Current Projects – Geospatial Ecology of Marine Megafauna Laboratory

How Humans and Cetaceans Shape Each Other

Marc Rams i Rios, PhD Student, Oregon State University Department of Fisheries, Wildlife, and Conservation Sciences, Geospatial Ecology of Marine Megafauna Lab

When I moved to Oregon to begin my PhD, I pictured long days on the water watching gray whales feed and travel along the coast. That does happen, and it is as incredible as I imagined. But I have learned that studying cetaceans is about much more than observing whales. It is also about people: how cultures – past and present – perceive these animals and share space with them.

In addition to marine mammals, I have always loved history and geography. Now, as I start my work with the GRANITE Project in the GEMM Lab, I find myself thinking about how these relationships between humans and whales unfold across time and space. In this post, I want to share a few examples of how whales have shaped human traditions for hundreds, even thousands of years, across societies that have never crossed. Then I will discuss how our research fits into this larger picture of human–cetacean connections.

Our journey begins in India, where the Ganges River dolphin inhabits a river that millions of people consider sacred. Its presence has long been linked to the health of the river, giving the species spiritual and cultural significance. Over the past century, the river’s ecological integrity has declined due to pollution, altered flow, and habitat disturbances, and this has caused the dolphin population to diminish^{1, 2}. Conservation efforts that improve water quality, restore natural flow, and reduce disturbances not only help the dolphin recover but also protect the river and the human communities that rely on it^{1, 2}. In this way, cultural reverence for the dolphin drives conservation measures that benefit both people and ecosystems^{1, 2}.

From there we move to Aotearoa, New Zealand, where Māori tradition speaks of tohorā, or whales, as guardians and ancestors³. They appear in ancestral stories as guides and protectors, and whale strandings have historically brought communities together in collective response. The Māori principles of kaitiakitanga, or guardianship, continue to shape marine conservation decisions today, guiding policies that integrate ecological and cultural values⁴. Here, whales are not seen as resources. They are part of a living genealogy that binds people to the sea and the life it sustains. In fact, team members of the SAPPHIRE project in the GEMM lab frequently engage with multiple iwi (Māori tribes) across Aotearoa through hui (meetings) where knowledge, stories, and culture are shared about blue whales and their ecosystem.

Traveling nearly to the antipodes, we arrive on the Atlantic coast of Brazil, in the town of Laguna, where an extraordinary partnership has endured for centuries. Artisanal fishers work alongside bottlenose dolphins, who drive schools of fish toward the shore and signal the right moment to cast the nets^{5, 6, 7}. This cooperation benefits both species, and the knowledge behind it is passed down through generations of humans and dolphins through observation and shared practice^{5, 6, 7}. It is a powerful example of how species can learn from one another, creating connections that challenge the idea of humans and wildlife as competitors and showing the potential for collaboration across species^{5, 6, 7}. The LABIRINTO Lab in MMI has studied this interspecific relationship for decades, helping us learn about the patterns and endurance of these cultures.

PELD-SELA: Long-term ecological project on the Laguna Estuarine System and Adjacent Areas Projects. (n.d.). https://thelabirinto.com/projects1/

At the top of the Americas, in the Arctic, Inuit communities have hunted bowhead whales for thousands of years. These hunts are not only a source of food but also form the foundation of cultural identity and social life⁸. Knowledge of the ice, weather, and whale behavior is passed down through generations, and the hunt itself is embedded in ceremonies and practices that sustain the community⁸. Today, these traditions continue under strict quotas set through international agreements, carefully balancing cultural continuity with conservation⁹. The MMBEL lab in MMI studies the communication and ecology of bowhead whales to support the survival of this iconic species and the culture of Inuit people.

Finally, our journey brings us to Oregon, where gray whales feed along a coastline rich with reefs, kelp beds, and sandy bottoms. These waters support a variety of human activities, from commercial fishing to recreation, creating risks such as entanglement, vessel strikes, and disturbance^{10, 11}. Even well-intentioned actions like whale watching can cause harm if not carefully managed^{12, 13}. Around the world, many communities have shifted from whaling to whale watching, transforming former hunting grounds into tourism destinations. While this is a positive change, it still requires monitoring. Noise can stress whales, boats can disrupt their behavior, and too much interaction can alter natural feeding and social patterns^{12, 13}. In Oregon, research on gray whale habitat use and feeding home ranges helps inform management and conservation¹⁴.

Tradewind Charters Whale Watching and Fishing

This is where project GRANITE, Gray whale Response to Ambient Noise Informed by Technology and Ecology, comes in¹⁵. The project studies how whales respond to human activities by using drones to monitor health and behavior, photo-ID to track individuals, prey mapping to understand feeding choices, and acoustic recorders to capture the soundscape^{15, 16, 17}. Equally important is collaborating directly with fishers and resource managers to reduce risks and develop solutions that benefit both whales and people. Healthy whale populations support communities too, through ecotourism, cultural continuity, education, and the ecological services whales provide. Conservation is reciprocal: caring for whales strengthens the ocean systems that sustain us all.

The tools and techniques developed by GRANITE, including drones, acoustic monitoring, and prey mapping, are not limited to Oregon. They can be applied globally, contributing to the protection of cetaceans in diverse habitats¹⁵. In this way, Oregon becomes more than the final stop on our tour. It is a place where centuries of human–whale relationships, lessons from around the world, and modern science converge. These examples across the world remind us that conservation is about more than preventing harm. It is about fostering a future where humans and whales thrive together, as they have shared the ocean for millennia.

