and equal area facility layout problem that every facility could assign to any location. Second case is an unequal area version of discrete facility layout problem with more constraints and the last case is a continuous model of construction site layouts. These cases are studied by WOA, CBO and WOA-CBO, and the results are compared with each other.

Combined heat and power economic dispatch problem solution by implementation of whale optimization method

Combined heat and power economic dispatch (CHPED) is introduced as a difficult optimization problem, which provides optimal generation scheduling of heat and power units. The CHPED problem aims to minimize the fuel cost of CHP units with the consideration of operational constraints. In this paper, whale optimization algorithm (WOA) is employed to solve CHPED problem. WOA is a new meta-heuristic optimization technique, which is introduced recently for solving optimization problems. Social behavior of humpback whales is the basic idea of proposal of WOA, where the bubble-net hunting strategy inspires this optimization procedure. Three test systems are considered for evaluation of the performance of the WOA in solving the non-convex nonlinear CHPED problem. The first test instance, which includes 24 units, is studied for evaluating WOA performance in finding the optimal solution of CHPED problem. 84-Unit and 96-unit test systems are introduced for the first time in this paper to show the superiority of WOA in solving non-convex CHPED optimization problem. The second test system contains 40 power-only units, 24 CHP units, and 20 heat-only units. Additionally, the third test instance contains 52 power-only units, 24 CHP units, and 20 heat-only units. The obtained optimal solutions represent WOA efficiency and feasibility and capability of obtaining better solutions with respect to other optimization techniques in terms of operational cost and ability of implementation of WOA on large systems.

Optimal renewable resources placement in distribution networks by combined power loss index and whale optimization algorithms

Distributed generator (DG) resources are the emerging micro-generating technologies such as fuel cells, micro turbines, IC engines. They also make use of renewable energy sources such as PV arrays and wind turbines. DG units have low emission rates and are environment friendly and economical. Power loss reductions, voltage profile improvement and increasing reliability are some advantages of DG units. The above benefits can be achieved by optimal placement of DGs. Optimal DG locations are obtained from power loss index method. A novel meta heuristic algorithm called whale optimization algorithm (WOA) is used to determine the optimal DG-unit's size in this paper. WOA modeled based on the unique hunting behavior of humpback whales. The WOA algorithm is tested on IEEE 15-bus, 33-bus, 69-bus, 85-bus and 118-bus test systems. The results obtained by the proposed WOA algorithm was compared with different types of DGs and other evolutionary algorithms. When compared with other algorithms the WOA algorithm gives better results. From the analysis best results have been achieved from type III DG operating at 0.9pf.

Continuous movement behavior of humpback whales during the breeding season in the southwest Indian Ocean: on the road again!

BackgroundHumpback whales are known to undertake long-distance migration between feeding and breeding sites, but their movement behavior within their breeding range is still poorly known. Satellite telemetry was used to investigate movement of humpback whales during the breeding season and provide further understanding of the breeding ecology and sub-population connectivity within the southwest Indian Ocean (SWIO). Implantable Argos satellite tags were deployed on 15 whales (7 males and 6 females) during the peak of the breeding season in Reunion Island. A switching-state-space model was applied to the telemetry data, in order to discriminate between “transiting” and “localized” movements, the latter of which relates to meandering behavior within putative breeding habitats, and a kernel density analysis was used to assess the spatial scale of the main putative breeding sites.ResultsWhales were tracked for up to 71 days from 31/07/2013 to 16/10/2013. The mean transmission duration was 25.7 days and the mean distance travelled was 2125.8 km. The tracks showed consistent movement of whales from Reunion to Madagascar, demonstrating a high level of connectivity between the two sub-regions, and the use of yet unknown breeding sites such as underwater seamounts (La Perouse) and banks (Mascarene Plateau). A localized movement pattern occurred in distinct bouts along the tracks, suggesting that whales were involved in breeding activity for 4.3 consecutive days on average, after which they resume transiting for an average of 6.6 days. Males visited several breeding sites within the SWIO, suggesting for the first time a movement strategy at a basin scale to maximize mating. Unexpectedly, females with calf also showed extensive transiting movement, while they engaged in localized behavior mainly off Reunion and Sainte-Marie (East Madagascar).ConclusionsThe results indicated that whales from Reunion do not represent a discrete population. Discrete breeding sites were identified, thereby highlighting priority areas for conservation. The study is a first attempt to quantify movement of humpback whales within the southwestern Indian Ocean breeding range. We demonstrate a wandering behavior with stopovers at areas that likely represent key breeding habitat, a strategy which may enhance likelihood of individual reproductive success.

