Behavior Of Whales Research Articles

A new whale optimisation algorithm based on self-adapting parameter adjustment and mix mutation strategy

ABSTRACT The Whale Optimization Algorithm (WOA), which mimics the social behavior of humpback whales, is a recently developed meta-heuristic algorithm. However, WOA exists the defect of easily falling into local optimum. This paper proposes a new WOA based on a self-adapting parameter adjustment and a mix mutation strategy (abbreviated as SMWOA). The self-adapting parameter adjustment strategy based on a normal distribution is adopted to make the algorithm jump out of local optima and enhance the global exploration capability. Meanwhile, in order to obtain a better tradeoff between the exploration and exploitation capabilities of the WOA, a novel mix mutation strategy is embedded in the proposed algorithm. The performance of SMWOA is tested on 23 benchmark functions and test suites composed of four engineering design problems. Experimental results and statistical analyses indicate that the proposed algorithm is very competitive when compared to the original WOA as well as some state-of-the-art algorithms.

Fear of Killer Whales Drives Extreme Synchrony in Deep Diving Beaked Whales

Fear of predation can induce profound changes in the behaviour and physiology of prey species even if predator encounters are infrequent. For echolocating toothed whales, the use of sound to forage exposes them to detection by eavesdropping predators, but while some species exploit social defences or produce cryptic acoustic signals, deep-diving beaked whales, well known for mass-strandings induced by navy sonar, seem enigmatically defenceless against their main predator, killer whales. Here we test the hypothesis that the stereotyped group diving and vocal behaviour of beaked whales has benefits for abatement of predation risk and thus could have been driven by fear of predation over evolutionary time. Biologging data from 14 Blainville’s and 12 Cuvier’s beaked whales show that group members have an extreme synchronicity, overlapping vocal foraging time by 98% despite hunting individually, thereby reducing group temporal availability for acoustic detection by killer whales to <25%. Groups also perform a coordinated silent ascent in an unpredictable direction, covering a mean of 1 km horizontal distance from their last vocal position. This tactic sacrifices 35% of foraging time but reduces by an order of magnitude the risk of interception by killer whales. These predator abatement behaviours have likely served beaked whales over millions of years, but may become maladaptive by playing a role in mass strandings induced by man-made predator-like sonar sounds.

Humpback whale (Megaptera novaeangliae) sonar: Ten predictions.

Bats and dolphins echolocate ultrasonically while foraging, an active mode of perception that is effective for intercepting small, fast-moving targets, but less so for tracking large targets from long distances. Unlike toothed whales, humpback whales and other baleen whales are widely assumed not to echolocate. Echoes generated by humpback whale vocalizations often have been viewed either as low-level background noise that minimally affects acoustic communication between whales or as indirect cues to large environmental features. An additional possibility is that vocalizing humpback whales (and perhaps other whales) produce sonic sounds to actively generate echoes that they localize and interpret. Animals attempting to echolocate using lower frequency sounds underwater face some of the same signal processing challenges faced by ultrasonic echolocators, as well as some unique challenges. The extent to which listening whales can meet these challenges largely determines what they can actively perceive by monitoring self-generated echoes. In the absence of psychophysical experiments with baleen whales, comparisons with auditory processing by echolocating species provide the best indications of what humpback whales may echoically perceive. Empirical tests of key predictions derived from the hypothesis that humpback whales echolocate are also critical to understanding how they use sound. Recognizing that sonic echolocation by whales may differ substantially from ultrasonic echolocation in smaller species is an important step toward clarifying the role that active auditory perception plays in whale behavior. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

Using two drones to simultaneously monitor visual and acoustic behaviour of gray whales (Eschrichtius robustus) in Baja California, Mexico

