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Rendezvous with sperm whales for biological observations is made challenging by their prolonged dive patterns. Here, we propose an algorithmic framework that codevelops multiagent reinforcement learning--based routing (autonomy module) and synthetic aperture radar--based very high frequency (VHF) signal--based bearing estimation (sensing module) for maximizing rendezvous opportunities of autonomous robots with sperm whales. The sensing module is compatible with low- energy VHF tags commonly used for tracking wildlife. The autonomy module leverages in situ noisy bearing measurements of whale vocalizations, VHF tags, and whale dive behaviors to enable time- critical rendezvous of a robot team with multiple whales in simulation. We conducted experiments at sea in the native habitat of sperm whales using an "engineered whale"--a speedboat equipped with a VHF-emitting tag, emulating five distinct whale tracks, with different whale motions. The sensing module shows a median bearing error of 10.55° to the tag. Using bearing measurements to the engineered whale from an acoustic sensor and our sensing module, our autonomy module gives an aggregate rendezvous success rate of 81.31% for a 500-meter rendezvous distance using three robots in postprocessing. A second class of fielded experiments that used acoustic- only bearing measurements to three untagged sperm whales showed an aggregate rendezvous success rate of 68.68% for a 1000-meter rendezvous distance using two robots in postprocessing. We further validated these algorithms with several ablation studies using a sperm whale visual encounter dataset collected by marine biologists. [ABSTRACT FROM AUTHOR]

Background: Studying movement patterns of individual animals over time can give insight into how they interact with the environment and optimize foraging strategies. Humpback whales (Megaptera novaeangliae) undertake long seasonal migrations between feeding areas in polar regions and breeding grounds in tropical areas. During the last decade, several individuals have had up to a 3-month stop-over period around specific fjord-areas in Northern Norway to feed on Norwegian spring-spawning (NSS-) herring (Culpea harengus L.). Their behavioral patterns during this period are not well understood, including why some whales seemingly leave the fjords and then later return within the same season. Methods: To investigate whale behavior during this seasonal stopover, we classified humpback whale tracks into five distinct movement modes; ranging, encamped, nomadic, roundtrip and semi-roundtrip. A behavioral change point analysis (BCPA) was used to select homogeneous segments based on persistence velocity. Then, net squared displacement (NSD) over time was modeled to differentiate movement modes. This study also manually identified longer roundtrips away from the fjords that lasted several days and examined movement modes within these. Results: Inside the fjord systems, encamped mode was most prevalent in December–January, suggesting the whales were mainly foraging on overwintering NSS-herring in this area. During the same winter seasons, half of the whales left the fjords and then returned. We hypothesize that these trips serve as 'searching trips' during which the whales seek better feeding opportunities outside the fjords. If better foraging conditions are not found, they return to the fjords to continue their feeding. The overall most common mode was ranging (54%), particularly seen during the start of their southwards migration and in areas outside the fjord systems, indicating that the whales mainly moved over larger distances in the offshore habitat. Conclusions: This study serves as a baseline for future studies investigating both the searching trip theory and humpback whale behavior in general, and confirms that this method could be useful to analyze local scale movement patterns of satellite tagged whales. [ABSTRACT FROM AUTHOR]

Goose-beaked whales (Ziphius cavirostris) are deep-diving cetaceans known for their elusive nature and specialized foraging behavior. In 2019 and 2020, six telemetry tags were deployed on these whales in Southern California, resulting in 395 h of acoustic and diving data. Foraging dives were manually identified by the presence of echolocation pulses and buzzes, and generalized additive models assessed factors influencing foraging behavior. The median bathymetric depth at foraging sites was 1,419 m (IQR = 359), and the maximum dive depth was highly correlated with bathymetry depth. Individuals started echolocating on descent at a median depth of 410 m (IQR = 74); pulses were not observed shallower than 292 m. Echolocation ceased during the bottom phase for 81.6% of dives, at a median depth of 1,265 m (IQR = 472); pulses were not observed shallower than 587 m on ascent. The median depth of buzzes was 1,215 m (IQR = 479) with 63% occurring during the bottom phase. Deeper dives correlated with longer durations of diving and echolocation, greater echolocation end depths, and wider bottom phase echolocation depth inter-quartile range. The median difference between dive depth and bottom phase median echolocation depth was 98.3 m (IQR = 48.5), suggesting whales in this region forage in a narrow band close to the seafloor. In the San Nicolas Basin, individuals exhibited longer echolocation durations, produced more pulses, and started and ended echolocating at greater depths compared to adjacent regions. These records validate and expand upon previous studies, providing insights into factors influencing foraging behavior in an area with high anthropogenic disturbance. [ABSTRACT FROM AUTHOR]

Summary: In a highly dense multiple‐input multiple‐output (MIMO) communication system, proper resource allocation is exceedingly challenging. The simultaneous selection of antennas at the base‐station (BS) and scheduling of users in an uplink multiple access channel (MAC) system add up to the signal processing load in the MIMO wireless system. The method chosen for combining the user scheduling and antenna selection must have a very low computational complexity. However, the exhaustive search algorithm (ESA), which achieves the best sum‐rate capacity in a MIMO‐MAC system, has a very high level of complexity. In this paper, we use a metaheuristic‐based optimization algorithms to optimize the sum‐rate capacity in a MAC system with significantly less computational complexity. First, we use the beluga whale optimization (BWO) metaheuristic method to solve the optimization problem. The BWO is a swarm‐based algorithm that draws inspiration from beluga whale behavior. An improved BWO (iBWO) is also presented and is utilized for the same optimization challenge. The proposed iBWO scheme improves the search capability of the algorithm and thereby ensures better exploration and exploitation capabilities of the beluga whales. We compare the performance of these algorithms with a standard differential evolution (DE) algorithm. The simulation results demonstrate that the proposed iBWO is a very competitive meta‐heuristic algorithm for solving optimization problems. The proposed iBWO algorithm achieves near optimal throughput in a MIMO‐MAC system. Also, the computational complexity related to the suggested optimization technique in a MIMO‐MAC system is found to be very less compared with the complexity related to ESA. [ABSTRACT FROM AUTHOR]

Foraging efficiency is key to animal fitness. Consequently, animals evolved a variety of kinematic, morphological, physiological, and behavioral adaptations for efficient locomotion to reduce energy expenditure while moving to find, capture, and consume prey. Often suited to specific habitat and prey types, these adaptations correspond to the terrain or substrate the animal moves through. In aquatic systems, adaptations focus on overcoming drag, buoyancy, and hydrostatic forces. Buoyancy both benefits and hinders diving animals; in particular, shallow divers constantly contend with the costs of overcoming buoyancy to dive and maintain position. Pacific Coast Feeding Group (PCFG) gray whales forage in shallow habitats where they work against buoyancy to dive and feed using various foraging tactics. Bubble blasts (underwater exhalations) have been observed during several foraging tactics performed by PCFG whales. As exhalations aid buoyancy regulation in other diving animals, we hypothesize that bubble blasts are performed by longer, more buoyant whales in shallower water and that bubble blasts increase dive duration while accounting for size and tactic. We test our hypotheses using Bayesian linear mixed effects models and a 7‐year dataset of drone footage containing concurrent individual morphological and behavioral data. We find that while headstanding – a stationary, head‐down tactic – bubble blasts are performed by longer, more buoyant whales and extend the dive duration, whereas whales using forward‐swimming tactics are less likely to bubble blast. Our results suggest that PCFG gray whales may use bubble blasts as a behavioral adaption to mitigate the cost of energetically expensive tactics in their shallow habitat foraging niche. [ABSTRACT FROM AUTHOR]

