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Abstract 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.

Abstract 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 (

Abstract 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.

Drones provide a privileged birds’-eye view for collecting high-resolution imagery for morphometric and behavioral sampling of animals. Biologically meaningful measurements extracted from overhead images require an accurate estimate of altitude, but current commercial drones include inaccurate barometer estimates. Recent proposals for coupling altimeter systems to drones have provided customized, open-source solutions, yet assembling such altimeter systems requires advanced technical skills, thereby potentially limiting their use. Here, we built upon recent advances to provide a 3D-printed enclosure for an altimeter system that is inexpensive, self-contained, easy to setup, and transferable across commercial drones. We depart from a published, successful data logger system composed of a GPS and LiDAR sensor and design a more compact and self-powered version (“LidarBoX”) that easily attaches to a variety of commercial drones. We compare flight times with/without LidarBoX attached, test flight maneuverability and performance, and validate the reliability of measurement accuracy. To make LidarBoX accessible, we provide an open-source repository with design code and files and a how-to-assemble guide for non-specialists. We hope this work helps popularize LiDAR altimeter systems on commercial drones to improve the accuracy and reliability of drones as a sampling platform for ecology and wildlife research.

Abstract The combination of very high resolution (VHR) satellite remote sensing imagery and deep learning via convolutional neural networks provides opportunities to improve global whale population surveys through increasing efficiency and spatial coverage. Many whale species are recovering from commercial whaling and face multiple anthropogenic threats. Regular, accurate population surveys are therefore of high importance for conservation efforts. In this study, a state‐of‐the‐art object detection model (YOLOv5) was trained to detect gray whales (Eschrichtius robustus) in VHR satellite images, using training data derived from satellite images spanning different sea states in a key breeding habitat, as well as aerial imagery collected by unoccupied aircraft systems. Varying combinations of aerial and satellite imagery were incorporated into the training set. Mean average precision, whale precision, and recall ranged from 0.823 to 0.922, 0.800 to 0.939, and 0.843 to 0.889, respectively, across eight experiments. The results imply that including aerial imagery in the training data did not substantially impact model performance, and therefore, expansion of representative satellite datasets should be prioritized. The accuracy of the results on real‐world data, along with short training times, indicates the potential of using this method to automate whale detection for population surveys.

Abstract Researchers can investigate many aspects of animal ecology through noninvasive photo–identification. Photo–identification is becoming more efficient as matching individuals between photos is increasingly automated. However, the convolutional neural network models that have facilitated this change need many training images to generalize well. As a result, they have often been developed for individual species that meet this threshold. These single‐species methods might underperform, as they ignore potential similarities in identifying characteristics and the photo–identification process among species. In this paper, we introduce a multi‐species photo–identification model based on a state‐of‐the‐art method in human facial recognition, the ArcFace classification head. Our model uses two such heads to jointly classify species and identities, allowing species to share information and parameters within the network. As a demonstration, we trained this model with 50,796 images from 39 catalogues of 24 cetacean species, evaluating its predictive performance on 21,192 test images from the same catalogues. We further evaluated its predictive performance with two external catalogues entirely composed of identities that the model did not see during training. The model achieved a mean average precision (MAP) of 0.869 on the test set. Of these, 10 catalogues representing seven species achieved a MAP score over 0.95. For some species, there was notable variation in performance among catalogues, largely explained by variation in photo quality. Finally, the model appeared to generalize well, with the two external catalogues scoring similarly to their species' counterparts in the larger test set. From our cetacean application, we provide a list of recommendations for potential users of this model, focusing on those with cetacean photo–identification catalogues. For example, users with high quality images of animals identified by dorsal nicks and notches should expect near optimal performance. Users can expect decreasing performance for catalogues with higher proportions of indistinct individuals or poor quality photos. Finally, we note that this model is currently freely available as code in a GitHub repository and as a graphical user interface, with additional functionality for collaborative data management, via Happywhale.com.

