Modeling individual growth reveals decreasing gray whale body length and correlations with ocean climate indices at multiple scales.

Changes in body size have been documented across taxa in response to human activities and climate change. Body size influences many aspects of an individual's physiology, behavior, and ecology, ultimately affecting life history performance and resilience to stressors. In this study, we developed an analytical approach to model individual growth patterns using aerial imagery collected via drones, which can be used to investigate shifts in body size in a population and the associated drivers. We applied the method to a large morphological dataset of gray whales (Eschrichtius robustus) using a distinct foraging ground along the NE Pacific coast, and found that the asymptotic length of these whales has declined since around the year 2000 at an average rate of 0.05-0.12 m/y. The decline has been stronger in females, which are estimated to be now comparable in size to males, minimizing sexual dimorphism. We show that the decline in asymptotic length is correlated with two oceanographic metrics acting as proxies of habitat quality at different scales: the mean Pacific Decadal Oscillation index, and the mean ratio between upwelling intensity in a season and the number of relaxation events. These results suggest that the decline in gray whale body size may represent a plastic response to changing environmental conditions. Decreasing body size could have cascading effects on the population's demography, ability to adjust to environmental changes, and ecological influence on the structure of their community. This finding adds to the mounting evidence that body size is shrinking in several marine populations in association with climate change and other anthropogenic stressors. Our modeling approach is broadly applicable across multiple systems where morphological data on megafauna are collected using drones.

Machine learning with taxonomic family delimitation aids in the classification of ephemeral beaked whale events in passive acoustic monitoring.

Passive acoustic monitoring is an essential tool for studying beaked whale populations. This approach can monitor elusive and pelagic species, but the volume of data it generates has overwhelmed researchers' ability to quantify species occurrence for effective conservation and management efforts. Automation of data processing is crucial, and machine learning algorithms can rapidly identify species using their sounds. Beaked whale acoustic events, often infrequent and ephemeral, can be missed when co-occurring with signals of more abundant, and acoustically active species that dominate acoustic recordings. Prior efforts on large-scale classification of beaked whale signals with deep neural networks (DNNs) have approached the class as one of many classes, including other odontocete species and anthropogenic signals. That approach tends to miss ephemeral events in favor of more common and dominant classes. Here, we describe a DNN method for improved classification of beaked whale species using an extensive dataset from the western North Atlantic. We demonstrate that by training a DNN to focus on the taxonomic family of beaked whales, ephemeral events were correctly and efficiently identified to species, even with few echolocation clicks. By retrieving ephemeral events, this method can support improved estimation of beaked whale occurrence in regions of high odontocete acoustic activity.

Universal wing- and fin-beat frequency scaling.

We derive an equation that applies for the wing-beat frequency of flying animals and to the fin-stroke frequency of diving animals like penguins and whales. The equation states that the wing/fin-beat frequency is proportional to the square root of the animal's mass divided by the wing area. Data for birds, insects, bats, and even a robotic bird-supplemented by data for whales and penguins that must swim to stay submerged-show that the constant of proportionality is to a good approximation the same across all species; thus the equation is universal. The wing/fin-beat frequency equation is derived by dimensional analysis, which is a standard method of reasoning in physics. We finally demonstrate that a mathematically even simpler expression without the animal mass does not apply.

Improved Latin hypercube sampling initialization-based whale optimization algorithm for COVID-19 X-ray multi-threshold image segmentation.

Image segmentation techniques play a vital role in aiding COVID-19 diagnosis. Multi-threshold image segmentation methods are favored for their computational simplicity and operational efficiency. Existing threshold selection techniques in multi-threshold image segmentation, such as Kapur based on exhaustive enumeration, often hamper efficiency and accuracy. The whale optimization algorithm (WOA) has shown promise in addressing this challenge, but issues persist, including poor stability, low efficiency, and accuracy in COVID-19 threshold image segmentation. To tackle these issues, we introduce a Latin hypercube sampling initialization-based multi-strategy enhanced WOA (CAGWOA). It incorporates a COS sampling initialization strategy (COSI), an adaptive global search approach (GS), and an all-dimensional neighborhood mechanism (ADN). COSI leverages probability density functions created from Latin hypercube sampling, ensuring even solution space coverage to improve the stability of the segmentation model. GS widens the exploration scope to combat stagnation during iterations and improve segmentation efficiency. ADN refines convergence accuracy around optimal individuals to improve segmentation accuracy. CAGWOA's performance is validated through experiments on various benchmark function test sets. Furthermore, we apply CAGWOA alongside similar methods in a multi-threshold image segmentation model for comparative experiments on lung X-ray images of infected patients. The results demonstrate CAGWOA's superiority, including better image detail preservation, clear segmentation boundaries, and adaptability across different threshold levels.