Knowledge about species-specific hearing is vital to assessing how anthropogenic noise impacts marine mammals. Unfortunately, no empirical audiogram exists for any mysticete whale. We therefore developed a catch-and-release method to assess hearing in a small mysticete, the minke whale (Balaenoptera acutorostrata). Stationary lead nets were placed to intercept migratory routes and direct the whales into an ocean basin enclosed by nets and islets, while another net was pulled across the entrance once a whale entered the basin. The minke whales were then slowly corralled into a modified aquaculture pen using a net suspended between two boats. Subsequently, the water volume available to the whales was gradually reduced by raising the pen net by hand until the whales were secured in a “hammock” between the floating pen ring and a raft. From the raft, researchers could access the whales to monitor their health, apply instruments for hearing tests, or perform other research objectives, and then attach tags to monitor the movements and diving behavior of the whale post-release. The method is a slow and controlled procedure, allowing continuous monitoring and quick release of the whales, if needed. In the first three field seasons employing the method, three minke whales were caught for research procedures. Initial hearing measurements using auditory evoked potentials were successfully completed. After release, the whales resumed migration, and dive behavior was considered normal. Our observations demonstrated that minke whales can be guided safely via moored net barriers, corralled into an aquaculture pen, and safely handled for research purposes, before being released back into the wild. [ABSTRACT FROM AUTHOR]

Fin whales (Balaenoptera physalus) aggregate west of Iceland during summer, where they feed mostly on krill, but their winter distribution is poorly known. This study investigates the winter behavior of fin whales that summer off Iceland by analyzing amino acid‐specific nitrogen isotope ratios in the baleen plates. This technique is increasingly used in large marine vertebrates to discriminate between changes in trophic position and changes in isotopic baseline levels, while ruling out the effect of fasting on these patterns. Analyses were conducted on samples extracted from two baleen plate segments: one corresponding to winter, another to summer. The trophic position was higher and slightly more variable in winter (3.6 ± 0.7) than in summer (3.0 ± 0.4), which indicates that during winter fin whales tend to feed on fish and are more generalist in feeding habits. Interestingly, the δ15NPhe values were not lower in winter than in summer (winter: 5.2‰ ± 2.4‰; summer: 4.0‰ ± 2.1‰). This was unexpected because baseline δ15N values (e.g., zooplankton) tend to be lower at low latitudes, where fin whales are believed to spend the winter. Fin whales may remain in relatively high latitudes during winter or visit low‐latitude areas with locally higher than average δ15N values, such as upwelling areas. [ABSTRACT FROM AUTHOR]

In many aquatic taxa, formation traveling can reduce the energetic expenditure of locomotion by exploiting the vorticity trails shed by neighbors or through drafting. Cetaceans, especially odontocetes, often swim in groups; nevertheless, the possibility that whales gain energetic benefits from swimming in formation remains poorly studied, apart from mother-calf pairs. Between June and September in 2019 and 2021, we recorded aerial videos of Southern Resident killer whales (Orcinus orca) in the Salish Sea (USA) travelling in groups. We estimated whale tailbeat and breathing frequencies as proxies of the relative energetic costs of swimming, and tested the effect of swimming speed, relative positioning (e.g., leaders, whales in the middle of groups, or followers), sex and estimated size on these observed proxies. Our results reveal a complex relationship between physical characteristics, relative positioning, and energetic proxies. Intervals between respiration lasted longer in large-sized trailing individuals, but the overall breathing frequency was similar for all whales regardless of their position. The tailbeat frequency was mainly associated to whale sex, size, and swimming speed; in addition, tailbeat frequency showed a decreasing trend as the number of individuals in the formation increased. We found moderate evidence that position-based energetic effects may be present in the formation swimming of killer whales, and it is likely that additional factors such as social ties and hierarchies, play a key role in determining individual positioning in travelling groups. Significance: Swimming in formation has been extensively studied in fish and other aquatic animals and has been documented to provide energetic advantages. Our understanding of the potential energetic benefits of wild cetacean formation swimming has been constrained by the difficulties of studying the movement of whale groups from traditional observation platforms. In recent years, non-invasive observations of cetaceans using unoccupied aerial systems have significantly improved the observation of these species in the wild, providing an exciting opportunity to better understand their behaviors and habits. Our results show a tendency for formation swimming to affect two energetic proxies (tailbeat frequency and the duration of underwater intervals between surfacing events). The results of this study set the stage for further research to identify the multiple determinants affecting killer whale formation swimming which go beyond purely energetic advantages, e.g. social relationships. [ABSTRACT FROM AUTHOR]

Fin whale song is a ubiquitous low-frequency pulsing that has been recorded in every ocean basin. In recent years, the complexity of fin whale song has been realized. In the North Atlantic, this song is made up of two low-frequency note types (A and B notes) and one higher-frequency note type (upsweeps). The A and B notes are produced with both singlet and doublet inter-note intervals. These song patterns are interwoven throughout an individual's song and have been observed to shift over time, both gradually and suddenly. Like many baleen whales, the population size of fin whales is poorly defined. Passive acoustic monitoring has been suggested as a way to estimate abundance if a cue rate or calling rate can be determined. In this study, we used recordings from 119 fin whale tracks from 2013-2023 generated from passive acoustic recorders in the North Atlantic to define fin whale song patterns in this ocean basin, identify changes in these song patterns over time, and calculate cue rates. The fin whales recorded sang in 4 distinct patterns. Inter-note intervals were 25 s for A-A singlets, 13 s for B-B singlets, 12/20 s for B-B doublets, and 10/11 s for A-B doublets. B-B doublet inter-note intervals significantly increased from May 2019--April 2023 and A-B inter-note intervals showed an intra-annual increasing trend that reset each summer. Fin whale song in the North Atlantic also often includes higher frequency upsweep notes immediately prior to B notes. While A and B note peak frequency was steady over these years, upsweep peak frequency significantly decreased, continuing a similar trend that has been observed over 30 years. Despite these changes, the dominant song pattern remained consistent and cue rate for actively singing whales was relatively stable, which is in contrast to patterns observed in the North Pacific. Many of these nuances in fin whale singing behavior are newly described herein, and these findings are vital for monitoring baseline behavior, behavioral trends over time, and ultimately estimating abundance of a poorly understood species. [ABSTRACT FROM AUTHOR]

Abundance estimation of wildlife populations is frequently derived from systematic survey data. Accuracy and precision of estimates, however, depend on the number of replicate surveys, and on adjustments made for animals unavailable to (availability bias), or available but undetected (perception bias) by observers. This study offers a comprehensive analysis of the relative influence of methodological, environmental and behavioral factors on availability bias estimates from photographic and visual aerial surveys of a small cetacean with a highly clumped distribution, the beluga (Delphinapterus leucas). It also estimates the effect of the number of surveys on accuracy and precision of abundance estimates, using 28 replicate visual surveys flown within a 16--29 day window depending on survey year. Availability bias was estimated using detailed dive data from 27 beluga from the St. Lawrence Estuary, Canada, and applied to systematic visual and photographic aerial surveys of this population, flown using various survey platforms. Dive and surface interval durations varied among individuals, and averaged (weighted) 176.6 s (weighted s.e. = 12.6 s) and 51.6 s (weighted s.e. = 4.5 s), respectively. Dive time and instantaneous availability, but not surface time, were affected by local turbidity, seafloor depth, whale behavior (i.e., whether beluga were likely in transit or not), and latent processes that were habitat-specific. Overall, adjustments of availability for these effects remained minor compared to effects from survey design (photographic or visual) and type of platform, and observer search patterns. For instance, mean availability varied from 0.33--0.38 among photographic surveys depending on sightings distribution across the study area, but exceeded 0.40 for all visual surveys. Availability also varied considerably depending on whether observers searched within 0-90° (0.42--0.60) or 170° (0.70--0.80). Simulation-based power analysis indicates a large benefit associated with conducting more than 1 or 2 survey reps, but a declining benefit of conducting > 5--10 survey reps. An increase in sample size from 2, to 5, and 10 reps decreased the CV from 30, to 19 and 13%, respectively, and increased the probability of the abundance estimate being within 15% of true abundance from 0.42, to 0.59 and 0.69 in species like beluga. [ABSTRACT FROM AUTHOR]