Whale optimization algorithm for optimal sizing of renewable resources for loss reduction in distribution systems

Distributed generator (DG) resources are small scale electric power generating plants that can provide power to homes, businesses or industrial facilities in distribution systems. Power loss reductions, voltage profile improvement and increasing reliability are some advantages of DG units. The above benefits can be achieved by optimal placement of DGs. Whale optimization algorithm (WOA), a novel metaheuristic algorithm, is used to determine the optimal DG size. WOA is modeled based on the unique hunting behavior of humpback whales. The WOA is evaluated on IEEE 15, 33, 69 and 85-bus test systems. WOA was compared with different types of DGs and other evolutionary algorithms. When compared with voltage sensitivity index method, WOA and index vector methods gives better results. From the analysis best results have been achieved from type III DG operating at 0.9 pf.

Naval sonar disrupts foraging in humpback whales

Modern long-range naval sonars are a potential disturbance for marine mammals and can cause disruption of feeding in cetaceans. We examined the lunge-feeding behaviour of humpback whales Megaptera novaeangliae before, during and after controlled exposure experiments with naval sonar by use of acoustic and motion sensor archival tags attached to each animal. Lunge-feeding by humpback whales entails a strong acceleration to increase speed before engulfing a large volume of prey-laden water, which can be identified by an acoustic signature characterized by a few seconds of high-level flow-noise followed by a rapid reduction, coinciding with a peak in animal acceleration. Over 2 successive seasons, 13 humpback whales were tagged. All were subject to a no-sonar control exposure, and 12 whales were exposed to 2 consecutive sonar exposure sessions, with 1 h between sessions. The first sonar session resulted in an average 68% reduction in lunge rate during exposure compared to pre-exposure, and this reduction was significantly greater than any changes observed during the no-sonar control. During the second sonar session, reduction in lunge rate was 66% during sonar exposure compared to the pre-exposure level, but was not significant compared to the no-sonar control, likely due to a larger inter-individual variability because some individuals appeared to have habituated whereas others had not. Our results indicate that naval sonars operating near humpback whale feeding grounds may lead to reduced foraging and negative impacts on energy balance. © 2016 The authors.

Enhanced whale optimization algorithm for sizing optimization of skeletal structures

ABSTRACTThe whale optimization algorithm (WOA) is a recently developed swarm-based optimization algorithm inspired by the hunting behavior of humpback whales. This study attempts to enhance the original formulation of the WOA in order to improve solution accuracy, reliability and convergence speed. The new method, called enhanced whale optimization algorithm (EWOA), is tested in sizing optimization problems of truss and frame structures. The EWOA is compared with WOA and other metaheuristic methods developed in literature in four optimization problems of skeletal structures. Numerical results demonstrate the efficiency of the EWOA and WOA with the former algorithm being more efficient than its standard version.

Diel and Spatial Dependence of Humpback Song and Non-Song Vocalizations in Fish Spawning Ground

The vocalization behavior of humpback whales was monitored over vast areas of the Gulf of Maine using the passive ocean acoustic waveguide remote sensing technique (POAWRS) over multiple diel cycles in Fall 2006. The humpback vocalizations comprised of both song and non-song are analyzed. The song vocalizations, composed of highly structured and repeatable set of phrases, are characterized by inter-pulse intervals of 3.5 ± 1.8 s. Songs were detected throughout the diel cycle, occuring roughly 40% during the day and 60% during the night. The humpback non-song vocalizations, dominated by shorter duration (≤3 s) downsweep and bow-shaped moans, as well as a small fraction of longer duration (∼5 s) cries, have significantly larger mean and more variable inter-pulse intervals of 14.2 ± 11 s. The non-song vocalizations were detected at night with negligible detections during the day, implying they probably function as nighttime communication signals. The humpback song and non-song vocalizations are separately localized using the moving array triangulation and array invariant techniques. The humpback song and non-song moan calls are both consistently localized to a dense area on northeastern Georges Bank and a less dense region extended from Franklin Basin to the Great South Channel. Humpback cries occur exclusively on northeastern Georges Bank and during nights with coincident dense Atlantic herring shoaling populations, implying the cries are feeding-related.