Annual phenology and migration routes to breeding grounds in western-central North Pacific sei whales.

The sei whale (Balaenoptera borealis) is an important species among baleen whales in the North Pacific and plays a significant role in the ecosystem. Despite the importance of this species, information regarding its migration patterns and breeding locations remains limited. To enhance the understanding of the phenology of North Pacific sei whales, we deployed satellite-monitored tags on these whales in the western and central North Pacific from 2017 to 2023. We fitted 55 sei whale tracks to a state-space model to describe the whales' seasonal movements at feeding grounds and their migratory behavior. The whales typically leave their feeding grounds between November and December, with migration pathways extending from off Japan to the west of the Hawaiian Islands. These southward transits converge in the waters of the Marshall Islands and north of Micronesia between 20° N and 7° N, which appear to be breeding grounds. After a brief stay at these breeding grounds, the whales migrate northward from January to February, reaching their feeding grounds around 30°N by March. To the best of our knowledge, this is the first study to present the phenology of feeding and breeding seasons and the migration pattern of North Pacific sei whales.

Contaminant assessment of stranded and deceased beaked whales (Ziphiidae) on the New South Wales coast of Australia.

Metal and organic pollutants are prominent marine contaminants that disperse widely throughout the environment. Some contaminants biomagnify, leaving long-lived apex predators such as cetaceans at risk of toxicity. Various tissues collected post-mortem from 16 Ziphiidae individuals that stranded on the New South Wales (NSW) coast, Australia, over ∼15 years were investigated for 16 metals/metalloids and 33 organic contaminants. Polychlorinated biphenyls (PCBs) and Dichlorodiphenyltrichloroethanes (DDTs) were commonly detected in blubber and liver tissues. Mercury, cadmium and silver exceeded reported toxicity thresholds in several individuals. The liver tissue of a Mesoplodon layardii specimen had the highest mercury (386 mg/kg dry weight). Liver tissue of a Mesoplodon grayi specimen had the highest silver concentration (19.7 mg/kg dry weight), and the highest cadmium concentration was in Ziphius cavirostris kidney (478 mg/kg dry weight). This study provides important new information for rare Ziphiidae species globally.

Click detection rate variability of central North Pacific sperm whales from passive acoustic towed arrays.

Passive acoustic monitoring (PAM) is an optimal method for detecting and monitoring cetaceans as they frequently produce sound while underwater. Cue counting, counting acoustic cues of deep-diving cetaceans instead of animals, is an alternative method for density estimation, but requires an average cue production rate to convert cue density to animal density. Limited information about click rates exists for sperm whales in the central North Pacific Ocean. In the absence of acoustic tag data, we used towed hydrophone array data to calculate the first sperm whale click rates from this region and examined their variability based on click type, location, distance of whales from the array, and group size estimated by visual observers. Our findings show click type to be the most important variable, with groups that include codas yielding the highest click rates. We also found a positive relationship between group size and click detection rates that may be useful for acoustic predictions of group size in future studies. Echolocation clicks detected using PAM methods are often the only indicator of deep-diving cetacean presence. Understanding the factors affecting their click rates provides important information for acoustic density estimation.

Debris flow volume prediction model based on back propagation neural network optimized by improved whale optimization algorithm.

Debris flow is a sudden natural disaster in mountainous areas, which seriously threatens the lives and property of nearby residents. Therefore, it is necessary to predict the volume of debris flow accurately and reliably. However, the predictions of back propagation neural networks are unstable and inaccurate due to the limited dataset. In this study, the Cubic map optimizes the initial population position of the whale optimization algorithm. Meanwhile, the adaptive weight adjustment strategy optimizes the weight value in the shrink-wrapping mechanism of the whale optimization algorithm. Then, the improved whale optimization algorithm optimizes the final weights and thresholds in the back propagation neural network. Finally, to verify the performance of the final model, sixty debris flow gullies caused by earthquakes in Longmenshan area are selected as the research objects. Through correlation analysis, 4 main factors affecting the volume of debris flow are determined and inputted into the model for training and prediction. Four methods (support vector machine regression, XGBoost, back propagation neural network optimized by artificial bee colony algorithm, back propagation neural network optimized by grey wolf optimization algorithm) are used to compare the prediction performance and reliability. The results indicate that loose sediments from co-seismic landslides are the most important factor influencing the flow of debris flows in the earthquake area. The mean absolute percentage error, mean absolute error and R2 of the final model are 0.193, 29.197 × 104 m3 and 0.912, respectively. The final model is more accurate and stable when the dataset is insufficient and under complexity. This is attributed to the optimization of WOA by Cubic map and adaptive weight adjustment. In general, the model of this paper can provide reference for debris flow prevention and machine learning algorithms.