Gray whales (Eschrichtius robustus) evolved to suction feed on benthic invertebrates and typically do not consume adult fish. Yet, these whales are flexible foragers, occasionally skim feeding on planktonic invertebrates and rarely lunge feeding on fish, the latter according to anecdotal accounts. We documented the unusual phenomenon of multiple gray whales predating dense schools of anchovy over a sustained period (22 days) in June 2022 at Pacifica, California, in the Gulf of the Farallones. Analysis of 11,265 photos and 11 video clips (totaling 4 min 16 s) for behavior and whale identification resulted in a total of 165 foraging events by six identified gray whales. Attribution of foraging behavior to the most active individuals was achieved by matching left pectoral fins, visible during lateralized feeding behavior. Whales rolled onto their right sides in 96% of near-surface side-swimming bouts. Another behavior, first photographed here, was dynamic surface lunge feeding by one gray whale. Five gray whales interspersed fish feeding with benthic suction feeding evidenced by sediment streaming: prey type switching was executed rapidly, in less than 1 minute in several instances, the shortest intervals reported for a baleen whale. Similar results were obtained for foraging behavior switching (continuous side-swimming or intermittent lunging) in pursuit of fish. Four photo-identified Pacifica whales were sighted in San Francisco Bay/Gulf of the Farallones, one of which was also matched to the Pacific Coast Feeding Group. Such local and regional connections warrant efforts to determine whether gray whales use this area as a migratory stopover site or for summer foraging, or both. Our observations confirm gray whale behavioral plasticity and opportunistic exploitation of food resources in mid-latitudes, which may enhance their resilience to climate change. [ABSTRACT FROM AUTHOR]

The Whale Optimization Algorithm (WOA) is an efficient meta-heuristic algorithm inspired by the feeding behavior of whales. Although it has successfully solved many optimization problems, it still suffers from premature convergence and poor accuracy when solving complex problems. To address these issues, this paper proposes an improved whale optimization algorithm called EIWOA to improve the search efficiency and accuracy. First, we introduce a new global search mechanism and encircling prey strategy in EIWOA, which utilizes differential evolution, and sine-cosine search strategy to improve the global search efficiency and avoid premature convergence. Second, we use a lévy flight-based spiral update position strategy to improve the local search efficiency of the algorithm, thus improving the convergence speed and accuracy. Again, we introduce a balancing factor with fluctuating decay properties into EIWOA to better balance exploration and exploitation. Finally, we introduce a dynamic opposite learning-based whale-fall strategy in EIWOA to equip the algorithm with the ability to jump out of the local optimum. The qualitative analysis of the algorithm shows that the EIWOA algorithm converges quickly, is highly accurate, and has the ability to jump out of the local optimum. In order to validate the performance of the proposed EIWOA algorithm, we evaluated the algorithm on CEC2017 benchmark function and four real world engineering problems. We also conduct a comparative study of the EIWOA algorithm with EWOA, an excellent variant of WOA, as well as some excellent meta-heuristics developed recently. The results of numerical experiments demonstrate the superiority of the proposed EIWOA, which is further confirmed statistically by the results of Friedman's test and Wilcoxon signed rank test. The proposed EIWOA algorithm is significantly better than WOA and other competing algorithms in terms of convergence speed, accuracy and optimization ability in dealing with complex optimization problems. [ABSTRACT FROM AUTHOR]

The whale optimization algorithm has received much attention since its introduction due to its outstanding performance. However, like other algorithms, the whale optimization algorithm still suffers from some classical problems. To address the issues of slow convergence, low optimization precision, and susceptibility to local convergence in the whale optimization algorithm (WOA). Defining the optimization behavior of whale individuals as quantum mechanical behavior, a whale optimization algorithm based on atom-like structure differential evolution (WOAAD) is proposed. Enhancing the spiral update mechanism by introducing a sine strategy guided by the electron orbital center. Improving the random-walk foraging mechanism by applying mutation operations to both the electron orbital center and random individuals. Performing crossover operations between the newly generated individuals from the improved mechanisms and random dimensions, followed by a selection process to retain superior individuals. This accelerates algorithm convergence, enhances optimization precision, and prevents the algorithm from falling into local convergence. Finally, implementing a scouting bee strategy, where whale individuals progressively increase the number of optimization failures within a limited parameter L. When a threshold is reached, random initialization is carried out to enhance population diversity. Conducting simulation experiments to compare the improved algorithm with the whale optimization algorithm, other optimization algorithms, and other enhanced whale optimization algorithms. The experimental results indicate that the improved algorithm significantly accelerates convergence, enhances optimization precision, and prevents the algorithm from falling into local convergence. Applying the improved algorithm to five engineering design problems, the experimental results demonstrate that the improved algorithm exhibits good applicability. [ABSTRACT FROM AUTHOR]

Beluga Whale Optimization (BWO) is a new metaheuristic algorithm that simulates the social behaviors of beluga whales swimming, foraging, and whale falling. Compared with other optimization algorithms, BWO shows certain advantages in solving unimodal and multimodal optimization problems. However, the convergence speed and optimization performance of BWO still have some performance deficiencies when solving complex multidimensional problems. Therefore, this paper proposes a hybrid BWO method called HBWO combining Quasi-oppositional based learning (QOBL), adaptive and spiral predation strategy, and Nelder-Mead simplex search method (NM). Firstly, in the initialization phase, the QOBL strategy is introduced. This strategy reconstructs the initial spatial position of the population by pairwise comparisons to obtain a more prosperous and higher quality initial population. Subsequently, an adaptive and spiral predation strategy is designed in the exploration and exploitation phases. The strategy first learns the optimal individual positions in some dimensions through adaptive learning to avoid the loss of local optimality. At the same time, a spiral movement method motivated by a cosine factor is introduced to maintain some balance between exploration and exploitation. Finally, the NM simplex search method is added. It corrects individual positions through multiple scaling methods to improve the optimal search speed more accurately and efficiently. The performance of HBWO is verified utilizing the CEC2017 and CEC2019 test functions. Meanwhile, the superiority of HBWO is verified by utilizing six engineering design examples. The experimental results show that HBWO has higher feasibility and effectiveness in solving practical problems than BWO and other optimization methods. [ABSTRACT FROM AUTHOR]

With the wide application of mobile robots, mobile robot path planning (MRPP) has attracted the attention of scholars, and many metaheuristic algorithms have been used to solve MRPP. Swarm-based algorithms are suitable for solving MRPP due to their population-based computational approach. Hence, this paper utilizes the Whale Optimization Algorithm (WOA) to address the problem, aiming to improve the solution accuracy. Whale optimization algorithm (WOA) is an algorithm that imitates whale foraging behavior, and the firefly algorithm (FA) is an algorithm that imitates firefly behavior. This paper proposes a hybrid firefly-whale optimization algorithm (FWOA) based on multi-population and opposite-based learning using the above algorithms. This algorithm can quickly find the optimal path in the complex mobile robot working environment and can balance exploitation and exploration. In order to verify the FWOA's performance, 23 benchmark functions have been used to test the FWOA, and they are used to optimize the MRPP. The FWOA is compared with ten other classical metaheuristic algorithms. The results clearly highlight the remarkable performance of the Whale Optimization Algorithm (WOA) in terms of convergence speed and exploration capability, surpassing other algorithms. Consequently, when compared to the most advanced metaheuristic algorithm, FWOA proves to be a strong competitor. [ABSTRACT FROM AUTHOR]

