Integrative Approaches to the Study of Baleen Whale Diving Behavior, Feeding Performance, and Foraging Ecology

Morphology and Mechanics of the Fin Whale Esophagus: The Key to Fast Processing of Large Food Volumes by Rorquals

Lunge feeding rorqual whales feed by engulfing a volume of prey laden water that can be as large as their own body. Multiple feeding lunges occur during a single foraging dive and the time between each lunge can be as short as 30 s (Goldbogen et al. 2013). During this short inter-lunge time, water is filtered out through baleen to concentrate prey in the oral cavity, and then the prey is swallowed prior to initiating the next lunge. Prey density in the ocean varies greatly, and despite the potential of swallowing a massive volume of concentrated prey as a slurry, the esophagus of rorqual whales has been anecdotally described as unexpectedly narrow with a limited capacity to expand. How rorquals swallow large quantities of food down a narrow esophagus during a limited inter-lunge time remains unknown. Here, we show that the small diameter muscular esophagus in the fin whale is optimized to transport a slurry of food to the stomach. A thick wall of striated muscle occurs at the pharyngeal end of the esophagus which, together with the muscular wall of the pharynx, may generate a pressure head for transporting the food down the esophagus to the stomach as a continuous stream rather than separating the food into individual boluses swallowed separately. This simple model is consistent with estimates of prey density and stomach capacity. Rorquals may be the only animals that capture a volume of food too large to swallow as a single intact bolus without oral processing, so the adaptations of the esophagus are imperative for transporting these large volumes of concentrated food to the stomach during a time-limited dive involving multiple lunges.

Diagnosis of Covid-19 from CT slices using Whale Optimization Algorithm, Support Vector Machine and Multi-Layer Perceptron

BACKGROUND

The coronavirus disease 2019 is a serious and highly contagious disease caused by infection with a newly discovered virus, named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).

OBJECTIVE

A Computer Aided Diagnosis (CAD) system to assist physicians to diagnose Covid-19 from chest Computed Tomography (CT) slices is modelled and experimented.

METHODS

The lung tissues are segmented using Otsu's thresholding method. The Covid-19 lesions have been annotated as the Regions of Interest (ROIs), which is followed by texture and shape extraction. The obtained features are stored as feature vectors and split into 80:20 train and test sets. To choose the optimal features, Whale Optimization Algorithm (WOA) with Support Vector Machine (SVM) classifier's accuracy is employed. A Multi-Layer Perceptron (MLP) classifier is trained to perform classification with the selected features.

RESULTS

Comparative experimentations of the proposed system with existing eight benchmark Machine Learning classifiers using real-time dataset demonstrates that the proposed system with 88.94% accuracy outperforms the benchmark classifier's results. Statistical analysis namely, Friedman test, Mann Whitney U test and Kendall's Rank Correlation Coefficient Test has been performed which indicates that the proposed method has a significant impact on the novel dataset considered.

CONCLUSION

The MLP classifier's accuracy without feature selection yielded 80.40%, whereas with feature selection using WOA, it yielded 88.94%.

Evaluating short- to medium-term effects of implantable satellite tags on southern right whales Eubalaena australis

Improving our understanding of the effects of satellite tags on large whales is a critical step in ongoing tag development to minimise potential health effects whilst addressing important research questions that enhance conservation management policy. In 2014, satellite tags were deployed on 9 female southern right whales Eubalaena australis accompanied by a calf off Australia. Photo-identification resights (n = 48) of 4 photo-identified individuals were recorded 1 to 2894 d (1-8 yr) post-tagging. Short-term (<22 d) effects observed included localised and regional swelling, depression at the tag site, blubber extrusion, skin loss and pigmentation colour change. Broad swelling observable from lateral but not aerial imagery (~1.2 m diameter or ~9% of body length) and depression at the tag site persisted up to 1446 d post-tagging for 1 individual, indicating a persistent foreign-body response or infection. Two tagged individuals returned 4 yr post-tagging in 2018 with a calf, and the medium-term effects were evaluated by comparing body condition of tagged whales with non-tagged whales. These females calved in a typical 4 yr interval, suggesting no apparent immediate impact of tagging on reproduction for these individuals, but longer-term monitoring is needed. There was no observable difference in the body condition between the 2 tagged and non-tagged females. Ongoing monitoring post-tagging is required to build on the sample size and statistical power. We demonstrate the value of long-term monitoring programmes and a collaborative approach for evaluating effects from satellite-tagging cetaceans to support species management.