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References

¹Sinha, R. K., & Kannan, K. (2014). Ganges river dolphin: An overview of biology, ecology, and conservation status in India. AMBIO, 43(8), 1029–1046. https://doi.org/10.1007/s13280-014-0534-7

²Braulik, G., Atkore, V., Khan, M. S., & Malla, S. (2021). Review of scientific knowledge of the Ganges river dolphin. WWF. https://riverdolphins.org/wp-content/uploads/2021/07/Ganges-River-dolphin-Scientific-Knowledge-Review-July2021.pdf

³Taonga, N. Z. M. for C. and H. T. M. (n.d.). Whales in Māori tradition. Teara.govt.nz. https://teara.govt.nz/en/te-whanau-puha-whales/page-1

⁴ McAllister, T., Hikuroa, D., & Macinnis‑Ng, C. (2023). Connecting science to Indigenous knowledge: Kaitiakitanga, conservation, and resource management. New Zealand Journal of Ecology, 47(1), 3521. https://doi.org/10.20417/nzjecol.47.3521

⁵Simões‑Lopes, P. C., Fabián, M. E., & Menegheti, J. O. (1998). Dolphin interactions with the mullet artisanal fishing on southern Brazil: A qualitative and quantitative approach. Revista Brasileira de Zoologia, 15(3), 709–726. https://doi.org/10.1590/S0101-81751998000300008

⁶Daura Jorge, F. G., Cantor, M., Ingram, S. N., Lusseau, D., & Simões Lopes, P. C. (2012). The structure of a bottlenose dolphin society is coupled to a unique foraging cooperation with artisanal fishermen. Biology Letters, 8(5), 702–705. https://doi.org/10.1098/rsbl.2012.0174

⁷Cantor, M., Farine, D. R., & Daura‑Jorge, F. G. (2023). Foraging synchrony drives resilience in human–dolphin mutualism. Proceedings of the National Academy of Sciences, 120(6), e2207739120. https://doi.org/10.1073/pnas.2207739120

⁸Jensen, A. M. (2012). The material culture of Iñupiat whaling: An ethnographic and ethnohistorical perspective. Arctic Anthropology, 49(2), 143–161. https://doi.org/10.1353/arc.2012.0020

⁹Description of the USA Aboriginal Subsistence Hunt: Alaska. (n.d.). Iwc.int. https://iwc.int/management-and-conservation/whaling/aboriginal/usa/alaska

¹⁰Derville, S., Buell, T. V., Corbett, K. C., Hayslip, C., & Torres, L. G. (2023). Exposure of whales to entanglement risk in Dungeness crab fishing gear in Oregon, USA. Biological Conservation, 281, 109989. https://doi.org/10.1016/j.biocon.2023.109989

¹¹Silber, G. K., Weller, D. W., Reeves, R. R., Adams, J. D., & Moore, T. J. (2021). Co‑occurrence of gray whales and vessel traffic in the North Pacific Ocean. Endangered Species Research, 44, 177–201. https://doi.org/10.3354/esr01093

¹²Sullivan, F. A., & Torres, L. G. (2018). Assessment of vessel disturbance to gray whales to inform sustainable ecotourism. Journal of Wildlife Management, 82(5), 896–905. https://doi.org/10.1002/jwmg.21462

¹³Sprogis, K. R., Videsen, S., & Madsen, P. T. (2020). Vessel noise levels drive behavioural responses of humpback whales with implications for whale‑watching. eLife, 9, e56760. https://doi.org/10.7554/eLife.56760

¹⁴Lagerquist, B. A., Palacios, D. M., Winsor, M. H., Irvine, L. M., Follett, T. M., & Mate, B. R. (2019). Feeding home ranges of Pacific Coast Feeding Group gray whales. Journal of Wildlife Management, 83(4), 925–937. https://doi.org/10.1002/jwmg.21642

¹⁵GRANITE: Gray whale Response to Ambient Noise Informed by Technology and Ecology | Marine Mammal Institute | Oregon State University. (n.d.). Mmi.oregonstate.edu. https://mmi.oregonstate.edu/gemm-lab/granite-gray-whale-response-ambient-noise-informed-technology-ecology

¹⁶Pirotta, E., Bierlich, K. C., New, L., Bird, C. N., Fernandez Ajó, A., Hildebrand, L., Buck, C. L., Hunt, K. E., Calambokidis, J., & Torres, L. G. (2025). Body size, nutritional state and endocrine state are associated with calving probability in a long‑lived marine species. Journal of Animal Ecology. Advance online publication. https://doi.org/10.1111/1365-2656.70068

¹⁷Bierlich, K. C., Kane, A., Hildebrand, L., Bird, C. N., Fernandez Ajó, A., Stewart, J. D., Hewitt, J., Hildebrand, I., Sumich, J., & Torres, L. G. (2023). Downsized: Gray whales using an alternative foraging ground have smaller morphology. Biology Letters, 19(7), 20230043. https://doi.org/10.1098/rsbl.2023.0043

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The Final Chapter: Concluding a PhD

By Rachel Kaplan, PhD candidate, Oregon State University College of Earth, Ocean, and Atmospheric Sciences and Department of Fisheries, Wildlife, and Conservation Sciences, Geospatial Ecology of Marine Megafauna Lab

At the beginning of a graduate program, it’s common for people to tell you how quickly the time will pass, but hard to imagine that will really be the case. Suddenly, I’ve been working on my PhD for almost five years, and I’ll defend in just over two weeks. As I look back, I am amazed by how much I have learned and grown during this time, and how all the different parts of my graduate school experience have woven together. I began my program in 2020 with an intense “bootcamp” of oceanographic coursework, and am ending in 2025 with new analytical skills, a few publications, and a ton of new thoughts about whales and the zooplankton krill, the subjects of my research. My PhD work encapsulates all those different elements in an exploration of ecological relationships between baleen whale predators and their krill prey – which I now see as an expression of oceanographic and atmospheric processes.