This study provides an initial demonstration of a combined two-UAV (Unmanned Aerial Vehicle) system for measuring the underwater source levels and behavioural context of vocal and non-vocal marine mammal signals, information that is highly ecologically-relevant in terms of understanding how a species interacts and copes with conspecifics and its acoustic environment. Although the calls of a few species are well known, major gaps exist in our knowledge about the relationship between vocal output and behavioural context, gender and age for most species. Accurate parameter estimates (e.g., typical source levels, frequency ranges, and temporal characteristics of animal sounds) relevant to their behaviour (activities such as foraging, migrating, mating, or parental care) are needed to establish use of critical habitats (when monitored by acoustics) or to assess potential effects of anthropogenic sound exposure (including reduction of the detection space of sounds used for communication). The emergence of UAVs provides new perspectives and data collection capabilities for marine mammal research. Although UAVs have been frequently exploited for visual observations of whales, most approaches for monitoring and recording sounds from individual whales are still performed using overside hydrophones from a boat or using acoustic tags attached to the animals. Laguna San Ignacio (LSI), Mexico, is one of the breeding and calving grounds of the Eastern North Pacific gray whale (Eschrichtius robustus) population. LSI area's restricted geography, combined with the short dive times of the whales, provided an excellent field laboratory to test a dual drone approach. We used two UAVs: one to obtain acoustic measurements close to the whales and another one to obtain overhead visual observations. For the acoustic drone, a hydrophone (SoundTrap) was suspended via a 2-m line to a waterproof UAV quadcopter (Swellpro), which has the ability to take off and land from the surface of water. Simultaneously, the visual drone (DJI) monitored the whales in the area. Between 27 February and 17 March 2019, we simultaneously recorded underwater gray whale sounds and visual behavioural observations. During 92 min of underwater acoustic recordings, the acoustic drone recorded 11 call types. By time-synching underwater audio with the behavioural video, we obtained new insights into the source levels and functions of various quiet underwater sound that are difficult to impossible to obtain with standard methods. To our knowledge, no studies combining overhead visual observations and underwater acoustic recordings to describe acoustic behaviour and sound parameters of calls have been previously published.

Changes in habitat use by a deep-diving predator in response to a coastal earthquake

Earthquakes can significantly impact ecosystem function and survivability of marine organisms, however their effect on marine predators remains unknown. In November 2016, a 7.8 magnitude earthquake triggered a ‘canyon flushing’ event in the submarine canyon of Kaikōura (New Zealand), a year-round foraging ground for sperm whales (Physeter macrocephalus). Underwater landslips and turbidity currents caused significant changes to the seafloor and removed large quantities of benthic biomass from the canyon. To investigate the potential impact of the earthquake on habitat use by sperm whales, we used a multi-year dataset to quantify changes in their behaviour, foraging distribution and use of food resources before and after the earthquake. The diving locations and behaviour of individual whales were recorded during summer and winter from January 2014 to January 2018, and samples of sloughed skin were collected for bulk and amino acid specific stable isotope analyses. While blow rates remained unchanged, the mean surface interval between dives was 25% longer for about one year after the earthquake, potentially reflecting increased effort searching for prey. Stable isotope ratios of sperm whale skin provided no evidence for change in diet. However, significant changes in the distribution of core foraging areas indicated shifts in habitat use for at least one year, potentially driven by changes in the seafloor and prey availability following the canyon flushing. Overall, our observations suggested that the earthquake caused alterations in the foraging patterns of sperm whales over a period of at least 12 months. This was the first study to quantify the impact of an earthquake on a marine mammal population, providing new insights into how top predators react and adapt to large-scale events of natural disturbance.

Refraction-learning-based whale optimization algorithm for high-dimensional problems and parameter estimation of PV model

Whale optimization algorithm (WOA) is a relatively new meta-heuristic optimization algorithm which mimics the hunting behavior of humpback whales. This paper presents a modified version of WOA, called RLWOA, for solving high-dimensional optimization problems. The proposed RLWOA adopts a modified conversion parameter update rule that relies on Logistic model to balance between diversity and convergence during the search process, and a new refraction-learning strategy based on the principle of refraction of light is proposed to help the population jump out of a local optimum. The experiments on a set of benchmark test functions with various features, i.e., 12 widely used benchmark functions with 100, 1000, and 10000 dimensions, two practical engineering design problems, and parameter estimation problem of photovoltaic model. The comparisons demonstrate that the proposed RLWOA shows better or at least competitive performance against the standard WOA, WOA variants and other state-of-the-art meta-heuristic algorithms for solving high-dimensional numerical optimization, practical engineering design optimization, and photovoltaic model parameter estimation problems.