Cetacean tongue mobility and function: A comparative review

Cetaceans are atypical mammals whose tongues often depart from the typical (basal) mammalian condition in structure, mobility, and function. Their tongues are dynamic, innovative multipurpose tools that include the world's largest muscular structures. These changes reflect the evolutionary history of cetaceans' secondary adaptation to a fully aquatic environment. Cetacean tongues play no role in mastication and apparently a greatly reduced role in nursing (mainly channeling milk ingestion), two hallmarks of Mammalia. Cetacean tongues are not involved in drinking, breathing, vocalizing, and other non-feeding activities; they evidently play no or little role in taste reception. Although cetaceans do not masticate or otherwise process food, their tongues retain key roles in food ingestion, transport, securing/positioning, and swallowing, though by different means than most mammals. This is due to cetaceans' aquatic habitat, which in turn altered their anatomy (e.g., the intranarial larynx and consequent soft palate alteration). Odontocetes ingest prey via raptorial biting or tongue-generated suction. Odontocete tongues expel water and possibly uncover benthic prey via hydraulic jetting. Mysticete tongues play crucial roles driving ram, suction, or lunge ingestion for filter feeding. The uniquely flaccid rorqual tongue, not a constant volume hydrostat (as in all other mammalian tongues), invaginates into a balloon-like pouch to temporarily hold engulfed water. Mysticete tongues also create hydrodynamic flow regimes and hydraulic forces for baleen filtration, and possibly for cleaning baleen. Cetacean tongues lost or modified much of the mobility and function of generic mammal tongues, but took on noteworthy morphological changes by evolving to accomplish new tasks.

Assessment of coal supply chain under carbon trade policy by extended exergy accounting method

Within an uncertain environment and following carbon trade policies, this study uses the Extended Exergy Accounting (EEA) method for coal supply chains (SCs) in eight of the world's most significant coal consuming countries. The purpose is to improve the sustainability of coal SCs in terms of Joules rather than money while considering economic, environmental, and social aspects. This model is a multi-product economic production quantity (EPQ) with a single-vendor multi-buyer with shortage as a backorder. Within the SC, there are some real constraints, such as inventory turnover ratio, waste disposal to the environment, carbon dioxide emissions, and available budgets for customers. For optimization purposes, three recent metaheuristic algorithms, including Ant Lion Optimizer, Lion Optimization Algorithm, and Whale Optimization Algorithm, are suggested to determine a near-optimum solution to an "exergy fuzzy nonlinear integer-programming (EFNIP)." Moreover, an exact method (GAMS) is employed to validate the results of the suggested algorithms. Additionally, sensitivity analyses with different percentages of exergy parameters, such as capital, labor, and environmental remediation, are done to gain a deeper understanding of sustainability improvement in coal SCs. The results showed that sustainable coal SC in the USA has the lowest fuzzy total exergy, while Poland and China have the highest.

Critically endangered Rice's whales (Balaenoptera ricei) selectively feed on high-quality prey in the Gulf of Mexico

Determining the drivers of prey selection in marine predators is critical when investigating ecosystem structure and function. The newly recognized Rice's whale (Balaenoptera ricei) is one of the most critically endangered large whales in the world and endemic to the industrialized Gulf of Mexico. Here, we investigated the drivers of resource selection by Rice's whales in relation to prey availability and energy density. Bayesian stable isotope (δ¹³C, δ¹⁵N) mixing models suggest that Rice's whales feed primarily on a schooling fish, Ariomma bondi (66.8% relative contribution). Prey selection using the Chesson's index revealed that active prey selection was found to be positive for three out of the four potential prey identified in the mixing model. A low degree of overlap between prey availability and diet inferred from the mixing model (Pianka Index: 0.333) suggests that prey abundance is not the primary driver of prey selection. Energy density data suggest that prey selection may be primarily driven by the energy content. Results from this study indicate that Rice's whales are selective predators consuming schooling prey with the highest energy content. Environmental changes in the region have the potential to influence prey species that would make them less available to Rice's whales.

Integrating technologies provides insight into the subsurface foraging behaviour of a humpback whale (Megaptera novaeangliae) feeding on walleye pollock (Gadus chalcogrammus) in Juan de Fuca Strait, Canada

Subsurface foraging is an important proportion of the activity budget of rorqual whales, yet information on their behaviour underwater remains challenging to obtain. Rorquals are assumed to feed throughout the water column and to select prey as a function of depth, availability and density, but there remain limitations in the precise identification of targeted prey. Current data on rorqual foraging in western Canadian waters have thus been limited to observations of prey species amenable to surface feeding, such as euphausiids and Pacific herring (Clupea pallasii), with no information on deeper alternative prey sources. We measured the foraging behaviour of a humpback whale (Megaptera novaeangliae) in Juan de Fuca Strait, British Columbia, using three complimentary methods: whale-borne tag data, acoustic prey mapping, and fecal sub-sampling. Acoustically detected prey layers were near the seafloor and consistent with dense schools of walleye pollock (Gadus chalcogrammus) distributed above more diffuse aggregations of pollock. Analysis of a fecal sample from the tagged whale confirmed that it had been feeding on pollock. Integrating the dive profile with the prey data revealed that the whale's foraging effort followed the general pattern of areal prey density, wherein the whale had a higher lunge-feeding rate at the highest prey abundance and stopped feeding when prey became limited. Our findings of a humpback whale feeding on seasonally energy-dense fish like walleye pollock, which are potentially abundant in British Columbia, suggests that pollock may be an important prey source for this rapidly growing whale population. This result is informative when assessing regional fishing activities for semi-pelagic species as well as the whales' vulnerability to fishing gear entanglements and feeding disturbances during a narrow window of prey acquisition.