Abstract Human use of marinescapes is rapidly increasing, especially in populated nearshore regions where recreational vessel traffic can be dense. Marine animals can have a physiological response to such elevated human activity that can impact individual health and population dynamics. To understand the physiological impacts of vessel traffic on baleen whales, we investigated the adrenal stress response of gray whales (Eschrichtius robustus) to variable vessel traffic levels through an assessment of fecal glucocorticoid metabolite (fGC) concentrations. This analysis was conducted at the individual level, at multiple temporal scales (1–7 days), and accounted for factors that may confound fGC: sex, age, nutritional status, and reproductive state. Data were collected in Oregon, USA, from June to October of 2016–2018. Results indicate significant correlations between fGC, month, and vessel counts from the day prior to fecal sample collection. Furthermore, we show a significant positive correlation between vessel traffic and underwater ambient noise levels, which indicates that noise produced by vessel traffic may be a causal factor for the increased fGC. This study increases knowledge of gray whale physiological response to vessel traffic and may inform management decisions regarding regulations of vessel traffic activities and thresholds near critical whale habitats.

Giving students an opportunity to undertake field work, learn about data collection and analysis, and work and live as part of a team of diverse individuals is a unique experience that can influence and shape future careers and lives. Engagement of young science enthusiasts in a rural community is a key goal of the Journey for Aspiring Students Pursuing Ecological Research (JASPER) program run by Oregon State University’s Marine Mammal Institute that focuses on gray whale foraging ecology research. This unique project integrates research with STEM education by bringing together a team of graduate students, undergraduate students, and high school students for a six-week intensive field season each year where students conduct research, hone teamwork and leadership skills, and build their STEM identity. Over the course of this internship, students learn how to use diverse technology to collect data, engage with the local community, and gain an understanding of marine ecology and the scientific process. Additionally, interns develop science communication skills in both formal and informal settings, including a community presentation and a blog post. Over seven years, JASPER has given 25 students a chance to interact with scientists and to be a real scientist for a short while. We have been able to track 88% of these students; all are in STEM-related fields and reported that this program profoundly impacted their lives and careers. Whether or not students continue STEM career paths, the experience broadens their horizons and skill sets, and helps engage the local community in current marine research.

The ocean continues to be a sink for microparticle (MP) pollution, which includes microplastics and other anthropogenic debris. While documentation of MP in marine systems is now common, we lack information on rates of MP ingestion by baleen whales and their prey. We collected and assessed MP loads in zooplankton prey and fecal samples of gray whales (Eschrichtius robustus) feeding in coastal Oregon, USA and produced the first estimates of baleen whale MP consumption rates from empirical data of zooplankton MP loads (i.e., not modeled). All zooplankton species examined were documented gray whale prey items (Atylus tridens, Holmesimysis sculpta, Neomysis rayii) and contained an average of 4 MP per gram of tissue, mostly of the microfiber morphotype. We extrapolated MP loads in zooplankton prey to estimate the daily MP consumption rates of pregnant and lactating gray whales, which ranged between 6.5 and 21 million MP/day. However, these estimates do not account for MP ingested from ambient water or benthic sediments, which may be high for gray whales given their benthic foraging strategy. We also assessed MP loads in fecal samples from gray whales feeding in the same spatio-temporal area and detected MP in all samples examined, which included microfibers and significantly larger morphotypes than in the zooplankton. We theorize that gray whales ingest MP via both indirect trophic transfer from their zooplankton prey and directly through indiscriminate consumption of ambient MPs when foraging benthically where they consume larger MP morphotypes that have sunk and accumulated on the seafloor. Hence, our estimated daily MP consumption rates for gray whales are likely conservative because they are only based on indirect MP ingestion via prey. Our results improve the understanding of MP loads in marine ecosystems and highlight the need to assess the health impacts of MP consumption on zooplankton and baleen whales, particularly due to the predominance of microfibers in samples, which may be more toxic and difficult to excrete than other MP types. Furthermore, the high estimated rates of MP consumption by gray whales highlights the need to assess health consequences to individuals and subsequent scaled-up effects on population vital rates.