Figure 1. One of my favorite sightings during my PhD fieldwork was a group of seven fin whales in Antarctica, on Christmas 2024. Photo: Rachel Kaplan

Oceanographic processes drive prey quantity and quality across time and space, shaping the preyscape encountered by predators on their foraging grounds and driving habitat use (Fleming et al., 2016; Ryan et al., 2022). Aspects of prey including distribution, energy density, and biomass therefore represent mechanistic links between ocean and atmospheric conditions (e.g., El Niño Southern Oscillation cycles, circulation patterns, and upwelling processes) and diverse aspects of marine predator ecology, including spatiotemporal distributions, foraging behaviors, reproductive success, population size, and health. Both predator and prey species are impacted by environmental variability and climate change (e.g., Hauser et al., 2017; Atkinson et al., 2019; Perryman et al., 2021), and events like marine heatwaves and harmful algal blooms can force ecosystem changes on short, seasonal time scales (e.g. McCabe et al., 2016; Fisher et al., 2020). However, many marine species have some degree of plasticity that allows them to still accomplish life history events in the face of ecosystem variability (e.g., Lawrence, 1976; Oestreich, 2022), which may provide the capacity to adapt to climate change processes.

Observing and describing predator-prey relationships is complex due to the scale-dependent nature of these relationships (Levin, 1992). Each chapter of my dissertation considered krill, a globally-important prey type, from the perspective of baleen whales, which are krill predators. Chapter 2 used a comparative analysis to identify the optimal spatial scale at which to observe baleen whale-krill relationships on the Northern California Current (NCC) foraging grounds. We found correlations at a 5 km scale to be strongest, which can provide a useful starting point for further studies in the NCC and other systems. Chapter 3 used this spatial scale to compare several aspects of krill prey quality and quantity as predictors of humpback whale (Megaptera novaeangliae) distributions in the NCC. The best performing metric was a species, season, and spatially informed krill swarm biomass variable – yet the comparable performance of a simple acoustic abundance metric indicated that it can act as a reliable proxy for biomass. This finding may be advantageous for future research, as measuring the acoustic proxy is less computationally intensive and relies on fewer datastreams. Interestingly, one of this study’s best-performing models was based on only the proportion of Thysanoessa spinifera in krill swarms, which is also a highly accessible variable due to effective krill species distribution modeling in the NCC (Derville et al., 2024). Integrating the acoustic abundance proxy and krill species distribution predictions, two relatively simple metrics, could support predictions of humpback whale distributions in the NCC and inform whale-prey research in other ecosystems.

Figure 2. Collecting samples of individual krill gave us the opportunity to learn about their quality as prey for whales in the Northern California Current. Photo: Courtney Flatt

Studies relating predator foraging to prey characteristics often rely on metrics such as prey biomass or energy density (Schrimpf et al., 2012; Savoca et al., 2021; Cade et al., 2022), but the tendency of krill to form aggregations introduces dimensionality to krill prey quality. Chapter 4 showed that elements of krill swarm structure (particularly depth, proportion of T. spinifera, and metrics describing how krill occupy space within swarms) may be mechanistic drivers of variable blue, fin and humpback whale distribution patterns on the NCC foraging grounds. These findings suggest that krill swarm characteristics may be important links between baleen whales and the foraging environment. Swarm characteristics may be considered a component of krill prey quality for baleen whales, and future research could illuminate direct causal relationships between oceanographic conditions, krill swarming responses, and niche expression in baleen whale predators.

The relationships between baleen whale distributions and krill quantity and quality explored in the first chapters of my dissertation may also shed light on other aspects of baleen whale ecology. The final chapter considers overwintering trends in global baleen whale populations, and examines the wintertime Western Antarctic Peninsula (WAP) as a case study. Extended humpback whale presence on the WAP feeding grounds may be driven by the profitable feeding areas and elevated energy content of krill during the winter months, and may reflect the high energetic needs of certain demographic subgroups (e.g. lactating females, juveniles). Wintertime humpback whale presence may also reflect adaptation to multifaceted competitive pressure on krill resources that are declining due to climate change (Atkinson et al., 2019), including consumption by growing baleen whale populations (Johnston et al., 2011) and a fishery whose catch limits may be impacting krill predators (Watters et al., 2020; Savoca et al., 2024). This work demonstrates how investigating prey quality during the winter months can contextualize baleen whale overwintering on the foraging grounds. It also provides a meaningful violation of the canonical baleen whale migration paradigm central to marine mammal science, which may lessen the efficacy of whale monitoring programs and management policies.

Figure 3. We were surprised to see humpback whales like this one in Antarctica during the winter months — which raised a number of questions about overwintering of baleen whales on foraging grounds around the world. Photo: Giulia Wood

Management efforts that aim to mitigate risk to whales often hinge on predictive modeling of whale distributions. Species distribution models (SDMs) can provide managers with spatially and temporally explicit predictions of protected species occurrences (Wikgren et al., 2014; Santora et al., 2020), but species distributions in rapidly changing ecosystems are difficult to predict (Muhling et al., 2020). Findings from this dissertation may inform modeling efforts by suggesting meaningful predictor variables for SDMs, such as krill species on the NCC foraging grounds and swarm energy density at the WAP. This work also speaks to meaningful spatial scales for analyzing predator-prey relationships (i.e., 5 km), and relevant elements of temporal variability (e.g., seasonal cycles of krill energy density).