This paper proposes a novel approach for solar power forecasting using an Adaptive Neuro-Fuzzy Inference System (ANFIS) enhanced with Whale Swarm Optimization (WSO). The synergy between ANFIS and WSO aims to overcome the limitations of traditional forecasting models by controlling the collective intelligence of a whale-inspired swarm algorithm. The WSO optimizes the parameters of the ANFIS, leading to improved accuracy in solar power predictions. The integration of WSO introduces a parallelism and exploration-exploitation balance inspired by the natural behaviors of whales, enhancing the ANFIS model's adaptability to dynamic solar power generation patterns. The experimental results demonstrate the superiority of the proposed Whale Swarm-based ANFIS over conventional methods, showcasing its ability to handle non-linear and complex relationships in solar power data. This research contributes to the field of renewable energy forecasting by presenting an innovative hybrid model that leverages the strengths of both ANFIS and WSO for more reliable and precise solar power predictions. [ABSTRACT FROM AUTHOR]

The acoustic ecology of sei whales (Balaenoptera borealis) is poorly understood due to limited direct observation of the behavioral context of sound production and individual behavior. Suction cup–attached acoustic recording tags were deployed on sei whales to unambiguously assign call types and explore the acoustic behavior of this endangered species. Twelve tag deployments resulted in ∼173 h of acoustic data and 1030 calls. Sound types included downsweeps and three previously undescribed call types. Knocks were short duration (<1 s), with an average peak frequency of 330 Hz. Pulse type 1 and pulse type 2 calls, typically produced in sequences, were short in duration (0.08 and 0.28 s) and low in average peak frequency (50 and 26 Hz), with relatively high received levels. Average call rates for all call types combined were three calls per hour, but increased during twilight. Sex differences in call type usage included a higher use of pulses by females and knocks by males. Calls were almost exclusively produced at depths <10 m, although whales rarely dove deeper in this study. These data provide a more comprehensive picture of the acoustic and behavioral ecology of sei whales than previously possible, which can inform future conservation efforts for this endangered species. [ABSTRACT FROM AUTHOR]

The beluga whale optimization (BWO) algorithm is a recently proposed metaheuristic optimization algorithm that simulates three behaviors: beluga whales interacting in pairs to perform mirror swimming, population sharing information to cooperate in predation, and whale fall. However, the optimization performance of the BWO algorithm still needs to be improved to enhance its practicality. This paper proposes a modified beluga whale optimization (MBWO) with a multi-strategy. It was inspired by beluga whales' two behaviors: group gathering for foraging and searching for new habitats in long-distance migration. This paper proposes a group aggregation strategy (GAs) and a migration strategy (Ms). The GAs can improve the local development ability of the algorithm and accelerate the overall rate of convergence through the group aggregation fine search; the Ms randomly moves towards the periphery of the population, enhancing the ability to jump out of local optima. In order to verify the optimization ability of MBWO, this article conducted comprehensive testing on MBWO using 23 benchmark functions, IEEE CEC2014, and IEEE CEC2021. The experimental results indicate that MBWO has a strong optimization ability. This paper also tests MBWO's ability to solve practical engineering optimization problems through five practical engineering problems. The final results prove the effectiveness of MBWO in solving practical engineering optimization problems. [ABSTRACT FROM AUTHOR]

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Commercial fisheries have increased in all the world's oceans with diverse unintended impacts on marine ecosystems. As a result of resource overlap, interactions between cetaceans and fisheries are a common occurrence and, in many cases, can give rise to significant conservation issues. Research on the distribution and types of such interactions is important for efficient management. In this study, we describe the behaviors of two whale species: sperm whales (Physeter macrocephalus) and northern bottlenose whales (Hyperoodon ampullatus), interacting with benthic trawlers fishing off the eastern Grand Banks of the western North Atlantic in 2007. Whale interactions were only observed when vessels were targeting Greenland halibut (Reinhardtius hippoglossoides) in deep-water fishing areas and were most common during net hauling. Sperm whales and northern bottlenose whales appeared to engage in feeding behavior close to the surface during hauling, especially during the latter stages, suggesting they targeted fish escapees rather than discards. Using photo-identification methods, seven individual sperm whales were identified with multiple resights of six individuals being recorded over an almost two month period. The maximum distance between two resights was 234 km, suggesting individual sperm whales were repeatedly targeting and even following fishing vessels over multiple days and between fishing areas. By contrast, there were no photographic resights of individual northern bottlenose whales within this study, or with substantial photo-identification catalogues from other adjacent high density areas, suggesting that individuals of this species may be less likely to follow vessels or move between areas. This study documents the earliest confirmed records of northern bottlenose whales in this remote region. These interactions and high encounter rates may indicate that adjacent populations are recovering from the previous century of commercial whaling. Our study provides new insights and details on whale-fisheries interactions, which can inform future research and help managers understand the real and perceived impacts of depredation behaviour on fisheries and whales. [ABSTRACT FROM AUTHOR]

Despite its biological importance, the nursing behavior in baleen whales has been poorly documented mainly because of the challenges in tracking whales in their natural environment. We studied the suckling behavior (nursing from the calf's perspective) in < 3-month-old humpback whale calves off Sainte Marie Island, Madagascar, South Western Indian Ocean (breeding/calving area). We investigated the temporal pattern of the suckling behavior, its spatial and behavioral context, and the ontogeny of these characteristics. We exploited data from both camera-equipped and non-camera-equipped animal-borne multi-sensor tags (Acousonde and CATS cam) collected from 2013 to 2022 (37 calves). Our dataset constitutes the largest sample assembled so far to investigate the suckling behavior in free-ranging whales. We found that the suckling event duration does not vary much with the calves' relative age. The estimated proportion of time spent suckling ranged between 0.8 and 1.6%. The suckling events mainly occurred during the descent and bottom phases of dives and rarely during the ascent phase of dives or surface activities. Strong evidence of humpback whale suckling at night is presented for the first time. We found that suckling events were often performed in bouts of 2–6 events. Suckling bouts mostly occurred less than 10 min apart, and suckling sessions were separated by about 2 h of non-suckling periods. In other words, humpback whale calves suckled several times throughout the day in short sessions similar to terrestrial "followers." Our results add to the evidence that humpback whales, and potentially most baleen whales, are behaviorally and functionally similar to terrestrial "followers" regarding maternal strategy. Significance statement: Young mammals rely on the milk provided by their mother to survive during their early life stage. The suckling behavior, i.e., the procurement of milk from the mother, has been widely studied for terrestrial mammals but not for fully aquatic mammals like the baleen whales due to the challenges in tracking them. By placing sensors and cameras on calves, we described the suckling pattern in humpback whales, the most common baleen whale species. We found that the temporal pattern of suckling in humpback whales is similar to those of terrestrial precocial mammals experiencing comparable environments (open habitat with predators): the young suckle frequently but in short sessions. Our results offer a new insight supporting the hypothesis that the rearing strategy used by baleen whales is an aquatic version of the "following" behavior found in these precocial terrestrial species. [ABSTRACT FROM AUTHOR]

Beluga whale optimization (BWO) algorithm is a recently proposed population intelligence algorithm. Inspired by the swimming, foraging, and whale falling behaviors of beluga whale populations, it shows good competitive performance compared to other state-ofthe-art algorithms. However,the original BWO faces the challenges of unbalanced exploration and exploitation, premature stagnation of iterations, and low convergence accuracy in high-dimensional complex applications. Aiming at these challenges, a hybrid BWO based on the jellyfish search optimizer (HBWO-JS), which combines the vertical crossover operator and Gaussian variation strategy with a fusion of jellyfish search (JS) optimizer, is developed for solving global optimization in this paper. First, the BWO algorithm is fused with the JS optimizer to improve the problem that BWO tends to fall into the best local solution and low convergence accuracy in the exploitation stage through multi-stage exploration and collaborative exploitation. Then, the introduced vertical cross operator solves the problem of unbalanced exploration and exploitation processes by normalizing the upper and lower bounds of two stochastic dimensions of the search agent, thus further improving the overall optimization capability. In addition, the introduced Gaussian variation strategy forces the agent to explore the minimum neighborhood, extending the entire iterative search process and thus alleviating the problem of premature stagnation of the algorithm. Finally, the superiority of the proposed HBWO-JS is verified in detail by comparing it with basic BWO and eight state-of-the-art algorithms on the CEC2019 and CEC2020 test suites, respectively. Also, the scalability of HBWO-JS is evaluated in three dimensions (10D, 30D, 50D), and the results show the stable performance of the proposed algorithm in terms of dimensional scalability. In addition, three practical engineering designs and two Truss topology optimization problems demonstrate the practicality of HBWO-JS. The optimization results show that HBWO-JS has a strong competitive ability and broad application prospects. [ABSTRACT FROM AUTHOR]