Abstract Animal behavior is motivated by the fundamental need to feed and reproduce, and these behaviors can be inferred from spatiotemporal variations in biological signals such as vocalizations. Yet, linking foraging and reproductive effort to environmental drivers can be challenging for wide‐ranging predator species. Blue whales are acoustically active marine predators that produce two distinct vocalizations: song and D calls. We examined environmental correlates of these vocalizations using continuous recordings from five hydrophones in the South Taranaki Bight region of Aotearoa New Zealand to investigate call behavior relative to ocean conditions and infer life history patterns. D calls were strongly correlated with oceanographic drivers of upwelling in spring and summer, indicating associations with foraging effort. In contrast, song displayed a highly seasonal pattern with peak intensity in fall, which aligned with the timing of conception inferred from whaling records. Finally, during a marine heatwave, reduced foraging (inferred from D calls) was followed by lower reproductive effort (inferred from song intensity).

Quantifying how animals respond to disturbance events bears relevance for understanding consequences to population health. We investigate whether blue whales respond acoustically to naturally occurring episodic noise by examining calling before and after earthquakes (27 040 calls, 32 earthquakes; 27 January–29 June 2016). Two vocalization types were evaluated: New Zealand blue whale song and downswept vocalizations ('D calls'). Blue whales did not alter the number of D calls, D call received level or song intensity following earthquakes (paired t-tests, p > 0.7 for all). Linear models accounting for earthquake strength and proximity revealed significant relationships between change in calling activity surrounding earthquakes and prior calling activity (D calls: R2 = 0.277, p < 0.0001; song: R2 = 0.080, p = 0.028); however, these same relationships were true for ‘null’ periods without earthquakes (D calls: R2 = 0.262, p < 0.0001; song: R2 = 0.149, p = 0.0002), indicating that the pattern is driven by blue whale calling context regardless of earthquake presence. Our findings that blue whales do not respond to episodic natural noise provide context for interpreting documented acoustic responses to anthropogenic noise sources, including shipping traffic and petroleum development, indicating that they potentially evolved tolerance for natural noise sources but not novel noise from anthropogenic origins.

Abstract Understanding relationships between physical drivers and biological response is central to advancing ecological knowledge. Wind is the physical forcing mechanism in coastal upwelling systems, however lags between wind input and biological responses are seldom quantified for marine predators. Lags were examined between wind at an upwelling source, decreased temperatures along the upwelling plume’s trajectory, and blue whale occurrence in New Zealand’s South Taranaki Bight region (STB). Wind speed and sea surface temperature (SST) were extracted for austral spring–summer months between 2009 and 2019. A hydrophone recorded blue whale vocalizations October 2016-March 2017. Timeseries cross-correlation analyses were conducted between wind speed, SST at different locations along the upwelling plume, and blue whale downswept vocalizations (D calls). Results document increasing lag times (0–2 weeks) between wind speed and SST consistent with the spatial progression of upwelling, culminating with increased D call density at the distal end of the plume three weeks after increased wind speeds at the upwelling source. Lag between wind events and blue whale aggregations (n = 34 aggregations 2013–2019) was 2.09 ± 0.43 weeks. Variation in lag was significantly related to the amount of wind over the preceding 30 days, which likely influences stratification. This study enhances knowledge of physical-biological coupling in upwelling ecosystems and enables improved forecasting of species distribution patterns for dynamic management.