Just as marine predator-prey relationships are shaped by ocean processes, they likewise have consequences for those processes. For example, krill and other zooplankton are capable of generating large-scale mixing that can overcome stratification of water masses and alter water column structure (Noss and Lorke, 2014). Baleen whales influence global carbon cycles due to the huge amount of prey they consume (Savoca et al., 2021; Pearson et al., 2023) and transport important nutrients along the “great whale conveyer belt” during their vast migrations (Roman et al., 2025). Baleen whales seek krill as an essential prey resource on foraging grounds around the globe, and the impact of this trophic interaction scales up, with implications for ecosystem functioning and management. Continued research into the spatiotemporally dynamic relationships between krill and baleen whales improves our understanding of ocean functioning, and can improve our capacity to live as part of this system.

References

Atkinson, A., Hill, S. L., Pakhomov, E. A., Siegel, V., Reiss, C. S., Loeb, V. J., Steinberg, D. K., et al. 2019. Krill (Euphausia superba) distribution contracts southward during rapid regional warming. Nature Climate Change, 9: 142–147.

Cade, D. E., Kahane-Rapport, S. R., Wallis, B., Goldbogen, J. A., and Friedlaender, A. S. 2022. Evidence for Size-Selective Predation by Antarctic Humpback Whales. Frontiers in Marine Science, 9: 747788.

Derville, S., Fisher, J. L., Kaplan, R. L., Bernard, K. S., Phillips, E. M., and Torres, L. G. 2024. A predictive krill distribution model for Euphausia pacifica and Thysanoessa spinifera using scaled acoustic backscatter in the Northern California Current. Progress in Oceanography: 103388.

Fisher, J. L., Menkel, J., Copeman, L., Shaw, C. T., Feinberg, L. R., and Peterson, W. T. 2020. Comparison of condition metrics and lipid content between Euphausia pacifica and Thysanoessa spinifera in the northern California Current, USA. Progress in Oceanography, 188.

Fleming, A. H., Clark, C. T., Calambokidis, J., and Barlow, J. 2016. Humpback whale diets respond to variance in ocean climate and ecosystem conditions in the California Current. Glob Chang Biol, 22: 1214–24.

Hauser, D. D. W., Laidre, K. L., Stafford, K. M., Stern, H. L., Suydam, R. S., and Richard, P. R. 2017. Decadal shifts in autumn migration timing by Pacific Arctic beluga whales are related to delayed annual sea ice formation. Global Change Biology, 23: 2206–2217.

Johnston, S. J., Zerbini, A. N., and Butterworth, D. S. 2011. A Bayesian approach to assess the status of Southern Hemipshere humpback whales (Megaptera novaeangliae) with an application to Breeding Stock G. J. Cetacean Res. Manage.: 309–317. International Whaling Commission.

Lawrence, J. M. 1976. Patterns of Lipid Storage in Post-Metamorphic Marine Invertebrates. American Zoologist, 16: 747–762. Oxford University Press (OUP).

Levin, S. A. 1992. The Problem of Pattern and Scale in Ecology: The Robert H. MacArthur Award Lecture. Ecology, 73: 1943–1967.

McCabe, R. M., Hickey, B. M., Kudela, R. M., Lefebvre, K. A., Adams, N. G., Bill, B. D., Gulland, F. M., et al. 2016. An unprecedented coastwide toxic algal bloom linked to anomalous ocean conditions. Geophys Res Lett, 43: 10366–10376.

Muhling, B. A., Brodie, S., Smith, J. A., Tommasi, D., Gaitan, C. F., Hazen, E. L., Jacox, M. G., et al. 2020. Predictability of Species Distributions Deteriorates Under Novel Environmental Conditions in the California Current System. Frontiers in Marine Science, 7.

Noss, C., and Lorke, A. 2014. Direct observation of biomixing by vertically migrating zooplankton. Limnology and Oceanography, 59: 724–732. Wiley.

Oestreich, W. 2022. Acoustic signature reveals blue whales tune life‐history transitions to oceanographic conditions. Functional Ecology. https://besjournals.onlinelibrary.wiley.com/doi/10.1111/1365-2435.14013 (Accessed 20 September 2024).

Pearson, H. C., Savoca, M. S., Costa, D. P., Lomas, M. W., Molina, R., Pershing, A. J., Smith, C. R., et al. 2023. Whales in the carbon cycle: can recovery remove carbon dioxide? Trends in Ecology & Evolution, 38: 238–249.

Perryman, W. L., Joyce, T., Weller, D. W., and Durban, J. W. 2021. Environmental factors influencing eastern North Pacific gray whale calf production 1994–2016. Marine Mammal Science, 37: 448–462. Wiley.

Roman, J., Abraham, A. J., Kiszka, J. J., Costa, D. P., Doughty, C. E., Friedlaender, A., Hückstädt, L. A., et al. 2025. Migrating baleen whales transport high-latitude nutrients to tropical and subtropical ecosystems. Nature Communications, 16: 2125. Nature Publishing Group.

Ryan, J. P., Benoit-Bird, K. J., Oestreich, W. K., Leary, P., Smith, K. B., Waluk, C. M., Cade, D. E., et al. 2022. Oceanic giants dance to atmospheric rhythms: Ephemeral wind-driven resource tracking by blue whales. Ecology Letters, 25: 2435–2447.

Santora, J. A., Mantua, N. J., Schroeder, I. D., Field, J. C., Hazen, E. L., Bograd, S. J., Sydeman, W. J., et al. 2020. Habitat compression and ecosystem shifts as potential links between marine heatwave and record whale entanglements. Nat Commun, 11: 536.