Three decades of nearshore surveys reveal long-term patterns in gray whale habitat use, distribution, and abundance in the Northern California Current.

The nearshore waters of the Northern California Current support an important seasonal foraging ground for Pacific Coast Feeding Group (PCFG) gray whales. We examine gray whale distribution, habitat use, and abundance over 31 years (1992-2022) using standardized nearshore (< 5 km from shore) surveys spanning a large swath of the PCFG foraging range. Specifically, we generated density surface models, which incorporate detection probability into generalized additive models to assess environmental correlates of gray whale distribution and predict abundance over time. We illustrate the importance of coastal upwelling dynamics, whereby increased upwelling only yields higher gray whale density if interspersed with relaxation events, likely because this combination optimizes influx and retention of nutrients to support recruitment and aggregation of gray whale prey. Several habitat features influence gray whale distribution, including substrate, shelf width, prominent capes, and river estuaries. However, the influence of these features differs between regions, revealing heterogeneity in habitat preferences throughout the PCFG foraging range. Predicted gray whale abundance fluctuated throughout our study period, but without clear directional trends, unlike previous abundance estimates based on mark-recapture models. This study highlights the value of long-term monitoring, shedding light on the impacts of variable environmental conditions on an iconic nearshore marine predator.

Geographical distribution of close kin in southern right whales on feeding grounds.

This study investigated the close kinship structure of southern right whales on feeding grounds during austral summer seasons. The study was based on biopsy samples of 171 individual whales, which were genotyped with 14 microsatellite DNA loci. Kinship was investigated by using the LOD (Log Odds) score, a relatedness index for a pair of genotypes. Based on a cut-off point of LODPO > 6, which was chosen to balance false positives and negatives, a total of 28 dyads were inferred. Among these, 25 were classified as parent-offspring pairs. Additional genetic (mitochondrial DNA haplotypes) and biological (estimated body length, sex) data were used to provide additional information on the inferred close kin pairs. The elapsed time between sampling varied from 0 (close kin detected in the same austral summer season) to 17 years. All the kin pairs occurred within the Antarctic Indo sector (85°-135°E) and no pair occurred between whales within and outside of this sector. Six pairs were between individuals in high (Antarctic) and lower latitudes. Results of the present analysis on kinship are consistent with the views that whales in the Indo sector of the Antarctic are related with the breeding ground in Southwest Australia, and that whales from this population can occupy different feeding grounds. The present study has the potential to contribute to the conservation of the southern right whales through the monitoring of important population parameters such as population sizes and growth rate, in addition to assist the interpretation of stock structure derived from standard population genetic analyses.

Exploring indirect effects of a classic trophic cascade between urchins and kelp on zooplankton and whales.

Kelp forest trophic cascades have been extensively researched, yet indirect effects to the zooplankton prey base and gray whales have not been explored. We investigate the correlative patterns of a trophic cascade between bull kelp and purple sea urchins on gray whales and zooplankton in Oregon, USA. Using generalized additive models (GAMs), we assess (1) temporal dynamics of the four species across 8 years, and (2) possible trophic paths from urchins to kelp, kelp as habitat to zooplankton, and kelp and zooplankton to gray whales. Temporal GAMs revealed an increase in urchin coverage, with simultaneous decline in kelp condition, zooplankton abundance and gray whale foraging time. Trophic path GAMs, which tested for correlations between species, demonstrated that urchins and kelp were negatively correlated, while kelp and zooplankton were positively correlated. Gray whales showed nuanced and site-specific correlations with zooplankton in one site, and positive correlations with kelp condition in both sites. The negative correlation between the kelp-urchin trophic cascade and zooplankton resulted in a reduced prey base for gray whales. This research provides a new perspective on the vital role kelp forests may play across multiple trophic levels and interspecies linkages.

Accurate species classification of Arctic toothed whale echolocation clicks using one-third octave ratios.