Few studies have assessed the influence of data quality on the predicted probability of occurrence and preferred habitat of marine predators. We compared results from four species distribution models (SDMs) for four southern-hemisphere albatross species, Buller’s (Thalassarche bulleri), Campbell (T. impavida), grey-headed (T. chrysostoma), and white-capped (T. steadi), based on datasets of differing quality, ranging from no location data to twice-daily locations of individual birds collected by geolocation devices. Two relative environmental suitability (RES) models were fit using minimum and maximum preferred and absolute values for each environmental variable based on (1) monthly 50% kernel density contours and background environmental data, and (2) primary literature or expert opinion. Additionally, two boosted regression tree (BRT) models were fit using (1) opportunistic sightings data, and (2) geolocation data from bird-borne electronic tags. Using model-specific threshold values, habitat was quantified for each species and model. Model variables included distance from land, bathymetry, sea surface temperature, and chlorophyll-a concentration. Results from both RES models and the BRT model fit with opportunistic sightings were compared to those from the BRT model fit using geolocation data to assess the influence of data quality on predicted occupancy and habitat. For all species, BRT models outperformed RES models. BRT models offer a predictive advantage over RES models by being able to identify relevant variables, incorporate environmental interactions, and provide spatially explicit estimates of model uncertainty. RES models resulted in larger, less refined areas of predicted habitat for all species. Our study highlights the importance of data quality in predicting the distribution and habitat of albatrosses and emphasises the need to consider the pros and cons associated with different levels of data quality when using SDMs to inform management decisions. Furthermore, we examine the overlap in preferred habitat predicted by each SDM with fishing effort. We discuss the influence of data quality on predicting the wide-scale distributions of pelagic seabirds and how these impacts could result in different protection measures.

Climate change is a global phenomenon, yet impacts on resource availability to predators may be spatially and temporally diverse and asynchronous. As capital breeders, whales are dependent on dense, predictable prey resources during foraging seasons. An Unusual Mortality Event (UME) of Eastern North Pacific (ENP) gray whales (Eschrichtius robustus) was declared in 2019 due to a dramatic rise in stranded animals, many emaciated. Climate change impacts may have affected prey availability on the primary foraging grounds of ENP gray whales (~20,000 individuals) in the Arctic and sub-Arctic region and in coastal habitats between northern California, USA and British Columbia, Canada where a small sub-group of ENP whales called the Pacific Coast Feeding Group (PCFG; ~230 individuals) forages. To investigate variability of gray whale body condition relative to changing ocean conditions, we compare two datasets of gray whale aerial photogrammetry images collected via Unoccupied Aircraft Systems (UAS) on the ENP wintering grounds in San Ignacio Lagoon, Mexico (SIL; n=111) and on the PCFG feeding grounds in Oregon, USA (n=72) over the same three-year period (2017–2019). We document concurrent body condition improvement of PCFG whales in Oregon while body condition of whales in SIL declined. This result indicates that the UME may have affected ENP whales due to reduced energetic gain on some Arctic/sub-Arctic foraging grounds, while PCFG whales are recovering from poor prey conditions during the NE Pacific marine heatwave event of 2014–2016. Surprisingly, we found that PCFG whales in Oregon had significantly worse body condition than whales in SIL, even when accounting for year and phenology. We derive support for this unexpected finding via photogrammetry analysis of opportunistic aerial images of gray whales on Arctic foraging grounds (n=18) compared to PCFG whales in Oregon (n=30): the body condition of PCFG whales was significantly lower (t=2.96, p=0.005), which may cause PCFG whales to have reduced reproductive capacity or resilience to environmental perturbations compared to ENP whales. Overall, our study elucidates divergent gray whale body condition across sub-groups and time, and we demonstrate the value of UAS to effectively monitor and identify the physiological response of whales to climate change.

Mechanisms promoting coexistence between closely related species are fundamental for maintaining species diversity. Mechanisms of niche differentiation include allochrony which offsets the peak timing of resource utilisation between species. Many studies focus on spatial and temporal niche partitioning during the breeding season, few have investigated the role allochrony plays in influencing interspecific segregation of foraging distribution and ecology between congeneric species during the non-breeding season. We investigated the non-breeding migrations of Snares (Eudyptes robustus) and Fiordland penguins (Eudyptes pachyrhynchus), closely related species breeding between 100–350 km apart whose migration phenology differs by two months. Using light geolocation tracking, we examined the degree of overlap given the observed allochrony and a hypothetical scenario where the species commence migration simultaneously. We found that Fiordland penguins migrated to the Sub-Antarctic Frontal Zone and Polar Frontal Zone in the austral autumn whereas Snares penguins disperse westwards staying north of the Sub-Tropical Front in the austral winter. Our results suggest that allochrony is likely to be at the root of segregation because the relative profitability of the different water masses that the penguins forage in changes seasonally which results in the two species utilising different areas over their core non-breeding periods. Furthermore, allochrony reduces relatively higher levels of spatiotemporal overlap during the departure and arrival periods, when the close proximity of the two species’ colonies would cause the birds to congregate in similar areas, resulting in high interspecific competition just before the breeding season. Available evidence from other studies suggests that the shift in phenology between these species has arisen from adaptive radiation and phenological matching to the seasonality of local resource availability during the breeding season and reduced competitive overlap over the non-breeding season is likely to be an incidental outcome.