Breaching is frequently reported for many large cetacean species, but this behavior is considered very rare in fin whales (Balaenoptera physalus). Fin whales are regularly observed in the Mediterranean Sea, and they perform seasonal concentration/dispersal movements throughout this basin. This study aimed to investigate the influence that environmental parameters, social factors, and anthropogenic disturbance may have on breaching behavior in fin whales to deepen the understanding of these displays. Fin whale sightings were collected between 2012 and 2020 within the Fixed Line Transect Monitoring Network along the ferry route from Italy to Spain, crossing the mid‐latitudes of the western Mediterranean Sea. Breaching events were analyzed with respect to season, chlorophyll concentration, sea state, group size, fin whale frequency, distance between a breaching event and the closest whales, distance from the observation platform, and maritime traffic. During the study, breaching events were recorded 27 times over 721 fin whale sightings (3.74%), with a higher frequency during summer and fall (>4.96%) compared to spring (1.77%); no events were observed during winter. The most significant variables were distance from the observation platform as an inhibitory factor and distance between whales, possibly related to socialization and communication. [ABSTRACT FROM AUTHOR]

Simple Summary: When live whales strand, we need to choose our actions about whether the whale should be rescued, euthanized for animal welfare reasons, or left alone without any kind of interference whatsoever. This important choice is based on sparse information about its true health condition, since this is often either not available or difficult to assess. Based on the stranding of a live male killer whale in inner Danish Waters in 2021 and 2022, we discuss here these dilemmas and how to decide upon our action given these knowledge gaps, in order to predict the whale's chances of survival. The rescue attempts of stranded whales and euthanasia considerations must include condition assessments of the individual involved, but this is challenged by our insufficient knowledge about the health statuses of these whales. Here, we describe three separate strandings of a young male killer whale (Orcinus orca) in shallow Danish waters during 2021–2022. During the first two stranding events, the whale exhibited remarkable behavior and, after refloating attempts and several kilometers of swimming, it returned to shallow water. This suggests that it actively chose to be in this shallow water, perhaps to ensure free airways and respiration. During the last stranding, it stayed in shallow water for 30 days, during which, euthanasia was considered due to its seemingly worsened condition, including a collapsed dorsal fin. However, suddenly, the whale swam away and, a year later, he was seen alive, confirming that euthanasia would have been the wrong decision. This case raises an important question as to when and under what circumstances active human interventions, such as refloating attempts, should be launched and when euthanasia should be carried out. Every stranding is unique and decisions should be based on thorough considerations of the animal's health and the chance of a successful rescue. [ABSTRACT FROM AUTHOR]

Rorqual foraging behavior varies with species, prey type and foraging conditions, and can be a determining factor for their fitness. Little is known about the foraging ecology of Rice's whales (Balaenoptera ricei), an endangered species with a population of fewer than 100 individuals. Suction cup tags were attached to two Rice's whales to collect information on their diving kinematics and foraging behavior. The tagged whales primarily exhibited lunge-feeding near the sea bottom and to a lesser extent in the water-column and at the sea surface. During 6–10 min foraging dives, the whales typically circled their prey before executing one or two feeding lunges. Longer duration dives and dives with more feeding-lunges were followed by an increase in their breathing rate. The median lunge rate of one lunge per dive of both animals was much lower than expected based on comparative research on other lunge-feeding baleen whales, and may be associated with foraging on fish instead of krill or may be an indication of different foraging conditions. Both animals spent extended periods of the night near the sea surface, increasing the risk for ship strike. Furthermore, their circling before lunging may increase the risk for entanglement in bottom-longline fishing gear. Overall, these data show that Rice's whale foraging behavior differs from other lunge feeding rorqual species and may be a significant factor in shaping our understanding of their foraging ecology. Efforts to mitigate threats to Rice's whales will benefit from improved understanding of patterns in their habitat use and fine-scale ecology. [ABSTRACT FROM AUTHOR]

Península Valdés, Patagonia, Argentina, is recognized as a calving ground for the southern right whale (SRW, Eubalaena australis) population from the southwestern Atlantic Ocean. Previous studies have reported that SRWs feed during their calving season, but little is known about their foraging ecology in this area. Here, we collected photo data of SRWs at Península Valdés from 2007 to 2019 to monitor and investigate the SRW feeding frequency and to know whether calves also feed on zooplankton (i.e., the diet composed of both milk and solid food). In addition, we systematically reviewed studies on the composition and abundance of zooplankton to assess the available prey for SRWs in the area. Finally, we examined satellite-derived chlorophyll-a (chl-a) to study if the chl-a variability shows any relationship with SRW feeding. Observations show that at Península Valdés, SRWs feed at and below the surface, primarily on calanoid copepods. We also found evidence that SRWs feed near-bottom. In addition, we report calves feeding at surface including the first-ever photographs documentation. Whales feed mainly during austral spring, with a higher mean frequency in November. A time lag of 1 month was found between highest chl-a levels and the highest number of feeding events observed. Over the 12-year study period, we observed that whales were foraging yearly, which indicates that feeding in this calving area is more frequent than prior studies suggested. These data reveal the importance of the waters off Península Valdés as a multi-use habitat for SRW. [ABSTRACT FROM AUTHOR]

Interactions between killer whales (Orcinus orca (Linnaeus, 1758)) and long-finned pilot whales (Globicephala melas (Traill, 1809)) have been documented on numerous occasions, usually involving predation events and pursuits. Here, the first documented account of a long-finned pilot whale calf seen in echelon position with one killer whale in a group of three killer whales is described, along with one further interaction of the same killer whale group with other long-finned pilot whales. Behavioral, locational, and photographic data were recorded and analyzed for killer whales between 2011 and 2022 and for long-finned pilot whales between 2019 and 2022 off West Iceland. The data were used to obtain background information on the killer whale group involved in the apparent alloparental behavior. The described event also presents the first documented account of epimeletic behavior of a killer whale toward a non-conspecific. The movements of the same killer whale group in conjunction with other killer whales during a subsequent interaction with a group of long-finned pilot whales do not fit any previously observed behavioral patterns described for interactions between these species and may represent an active effort to obtain another long-finned pilot whale calf. Long-finned pilot whale and killer whale interactions might be more complex than previously thought and influenced by multiple drivers. [ABSTRACT FROM AUTHOR]

Monitoring the presence of blue whale (Balaenoptera musculus ssp.) stereotyped calls has been a widely used method to assess the different populations' distribution worldwide. All blue whale populations also produce nonstereotyped vocalizations, or D‐calls. Here, we monitored the presence of D‐calls in long‐term records from a large hydrophone array located in the open southern Indian Ocean, using an automated detection method and manual validation of the detections. D‐calls were detected at all sites of the array, which extends from 24°S to 56°S, but the majority of them were detected at the two southernmost sites. We observed a latitudinal shift in their seasonal occurrence, with more D‐calls in the north during austral autumn and winter and more in the south during austral spring. The geographical occurrence of D‐calls compared to that of songs indicates that blue whale acoustic behavior switches from a song‐intensive and sparse‐D‐call emission in the north to song‐moderate and more intensive D‐call emissions in the south. These findings support the hypothesis that both call types are used for different purposes, as D‐calls are mainly detected around foraging grounds and songs in wintering grounds. Monitoring both call types might therefore be a relevant acoustic indicator of blue whale behavior. [ABSTRACT FROM AUTHOR]