RETRACTED ARTICLE: A new whale optimizer for workflow scheduling in cloud computing environment

Cloud computing environments enable real time applications on virtualized resources that can be provisioned dynamically. It is one of the efficient platform service which permits to enable the various applications based on cloud infrastructure. Nowadays workflow systems become an easy and efficient task for the development of scientific applications. Efficient workflow scheduling algorithms are employed to improve the resource utilization by enhancing the cloud computing performance and to meet the users’ requirements. Many scheduling algorithms have been proposed but they are not optimal to incorporate benefits of cloud computing. In this paper a new framework are introduced as whale optimizer algorithm (WOA) which mimics the social behaviour of humpback whales and aims to maximize the work completion for meeting QoS constraints such as deadline and budget. This proposed method outperforms well when compared with other techniques and measured in terms of makespan, deadline and it is applicable for real time applications.

Hybrid Whale Optimization Algorithm with Modified Conjugate Gradient Method to Solve Global Optimization Problems

Whale Optimization Algorithm (WOA) is a meta-heuristic algorithm. It is a new algorithm, it simulates the behavior of Humpback Whales in their search for food and migration. In this paper, a modified conjugate gradient algorithm is proposed by deriving new conjugate coefficient. The sufficient descent and the global convergence properties for the proposed algorithm proved. Novel hybrid algorithm of the Whale Optimization Algorithm (WOA) proposed with modified conjugate gradient Algorithm develops the elementary society that randomly generated as the primary society for the Whales optimization algorithm using the characteristics of the modified conjugate gradient algorithm. The efficiency of the hybrid algorithm measured by applying it to (10) of the optimization functions of high measurement with different dimensions and the results of the hybrid algorithm were very good in comparison with the original algorithm.

Critical threshold identified in the functional relationship between beaked whales and their prey

Anthropogenic noise is increasingly recognized as a potentially significant stressor for marine animals. Beaked whales, deep-diving cephalopod predators, have been disproportionally present in atypical mass stranding events coincident with military sonar exercises, while frequently disturbed populations that do not strand may have reductions in fitness. We presentin situmeasures of prey availability, a key factor affecting fitness, for 2 distinct populations ofMesoplodon densirostris: one on a US Navy range in The Bahamas and one nearby in an area less exposed to sonar. The variables most strongly correlated with beaked whale habitat use were related to the distribution of deep-sea squid (mode spacing, peak depth, and 100 m scale variability). All squid metrics were more favorable for beaked whales at the less exposed site than those on the range. To develop a generalized functional relationship between prey resources and beaked whale habitat use, data from The Bahamas were combined with comparable data from another Navy range and the larger beaked whale,Ziphius cavirostris. A power-law relationship was observed between a normalized metric of prey quality and whale habitat use. A critical threshold in prey characteristics, below which beaked whales appear unlikely to be successful, but above which small changes in resource availability enable large gains for predators, was observed. This implies that modest changes in the behavior of individual whales associated with disturbance can have consequential population effects. Our results elucidate the ecological realities of these elusive and sensitive beaked whales, and the importance of environmental context in effective spatial planning for the deep sea.

Whale optimization algorithm based on lateral inhibition for image matching and vision-guided AUV docking

The accuracy and stability of relative pose estimation of an autonomous underwater vehicle (AUV) and a target depend on whether the characteristics of the underwater image can be accurately and quickly extracted. In this paper, a whale optimization algorithm (WOA) based on lateral inhibition (LI) is proposed to solve the image matching and vision-guided AUV docking problem. The proposed method is named the LI-WOA. The WOA is motivated by the behavior of humpback whales, and it mainly imitates encircling prey, bubble-net attacking and searching for prey to obtain the globally optimal solution in the search space. The WOA not only balances exploration and exploitation but also has a faster convergence speed, higher calculation accuracy and stronger robustness than other approaches. The lateral inhibition mechanism can effectively perform image enhancement and image edge extraction to improve the accuracy and stability of image matching. The LI-WOA combines the optimization efficiency of the WOA and the matching accuracy of the LI mechanism to improve convergence accuracy and the correct matching rate. To verify its effectiveness and feasibility, the WOA is compared with other algorithms by maximizing the similarity between the original image and the template image. The experimental results show that the LI-WOA has a better average value, a higher correct rate, less execution time and stronger robustness than other algorithms. The LI-WOA is an effective and stable method for solving the image matching and vision-guided AUV docking problem.