Evolutionary assembly and disassembly of the mammalian sternum

Evolutionary transitions are frequently associated with novel anatomical structures,¹ but the origins of the structures themselves are often poorly known. We use developmental, genetic, and paleontological data to demonstrate that the therian sternum was assembled from pre-existing elements. Imaging of the perinatal mouse reveals two paired sternal elements, both composed primarily of cells with lateral plate mesoderm origin. Location, articulations, and development identify them as homologs of the interclavicle and the sternal bands of synapsid outgroups. The interclavicle, not previously recognized in therians,² articulates with the clavicle and differs from the sternal bands in both embryonic HOX expression and pattern of skeletal maturation. The sternal bands articulate with the ribs in two styles, most clearly differentiated by their association with sternebrae. Evolutionary trait mapping indicates that the interclavicle and sternal bands were independent elements throughout most of synapsid history. The differentiation of rib articulation styles and the subdivision of the sternal bands into sternebrae were key innovations likely associated with transitions in locomotor and respiratory mechanics.^3,4 Fusion of the interclavicle and the anterior sternal bands to form a presternum anterior to the first sternebra was a historically recent innovation unique to therians. Subsequent disassembly of the radically reduced sternum of mysticete cetaceans was element specific, reflecting the constraints that conserved developmental programs exert on composite structures.

Improved Whale Optimization Algorithm for Transient Response, Robustness, and Stability Enhancement of an Automatic Voltage Regulator System

The proportional integral derivative (PID) controller is one of the most robust and simplest configuration controllers used for industrial applications. However, its performance purely depends on the tuning of its proportional (KP), integral (KI) and derivative (KD) gains. Therefore, a proper combination of these gains is primarily required to achieve an optimal performance of the PID controllers. The conventional methods of PID tuning such as Cohen-Coon (CC) and Ziegler–Nichols (ZN) generate unwanted overshoots and long-lasting oscillations in the system. Owing to the mentioned problems, this paper attempts to achieve an optimized combination of PID controller gains by exploiting the intelligence of the whale optimization algorithm (WOA) and one of its recently introduced modified versions called improved whale optimization algorithm (IWOA) in an automatic voltage regulator (AVR) system. The stability of the IWOA-AVR system was studied by assessing its root-locus, bode maps, and pole/zero plots. The performance superiority of the presented IWOA-AVR design over eight of the recently explored AI-based approaches was validated through a comprehensive comparative analysis based on the most important transient response and stability metrics. Finally, to assess the robustness of the optimized AVR system, robustness analysis was conducted by analyzing the system response during the variation in the time constants of the generator, exciter, and amplifier from −50% to 50% range. The results of the study prove the superiority of the proposed IWOA-based AVR system in terms of transient response and stability metrics.

Acoustic signalling and behaviour of Antarctic minke whales (Balaenoptera bonaerensis)

Acoustic signalling is the predominant form of communication among cetaceans. Understanding the behavioural state of calling individuals can provide insights into the specific function of sound production; in turn, this information can aid the evaluation of passive monitoring datasets to estimate species presence, density, and behaviour. Antarctic minke whales are the most numerous baleen whale species in the Southern Ocean. However, our knowledge of their vocal behaviour is limited. Using, to our knowledge, the first animal-borne audio-video documentation of underwater behaviour in this species, we characterize Antarctic minke whale sound production and evaluate the association between acoustic behaviour, foraging behaviour, diel patterns and the presence of close conspecifics. In addition to the previously described downsweep call, we find evidence of three novel calls not previously described in their vocal repertoire. Overall, these signals displayed peak frequencies between 90 and 175 Hz and ranged from 0.2 to 0.8 s on average (90% duration). Additionally, each of the four call types was associated with measured behavioural and environmental parameters. Our results represent a significant advancement in understanding of the life history of this species and improve our capacity to acoustically monitor minke whales in a rapidly changing Antarctic region.

Metaheuristic algorithms for PID controller parameters tuning: review, approaches and open problems

The simplicity, transparency, reliability, high efficiency and robust nature of PID controllers are some of the reasons for their high popularity and acceptance for control in process industries around the world today. Tuning of PID control parameters has been a field of active research and still is. The primary objectives of PID control parameters are to achieve minimal overshoot in steady state response and lesser settling time. With exception of two popular conventional tuning strategies (Ziegler Nichols closed loop oscillation and Cohen-Coon's process reaction curve) several other methods have been employed for tuning. This work accords a thorough review of state-of-the-art and classical strategies for PID controller parameters tuning using metaheuristic algorithms. Methods appraised are categorized into classical and metaheuristic optimization methods for PID parameters tuning purposes. Details of some metaheuristic algorithms, methods of application, equations and implementation flowcharts/algorithms are presented. Some open problems for future research are also presented. The major goal of this work is to proffer a comprehensive reference source for researchers and scholars working on PID controllers.