Passive acoustic monitoring has been an effective tool to study cetaceans in remote regions of the Arctic. Here, we advance methods to acoustically identify the only two Arctic toothed whales, the beluga (Delphinapterus leucas) and narwhal (Monodon monoceros), using echolocation clicks. Long-term acoustic recordings collected from moorings in Northwest Greenland were analyzed. Beluga and narwhal echolocation signals were distinguishable using spectrograms where beluga clicks had most energy >30 kHz and narwhal clicks had a sharp lower frequency limit near 20 kHz. Changes in one-third octave levels (TOL) between two pairs of one-third octave bands were compared from over one million click spectra. Narwhal clicks had a steep increase between the 16 and 25 kHz TOL bands that was absent in beluga click spectra. Conversely, beluga clicks had a steep increase between the 25 and 40 kHz TOL bands that was absent in narwhal click spectra. Random Forest classification models built using the 16 to 25 kHz and 25 to 40 kHz TOL ratios accurately predicted the species identity of 100% of acoustic events. Our findings support the use of echolocation TOL ratios in future automated click classifiers for acoustic monitoring of Arctic toothed whales and potentially for other odontocete species.

Whale evolution: Ancient toothed relative of baleen whales breaches northward.

The mysticetes - baleen whales and their toothed ancestors - have a long evolutionary history that, despite many recent paleontological discoveries, remains highly debated. The description of a new mysticete from the latest Eocene of North America opens promising new research directions.

The evolution of menopause in toothed whales.

Understanding how and why menopause has evolved is a long-standing challenge across disciplines. Females can typically maximize their reproductive success by reproducing for the whole of their adult life. In humans, however, women cease reproduction several decades before the end of their natural lifespan1,2. Although progress has been made in understanding the adaptive value of menopause in humans3,4, the generality of these findings remains unclear. Toothed whales are the only mammal taxon in which menopause has evolved several times5, providing a unique opportunity to test the theories of how and why menopause evolves in a comparative context. Here, we assemble and analyse a comparative database to test competing evolutionary hypotheses. We find that menopause evolved in toothed whales by females extending their lifespan without increasing their reproductive lifespan, as predicted by the 'live-long' hypotheses. We further show that menopause results in females increasing their opportunity for intergenerational help by increasing their lifespan overlap with their grandoffspring and offspring without increasing their reproductive overlap with their daughters. Our results provide an informative comparison for the evolution of human life history and demonstrate that the same pathway that led to menopause in humans can also explain the evolution of menopause in toothed whales.

Predicting the cognitive function status in end-stage renal disease patients at a functional subnetwork scale.

Brain functional networks derived from functional magnetic resonance imaging (fMRI) provide a promising approach to understanding cognitive processes and predicting cognitive abilities. The topological attribute parameters of global networks are taken as the features from the overall perspective. It is constrained to comprehend the subtleties and variances of brain functional networks, which fell short of thoroughly examining the complex relationships and information transfer mechanisms among various regions. To address this issue, we proposed a framework to predict the cognitive function status in the patients with end-stage renal disease (ESRD) at a functional subnetwork scale (CFSFSS). The nodes from different network indicators were combined to form the functional subnetworks. The area under the curve (AUC) of the topological attribute parameters of functional subnetworks were extracted as features, which were selected by the minimal Redundancy Maximum Relevance (mRMR). The parameter combination with improved fitness was searched by the enhanced whale optimization algorithm (E-WOA), so as to optimize the parameters of support vector regression (SVR) and solve the global optimization problem of the predictive model. Experimental results indicated that CFSFSS achieved superior predictive performance compared to other methods, by which the mean absolute error (MAE), mean absolute percentage error (MAPE), and root mean square error (RMSE) were up to 0.5951, 0.0281 and 0.9994, respectively. The functional subnetwork effectively identified the active brain regions associated with the cognitive function status, which offered more precise features. It not only helps to more accurately predict the cognitive function status, but also provides more references for clinical decision-making and intervention of cognitive impairment in ESRD patients.

Reproducibility and validity of a 45 item food-frequency questionnaire for inuit in Greenland.

Since 1993, dietary assessment has been carried out in Greenland as part of recurrent population health surveys. In preparation for the next survey in 2024, 91 participants from the survey in 2018 were selected for a validation study of the Food Frequency Questionnaire (FFQ). The 91 participants were reinterviewed 38-50 months after the first FFQ and invited to complete a food diary. As part of the 2018 survey, blood was analysed for mercury. The food diary was completed by 65 participants. The agreement between the two FFQ interviews was very good for macronutrients and fatty acids (p > 0.20), whereas the calculated intake of mercury was 22% higher in the second FFQ (p = 0.04) due to a higher intake of whale meat and muktuk (whale skin). The agreement between the second FFQ and the food diary was good for local food, imported meat and cakes/sweets/snacks but fruit and vegetables, dairy products, beverages and added sugar were significantly underreported in the food diary. Food items not included in the FFQ were identified from the food diaries. The correlation between the intake of marine mammals and blood mercury was moderate (Spearman's rho = 0.41-0.50; p < 0.0001). The results will inspire future dietary studies in the circumpolar North.