An adaptive optimisation algorithm based on modified whale optimisation algorithm and Laplace crossover

Whale optimisation algorithm (WOA) is a new bio-inspired algorithm which mimics the hunting behaviour of humpback whale in nature. Standard WOA is easily trapped in local optima, provide slow convergence rate and lack of diversity, as the dimension of the search space expansion. In this paper, modified whale optimisation algorithm (MWOA) is proposed to improve the quality of standard WOA algorithm performance. Moreover, an adaptive optimisation algorithm based on modified whale optimisation algorithm and Laplace crossover (ALMWOA) is presented in this paper to increase the diversity of search space and enhance the capability to avoid local optimal solutions. The proposed MWOA and ALMWOA algorithms are tested on a set of 23 benchmark functions and the results are compared with standard WOA and other well-known meta-heuristic optimisation algorithms. Experimental results show that MWOA and ALMWOA can significantly outperform other optimisation algorithms in most of benchmark functions.

An Efficient-Assembler Whale Optimization Algorithm for DNA Fragment Assembly Problem: Analysis and Validations

The study of deoxyribonucleic acid (DNA) is crucial in many fields, including medicine, biology, zoology, agriculture, and forensics. Since reading a DNA sequence is onerous because of its massive length, it is common in many DNA analysis applications to divide DNA strands into small segments or fragments which, after analysis, must be reassembled. Since this reassembly takes a non-specific polynomial time to solve, the DNA fragment assembly problem (DFAP) is NP-hard. This paper proposes a new assembler for tackling the DFAP based on the overlap-layout-consensus (OLC) approach. The proposed assembler adapts a discrete whale optimization algorithm (DWOA) using standard operators adopted from evolutionary algorithms to simulate the strategy adopted by humpback whales when searching for prey. For the first time, we formulate the behaviors of whales to be applied directly to any discrete optimization problem based on three primary operations: a swap-based best-position operator, an ordered crossover operator, and selection of a random whale operation to perform the exploitation and exploration phases of the algorithm. These operations were carefully designed to preserve the methodology of the original whale algorithm. DFAP is a multi-objective problem that seeks to reach the optimal order of segments that maximizes the overlap score and minimizes the number of contigs (set of overlapping DNA segments) to compose a one-contig DNA strand. Existing local search methods, such as problem aware local search (PALS) many non-conflicting movements (PALS2-many), suffer from being trapped in local optima. Hence, the integration of DWOA with PALS2-many improves the search capability for finding the optimal order of fragments. In addition, we propose a new variation of PALS2-many that achieves simultaneously the two objectives of DFAP. Our proposed DWOA was compared with a number of the most recent robust assemblers: a hybrid crow search algorithm for solving the DFAP (CSA-P2M*Fit), P2M*Fit, and a hybrid genetic algorithm (GA-P2M*Fit). The experimental results and statistical analyses of the proposed DWOA on thirty benchmark instances show that DWOA significantly outperforms those algorithms in reaching fewer contigs, in addition to being competitive with CSA-P2M*Fit and superior to P2M*Fit and GA-P2M*Fit for the overlap score.

When the noise goes on: received sound energy predicts sperm whale responses to both intermittent and continuous navy sonar.

ABSTRACTAnthropogenic noise sources range from intermittent to continuous, with seismic and navy sonar technology moving towards near-continuous transmissions. Continuous active sonar (CAS) may be used at a lower amplitude than traditional pulsed active sonar (PAS), but potentially with greater cumulative sound energy. We conducted at-sea experiments to contrast the effects of navy PAS versus CAS on sperm whale behaviour using animal-attached sound- and movement-recording tags (n=16 individuals) in Norway. Changes in foraging effort and proxies for foraging success and cost during sonar and control exposures were assessed while accounting for baseline variation [individual effects, time of day, bathymetry and blackfish (pilot/killer whale) presence] in generalized additive mixed models (GAMMs). We found no reduction in time spent foraging during exposures to medium-level PAS (MPAS) transmitted at the same peak amplitude as CAS. In contrast, we found similar reductions in foraging during CAS (d.f.=1, F=8.0, P=0.005) and higher amplitude PAS (d.f.=1, F=20.8, P<0.001) when received at similar energy levels integrated over signal duration. These results provide clear support for sound energy over amplitude as the response driver. We discuss the importance of exposure context and the need to measure cumulative sound energy to account for intermittent versus more continuous sources in noise impact assessments.