Novel hybrid informational model for predicting the creep and shrinkage deflection of reinforced concrete beams containing GGBFS

This study investigates a Novel Hybrid Informational model for the prediction of creep and shrinkage deflection of reinforced concrete (RC) beams containing different percentages of ground granulated blast furnace slag (GGBFS) at different ages, varying from 1 to 150 days. The percentage of cement replacement by GGBFS varies from 20 to 60%. In order to examine the effects of the applied load and tensile reinforcement on creep behavior, the magnitude of two-point loading was varied from 200 kg to a maximum of 350 kg while the percentage of tensile reinforcement (ρ) was selected as either 0.77% or 1.2%. The current situation about short-term and long-term deflections due to creep and shrinkage available in the international standards, including ACI, BS and Eurocode 2, is discussed. The results indicate that RC beams containing GGBFS have larger deflections than the ones with conventional concrete (i.e., ordinary Portland cement concrete). After 150 days, the average creep deflection of RC beams containing 20, 40, and 60% GGBFS was 30, 70, and 100% higher than the ones for conventional concrete beams, respectively. A hybrid artificial neural network coupled with a metaheuristic Whale optimization algorithm has been developed to estimate the overall deflection of concrete beams due to creep and shrinkage. Several statistical metrics, including the root mean square error and the coefficient of variation, revealed that the generalized model achieved the most reliable and accurate prediction of the concrete beam’s deflection in comparison with international standards and other models. This novel informational model can simplify the design processes in computational intelligence structural design platforms in future.

Seasonal Trends and Diel Patterns of Downsweep and SEP Calls in Chilean Blue Whales

To learn more about the occurrence and behaviour of a recently discovered population of blue whales, passive acoustic data were collected between January 2012 and April 2013 in the Chiloense ecoregion of southern Chile. Automatic detectors and manual auditing were used to detect blue whale songs (SEP calls) and D calls, which were then analysed to gain insights into temporal calling patterns. We found that D call rates were extremely low during winter (June–August) but gradually increased in spring and summer, decreasing again later during fall. SEP calls were absent for most winter and spring months (July–November) but increased in summer and fall, peaking between March and April. Thus, our results support previous studies documenting the austral summer residency of blue whales in this region, while suggesting that some individuals stay longer, highlighting the importance of this area as a blue whale habitat. We also investigated the daily occurrence of each call type and found that D calls occurred more frequently during dusk and night hours compared to dawn and day periods, whereas SEP calls did not show any significant diel patterns. Overall, these findings help to understand the occurrence and behaviour of endangered Chilean blue whales, enhancing our ability to develop conservation strategies in this important Southern Hemisphere habitat.

Baleen whale prey consumption based on high-resolution foraging measurements

Baleen whales influence their ecosystems through immense prey consumption and nutrient recycling^1-3. It is difficult to accurately gauge the magnitude of their current or historic ecosystem role without measuring feeding rates and prey consumed. To date, prey consumption of the largest species has been estimated using metabolic models^3-9 based on extrapolations that lack empirical validation. Here, we used tags deployed on seven baleen whale (Mysticeti) species (n = 321 tag deployments) in conjunction with acoustic measurements of prey density to calculate prey consumption at daily to annual scales from the Atlantic, Pacific, and Southern Oceans. Our results suggest that previous studies^3-9 have underestimated baleen whale prey consumption by threefold or more in some ecosystems. In the Southern Ocean alone, we calculate that pre-whaling populations of mysticetes annually consumed 430 million tonnes of Antarctic krill (Euphausia superba), twice the current estimated total biomass of E. superba¹⁰, and more than twice the global catch of marine fisheries today¹¹. Larger whale populations may have supported higher productivity in large marine regions through enhanced nutrient recycling: our findings suggest mysticetes recycled 1.2 × 10⁴ tonnes iron yr^-1 in the Southern Ocean before whaling compared to 1.2 × 10³ tonnes iron yr^-1 recycled by whales today. The recovery of baleen whales and their nutrient recycling services^2,3,7 could augment productivity and restore ecosystem function lost during 20th century whaling^12,13.

A Consolidated Review of Path Planning and Optimization Techniques: Technical Perspectives and Future Directions

In this paper, a review on the three most important communication techniques (ground, aerial, and underwater vehicles) has been presented that throws light on trajectory planning, its optimization, and various issues in a summarized way. This kind of extensive research is not often seen in the literature, so an effort has been made for readers interested in path planning to fill the gap. Moreover, optimization techniques suitable for implementing ground, aerial, and underwater vehicles are also a part of this review. This paper covers the numerical, bio-inspired techniques and their hybridization with each other for each of the dimensions mentioned. The paper provides a consolidated platform, where plenty of available research on-ground autonomous vehicle and their trajectory optimization with the extension for aerial and underwater vehicles are documented.