Savoca, M. S., Czapanskiy, M. F., Kahane-Rapport, S. R., Gough, W. T., Fahlbusch, J. A., Bierlich, K. C., Segre, P. S., et al. 2021. Baleen whale prey consumption based on high-resolution foraging measurements. Nature, 599: 85–90.

Savoca, M. S., Kumar, M., Sylvester, Z., Czapanskiy, M. F., Meyer, B., Goldbogen, J. A., and Brooks, C. M. 2024. Whale recovery and the emerging human-wildlife conflict over Antarctic krill. Nature Communications, 15: 7708. Nature Publishing Group.

Schrimpf, M., Parrish, J., and Pearson, S. 2012. Trade-offs in prey quality and quantity revealed through the behavioral compensation of breeding seabirds. Marine Ecology Progress Series, 460: 247–259.

Watters, G. M., Hinke, J. T., and Reiss, C. S. 2020. Long-term observations from Antarctica demonstrate that mismatched scales of fisheries management and predator-prey interaction lead to erroneous conclusions about precaution. Scientific Reports, 10: 2314.

Wikgren, B., Kite-Powell, H., and Kraus, S. 2014. Modeling the distribution of the North Atlantic right whale Eubalaena glacialis off coastal Maine by areal co-kriging. Endangered Species Research, 24: 21–31.

New GEMM Lab study indicates troubled times for PCFG gray whales

Dr. Enrico Pirotta (CREEM, University of St Andrews) and Dr. Leigh Torres (GEMM Lab, MMI, OSU)

The health of animals affects their ability to survive and reproduce, which, in turn, drives the dynamics of populations, including whether their abundance trends up or down. Thus, understanding the links between health and reproduction can help us evaluate the impact of human activities and climate change on wildlife, and effectively guide our management and conservation efforts. In long-lived species, such as whales, once a decline in population abundance is detected, it can be too late to reverse the trend, so early warning signals are needed to indicate how these populations are faring.

We worked on this complex issue in a study that was recently published in the Journal of Animal Ecology. In this paper, we developed a new statistical approach to link three key components of the health of a Pacific Coast Feeding Group (PCFG) gray whale (namely, its body size, body condition, and stress levels) to a female’s ability to give birth to a calf. We were able to inform these metrics of whale health using an eight-year dataset derived from the GRANITE project of aerial images from drones for measurements of body size and condition, and fecal samples for glucocorticoid hormone analysis as an indicator of stress. We combined these data with observations of females with or without calves throughout the PCFG range over our study period.

We found that for a female to successfully have a calf, she needs to be both large and fat, as these factors indicate if the female has enough energy stored to support reproduction that year (Fig. 1). Remarkably, we also found indication that females with particularly high stress hormone levels may not get pregnant in the first place, which is the first demonstration of a link between stress physiology and vital rates in a baleen whale, to our knowledge.

Figure 1. Taken from Pirotta et al. (2025), Fig. 5. Combined relationship of PCFG gray whale length and nutritional state (combination of body size and condition) in the previous year with calving probability, colored by whether the model estimated an individual to have calved or not at a given reproductive opportunity.

Our study’s findings are concerning given our previous research indicating that gray whales in this PCFG sub-group have been growing to shorter lengths over the last couple of decades (Pirotta et al. 2023), are thinner than animals in the broader Eastern North Pacific gray whale population (Torres et al, 2022), and show an increase in stress-related hormones when exposed to human activities (Lemos et al, 2022; Pirotta et al. 2023). Furthermore, in our recent study we also documented that there are fewer young individuals than expected for a growing or stable population (Fig. 2), which can be an indicator of a population in decline since there may not be many individuals entering the reproductive adult age groups. Altogether, our results act as early warning signals that the PCFG may be facing a possible population decline currently or in the near future.

Figure 2. Taken from Pirotta et al. (2025), Fig. 1. Age structure diagram for 139 PCFG gray whales in our dataset. Each bar represents the number of individuals of a given age in 2023, with the color indicating the proportion of individuals of that age for which age is known (vs. estimated from a minimum estimate following Pirotta, Bierlich, et al., 2024). The red line reports a smooth kernel density estimate of the distribution.

These findings are sobering news for Oregon residents and tourists who enjoy watching these whales along our coast every summer and fall. We have gotten to know many of these whales so well – like Scarlett, Equal, Clouds, Lunita, and Pacman, who you can meet on our IndividuWhale website – that we wonder how they will adapt and survive as their once reliable habitat and prey-base changes. We hope our work sparks collective and multifaceted efforts to reduce impacts on these unique PCFG whales, and that we can continue the GRANITE project for many more years to come to monitor these whales and learn from their response to change.

This work exemplifies the incredible value of long-term studies, interdisciplinary methods, and effective collaboration. Through many years of research on this gray whale group, we have collected detailed data on diverse aspects of their behavior, ecology and life history that are critical to understanding their response to disturbance and environmental change, which are both escalating in the study region. We are incredibly grateful to the following members of the PCFG Consortium for contributing sightings and calf observation data that supported this study: Jeff Jacobsen, Carrie Newell, NOAA Fisheries (Peter Mahoney and Jeff Harris), Cascadia Research Collective (Alie Perez), Department of Fisheries and Oceans, Canada (Thomas Doniol-Valcroze and Erin Foster), Mark Sawyer and Ashley Hoyland, Wendy Szaniszlo, Brian Gisborne, Era Horton.

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References:

Lemos, Leila S., Joseph H. Haxel, Amy Olsen, Jonathan D. Burnett, Angela Smith, Todd E. Chandler, Sharon L. Nieukirk, Shawn E. Larson, Kathleen E. Hunt, and Leigh G. Torres. “Effects of Vessel Traffic and Ocean Noise on Gray Whale Stress Hormones.” Scientific Reports 12, no. 1 (2022): 18580. https://dx.doi.org/10.1038/s41598-022-14510-5.