Body condition is a crucial and indicative measure of an animal’s fitness, reflecting overall foraging success, habitat quality, and balance between energy intake and energetic investment toward growth, maintenance, and reproduction. Recently, drone-based photogrammetry has provided new opportunities to obtain body condition estimates of baleen whales in one, two or three dimensions (1D, 2D, and 3D, respectively) – a single width, a projected dorsal surface area, or a body volume measure, respectively. However, no study to date has yet compared variation among these methods and described how measurement uncertainty scales across these dimensions. This associated uncertainty may affect inference derived from these measurements, which can lead to misinterpretation of data, and lack of comparison across body condition measurements restricts comparison of results between studies. Here we develop a Bayesian statistical model using known-sized calibration objects to predict the length and width measurements of unknown-sized objects (e.g., a whale). We use the fitted model to predict and compare uncertainty associated with 1D, 2D, and 3D photogrammetry-based body condition measurements of blue, humpback, and Antarctic minke whales – three species of baleen whales with a range of body sizes. The model outputs a posterior predictive distribution of body condition measurements and allows for the construction of highest posterior density intervals to define measurement uncertainty. We find that uncertainty does not scale linearly across multi-dimensional measurements, with 2D and 3D uncertainty increasing by a factor of 1.45 and 1.76 compared to 1D, respectively. Each standardized body condition measurement is highly correlated with one another, yet 2D body area index (BAI) accounts for potential variation along the body for each species and was the most precise body condition metric. We hope this study will serve as a guide to help researchers select the most appropriate body condition measurement for their purposes and allow them to incorporate photogrammetric uncertainty associated with these measurements which, in turn, will facilitate comparison of results across studies.

Predators must consume enough prey to support costly events, such as reproduction. Meeting high energetic requirements is particularly challenging for migrating baleen whales as their feeding seasons are typically restricted to a limited temporal window and marine prey are notoriously patchy. We assessed the energetic value of the six most common nearshore zooplankton species collected within the Oregon, United States range of the Pacific Coast Feeding Group (PCFG) gray whale (Eschrichtius robustus) feeding grounds, and compared these results to the energetic value of the predominant amphipod species fed on by Eastern North Pacific (ENP) gray whales in the Arctic. Energetic values of Oregon zooplankton differed significantly between species (Kruskal–Wallis χ2 = 123.38, df = 5, p < 0.0001), with Dungeness crab (Cancer magister) megalopae displaying the highest mean caloric content of all tested species (4.21 ± 1.27 kJ g– 1). This value, as well as the mean energetic value of the mysid Neomysis rayii (2.42 ± 1.06 kJ g– 1), are higher than the mean caloric content of Ampelisca macrocephala, the predominant Arctic amphipod. Extrapolations of these results to daily energetic requirements of gray whales indicate that lactating and pregnant gray whales feeding in the PCFG range would require between 0.7–1.03 and 0.22–0.33 metric tons of prey less per day if they fed on Dungeness crab megalopae or N. rayii, respectively, than a whale feeding on A. macrocephala in the Arctic. Yet, these results do not account for differences in availability of these prey species to foraging gray whales. We therefore suggest that other factors, such as prey density, energetic costs of feeding, or natal philopatry and foraging site fidelity play a role in the differences in population sizes between the PCFG and ENP gray whales. Climate change is implicated in causing reduced body condition and increased mortality of both PCFG and ENP gray whales due to decreased prey availability and abundance. Therefore, improved understanding of prey dynamics in response to environmental variability in both regions is critical.