The Rapid Rise of Next-Generation Natural History

Many ecologists have lamented the demise of natural history and have attributed this decline to a misguided view that natural history is outdated and unscientific. Although there is a perception that the focus in ecology and conservation have shifted away from descriptive natural history research and training toward hypothetico-deductive research, we argue that natural history has entered a new phase that we call “next-generation natural history.” This renaissance of natural history is characterized by technological and statistical advances that aid in collecting detailed observations systematically over broad spatial and temporal extents. The technological advances that have increased exponentially in the last decade include electronic sensors such as camera-traps and acoustic recorders, aircraft- and satellite-based remote sensing, animal-borne biologgers, genetics and genomics methods, and community science programs. Advances in statistics and computation have aided in analyzing a growing quantity of observations to reveal patterns in nature. These robust next-generation natural history datasets have transformed the anecdotal perception of natural history observations into systematically collected observations that collectively constitute the foundation for hypothetico-deductive research and can be leveraged and applied to conservation and management. These advances are encouraging scientists to conduct and embrace detailed descriptions of nature that remain a critically important component of the scientific endeavor. Finally, these next-generation natural history observations are engaging scientists and non-scientists alike with new documentations of the wonders of nature. Thus, we celebrate next-generation natural history for encouraging people to experience nature directly.

Drivers and constraints on offshore foraging in harbour seals

Central place foragers are expected to offset travel costs between a central place and foraging areas by targeting productive feeding zones. Harbour seals (Phoca vitulina) make multi-day foraging trips away from coastal haul-out sites presumably to target rich food resources, but periodic track points from telemetry tags may be insufficient to infer reliably where, and how often, foraging takes place. To study foraging behaviour during offshore trips, and assess what factors limit trip duration, we equipped harbour seals in the German Wadden Sea with high-resolution multi-sensor bio-logging tags, recording 12 offshore trips from 8 seals. Using acceleration transients as a proxy for prey capture attempts, we found that foraging rates during travel to and from offshore sites were comparable to offshore rates. Offshore foraging trips may, therefore, reflect avoidance of intra-specific competition rather than presence of offshore foraging hotspots. Time spent resting increased by approx. 37 min/day during trips suggesting that a resting deficit rather than patch depletion may influence trip length. Foraging rates were only weakly correlated with surface movement patterns highlighting the value of integrating multi-sensor data from on-animal bio-logging tags (GPS, depth, accelerometers and magnetometers) to infer behaviour and habitat use.

Distribution of rorquals and Atlantic cod in relation to their prey in the Norwegian high Arctic

Recent warming in the Barents Sea has led to changes in the spatial distribution of both zooplankton and fish, with boreal communities expanding northwards. A similar northward expansion has been observed in several rorqual species that migrate into northern waters to take advantage of high summer productivity, hence feeding opportunities. Based on ecosystem surveys conducted during August–September in 2014–2017, we investigated the spatial associations among the three rorqual species of blue, fin, and common minke whales, the predatory fish Atlantic cod, and their main prey groups (zooplankton, 0-group fish, Atlantic cod, and capelin) in Arctic Ocean waters to the west and north of Svalbard. During the surveys, whale sightings were recorded by dedicated whale observers on the bridge of the vessel, whereas the distribution and abundance of cod and prey species were assessed using trawling and acoustic methods. Based on existing knowledge on the dive habits of these rorquals, we divided our analyses into two depth regions: the upper 200 m of the water column and waters below 200 m. Since humpback whales were absent in the area in 2016 and 2017, they were not included in the subsequent analyses of spatial association. No association or spatial overlap between fin and blue whales and any of the prey species investigated was found, while associations and overlaps were found between minke whales and zooplankton/0-group fish in the upper 200 m and between minke whales and Atlantic cod at depths below 200 m. A prey detection range of more than 10 km was suggested for minke whales in the upper water layers.

New optimization methods for designing rain stations network using new neural network, election, and whale optimization algorithms by combining the Kriging method

In many studies of water and hydrological sources, estimation of the spatial distribution of precipitation based on point data recorded in rain gauge stations is of particular importance. The purpose of this paper is to optimize the network of rain gauge stations in the Sistan and Baluchestan Province with respect to the variance of Kriging and topography estimation in the region and to maintain or reduce the number of stations in the region (without incurring additional costs). A new neural network algorithm has been presented in the present study to determine the optimum rain gauge stations. In this study, a new method of meta-heuristic optimization algorithm based on biological neural systems and artificial neural networks (ANNs) has been proposed. The proposed method is called a neural network algorithm (NNA) and has been developed based on unique structure (ANNs). In order to evaluate the proposed method, the election and whale algorithms have been used. The election algorithm is a repetitive algorithm that works with a set of known solutions as a population, and the whale optimization algorithm is derived from the new nature based on the special bubble hunting strategy used by the vultures. The results showed that 22 stations of the existing network had no significant effect on rainfall estimation in the province and their removal to the optimal network is suggested. Therefore, the remaining 27 stations can be effective in optimizing the rain gauge network. The results of comparing the abovementioned algorithms showed that the neural network algorithm with a mean error of 0.06 mm has a higher ability to optimize the rain gauges than blue whale and election algorithms.