Long-term study of killer whales reveals that sons stay with their mothers for life, and although this benefits sons, it negatively impacts the mother's reproductive output. [ABSTRACT FROM AUTHOR]

Device-to-Device (D2D) communication plays a prominent role in mobile data offloading from the cellular infrastructure (e.g., base station). This paradigm empowers user equipment to communicate with each other directly, offering an efficient resort for data communication that eliminates the need for the base station. However, significant challenges, such as interference, resource allocation, and energy efficiency, impede the performance of D2D communication. In the context of resource allocation, most of the existing work primarily focuses on game and graph theoretical models, which raises the computational complexity as the number of D2D users increases. In this article, we formulated a sum rate maximization problem, which is solved using a combinatorial scheme comprised of Whale Optimization Algorithm (WOA) and Federated Learning (FL). First, we discover the optimal CUs-D2D Groups (D2DGs) pairs by utilizing the social behavior of whales in the WOA. Only these optimal links are permitted to participate in the FL-based resource allocation, ensuring a physical layer access control. Next, we generated a dataset from the WOA-based optimal CU-D2DG links, which is employed by the Convolutional Neural Network (CNN) model for decentralized learning. FL offers a proactive decision for resource assignment, i.e., whose CU resources will be used by the D2DG. The proposed scheme is evaluated by considering different performance parameters, such as convergence rate, statistical measure (accuracy, loss), fairness (0.72), and overall sum rate (≈ 25 Mbps). [ABSTRACT FROM AUTHOR]

Marine protected areas (MPAs) are a commonly used management tool to safeguard marine life from anthropogenic impacts, yet their efficacy often remains untested. Evaluating how highly dynamic marine species use static MPAs is challenging but becoming more feasible with the advancement of telemetry data. Here, we focus on southern right whales (Eubalaena australis , SRWs) in the waters off Aotearoa/New Zealand, which declined from 30,000 whales to fewer than 40 mature females due to whaling. Now numbering in the low thousands, the key socializing and nursery areas for this population in the remote subantarctic islands are under the protection of different types of MPAs. However, the effectiveness of these MPAs in encompassing important whale habitat and protecting the whales from vessel traffic has not been investigated. To address this, we analyzed telemetry data from 29 SRWs tagged at the Auckland Islands between 2009 and 2022. We identified two previously unknown and currently unprotected areas that were used by the whales for important behaviors such as foraging, socializing, or resting. Additionally, by combining whale locations and vessel tracking data (2020–2022) during peak breeding period (June to October), we found high spatiotemporal overlap between whales and vessels within several MPAs, suggesting the whales could still be vulnerable to multiple anthropogenic stressors even when within areas designated for protection. Our results identify areas to be prioritized for future monitoring and investigation to support the ongoing recovery of this SRW population, as well as highlight the overarching importance of assessing MPA effectiveness post-implementation, especially in a changing climate. • Marine protected areas (MPAs) are a commonly used conservation management tool. • Protection afforded by MPAs in New Zealand is assessed using remotely sensed data. • Current MPAs encompass only a small portion of southern right whale habitat. • High level of spatiotemporal overlap of whales and vessels exists inside MPAs. • Assessing MPA effectiveness for dynamic species post-implementation is important. [ABSTRACT FROM AUTHOR]

The article reports that yawn is a ubiquitous behavior marked by involuntary mouth opening with elongated inspiration, a peak in mouth gape followed by a slow expiration with simultaneous mouth closure. Topics include examines hypotheses regarding yawn behavior range from sleepiness, respiration and circulatory needs, boredom and arousal, empathy, and thermoregulation among others.

A noninvasive instrumental method of classification the behavior of the beluga whale (Delphinapterus leucas) based on the parameters of movement was evaluated. Motor activity was characterized by the mean and standard deviation of the beluga tail fluke acceleration. It was found that, using the "decision tree" algorithm, at least two types of beluga behaviors can be distinguished: resting at the surface and active swimming in the pool. The determination accuracy (depending on the parameter) was, on average, 81–97% for resting at the surface and 54–99% for active swimming behaviors. Differences between the accuracy of classification of resting at the surface based on three axis and overall body acceleration were minimal. In the future, the accuracy may be improved by using other acceleration parameters, shortening the interval of analysis, and optimizing the classification algorithms. [ABSTRACT FROM AUTHOR]

Large whales, including the endangered sei whale (Balaenoptera borealis), sperm whale (Physeter macrocephalus), and North Atlantic right whale (Eubalaena glacialis), are known to occur in the New York Bight. However, relatively little data exist on social behavior typical of these species in the area. The U.S. Mid-Atlantic has traditionally been considered a large whale migratory corridor with few surveys documenting social dynamics of whale presence in these waters. To better understand the occurrence, distribution, abundance, and behavior of these species for management and conservation planning, monthly line-transect aerial surveys were conducted over a 3-year period from March 2017 to February 2020. During these surveys, three noteworthy sociosexual behavior events were observed and photographed within groups of sei whales (April 2019), sperm whales (September 2019), and right whales (December 2019). Events included what could be either non-reproductive sexual behavior (sociosexual behavior) or sexual behavior (copulation) among conspecifics, including mirror pair swimming, lateral and vertical presenting, and belly to belly contact. During all three events, groups were highly active at the surface, frequently and quickly changing speed and direction, and animals were predominantly less than one body length apart from other conspecifics in the group. All species were recorded rolling onto their sides and/or back while at or near the surface. Open mouth display occurred in the North Atlantic right whale event. Though copulation is unlikely to have transpired during the sperm whale event and could not have occurred during the right whale event due to the identification of same-sex individuals, it cannot be ruled out as the impetus for the sei whale event. These observations begin to describe the relative importance of the New York Bight as more than a migratory corridor and suggest that additional behaviorally focused data collection be incorporated into future surveys. [ABSTRACT FROM AUTHOR]

Gray whales utilizing their foraging grounds off northeastern Sakhalin Island, Russia, have been increasingly exposed to anthropogenic activities related to oil and gas development over the past two decades. In 2015, four seismic vessels, contracted by two operators, conducted surveys near and within the gray whale feeding grounds. Mitigation and monitoring plans were developed prior to the survey and implemented in the field, with real-time data transfers to assist the implementation of measures aimed at minimizing impacts of acoustic exposure. This study examined the behavioral response of gray whales relative to vessel proximities and sounds generated during seismic exploration. Five shore-based teams monitored gray whale behavior from 1 June to 30 September using theodolite tracking and focal follow methodologies. Behavioral data were combined with acoustic and benthic information from studies conducted during the same period. A total of 1270 tracks (mean duration = 0.9 h) and 401 focal follows (1.1 h) were collected with gray whales exposed to sounds ranging from 59 to 172 dB re 1 μPa2 SPL. Mixed models were used to examine 13 movement and 10 respiration response variables relative to "natural," acoustic, and non-acoustic explanatory variables. Water depth and behavioral state were the largest predictors of gray whale movement and respiration patterns. As vessels approached whales with increasing seismic/vessel sound exposure levels and decreasing distances, several gray whale movement and respiration response variables significantly changed (increasing speed, directionality, surface time, respiration intervals, etc.). Although the mitigation measures employed could have reduced larger/long-term responses and sensitization to the seismic activities, this study illustrates that mitigation measures did not eliminate behavioral responses, at least in the short-term, of feeding gray whales to the activities. [ABSTRACT FROM AUTHOR]