Pirotta, Enrico, K. C. Bierlich, Leslie New, Lisa Hildebrand, Clara N. Bird, Alejandro Fernandez Ajó, and Leigh G. Torres. “Modeling Individual Growth Reveals Decreasing Gray Whale Body Length and Correlations with Ocean Climate Indices at Multiple Scales.” Global Change Biology 30, no. 6 (2024): e17366. https://doi.org/https://doi.org/10.1111/gcb.17366. https://onlinelibrary.wiley.com/doi/abs/10.1111/gcb.17366.

Pirotta, Enrico, Alejandro Fernandez Ajó, K. C. Bierlich, Clara N Bird, C Loren Buck, Samara M Haver, Joseph H Haxel, Lisa Hildebrand, Kathleen E Hunt, Leila S Lemos, Leslie New, and Leigh G Torres. “Assessing Variation in Faecal Glucocorticoid Concentrations in Gray Whales Exposed to Anthropogenic Stressors.” Conservation Physiology 11, no. 1 (2023). https://dx.doi.org/10.1093/conphys/coad082.

Torres, Leigh G., Clara N. Bird, Fabian Rodríguez-González, Fredrik Christiansen, Lars Bejder, Leila Lemos, Jorge Urban R, et al. “Range-Wide Comparison of Gray Whale Body Condition Reveals Contrasting Sub-Population Health Characteristics and Vulnerability to Environmental Change.” Frontiers in Marine Science 9 (2022). https://doi.org/10.3389/fmars.2022.867258. https://www.frontiersin.org/article/10.3389/fmars.2022.867258

The whale’s scale: Emphasizing the scale of process, not the scale of observation

By Lisa Hildebrand, PhD candidate, OSU Department of Fisheries, Wildlife, & Conservation Sciences, Geospatial Ecology of Marine Megafauna Lab

Baleen whales must navigate a seemingly featureless world to locate the resources they need to survive. The task of finding prey to feed on in the vast seascapes relies on the use of several sensory modalities that operate at different scales (Torres 2017; Figure 1). For example, baleen whale vision is believed to be rather limited, with the ability to see objects about 10-100 meters away. Yet, baleen whale somatosensory perception of oceanographic stimuli is thought to be on the order of 100-1000s kilometers. This diversity in sensory ability has led scientists to believe that whales, in fact all animals, perceive cues and make decisions at several scales. As ecologists, we endeavor to understand why and when animals are found (or not found) in certain locations as this knowledge allows us to better manage and conserve animal populations. With this information we can aim to minimize potential anthropogenic disturbance and protect important resource areas, such as foraging or nursing grounds. In order to accomplish this goal, we ourselves must conduct studies and test hypotheses at several scales (Levin 1992; Hobbs 2003). As someone who tackles spatial foraging ecology questions, I am particularly interested in understanding whale behavior and movement in the context of feeding. Since accurately measuring predator and prey distribution at the same scales can be challenging, we often resort to environmental variables to serve as proxies for prey, whereby we look for correlations between environmental variables and whales to understand and predict the distribution of our population.

***Figure 1.*** Schematic of hypothetical interchange of sensory modalities used by baleen whales to locate prey at variable scales. X-axis represents log distance to prey from micro (left) to macro (right). Y-axis represents the relative use of each sensory modality between 0 (no contribution) to 10 (highest contribution). Each line and color represent a different sensory modality. Figure taken and caption adapted from Torres 2017.

What do I mean when I use the word ‘scale’? The term scale is typically explained by two components: grain and extent (Wiens 1989). The grain is the finest resolution measured; in other words, how detailed we are measuring. The extent is the overall coverage of what we are measuring. These components can be applied to both spatial scale and temporal scale. For example, spatially, if we were using a 1×1 meter sampling quadrat to count the number of crabs on a rocky shore, then our grain would be the 1 m² quadrat and the extent would be the entire exposed rocky intertidal area that we are surveying (Figure 2). Temporally, if we placed a temperature logger at the mouth of Yaquina Bay that took a temperature recording every minute for two years, then our grain would be one minute and the extent would be two years. So, when designing a study, it is imperative for us to decide on the spatiotemporal scales of the ecological questions we are asking and the hypotheses we are testing, as it will inform what data we need to collect. When making this decision, it is important to think about the scale at which the ecological process happens, as opposed to the scale at which we can observe the process (Levin 1992). In other words, we need to think from the perspective of our study species, as opposed to from our own human perspective. Making informed and ecologically reasonable decisions regarding the choice of scale relies on having prior knowledge of an animal’s biology, such as knowing that baleen whales might see a prey patch that is 50 meters away, but it may also somatosensorily perceive an oceanic front where zooplankton prey aggregate from 500 kilometers away.

***Figure 2.*** Schematic of spatial scale where the extent (depicted by dashed orange box) is the entire exposed rocky intertidal area being surveyed and the grain (solid yellow box) is the 1×1 m quadrat being used to count crabs.

There is a wealth of studies that have explored space use patterns of wildlife relative to environmental variables to better understand foraging behavior. I want to share a couple from the marine mammal realm with you that I find particularly fascinating. In their 2018 study, González García and colleagues used opportunistic sightings of blue whales around the Azorean islands of Portugal and modeled their distribution patterns relative to physiographic and oceanographic variables summarized at different spatial (fine [1-10 km] and meso [10-100 km]) and temporal (daily, weekly, monthly) scales. The two variables that were most correlated with blue whale occurrence was distance from the coast and eddy kinetic energy (a measure of mesoscale variability of ocean dynamics). Both of these variables were interestingly found to be scale invariant, meaning that no matter which spatial and temporal scale was investigated, the relationship between blue whales and these two variables stayed the same; blue whale occurrence increased with increasing distance from the coast and was maximal at an eddy kinetic energy value of 0.007 cm²/s² (Figure 3).