Modeling predator and prey hotspots: Management implications of baleen whale co-occurrence with krill in Central California

As global ocean-bound commerce increases, managing human activities has become important in reducing conflict with threatened wildlife. This study investigates environmental factors determining abundance and distribution of blue whales (Balaenoptera musculus), humpback whales (Megaptera novaeangliae) and their prey (Euphausia pacifica and Thysanoessa spinifera) in central California. We provide insights into environmental drivers of the ecology and distribution of these species, model whale distributions and determine coincident hotspots of whales and their prey that will help decrease human threats to whales and protect critical feeding habitat. We developed separate predictive models of whale abundances (using negative binomial regression on count data) and krill abundance (using a two-part hurdlemodel combining logistic and negative binomial regressions) over a 14 year period (2004-2017). Variables included in situ surface and midwater oceanographic measures (temperature, salinity, and fluorescence), basin-scale climate indices, and bathymetric- and distance-related data. Predictions were applied to 1 km2 cells spanning the study area for May, June, July, and September during each of the 14 years of surveys to identify persistent distribution patterns. Both whales and krill were found to consistently use the northeast region of Cordell Bank, the Farallon Escarpment, and the shelf-break waters. The main identified blue whale hotspots were also krill hotspots, while co-occurrence was more limited and varied seasonally for humpback whales and krill. These results are valuable in identifying patterns in important areas of ecological interaction to assist management of whales. Areas north of Cordell Bank are of particular management concern since they overlap with the end of the San Francisco Bay northern shipping lane. Our findings can help decrease threats to whales, particularly in important foraging areas, by supporting implementation of vessel management and informing potential conflicts with other human uses.

Why whales are big but not bigger: Physiological drivers and ecological limits in the age of ocean giants

The largest animals are marine filter feeders, but the underlying mechanism of their large size remains unexplained. We measured feeding performance and prey quality to demonstrate how whale gigantism is driven by the interplay of prey abundance and harvesting mechanisms that increase prey capture rates and energy intake. The foraging efficiency of toothed whales that feed on single prey is constrained by the abundance of large prey, whereas filter-feeding baleen whales seasonally exploit vast swarms of small prey at high efficiencies. Given temporally and spatially aggregated prey, filter feeding provides an evolutionary pathway to extremes in body size that are not available to lineages that must feed on one prey at a time. Maximum size in filter feeders is likely constrained by prey availability across space and time.

Constraining DNA Sequences With a Triplet-Bases Unpaired

DNA computing, the combination of computer science and molecular biology, is a burgeoning research field that holds promise for many applications. The accuracy of DNA computing is determined by reliable DNA sequences, the quality of which affects the accuracy of hybridization reactions. Evaluating the sequences obtained from the previous combination constraints in NUPACK for simulation experiments, we find that the concentration of the sequences after entering solution was significantly lower than that before entering solution, which should affect the accuracy of DNA hybridization reactions. Therefore, in this study, we propose a new constraint, a triplet-bases unpaired constraint, which can be combined with other constraints to form a new combination constraint. In addition, we combine the Harmony Search algorithm with the Whale Optimization Algorithm (WOA) to present a new algorithm, termed HSWOA, which we used to design DNA sequences that meet the new combination constraint. Finally, compared with previous findings, our result shows that our algorithm not only improves the efficiency of hybridization reactions but also yields a better fitness value.

Resource Scheduling in Cloud Computing Based on a Hybridized Whale Optimization Algorithm

The cloud computing paradigm, as a novel computing resources delivery platform, has significantly impacted society with the concept of on-demand resource utilization through virtualization technology. Virtualization enables the usage of available physical resources in a way that multiple end-users can share the same underlying hardware infrastructure. In cloud computing, due to the expectations of clients, as well as on the providers side, many challenges exist. One of the most important nondeterministic polynomial time (NP) hard challenges in cloud computing is resource scheduling, due to its critical impact on the cloud system performance. Previously conducted research from this domain has shown that metaheuristics can substantially improve cloud system performance if they are used as scheduling algorithms. This paper introduces a hybridized whale optimization algorithm, that falls into the category of swarm intelligence metaheuristics, adapted for tackling the resource scheduling problem in cloud environments. To more precisely evaluate performance of the proposed approach, original whale optimization was also adapted for resource scheduling. Considering the two most important mechanisms of any swarm intelligence algorithm (exploitation and exploration), where the efficiency of a swarm algorithm depends heavily on their adjusted balance, the original whale optimization algorithm was enhanced by addressing its weaknesses of inappropriate exploitation–exploration trade-off adjustments and the premature convergence. The proposed hybrid algorithm was first tested on a standard set of bound-constrained benchmarks with the goal to more accurately evaluate its performance. After, simulations were performed using two different resource scheduling models in cloud computing with real, as well as with artificial data sets. Simulations were performed on the robust CloudSim platform. A hybrid whale optimization algorithm was compared with other state-of-the-art metaheurisitcs and heuristics, as well as with the original whale optimization for all conducted experiments. Achieved results in all simulations indicate that the proposed hybrid whale optimization algorithm, on average, outperforms the original version, as well as other heuristics and metaheuristics. By using the proposed algorithm, improvements in tackling the resource scheduling issue in cloud computing have been established, as well enhancements to the original whale optimization implementation.