Does optimal foraging theory predict the foraging performance of a large air-breathing marine predator?

Optimal foraging theory (OFT) suggests that air-breathing diving animals should minimize costs associated with feeding under water (e.g. travel time, oxygen loss) while simultaneously maximizing benefits gained from doing so (e.g. foraging time, energy gain). Humpback whales, Megaptera novaeangliae , foraging along the Western Antarctic Peninsula appear to forage according to OFT, but the direct costs and benefits in terms of their behaviours (e.g. allocation of time) have not been examined. We compared the foraging behaviour of humpback whales in this region inferred from multisensor high-resolution recording tags to their behaviour predicted by OFT time allocation models assuming the following currencies were being maximized: (1) the proportion of time spent foraging, (2) the net rate of energetic gain and/or (3) the ratio of energy gained to energy expended (i.e. efficiency). Model predictions for all three currencies were similar, suggesting any of these OFT models were suitable for comparison with the observed data. However, agreement between observed and optimal behaviours varied widely depending on the physiological and behavioural values used to derive optimal predictions, highlighting the need for an improved understanding of cetacean physiology. Despite this, many of the theoretical OFT predictions were supported: shallow dives (i.e.

The effect of close approaches for tagging activities by small research vessels on the behavior of humpback whales (Megaptera novaeangliae)

AbstractSmall research vessels are often used as platforms for tagging activities to collect behavioral data on cetaceans and they have the potential to disturb that group or individual. If this disturbance is ignored, results and conclusions produced by that study could be inaccurate. Here land‐based behavioral data of migrating humpback whales (Megaptera novaeangliae) (n = 29) were used to determine the effect of close approaches for tagging by research vessels on their diving, movement and surface behaviors. Groups of whales were tagged, using digital recording tags, by small research vessels, as part of a behavioral response study. In groups that were approached for tagging, temporary changes in movement behaviors during close approaches were found, with subsequent recovery to “pre‐approach” levels. In female‐calf groups more long‐term changes in travel speed were found. Results suggest that, although close approaches for tagging by small vessels may cause behavioral changes in humpback whales, this change may be small and temporary. However, in female‐calf groups, the behavioral change may be greater and longer lasting. This study shows that when using small vessels for behavioral research, disturbance, and recovery should be measured to ensure integrity of data used for other analyses.

The Whale Optimization Algorithm

This paper proposes a novel nature-inspired meta-heuristic optimization algorithm, called Whale Optimization Algorithm (WOA), which mimics the social behavior of humpback whales. The algorithm is inspired by the bubble-net hunting strategy. WOA is tested with 29 mathematical optimization problems and 6 structural design problems. Optimization results prove that the WOA algorithm is very competitive compared to the state-of-art meta-heuristic algorithms as well as conventional methods. The source codes of the WOA algorithm are publicly available at http://www.alimirjalili.com/WOA.html

Comparing multiple sampling platforms for measuring the behavior of humpback whales (Megaptera novaeangliae)

AbstractMultiple platform approaches for measuring the behavior of marine mammals may strengthen data quality and quantity. However, if this approach is chosen, reconciliation of behavioral measures between each platform is required. This study compared typical measures of humpback whale (Megaptera novaeangliae) behavior collected from three different sampling platforms; land‐based, boat‐based, and digital tags (Dtags), to explore similarities and/or discrepancies in data. Visual observations from land‐based platforms significantly underestimated group blow rate when compared to boat‐based platforms, whereas broad‐scale spatial movements (speed and course traveled) were measured similarly by these two platforms. Dtags were used to define dive behavior based on a time and depth criteria, where bouts of short shallow respiration dives (≤80 s and ≤10 m) were separated from longer, deeper dives (>80 s and >10 m). At a group level, land and boat platforms agreed on the number of long dives but land platforms missed bouts of short dives. At an individual level, the number of short and long dives observed by boat‐based platforms agreed with Dtag recordings. This study highlights the importance of data exploration prior to analyses in multiple platform studies to identify potential discrepancies and appropriately account for any biases.