Diving behaviour of adult male white whales (Delphinapterus leucas) in Svalbard, Norway

White whales (Delphinapterus leucas) in Svalbard remain near the coast much of the year, spending most of their time in front of tidewater glaciers. In this article, the diving behaviour of adult male white whales in Svalbard (N = 16) is presented based on satellite-relay data loggers that record time and depth of diving as well as positions. The loggers transmitted data for an average of 87 ± 52 days (range 2–163 days). After filtering, 55 359 dives were available for the study. Most of the dives were extremely shallow (13 ± 26 m, maximum 350 m) and of short duration (97 ± 123 s, maximum 31.4 min). At tidewater glacier fronts, the white whales optimized their time at the bottom of dives and spent longer periods resting at the surface after dives, in accordance with what would be expected when foraging. This behaviour was also documented when animals were out in the fjords. When the whales moved between areas around the archipelago, they swam close to the coast, staying right below the surface most of the time, presumably to minimize energy expenditure during transits. When sea ice formed during the winter, the whales were forced offshore into somewhat deeper areas with drifting ice. In these areas, the whales minimized time at the surface and dove somewhat deeper, sometimes reaching the bottom, presumably to feed on neritic prey.

Quantifying the Behavior of Humpback Whales (Megaptera novaeangliae) and Potential Responses to Sonar

Quantifying the Behavior of Humpback Whales (Megaptera novaeangliae) and Potential Responses to Sonar

Foraging Behavior and Disruption in Blue, Fin, and Humpback Whales in Relation to Sonar Exposure: The Challenges of Generalizing Responsiveness in Species with High Individual Variability

Foraging Behavior and Disruption in Blue, Fin, and Humpback Whales in Relation to Sonar Exposure: The Challenges of Generalizing Responsiveness in Species with High Individual Variability

Behavioural responses of migrating humpback whales to swim-with-whale activities in the Ningaloo Marine Park, Western Australia

Swim-with-whale tourism is a lucrative and rapidly growing industry worldwide. Whale-watching can cause negative effects on the behaviour of targeted animals. Although this is believed to be particularly true for close-up interactions, such as swim-with operations, few empirical studies have investigated this. In 2016, the Western Australian State Government commenced a swim-with humpback whale (Megaptera novaeangliae) trial in the Ningaloo Marine Park, where 11 commercial licences were granted. The swim-with trial was conducted during both the northern and southern whale migration (August to November), during which we assessed potential short-term behavioural effects on humpback whales to swim-with activities. From both an independent research vessel (n = 300 h) and on-board commercial swim-with vessels (n = 357 h), we collected group-follow data (n = 224) on whale behaviour before, during and after swim-with activities. Behavioural effects on whales were investigated, including movement patterns (deviation and directness index, heading, swim speed), surfacing patterns (dive duration and respiration rate) and occurrence of agonistic behaviours. Results showed that the most common type of vessel approach to place swimmers in the water was in the path of whales (89.8% of interactions). During in-path approaches, vessels travelled significantly faster (P = .002) compared to when approaching from the side (side/line abreast approaches). When vessels approached in the whales' path, whales exhibited horizontal and vertical avoidance strategies by adopting a less predictable path (deviating from 32° to 46°), increasing turning angles away from the vessel (heading from 73° to >90°), increasing swim speeds (from 1.68 to 1.89 ms−1), and decreasing the duration of their dives (from 224 to 194 s). Whales displayed a higher frequency of agonistic behaviours when a swim-with vessel was <100 m distance from them compared to >100 m away (P = .011). Young-of-year calves were present during 19.6% (18 of 92) of group-follows that included swim attempts. To reduce potential impacts on whales and increase swimmer safety, we recommend to avoid in-path vessel approaches, not place swimmers in the water with groups of whales that perform agonistic behaviours, and avoid swimming with young-of-year calves.

