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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.

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.

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.

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.