Modeling the spatial and temporal dynamics of foraging movements of humpback whales (Megaptera novaeangliae) in the Western Antarctic Peninsula.

BackgroundA population of humpback whales (Megaptera novaeangliae) spends the austral summer feeding on Antarctic krill (Euphausia superba) along the Western Antarctic Peninsula (WAP). These whales acquire their annual energetic needs during an episodic feeding season in high latitude waters that must sustain long-distance migration and fasting on low-latitude breeding grounds. Antarctic krill are broadly distributed along the continental shelf and nearshore waters during the spring and early summer, and move closer to land during late summer and fall, where they overwinter under the protective and nutritional cover of sea ice. We apply a novel space-time utilization distribution method to test the hypothesis that humpback whale distribution reflects that of krill: spread broadly during summer with increasing proximity to shore and associated embayments during fall.ResultsHumpback whales instrumented with satellite-linked positional telemetry tags (n = 5), show decreased home range size, amount of area used, and increased proximity to shore over the foraging season.ConclusionsThis study applies a new method to model the movements of humpback whales in the WAP region throughout the feeding season, and presents a baseline for future observations of the seasonal changes in the movement patterns and foraging behavior of humpback whales (one of several krill-predators affected by climate-driven changes) in the WAP marine ecosystem. As the WAP continues to warm, it is prudent to understand the ecological relationships between sea-ice dependent krill and krill predators, as well as the interactions among recovering populations of krill predators that may be forced into competition for a shared food resource.

Whales and waves: Humpback whale foraging response and the shoaling of internal waves at Stellwagen Bank

AbstractWe tested the hypothesis that humpback whales aggregate at the southern flank of Stellwagen Bank (SB) in response to internal waves (IWs) generated semidiurnally at Race Point (RP) channel because of the presence of their preferred prey, planktivorous fish, which in turn respond to zooplankton concentrated by the predictable IWs. Analysis of synthetic aperture radar (SAR) images indicates that RP IWs approach the southern flank of SB frequently (∼62% of the images). Published reports of whale sighting data and archived SAR images point to a coarse spatial coincidence between whales and Race Point IWs at SB's southern flank. The responses of whales to IWs were evaluated via sightings and behavior of humpback whales, and IWs were observed in situ by acoustic backscatter and temperature measurements. Modeling of IWs complemented the observations, and results indicate a change of ∼0.4 m/s in current velocity, and ∼1.5 Pa in dynamic pressure near the bottom, which may be sufficient for bottom fish to detect the IWs. However, fish were rare in our acoustic observations, and fish response to the IWs could not be evaluated. RP IWs do not represent the leading edge of the internal tide, and they may have less mass‐transport potential than typical coastal IWs. There was large interannual variability in whale sightings at SB's southern flank, with decreases in both numbers of sightings and proportion of sightings where feeding was observed from 2008 to 2013. Coincidence of whales and IWs was inconsistent, and results do not support the hypothesis.

Formal comment to Gong et al.: Ecosystem scale acoustic sensing reveals humpback whale behavior synchronous with herring spawning processes and re-evaluation finds no effect of sonar on humpback song occurrence in the Gulf of Maine in fall 2006.