***Figure 3.*** Functional response curves between presence of Azorean blue whales and distance to the coast (panel 1 on left) and eddy kinetic energy (panel 2 on right). The top row of each panel represents the low spatial scale and the bottom row represents the high spatial scale. Each column represents a different temporal scale (from left to right: daily, weekly, monthly). Note that the general shape of the relationship remains similar across all spatiotemporal scales and that the peak of the curves tend to occur at the same values for distance to coast and eddy kinetic energy across all scales. Figures taken from González García et al. 2018.

However, not all studies find scale invariant relationships. For example, Cotté and co-authors (2009) found that habitat use of Mediterranean fin whales was very much scale dependent. At a large scale (700-1,000 km and annual), fin whales were more densely aggregated during the summer in the Western Mediterranean where there was consistently colder water than in the winter. However, at a meso scale (20-100 km and weekly-monthly), fin whale densities were highest in areas where there were steep changes in temperature, as opposed to consistently cold temperatures. The authors explain that these differences in fin whale density and temperature at different scales are likely due to whale movement being driven by annually persistent prey abundance at the large scale, but at the meso scale, where prey aggregations are less predictable, the fin whales’ distribution becomes more driven by areas of physical ocean mixing.

As I investigate the environmental drivers of individual gray whale space use using our 8-year GRANITE (Gray whale Response to Ambient Noise Informed by Technology and Ecology) dataset, these studies (and many more) are at the top of my mind to interpret the patterns we are detecting. Our goal is to quantify and describe what environmental conditions (1) lead to a higher probability of a gray whale being seen in our central Oregon coast study area (~70 km) at a daily scale, and (2) influence space use patterns (activity range, residency, activity center) of different individual whales at annual scales. Our results show both consistency and variation in the environmental drivers of gray whales across these scales, leading me to deeply consider how gray whales make decisions at different points in their lives, based on information gained through various senses, to maximize their chances of capturing food. Previous work from the GEMM Lab on the relationships between gray whales and prey, at both fine (read more here) and large (read more here) scales have guided my work by providing specific hypotheses regarding environmental variables and lag times for me to test. Investigating the environmental drivers of animal space use and behavior is exciting work as it reveals that no single environmental variable determines animal distribution, but rather that multiple processes are happening concomitantly that animals respond to at different scales continually. It is only by studying animal space use patterns across spatiotemporal scales that we can begin to understand their complex decision-making patterns.

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References

Cotté, C., Guinet, C., Taupier-Letage, I., Mate, B., & Petiau, E. (2009). Scale-dependent habitat use by a large free-ranging predator, the Mediterranean fin whale. Deep Sea Research Part I: Oceanographic Research Papers, 56(5), 801-811.

González García, L., Pierce, G. J., Autret, E., & Torres-Palenzuela, J. M. (2018). Multi-scale habitat preference analyses for Azorean blue whales. PLoS One, 13(9), e0201786.

Hobbs, N. T. (2003). Challenges and opportunities in integrating ecological knowledge across scales. Forest Ecology and Management, 181(1-2), 223-238.

Levin, S. A. (1992). The problem of pattern and scale in ecology: the Robert H. MacArthur award lecture. Ecology, 73(6), 1943-1967.

Torres, L. G. (2017). A sense of scale: Foraging cetaceans’ use of scale‐dependent multimodal sensory systems. Marine Mammal Science, 33(4), 1170-1193.

Wiens, J. A. (1989). Spatial scaling in ecology. Functional ecology, 3(4), 385-397.

New publication shows humpback whale distribution in the Northern California Current is related to krill swarm biomass, energetic density, and species composition

What does a whale look for at mealtime? Is it a lot of food, its quality, or the type of food? An improved understanding of what makes krill swarms, an important prey item, appetizing for humpback whales can help us anticipate where and when we will see them in our ocean backyard, the Northern California Current (NCC) foraging grounds. In a new paper, we found that humpback whale presence in the NCC is tied to several different metrics of krill swarm quality and quantity, particularly species composition (what types of krill are in the swarm), energetic density (the caloric richness of the average mouthful), and biomass (how much krill is in the swarm). Interestingly, relationships between humpback whales and these krill swarm quality metrics are variable in time and space, dependent on whether the whale is foraging on or off the continental shelf and if it is early or late in the foraging season.

This study required a special, fine-scale dataset of simultaneous observations of krill and whales at sea. While GEMM Lab members conducted marine mammal surveys, we simultaneously observed the prey that whales had access to, using active acoustics (essentially a fancy fish finder) to profile the water column and net tows to collect krill. When we put all these data streams together, we found that increases in biomass, energetic density, and the amount of a particular species, Thysanoessa spinifera, in a krill swarm were positively related to humpback whale presence. These results suggest that humpback whales balance multiple prey quality factors to select feeding areas that offer both plentiful and high-quality krill.

Figure 1. Top photo: Marine mammal observers Clara Bird (left) and Dawn Barlow (right) collect humpback whale distribution data. Bottom photo: At the same time, Talia Davis (left) and Rachel Kaplan (right) collect krill samples.