A whale of a tale: whale cells evade the driving mechanism for hexavalent chromium-induced chromosome instability.

Chromosome instability, a hallmark of lung cancer, is a driving mechanism for hexavalent chromium [Cr(VI)] carcinogenesis in humans. Cr(VI) induces structural and numerical chromosome instability in human lung cells by inducing DNA double-strand breaks and inhibiting homologous recombination repair and causing spindle assembly checkpoint (SAC) bypass and centrosome amplification. Great whales are long-lived species with long-term exposures to Cr(VI) and accumulate Cr in their tissue, but exhibit a low incidence of cancer. Data show Cr(VI) induces fewer chromosome aberrations in whale cells after acute Cr(VI) exposure suggesting whale cells can evade Cr(VI)-induced chromosome instability. However, it is unknown if whales can evade Cr(VI)-induced chromosome instability. Thus, we tested the hypothesis that whale cells resist Cr(VI)-induced loss of homologous recombination repair activity and increased SAC bypass and centrosome amplification. We found Cr(VI) induces similar amounts of DNA double-strand breaks after acute (24 h) and prolonged (120 h) exposures in whale lung cells, but does not inhibit homologous recombination repair, SAC bypass, or centrosome amplification, and does not induce chromosome instability. These data indicate whale lung cells resist Cr(VI)-induced chromosome instability, the major driver for Cr(VI) carcinogenesis at a cellular level, consistent with observations that whales are resistant to cancer.

Foraging behaviour and ecology of transient killer whales within a deep submarine canyon system.

Transient killer whales have been documented hunting marine mammals across a variety of habitats. However, relatively little has been reported about their predatory behaviours near deep submarine canyons and oceanic environments. We used a long-term database of sightings and encounters with these predators in and around the Monterey Submarine Canyon, California to describe foraging behaviour, diet, seasonal occurrence, and habitat use patterns. Transient killer whales belonging to the outer coast subpopulation were observed within the study area 261 times from 2006-2021. Occurrences, behaviours, and group sizes all varied seasonally, with more encounters occurring in the spring as grey whales migrated northward from their breeding and calving lagoons in Mexico (March-May). Groups of killer whales foraged exclusively in open water, with individuals within the groups following the contours of the submarine canyon as they searched for prey. Focal follows revealed that killer whales spent 51% of their time searching for prey (26% of their time along the shelf-break and upper slope of the canyon, and 25% in open water). The remainder of their time was spent pursuing prey (10%), feeding (23%), travelling (9%), socializing (6%), and resting (1%). Prey species during 87 observed predation events included California sea lions, grey whale calves, northern elephant seals, minke whales, common dolphins, Pacific white-sided dolphins, Dall's porpoise, harbour porpoise, harbour seals, and sea birds. The calculated kill rates (based on 270 hours of observing 50 predation events) were 0.26 California sea lions per killer whale over 24 hours, 0.11 grey whale calves, and 0.15 for all remaining prey species combined. These behavioural observations provide insights into predator-prey interactions among apex predators over submarine canyons and deep pelagic environments.

Effects of whaling and krill fishing on the whale-krill predation dynamics: bifurcations in a harvested predator-prey model with Holling type I functional response.

In the Antarctic, the whale population had been reduced dramatically due to the unregulated whaling. It was expected that Antarctic krill, the main prey of whales, would grow significantly as a consequence and exploratory krill fishing was practiced in some areas. However, it was found that there has been a substantial decline in abundance of krill since the end of whaling, which is the phenomenon of krill paradox. In this paper, to study the krill-whale interaction we revisit a harvested predator-prey model with Holling I functional response. We find that the model admits at most two positive equilibria. When the two positive equilibria are located in the region { ( N , P ) | 0 ≤ N < 2 N c , P ≥ 0 } , the model exhibits degenerate Bogdanov-Takens bifurcation with codimension up to 3 and Hopf bifurcation with codimension up to 2 by rigorous bifurcation analysis. When the two positive equilibria are located in the region { ( N , P ) | N > 2 N c , P ≥ 0 } , the model has no complex bifurcation phenomenon. When there is one positive equilibrium on each side of N = 2 N c , the model undergoes Hopf bifurcation with codimension up to 2. Moreover, numerical simulation reveals that the model not only can exhibit the krill paradox phenomenon but also has three limit cycles, with the outmost one crosses the line N = 2 N c under some specific parameter conditions.