In their paper: “Ecosystem scale acoustic sensing reveals humpback whale behavior synchronous with herring spawning processes and re-evaluation finds no effect of sonar on humpback song occurrence in the Gulf of Maine in Fall 2006” Gong et al. [1] used acoustic monitoring to detect synchronous herring spawning and humpback whale presence in the Gulf of Maine, presenting novel and interesting data on predator-prey relationships on a major humpback whale feeding ground in the western North Atlantic. In addition, their finding that singing humpback whales recorded on Georges Bank and in the vicinity to their active Ocean Acoustic Waveguide Remote Sensing (OAWRS) source array did not seem to respond acoustically to OAWRS transmissions during a Fall 2006 experiment is also new. Gong et al. [1] argue that it is different from our observations in the Stellwagen Bank National Marine Sanctuary (SBNMS), 200 km distant from the OAWRS source array during the same experiment [2]. However, in contrast to the conclusions of Gong et al. [1], we argue that their results do not contradict, nor necessarily conflict with, our findings. Variable behavioral responses to noise have been shown in a range of marine mammals. For example blue whales have been shown both to increase and decrease calling rates in response to different noise sources [3], [4]. Responses to noise are complex in nature and may depend on factors such as behavioral context, prey availability, distance from source, received level (RL), signal structure and novelty, as well as individual differences [5], [6]. We argue that the finding that humpback whales reacted differently towards the OAWRS signal depending on range to the source, RL above background noise and (likely) differences in behavioral state is an interesting result that should be highlighted rather than discounted. Here we will (1) outline some of the problems in the Gong et al. [1] analysis of humpback whale vocal behavior on Georges Bank, (2) respond to their critique of our findings reported in [2], and (3) discuss Gong et al.'s [1] presentation of the effects of the OAWRS signal source, a low-frequency sound source with source levels (SL) which may be in excess of 210 dB re 1 µPa @ 1 m [7].

Ecosystem scale acoustic sensing reveals humpback whale behavior synchronous with herring spawning processes and re-evaluation finds no effect of sonar on humpback song occurrence in the Gulf of Maine in fall 2006.

We show that humpback-whale vocalization behavior is synchronous with peak annual Atlantic herring spawning processes in the Gulf of Maine. With a passive, wide-aperture, densely-sampled, coherent hydrophone array towed north of Georges Bank in a Fall 2006 Ocean Acoustic Waveguide Remote Sensing (OAWRS) experiment, vocalizing whales could be instantaneously detected and localized over most of the Gulf of Maine ecosystem in a roughly 400-km diameter area by introducing array gain, of 18 dB, orders of magnitude higher than previously available in acoustic whale sensing. With humpback-whale vocalizations consistently recorded at roughly 2000/day, we show that vocalizing humpbacks (i) were overwhelmingly distributed along the northern flank of Georges Bank, coinciding with the peak spawning time and location of Atlantic herring, and (ii) their overall vocalization behavior was strongly diurnal, synchronous with the formation of large nocturnal herring shoals, with a call rate roughly ten-times higher at night than during the day. Humpback-whale vocalizations were comprised of (1) highly diurnal non-song calls, suited to hunting and feeding behavior, and (2) songs, which had constant occurrence rate over a diurnal cycle, invariant to diurnal herring shoaling. Before and during OAWRS survey transmissions: (a) no vocalizing whales were found at Stellwagen Bank, which had negligible herring populations, and (b) a constant humpback-whale song occurrence rate indicates the transmissions had no effect on humpback song. These measurements contradict the conclusions of Risch et al. Our analysis indicates that (a) the song occurrence variation reported in Risch et al. is consistent with natural causes other than sonar, (b) the reducing change in song reported in Risch et al. occurred days before the sonar survey began, and (c) the Risch et al. method lacks the statistical significance to draw the conclusions of Risch et al. because it has a 98–100% false-positive rate and lacks any true-positive confirmation.

Soundscapes and vocal behavior of humpback whales in Massachusetts Bay

In recent years, technological advances have revolutionized the study of acoustic communication in marine mammals. Exciting new perspectives on vocal behavior, acoustic habitats, and the influence of noise on communication are offered by passive acoustic monitoring (PAM) platforms such as acoustic tags (DTAGs), autonomous PAM recorders, drifting PAM buoys, and subsea gliders. These innovations bring the opportunity to integrate data from fixed and mobile PAM devices to gain deeper insight into the dynamic interactions between marine mammal vocalizations, behavioral context, and the acoustic environment. In this study, we bring together such data sources to study the vocal behavior and acoustic habitat of humpback whales in the context of their spring and summer feeding grounds. Recordings were made in Stellwagen Bank National Marine Sanctuary during 2008–2010, using arrays of autonomous PAM recorders and DTAGs. In addition, AIS ship-tracking data were obtained to study the influence of vessel movements. We present preliminary findings of this work and discuss future strategies for analyzing the spatiotemporal interactions between vocal behavior and acoustical context.