Sounds associated with foraging and prey capture in individual fish-eating killer whales, Orcinus orca.

Foraging behavior in odontocetes is fundamentally tied to the use of sound. Resident-type killer whales use echolocation to locate and capture elusive salmonid prey. In this investigation, acoustic recording tags were suction cup-attached to endangered Southern Resident killer whales to describe their acoustic behavior during different phases of foraging that, along with detections of prey handling sounds (e.g., crunches) and observed predation events, allow confirmation of prey capture. Echolocation click trains were categorized based on the inter-click interval (ICI) according to hypothesized foraging function. Whales produced slow click trains (ICI >100 ms) at shallowest depths but over the largest change of depth, fast click trains (10 ms < ICI ≤100 ms) at intermediate depths, and buzz trains (ICI ≤10 ms) at deepest depths over the smallest depth change. These results align with hypotheses regarding biosonar use to search, pursue and capture prey. Males exhibited a higher probability of producing slow click trains, buzzes and prey handling sounds, indicating higher levels of prey searching and capture to support the energy requirement of their larger body size. These findings identify relevant acoustic indicators of subsurface foraging behaviors of killer whales, enabling investigations of human impacts on sound use and foraging.

Performance Improvement in MIMO-OFDM Systems based on adaptive Whale Elephant Herd Optimization algorithm

Multiple-input, multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) is the leading air interface for 4G and 5G broadband wireless communications. Cognitive Radio (CR) is the trending technology, which facilitates spectrum sensing to determine the inadequate bands in the spectrum. Though there are so many spectrum sensing techniques, the existing methods suffered a lot in the communication environment. In the traditional CR network, data transmission is constrained to the secondary user within the available bands. With the aim to increase spectrum efficiency and throughput, this paper proposed the hybrid mixture model using Adaptive Whale Elephant Herd Optimization (Adaptive WEHO) algorithm for spectrum sensing. Adaptive WEHO is the integration of Elephant-Herd Optimization (EHO), and Whale Optimization Algorithm (WOA), with the adaptive concept. The signal received from the OFDM antenna is used to analyze the availability of spectrum based on the signal energy and Eigen statistics. The CR searches the availability of channel and makes the connection when it determines a free channel. Here, the spectrum sensing is achieved by the Gaussian Mixture Model (GMM), which is trained by the proposed Adaptive WEHO algorithm. The proposed Adaptive WEHO algorithm uses the foraging behavior of whales and the herding behavior of elephants, which is applied in the spectrum sensing technique to perform the optimal sensing. The proposed Adaptive WEHO attained better performance with the metrics of probability of detection as 1.0238, and the probability of false alarm as 0.01075, respectively. The proposed method ensures the effective communication in CR without any interference.

Lunar cycles influence the diving behavior and habitat use of short-finned pilot whales around the main Hawaiian Islands

The availability of light, both solar and lunar, is likely to influence the behavior of vertically migrating aquatic animals and their predators. However, the influence of light level on the diving behavior and habitat use of deep-diving cetaceans is not well understood. We used data from 28 depth-transmitting satellite tags deployed on short-finned pilot whales Globicephala macrorhynchus around the main Hawaiian Islands to examine movements and diving behavior in relation to lunar cycles and oceanographic season. During a full moon, dives were deeper (48.1%) and longer (16.7%) than during a new moon. This change appeared to be driven primarily by an increase (25.2%) in the depth of deep dives (>200 m) completed at night and an increase in the proportion of deeper daytime and twilight dives during a full moon. Dives occurred a mean of 18.3 km farther offshore (more than twice as far from shore) during a full moon compared to a new moon. During the oceanographic season with the shortest day length (fall), dives were shallower (25.4%) and shorter (14.2%) than seasons with longer days (summer). This suggests that changes in light level, both solar and lunar, affect the depth of prey targeted by pilot whales, which in turn influences pilot whale diving behavior and distribution. Future research should determine how these changes influence the feeding success and energetics of pilot whales.