Despite spending most time underwater, the technology in use to track whales over large geographic ranges via satellite has been largely limited to locational data, with most applications focusing on characterizing their horizontal movements. We describe the development of the RDW tag, a new Argos-based satellite telemetry device that incorporates sensors for monitoring the movements and dive behavior of large whales over several months without requiring recovery. Based on an implantable design, the tag features a saltwater conductivity switch, a tri-axial accelerometer, and an optional pressure transducer, along with onboard software for data processing and detection of behavioral events or activities of interest for transmission. We configured the software to detect dives and create per-dive summaries describing behavioral events associated with feeding activities in rorqual whales. We conducted a validation by proxy of the dive summary and event detection algorithms using field data from a medium-duration archival tag. We also conducted a simulation exercise to examine how the expected data recovery would vary under different dive behavior scenarios and compared those results to empirical values from field deployments of the RDW tag on blue (Balaenoptera musculus) and humpback (Megaptera novaeangliae) whales. The dive summary algorithm accurately reported dive depth and duration, while the accuracy of the lunge-feeding event detection algorithm was dependent on the precision of the accelerometer data that was used, with a predicted accuracy of 0.74 for correctly classifying feeding dives from 1/64-G precision data and 0.95 from 1-mG precision data. Simulated data recovery was lower with sparser transmission schedules, shorter mean dive durations, and lower rates of successfully received transmissions. Empirical data recovery was lower than expected from the simulation, suggesting the effect of additional factors, such as data gaps. By measuring key aspects of the per-dive behavior of large whales over multi-month timescales of movement, the RDW tags provide the ability to monitor previously unobservable behaviors across entire geographic ranges, extending the applications of satellite telemetry devices to new areas of whale physiology, behavior, ecology, and conservation. [ABSTRACT FROM AUTHOR]

The whale optimization algorithm (WOA) is a metaheuristic algorithm based on swarm intelligence and it mimics the hunting behavior of whales. It has the imperfection of premature convergence into local optima. In order to overcome this disadvantage, a multioperator WOA (MOWOA) is proposed. Four main strategies are introduced to the MOWOA to heighten the search capacity of WOA. The strategies include nonlinear adaptive parameter design, an exploration mechanism of honey badger, Cauchy factor strategy, and greedy strategy. This paper tests the versatility of MOWOA with three different types of benchmark functions, and a kind of seismic inversion problem are trialed run. From the experimental results, the performance of MOWOA outperforms the compared algorithms in global optimization. [ABSTRACT FROM AUTHOR]

Metaheuristics are proven solutions for complex optimization problems. Recently, bio-inspired metaheuristics have shown their capabilities for solving complex engineering problems. The Whale Optimization Algorithm is a popular metaheuristic, which is based on the hunting behavior of whale. For some problems, this algorithm suffers from local minima entrapment. To make WOA compatible with a number of challenging problems, two major modifications are proposed in this paper: the first one is opposition-based learning in the initialization phase, while the second is inculcation of Cauchy mutation operator in the position updating phase. The proposed variant is named the Augmented Whale Optimization Algorithm (AWOA) and tested over two benchmark suits, i.e., classical benchmark functions and the latest CEC-2017 benchmark functions for 10 dimension and 30 dimension problems. Various analyses, including convergence property analysis, boxplot analysis and Wilcoxon rank sum test analysis, show that the proposed variant possesses better exploration and exploitation capabilities. Along with this, the application of AWOA has been reported for three real-world problems of various disciplines. The results revealed that the proposed variant exhibits better optimization performance. [ABSTRACT FROM AUTHOR]

For many marine tetrapods, vision is important for finding food and navigating underwater, and eye size has increased to improve the capture of light in dim ocean depths. Odontocete whales, in contrast, rely instead on echolocation for navigation and prey capture. We tested whether the evolution of echolocation has influenced the orbit size, a proxy for eye size, and examined how orbit size evolved over time. We also assessed variation in orbit size amongst whales and tested how body size, diving ability, sound production, foraging habitat, and prey capture strategy influenced the orbit size using phylogenetic independent contrasts and phylogenetic ANOVAs. Using measurements of orbit length and bizygomatic width, we calculated proportional orbit size for 70 extant and 29 extinct whale taxa, with an emphasis on Odontoceti. We then performed ancestral character state reconstruction on a time‐calibrated composite phylogeny. Our analysis revealed that there was no shift in proportional orbit size from archaeocetes through stem odontocetes, indicating that the evolution of echolocation did not influence the orbit size. Proportional orbit size increased in Ziphiidae, Phocoenidae, and Cephalorhynchus. Proportional orbit size decreased in Balaenidae, Physeteridae, Platanistidae, and Lipotidae. Body size, diving ability, foraging environment, and prey capture strategy had a significant influence on orbit size, but only without phylogenetic correction. An increase in orbit size is associated with deep diving behavior in beaked whales, while progenesis and retention of juvenile features into adulthood explain the pattern observed in Phocoenidae and Cephalorhynchus. Decrease in proportional orbit size is associated with adaptation toward murky freshwater environments in odontocetes and skim feeding in balaenids. Our study reveals that the evolution of echolocation had little effect on orbit size, which is variable in whales, and that adaptation for different feeding modes and habitat explains some of this variance. [ABSTRACT FROM AUTHOR]

Whale optimization algorithm (WOA) is a new meta-heuristic algorithm for mathematical description of the foraging behavior of whales. Cloud model (CM) is an effective model to describe cognitive uncertainty, at the same time, it can comprehensively describe the randomness and fuzziness in uncertain phenomena. Skew normal distribution (SND) can better describe the biological behavior situation when the environment changes. In this paper, a new skew normal cloud model (SNCM) is established in the first place by combining the CM with the SND and the skew normal membership function to describe the fuzziness and randomness of environmental change. Secondly,because of the randomness and fuzziness of the whales' foraging behavior, in order to improve the exploration and exploitation ability of WOA,an emendatory WOA based on the skew normal cloud (SNC) is proposed through the use of the SNCM to modify the shrinking encircling and spiral update strategies of WOA, and the adaptive position and skewness parameters in the SNC are designed to increase the exploration capability in prophase and the exploitation capability in anaphase. Lastly,the experimental results of the complex CEC2017 test set verify the effectiveness of the emendatory WOA under different strategies and different dimensions and different improved WOA algorithm and other representative heuristic algorithms. Three degree reduction of S − λ curves verify the practicability of the the modified WOA in the field of curve design. [ABSTRACT FROM AUTHOR]

Whale sharks are known to feed primarily on zooplankton all over the world; however, recent findings suggest that they also prey on fish using behaviors that have not been fully described. Here, we provide detailed evidence of whale sharks interacting with schools of anchovy on four occasions in Bahia de Los Angeles, Baja California, Mexico. Three of these were predatory interactions in multi-species feeding frenzies, and one was a non-predatory interaction. In predatory interactions, whale sharks exhibited two types of feeding behaviors: (1) stationary suction-feeding, a previously described behavior for whale sharks, and (2) lunge-feeding, which has not been previously described in whale sharks, but has been observed among other large filter feeders, such as rorqual whales. The whale sharks moved simultaneously around the school of anchovy, lunging simultaneously or one after another into the school, with 66% (N = 17) of these lunges occurring in the same direction. In the non-predatory interaction, whale sharks exhibited "sit-and-wait" behavior. The evidence presented here, along with previous observations, suggests that whale sharks may change their feeding strategy from suction to lunge-feeding when other predators corner schooling fish. [ABSTRACT FROM AUTHOR]