Lunge Feeding in Rorqual Whales

The largest animals are baleen filter feeders that exploit large aggregations of small-bodied plankton. Although this feeding mechanism has evolved multiple times in marine vertebrates, rorqual whales exhibit a distinct lunge filter feeding mode that requires extreme physiological adaptations-most of which remain poorly understood. Here, we review the biomechanics of the lunge feeding mechanism in rorqual whales that underlies their extraordinary foraging performance and gigantic body size.

New views of humpback whale flow dynamics and oral morphology during prey engulfment

The rise of inexpensive, user-friendly cameras and editing software promises to revolutionize data collection with minimal disturbance to marine mammals. Video sequences recorded by aerial drones and GoPro cameras provided close-up views and unique perspectives of humpback whales engulfing juvenile salmon at or just below the water surface in Southeast Alaska and Prince William Sound. Although humpback feeding is famous for its flexibility, several stereotyped events were noted in the 47 lunges we analyzed. Engulfment was rapid (mean 2.07 s), and the entrance through which the tongue inverts into the ventral pouch was seen as water rushes in. Cranial elevation was a major contributor to gape, and pouch contraction sometimes began before full gape closure, with reverberating waves indicating rebounding flow of water within the expanded pouch. Expulsion of filtered water began with a small splash at the anterior of the mouth, followed by sustained excurrent flow in the mouth's central or posterior regions. Apart from a splash of rebounding water, water within the mouth was surprisingly turbulence-free during engulfment, but submersion of the whale's head created visible surface whirlpools and vortices which may aggregate prey for subsequent engulfment.

New insights into prime Southern Ocean forage grounds for thriving Western Australian humpback whales

Humpback whale populations migrate extensively between winter breeding grounds and summer feeding grounds, however known links to remote Antarctic feeding grounds remain limited in many cases. New satellite tracks detail humpback whale migration pathways from Western Australia into the Southern Ocean. These highlight a focal feeding area during austral spring and early summer at the southern Kerguelen plateau, in a western boundary current where a sharp northward turn and retroflection of ocean fronts occurs along the eastern plateau edge. The topographic steering of oceanographic features here likely supports a predictable, productive and persistent forage ground. The spatial distribution of whaling catches and Discovery era mark-recaptures confirms the importance of this region to Western Australian humpback whales since at least historical times. Movement modelling discriminates sex-related behaviours, with females moving faster during both transit and resident periods, which may be a consequence of size or indicate differential energetic requirements. Relatively short and directed migratory pathways overall, together with high-quality, reliable forage resources may provide a partial explanation for the ongoing strong recovery demonstrated by this population. The combination of new oceanographic information and movement data provides enhanced understanding of important biological processes, which are relevant within the context of the current spatial management and conservation efforts in the Southern Ocean.

A Novel Hybrid Genetic-Whale Optimization Model for Ontology Learning from Arabic Text

Ontologies are used to model knowledge in several domains of interest, such as the biomedical domain. Conceptualization is the basic task for ontology building. Concepts are identified, and then they are linked through their semantic relationships. Recently, ontologies have constituted a crucial part of modern semantic webs because they can convert a web of documents into a web of things. Although ontology learning generally occupies a large space in computer science, Arabic ontology learning, in particular, is underdeveloped due to the Arabic language’s nature as well as the profundity required in this domain. The previously published research on Arabic ontology learning from text falls into three categories: developing manually hand-crafted rules, using ordinary supervised/unsupervised machine learning algorithms, or a hybrid of these two approaches. The model proposed in this work contributes to Arabic ontology learning in two ways. First, a text mining algorithm is proposed for extracting concepts and their semantic relations from text documents. The algorithm calculates the concept frequency weights using the term frequency weights. Then, it calculates the weights of concept similarity using the information of the ontology structure, involving (1) the concept’s path distance, (2) the concept’s distribution layer, and (3) the mutual parent concept’s distribution layer. Then, feature mapping is performed by assigning the concepts’ similarities to the concept features. Second, a hybrid genetic-whale optimization algorithm was proposed to optimize ontology learning from Arabic text. The operator of the G-WOA is a hybrid operator integrating GA’s mutation, crossover, and selection processes with the WOA’s processes (encircling prey, attacking of bubble-net, and searching for prey) to fulfill the balance between both exploitation and exploration, and to find the solutions that exhibit the highest fitness. For evaluating the performance of the ontology learning approach, extensive comparisons are conducted using different Arabic corpora and bio-inspired optimization algorithms. Furthermore, two publicly available non-Arabic corpora are used to compare the efficiency of the proposed approach with those of other languages. The results reveal that the proposed genetic-whale optimization algorithm outperforms the other compared algorithms across all the Arabic corpora in terms of precision, recall, and F-score measures. Moreover, the proposed approach outperforms the state-of-the-art methods of ontology learning from Arabic and non-Arabic texts in terms of these three measures.