Abstract Many cetacean species are at risk from anthropogenic disturbances including climate change, pollution, and habitat degradation. Identifying cetacean hotspots for conservation management is therefore required. Aotearoa–New Zealand waters are used by 53% of the world’s cetacean species and are a global cetacean diversity hotspot. Using geographic predictions of cetacean taxa, we aimed to identify important areas within New Zealand waters using two methods: estimates of cetacean richness and a spatial prioritization analysis. For both methods, we investigated how varying levels of uncertainty in predictions of the taxa’ occurrence layers would affect our interpretation of cetacean hotspots. Despite some marked spatial differences in distribution of important areas for cetacean diversity, both methods, across all uncertainty scenarios, highlighted six distinct deep offshore regions as important habitat. Generally, inshore areas had lower richness estimates than offshore areas, but these remain important for conservation for species with limited ranges (e.g., the endemic Māui and Hector’s dolphins), and in some places had similar richness values to offshore hotspots. Furthermore, inshore hotspots had lower uncertainty in predicted taxa distribution and richness estimates. The use of two different uncertainty estimates allows the integration of distributional information from differing sources (different modeling methods with varying numbers of cetacean records) to be integrated in a robust and conservative way. Identification of cetacean hotspots with varying levels of uncertainty provides a robust and efficient step toward prioritizing areas for conservation management in a participatory process.

To understand how predators optimize foraging strategies, extensive knowledge of predator behavior and prey distribution is needed. Blue whales employ an energetically demanding lunge feeding method that requires the whales to selectively feed where energetic gain exceeds energetic loss, while also balancing oxygen consumption, breath holding capacity, and surface recuperation time. Hence, blue whale foraging behavior is primarily driven by krill patch density and depth, but many studies have not fully considered surface feeding as a significant foraging strategy in energetic models. We collected predator and prey data on a blue whale (Balaenoptera musculus brevicauda) foraging ground in New Zealand in February 2017 to assess the distributional and behavioral response of blue whales to the distribution and density of krill prey aggregations. Krill density across the study region was greater toward the surface (upper 20 m), and blue whales were encountered where prey was relatively shallow and more dense. This relationship was particularly evident where foraging and surface lunge feeding were observed. Furthermore, New Zealand blue whales also had relatively short dive times (2.83 ± 0.27 SE min) as compared to other blue whale populations, which became even shorter at foraging sightings and where surface lunge feeding was observed. Using an unmanned aerial system (UAS; drone) we also captured unique video of a New Zealand blue whale’s surface feeding behavior on well-illuminated krill patches. Video analysis illustrates the whale’s potential use of vision to target prey, make foraging decisions, and orient body mechanics relative to prey patch characteristics. Kinematic analysis of a surface lunge feeding event revealed biomechanical coordination through speed, acceleration, head inclination, roll, and distance from krill patch to maximize prey engulfment. We compared these lunge kinematics to data previously reported from tagged blue whale lunges at depth to demonstrate strong similarities, and provide rare measurements of gape size, and krill response distance and time. These findings elucidate the predator-prey relationship between blue whales and krill, and provide support for the hypothesis that surface feeding by New Zealand blue whales is an important component to their foraging ecology used to optimize their energetic efficiency. Understanding how blue whales make foraging decisions presents logistical challenges, which may cause incomplete sampling and biased ecological knowledge if portions of their foraging behavior are undocumented. We conclude that surface foraging could be an important strategy for blue whales, and integration of UAS with tag-based studies may expand our understanding of their foraging ecology by examining surface feeding events in conjunction with behaviors at depth.