Artificial neural network (ANN) is modeled to predict and classify problems. However, in the training phase of ANNs discovering faultless values of the weights of a network is extremely troublesome. Traditional weight updating methods often get stuck into local optima and converge to optimal solutions very slowly. Therefore, to overcome these drawbacks a modified version of a nature-based algorithm which merges meta-heuristics with weight-updating technique of ANN has been used in this paper. Whale optimization algorithm (WOA) is a well-established, efficient and competitive algorithm inspired by the hunting mechanism of the whales including their behavior in finding and attacking their prey with their bubble-net feeding technique. In WOA, the next location of the search individuals or whales is modified depending on some probability. Due to the high exploration rate of WOA, there is a disproportion between exploration and exploitation in the WOA and it also converges to the solution slowly. Thus, to establish an equilibrium between exploration and exploitation a new variant of WOA called modified whale optimization algorithm (MWOA) is proposed to overcome the problem of delayed convergence. In MWOA, roulette wheel selection is combined with WOA to enhance the convergence speed of WOA. MWOA is tested on 11 benchmark functions, and the outcomes are compared with WOA. The results prove that MWOA has gained success in overcoming the problem of the slow convergence of WOA. Also, the results show that the proposed MWOA technique, when applied to ANN, can overcome the problems of traditional techniques and has improved the results. [ABSTRACT FROM AUTHOR]

This paper intends to propose a power quality design model for the distributed system through nonlinear functions, and hence the prerequisite of power quality enhancements can be precisely quantified. As the model is adaptable, it needs a robust optimization algorithm for estimating the optimal location and compensation of the D-STATCOM. Hence, this paper develops a hybrid meta-heuristic optimization algorithm based on the prey targeting behavior of whales. The proposed hybrid whale optimization, Whale with Grey Wolf Optimization (WG), is used for determining the optimal placing and sizing of D-STATCOM by solving the power quality model. The solutions will be reactive power-encoded with two bound constraints to address both the localizing and sizing problems. Besides, along with the renowned literature, we determine the Mean Voltage Stability Index. The updating algorithm of the whale optimization will be hybridized with the hunting behavior of grey wolves so that the location and sizing of D-STATCOM can be estimated precisely. The proposed WG algorithm compares its performance over other conventional methods such as GA, ABC, PSO, GWO, and WOA in terms of convergence analysis, cost analysis, and total loss and determines the effectiveness of the proposed power quality model. [ABSTRACT FROM AUTHOR]

False killer whales (Pseudorca crassidens) depredate bait and catch in the Hawai'i‐based deep‐set longline fishery, and as a result, this species is hooked or entangled more than any other cetacean in this fishery. We analyzed data collected by fisheries observers and from satellite‐linked transmitters deployed on false killer whales to identify patterns of odontocete depredation that could help fishermen avoid overlap with whales. Odontocete depredation was observed on ˜6% of deep‐set hauls across the fleet from 2004 to 2018. Model outcomes from binomial GAMMs suggested coarse patterns, for example, higher rates of depredation in winter, at lower latitudes, and with higher fishing effort. However, explanatory power was low, and no covariates were identified that could be used in a predictive context. The best indicator of depredation was the occurrence of depredation on a previous set of the same vessel. We identified spatiotemporal scales of this repeat depredation to provide guidance to fishermen on how far to move or how long to wait to reduce the probability of repeated interactions. The risk of depredation decreased with both space and time from a previous occurrence, with the greatest benefits achieved by moving ˜400 km or waiting ˜9 d, which reduced the occurrence of depredation from 18% to 9% (a 50% reduction). Fishermen moved a median 46 km and waited 4.7 h following an observed depredation interaction, which our analysis suggests is unlikely to lead to large reductions in risk. Satellite‐tagged pelagic false killer whales moved up to 75 km in 4 h and 335 km in 24 h, suggesting that they can likely keep pace with longline vessels for at least four hours and likely longer. We recommend fishermen avoid areas of known depredation or bycatch by moving as far and as quickly as practical, especially within a day or two of the depredation or bycatch event. We also encourage captains to communicate depredation and bycatch occurrence to enable other vessels to similarly avoid high‐risk areas. [ABSTRACT FROM AUTHOR]

Understanding unexposed/baseline behavior of marine mammals is required to assess the effects of increasing levels of anthropogenic noise exposure in the marine environment. However, quantifying variation in the baseline behavior of whales is challenging due to the fact that they spend much of their time at depth, and therefore, their diving behavior is not directly observable. Data collection employs tags as measurement devices to record vertical movement. We focus here on satellite tags, which have the advantage of collection over a time window of weeks. The type of data we analyze here suffers the disadvantage of being in the form of depths attached to an arbitrarily created set of depth bins and being sparse in time. We provide a multi-stage generative model for deep dives using a continuous-time discrete-space Markov chain. Then, we build a likelihood, incorporating dive-specific random effects, in order to fit this model to a set of satellite tag records, each consisting of a temporally misaligned collection of deep dives with sparse binned depths for each dive. Through simulation, we demonstrate the ability to recover true model parameters. With real satellite tag records, we validate the model out of sample and also provide inference regarding stage behavior, inter-tag record behavior, dive duration, and maximum dive depth. Supplementary materials accompanying this paper appear online. [ABSTRACT FROM AUTHOR]

Orcas (Orcinus orca) are a charismatic species with multiple connections to local economies and culture in the Pacific Northwest. As such, emotions play a role in public perspectives and support for their conservation. This research presents the use of Natural Language Processing (NLP) emotion analysis to identify the basic emotions associated with written public responses to orca conservation proposals. We operationalized a multi‐dimensional emotion lexicon using Python 3 programing to extract the frequency and density of each basic emotion in over 17,000 public comments specific to orca conservation submitted to the Washington state governor's office. We found that respondents held a mixture of emotions. Trust was most often associated with the belief that urgent actions by state government could help orca populations, joy was most associated with statements reflecting how healthy orcas are icons for healthy ecosystems upon which all depend, and sadness was associated with statements lamenting the death of individual orcas and population extinction. These results can help conservation managers understand why people might support or reject conservation actions and move past conservation social science that has prioritized the emotional domain of fear. Moreover, NLP provides descriptive emotion analyses of big text datasets within specific conservation contexts that can be further explored through qualitative analyses. [ABSTRACT FROM AUTHOR]

Clustering, which is handled by many researchers, is separating data into clusters without supervision. In clustering, the data are grouped using similarities or differences between them. Many traditional and heuristic algorithms are used in clustering problems and new techniques continue to be developed today. In this study, a new and effective clustering algorithm was developed by using the Whale Optimization Algorithm (WOA) and Levy flight (LF) strategy that imitates the hunting behavior of whales. With the developed WOA-LF algorithm, clustering was performed using ten medical datasets taken from the UCI Machine Learning Repository database. The clustering performance of the WOA-LF was compared with the performance of k-means, k-medoids, fuzzy c-means and the original WOA clustering algorithms. Application results showed that WOA-LF has more successful clustering performance in general and can be used as an alternative algorithm in clustering problems. [ABSTRACT FROM AUTHOR]

The Equilibrium Optimizer (EO), Grey Wolf Optimizer (GWO), and Whale Optimizer (WO) algorithms are being recently developed for engineering optimization problems. In this paper, the EO, GWO, and WO algorithms are applied individually for a brushless direct current (BLDC) design optimization problem. The EO algorithm is inspired by the models utilized to find the system's dynamic state and equilibrium state. The GWO and WO algorithms are inspired by the hunting behavior of the wolf and the whale respectively. The primary purpose of any optimization technique is to find the optimal configuration by maximizing motor efficiency and/or minimizing the total mass. Therefore, two objective functions are being used to achieve these objectives. The first refers to a design with high power output and efficiency The second is a constraint imposed by the reality that the motor is built into the wheel of the vehicle and, therefore, a lightweight is needed. The EO,GWO, and WOA algorithms are then utilized to optimize the BLDC motor's design variables to minimize the motor's total mass or maximize the motor efficiency by simultaneously satisfying the six inequality constraints. The simulation is carried out using MATLAB simulation software, and the simulation results prove the dominance of the proposed algorithms. This paper also suggests an efficient method from the proposed three methods for the BLDC motor design optimization problem. [ABSTRACT FROM AUTHOR]