Extreme diel variation in the feeding behavior of humpback whales along the western Antarctic Peninsula during autumn

MEPS Marine Ecology Progress Series Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsTheme Sections MEPS 494:281-289 (2013) - DOI: https://doi.org/10.3354/meps10541 Extreme diel variation in the feeding behavior of humpback whales along the western Antarctic Peninsula during autumn A. S. Friedlaender1,*, R. B. Tyson1, A. K. Stimpert2, A. J. Read1, D. P. Nowacek1,3 1Division of Marine Science and Conservation, Duke University Marine Laboratory, 135 Duke Marine Lab Road, Beaufort, North Carolina 28516, USA 2Naval Postgraduate School, Department of Oceanography, 833 Dyer Road, Monterey, California 93943, USA 3Department of Electrical and Computer Engineering, Pratt School of Engineering, Duke University, Durham, North Carolina 27708, USA *Email: asf7@duke.edu ABSTRACT: Most humpback whale Megaptera novaeangliae populations partition their time between prey-rich feeding and prey-deficient breeding/calving regions. How these whales feed and optimize the consumption of prey resources prior to long-distance migrations and fasting is largely unknown. We deployed multi-sensor tags on humpback whales around the western Antarctic Peninsula to describe their daily activity patterns late in the feeding season to test the hypothesis that feeding behavior varies over the diel cycle so as to maximize energy intake and limit energy expenditure. Dives were assigned to a behavioral state (feeding, resting, traveling, exploring) to determine hourly rates and to build an ethogram of activity patterns. Our results show a distinct diel pattern of whales feeding exclusively at night. Feeding depth was deeper around sunrise/sunset and shallower (~50 m) at night, consistent with diel vertical prey movement. Shallow feeding dives typically contained a single feeding lunge, a strategy known to increase feeding efficiency and maximize intake rates by maintaining proximity to the surface and reducing the energetic costs of deep diving. The lack of feeding during daytime may indicate prey being too deep for efficient foraging. Our results add information where currently there is a paucity of data describing how baleen whales optimize feeding behavior, specifically in relation to prey distribution and movement, to fuel their extraordinary energetic requirements necessary for growth, migration, and reproduction. Understanding behavioral patterns and predator/prey dynamics in rapidly changing marine environments, like the Antarctic Peninsula, is critical for understanding how these changes will affect ecosystem structure and function. KEY WORDS: Humpback whale · Foraging ecology · Tagging · Antarctica Full text in pdf format PreviousNextCite this article as: Friedlaender AS, Tyson RB, Stimpert AK, Read AJ, Nowacek DP (2013) Extreme diel variation in the feeding behavior of humpback whales along the western Antarctic Peninsula during autumn. Mar Ecol Prog Ser 494:281-289. https://doi.org/10.3354/meps10541 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in MEPS Vol. 494. Online publication date: December 04, 2013 Print ISSN: 0171-8630; Online ISSN: 1616-1599 Copyright © 2013 Inter-Research.

Understanding the intentional acoustic behavior of humpback whales: A production-based approach

Following a production-based approach, this paper deals with the acoustic behavior of humpback whales. This approach investigates various physical factors, which are either internal (e.g., physiological mechanisms) or external (e.g., environmental constraints) to the respiratory tractus of the whale, for their implications in sound production. This paper aims to describe a functional scenario of this tractus for the generation of vocal sounds. To do so, a division of this tractus into three different configurations is proposed, based on the air recirculation process which determines air sources and laryngeal valves. Then, assuming a vocal function (in sound generation or modification) for several specific anatomical components, an acoustic characterization of each of these configurations is proposed to link different spectral features, namely, fundamental frequencies and formant structures, to specific vocal production mechanisms. A discussion around the question of whether the whale is able to fully exploit the acoustic potential of its respiratory tractus is eventually provided.