Abstract Baleen whales store energy gained on foraging grounds to support reproduction and other metabolic needs while fasting for long periods during migration. Whale body condition can be used to monitor foraging success, and thus better understand and anticipate individual‐ and population‐level trends in reproduction and survival. We assessed the body condition of eastern North Pacific gray whales (Eschrichtius robustus) on their foraging grounds along the Oregon coast, USA, from June to October of three consecutive years (2016–2018). We used drone photogrammetry and applied the body area index (BAI) to measure and compare whale body condition, which is a continuous, unitless metric similar to the body mass index in humans. A total of 289 drone flights were carried out over 106 photo‐identified whales, which were grouped into demographic units by sex, maturity, and female reproductive status. Calves and pregnant females displayed the highest BAIs, followed by resting females, mature males, and, finally, lactating females, reflecting the significant energetic demands on reproductive females. In all three years, gray whale body condition improved with the progression of feeding seasons, demonstrating the accumulation of body energy reserves on the foraging grounds. Yet, body condition was significantly better in 2016 than in 2017 and 2018 when overall body depletion was observed, indicating a difference in prey availability and/or quality between years. We analyzed local upwelling patterns between 2013 and 2018 as an oceanographic proxy for prey and determined significantly greater upwelling between 2013 and 2015 than low upwelling years between 2016 and 2018. We hypothesize that these upwelling patterns created ecosystem shifts in primary productivity and zooplankton prey of gray whales, causing carry‐over effects between foraging success and body condition in subsequent years. This study demonstrates the value of monitoring whale body condition to better understand temporal variation in foraging success, and potentially detect and describe the causes of anomalous changes in whale population health, such as the 2019 gray whale mortality event.

Skin condition assessment of wildlife can provide insight into individual and population health. Yet, logistics can limit skin condition assessment of large whales. We developed a standardized, quantitative protocol using photographs to assess skin condition of blue whales in New Zealand, and demonstrate the value gained by testing hypotheses, documenting new morphologies, and establishing baselines that can be monitored for change. We reviewed a photo-identification catalog to compile common markings, categorized markings according to existing definitions, and described markings not previously documented. Photographs of blue whale skin (n = 1,466) were assessed to quantify marking prevalence, severity, and co-occurrence patterns. Of the whales assessed (n = 148), 96.6% had cookie cutter shark bites, 80.4% had blister lesions, 56.0% had pigmentation blazes on the dorsal fin, and 33.7% had holes in the dorsal fin. Additionally, 35.8% had “starburst” lesions, a previously undocumented marking. Blister and cookie cutter shark bite severity did not accumulate linearly, indicating that the two marking types are unrelated. There was a positive relationship between blister severity and number of starbursts, indicating that the two could be related; based on morphological similarities, starburst lesions may derive from ruptured blisters. Whales with holes in their dorsal fin had significantly higher blister severity than those without, indicating that these markings could be related; this is supported by observed blisters on dorsal fins of blue whales. There was a significantly higher probability of fresher cookie cutter shark bites on whales observed at more northerly latitudes, but no relationship between blister severity or number of starbursts and latitude. These latitudinal patterns indicate that blue whales in New Zealand accumulate cookie cutter shark bites at more northerly latitudes; this finding is supported by the known range of cookie cutter sharks in New Zealand waters. Of the eight individual whales re-sighted across multiple years, there was no uniform pattern in lesion change over time, however, individual cases revealed lesion healing over a multi-year timeframe. Our protocol for quantifying skin condition can be applied to any cetacean photo-identification catalog, and can be used to compare across individuals and populations, and explore causal links between skin condition and cetacean health.