Multi-locus DNA metabarcoding of zooplankton communities and scat reveal trophic interactions of a generalist predator

To understand the ecosystem dynamics that underpin the year-round presence of a large generalist consumer, the Bryde's whale (Balaenoptera edeni brydei), we use a DNA metabarcoding approach and systematic zooplankton surveys to investigate seasonal and regional changes in zooplankton communities and if whale diet reflects such changes. Twenty-four zooplankton community samples were collected from three regions throughout the Hauraki Gulf, New Zealand, over two temperature regimes (warm and cool seasons), as well as 20 samples of opportunistically collected Bryde's whale scat. Multi-locus DNA barcode libraries were constructed from 18S and COI gene fragments, representing a trade-off between identification and resolution of metazoan taxa. Zooplankton community OTU occurrence and relative read abundance showed regional and seasonal differences based on permutational analyses of variance in both DNA barcodes, with significant changes in biodiversity indices linked to season in COI only. In contrast, we did not find evidence that Bryde's whale diet shows seasonal or regional trends, but instead indicated clear prey preferences for krill-like crustaceans, copepods, salps and ray-finned fishes independent of prey availability. The year-round presence of Bryde's whales in the Hauraki Gulf is likely associated with the patterns of distribution and abundance of these key prey items.

Capturing foraging and resting behavior using nested multivariate Markov models in an air-breathing marine vertebrate

BACKGROUND

Matching animal movement with the behaviors that shape life history requires a rigorous connection between the observed patterns of space use and inferred behavioral states. As animal-borne dataloggers capture a greater diversity and frequency of three dimensional movements, we can increase the complexity of movement models describing animal behavior. One challenge in combining data streams is the different spatial and temporal frequency of observations. Nested movement models provide a flexible framework for gleaning data from long-duration, but temporally sparse, data sources.

RESULTS

Using a two-layer nested model, we combined geographic and vertical movement to infer traveling, foraging and resting behaviors of Humpback whales off the West Antarctic Peninsula. This approach refined previous work using only geographic data to delineate coarser behavioral states. Our results showed increased intensity in foraging activity in late season animals as the whales prepared to migrate north to tropical calving grounds. Our model also suggests strong diel variation in movement states, likely linked to daily changes in prey distribution.

CONCLUSIONS

Using a combination of two-dimensional and three-dimensional movement data, we highlight the connection between whale movement and krill availability, as well as the complex spatial pattern of whale foraging in productive polar waters.

High mortality of blue, humpback and fin whales from modeling of vessel collisions on the U.S. West Coast suggests population impacts and insufficient protection

Mortality from collisions with vessels is one of the main human causes of death for large whales. Ship strikes are rarely witnessed and the distribution of strike risk and estimates of mortality remain uncertain at best. We estimated ship strike mortality for blue humpback and fin whales in U.S. West Coast waters using a novel application of a naval encounter model. Mortality estimates from the model were far higher than current minimum estimates derived from stranding records and are closer to extrapolations adjusted for detection probabilities of dead whales. Our most conservative model estimated mortality to be 7.8x, 2.0x and 2.7x the U.S. recommended limit for blue, humpback and fin whales, respectively, suggesting that death from vessel collisions may be a significant impediment to population growth and recovery. Comparing across the study area, the majority of strike mortality occurs in waters off California, from Bodega Bay south and tends to be concentrated in a band approximately 24 Nm (44.5 km) offshore and in designated shipping lanes leading to and from major ports. While some mortality risk exists across nearly all West Coast waters, 74%, 82% and 65% of blue, humpback and fin whale mortality, respectively, occurs in just 10% of the study area, suggesting conservation efforts can be very effective if focused in these waters. Risk is highest in the shipping lanes off San Francisco and Long Beach, but only a fraction of total estimated mortality occurs in these proportionally small areas, making any conservation efforts exclusively within these areas insufficient to address overall strike mortality. We recommend combining shipping lane modifications and re-locations, ship speed reductions and creation of ‘Areas to be Avoided’ by vessels in ecologically important locations to address this significant source of whale mortality.

Energy-Related CO2 Emissions Forecasting Using an Improved LSSVM Model Optimized by Whale Optimization Algorithm

Accurate and reliable forecasting on energy-related carbon dioxide (CO2) emissions is of great significance for climate policy decision making and energy planning. Due to the complicated nonlinear relationships of CO2 emissions with its driving forces, the accurate forecasting for CO2 emissions is a tedious work, which is an important issue worth studying. In this study, a novel CO2 emissions prediction method is proposed which employs the latest nature-enlightened optimization method, named the Whale optimization algorithm (WOA), to search the optimized values of two parameters of LSSVM (least squares support vector machine), namely the WOA-LSSVM model. Meanwhile, the driving forces of CO2 emissions including GDP (gross domestic product), energy consumption and population are chosen to be the import variables of the proposed WOA-LSSVM method. Taking China’s CO2 emissions as an instance, the effectiveness of WOA-LSSVM-based CO2 emissions forecasting is verified. The comparative analysis results indicate that the WOA-LSSVM model is significantly superior to other selected models, namely FOA (fruit fly optimization algorithm)-LSSVM, LSSVM, and OLS (ordinary least square) models in terms of CO2 emissions forecasting. The proposed WOA-LSSVM model has the potential to effectively improve the accuracy of CO2 emissions forecasting. Meanwhile, as a new nature-enlightened heuristic optimization algorithm, the WOA has the prospect for wide application.