During traditional boat-based surveys of marine megafauna, behavioral observations are typically limited to records of animal surfacings obtained from a horizontal perspective. Achieving an aerial perspective has been restricted to brief helicopter or airplane based observations that are costly, noisy, and risky. The emergence of commercial small unmanned aerial systems (UAS) has significantly reduced these constraints to provide a stable, relatively quiet, and inexpensive platform that enables replicate observations for prolonged periods with minimal disturbance. The potential of UAS for behavioral observation appears immense, yet quantitative proof of utility as an observational tool is required. We use UAS footage of gray whales foraging in the coastal waters of Oregon, United States to develop video behavior analysis methods, determine the change in observation time enabled by UAS, and describe unique behaviors observed via UAS. Boat-based behavioral observations from 53 gray whale sightings between May and October 2016 were compared to behavioral data extracted from video analysis of UAS flights during those sightings. We used a DJI Phantom 3 Pro or 4 Advanced, recorded video from an altitude ≥25 m, and detected no behavioral response by whales to the UAS. Two experienced whale ethologists conducted UAS video behavioral analysis, including tabulation of whale behavior states and events, and whale surface time and whale visible time (total time the whale was visible including underwater). UAS provided three times more observational capacity than boat-based observations alone (300 vs. 103 min). When observation time is accounted for, UAS data provided more and longer observations of all primary behavior states (travel, forage, social, and rest) relative to boat-based data, especially foraging. Furthermore, UAS enable documentation of multiple novel gray whale foraging tactics (e.g., headstands: n = 58; side-swimming: n = 17; jaw snapping and flexing: n = 10) and 33 social events (nursing and pair coordinated surfacings) not identified from boat-based observation. This study demonstrates the significant added value of UAS to marine megafauna behavior and ecological studies. With technological advances, robust study designs, and effective analytical tools, we foresee increased UAS applications to marine megafauna studies to elucidate foraging strategies, habitat associations, social patterns, and response to human disturbance.

Incidental fisheries bycatch is recognised as a major threat to albatross populations worldwide. However, fishery discards and offal produced in large quantities might benefit some scavenging seabirds. Here, we demonstrate an integrated approach to better understand the ecological ramifications of fine-scale overlap between seabirds and fisheries. As a case study, we examined whether foraging in association with a fishing vessel is advantageous for chick provisioning in terms of quantity of food delivered to chicks, in northern royal albatross (Diomedea sanfordi) at Taiaroa Head, New Zealand. Fine-scale overlap between albatrosses and vessels was quantified by integrating GPS tracking and Vessel Monitoring Systems (VMS). Meal size delivered to chicks was measured using custom-designed nest balances, and monitoring of attendance of adults fitted with radio transmitters was used in conjunction with time-lapse photography at the nest allowed us to allocate each feeding event to a specific parent. The combination of these techniques enabled comparison of meal sizes delivered to chicks with parental foraging trip durations with or without fishing vessels association. A total of 45 foraging trips and associated chick feeding events were monitored during the chick-rearing period in 2012. Differences in the meal size and foraging trip duration relative to foraging overlap with fisheries were examined using a linear mixed-effect model, adjusted for chick age. Our results, based on three birds, suggest that foraging in association with vessels does not confer an advantage for chick feeding for this population that demonstrated low rates of overlap while foraging. The integrated research design presented can be applied to other seabird species that are susceptible to bycatch, and offers a valuable approach to evaluate habitat quality by linking habitat use and foraging success in terms of total amount of food delivered to offspring.

This study investigates the use of a mobile application, Whale mAPP, as a citizen science tool for collecting marine mammal sighting data. In just over three months, 1261 marine mammal sightings were observed and recorded by 39 citizen scientists in Southeast Alaska. The resulting data, along with a preliminary and post-Whale mAPP questionnaires, were used to evaluate the tool’s scientific, educational, and engagement feasibility. A comparison of Whale mAPP Steller sea lion distribution data to a scientific dataset were comparable (91% overlap) given a high enough sample size (n = 73) and dense spatial coverage. In addition, after using Whale mAPP for two weeks, citizen scientists improved their marine mammal identification skills and self-initiated further learning, representing preliminary steps in developing an engaging citizen science project. While the app experienced high initial enthusiasm, maintaining prolonged commitment represents one of the fundamental challenges for this project. Increasing participation with targeted recruitment and sustained communication will help combat the limitations of sample size and spatial coverage. Overall, this study emphasizes the importance of early evaluation of the educational and scientific outcomes of a citizen science project, so that limitations are recognized and reduced.