Species composition

Euphausia pacifica and T. spinifera are the two most common krill species in the NCC region, and other research has shown that many krill foragers, including blue whales, seabirds, and fish, preferentially consume T. spinifera. Although this pickiness is well-warranted – individual T. spinifera tend to be larger than E. pacifica and much higher in calories during the late foraging season – targeting this juicy prey item could place humpback whales in competition with these other species, which may make it harder for them to find a square meal. Nevertheless, we found positive relationships between the proportion of T. spinifera in a krill swarm and humpback whale presence, suggesting humpback whales do in fact preferentially prey upon T. spinifera, particularly during the late foraging season (about July-November).

Energetic density

Humpback whales’ preference for T. spinifera during the late foraging season may be due to its higher caloric content. Although the two krill species offer a similar number of calories early in the foraging season,we found that the energetic density of T. spinifera was elevated during the late foraging season, after productive upwelling conditions have revved up the food web over several months. Krill swarm energetic density had a positive effect on humpback whale occurrence, particularly in the late season when T. spinifera and E. pacifica have significantly different caloric contents. Interestingly, this positive relationship was not present onshore during the early season, when the two krill species have similar caloric contents.

*Figure 2. In terms of caloric content,* Thysanoessa spinifera krill like this one are the winners in the NCC region! They pack on the milligrams through the productive summer season, making them advantageous prey for hungry whales.

Humpback whales also target forage fish on the continental shelf that have higher energetic densities than krill, indicating that whales may selectively forage on fish – even though it is more energetically expensive to capture them. Variation in seasonal and spatial relationships with krill swarm energetic density may explain why humpback whales prey-switch, selecting prey based on availability and quality. As flexible foragers, humpback whales can consistently target higher-quality swarms that offer more energy per lunge.

Biomass

Biomass, or the total amount of krill in a swarm, was the single best predictor of humpback whale presence that we tested. This result emphasizes the importance of large krill swarms in explaining where humpback whales forage. We found that krill swarm biomass tended to be higher offshore, where swarms were also located deeper in the water column. During the late season offshore, krill quality (elevated due to higher late season caloric contents) together with quantity (higher offshore biomass) may make these offshore swarms the most favorable for foraging whales, despite being deeper.

*Figure 3. When humpback whales “fluke,” as seen in this picture, it may indicate the beginning of a foraging dive to capture prey.*

Future food webs

Environmental conditions are changing in the NCC, with events like marine heatwaves and strong El Niño events shifting food webs. E. pacifica and T. spinifera may respond to climate change differently based on their life history strategies. Distributional shifts, such as the disappearance of T. spinifera from the NCC during the 2014–2015 “Blob” marine heatwave that transformed the northeast Pacific Ocean, could diminish or entirely remove this key prey item. As a result of such climate and environmental changes, humpback whales may encounter lower quality prey and/or shifts in prey distribution that could make it harder for them to find a meal. In changing oceans, better understanding krill prey quality for humpback whales will shape improved tools for conservation management.

References

Chenoweth, E., Boswell, K., Friedlaender, A., McPhee, M., Burrows, J., Heintz, R., and Straley, J. 2021. Confronting assumptions about prey selection by lunge‐feeding whales using a process‐based model. Funct. Ecol., 35.

Croll, D., Marinovic, B., Benson, S., Chavez, F., Black, N., Ternullo, R., and Tershy, B. 2005. From wind to whales: trophic links in a coastal upwelling system. Mar. Ecol. Prog. Ser., 289: 117–130.

Derville, S., Buell, T. V., Corbett, K. C., Hayslip, C., and Torres, L. G. 2023. Exposure of whales to entanglement risk in Dungeness crab fishing gear in Oregon, USA, reveals distinctive spatio-temporal and climatic patterns. Biol. Conserv., 281: 109989.

Fiedler, P. C., Reilly, S. B., Hewitt, R. P., Demer, D., Philbrick, V. A., Smith, S., Armstrong, W., et al. 1998. Blue whale habitat and prey in the California Channel Islands. Deep Sea Res. Part II, 45: 1781–1801.

Murdoch, W. W. 1969. Switching in General Predators: Experiments on Predator Specificity and Stability of Prey Populations. Ecol. Monog., 39: 335–354.

Nickels, C. F., Sala, L. M., and Ohman, M. D. 2018. The morphology of euphausiid mandibles used to assess selective predation by blue whales in the southern sector of the California Current System. J. Crustacean Biol., 38: 563–573.

Price, S. E., Savoca, M. S., Kumar, M., Czapanskiy, M. F., McDermott, D., Litvin, S. Y., Cade, D. E., et al. 2024. Energy densities of key prey species in the California Current Ecosystem. Front. Mar. Sci., 10: 1345525.

Robertson, R. R., and Bjorkstedt, E. P. 2020. Climate-driven variability in Euphausia pacifica size distributions off northern California. Prog. Oceanogr., 188.

Spitz, J., Trites, A. W., Becquet, V., Brind’Amour, A., Cherel, Y., Galois, R., and Ridoux, V. 2012. Cost of Living Dictates what Whales, Dolphins and Porpoises Eat: The Importance of Prey Quality on Predator Foraging Strategies. PLoS ONE, 7: e50096.

Tanasichuk, R. 1998a. Interannual variations in the population biology and productivity of Thysanoessa spinifera in Barkley Sound, Canada, with special reference to the 1992 and 1993 warm ocean years. Mar. Ecol. Prog. Ser., 173: 181–195.

Videsen, S. K. A., Simon, M., Christiansen, F., Friedlaender, A., Goldbogen, J., Malte, H., Segre, P., et al. 2023. Cheap gulp foraging of a giga-predator enables efficient exploitation of sparse prey. Sci. Adv., 9: eade3889.

Weber, E. D., Auth, T. D., Baumann-Pickering, S., Baumgartner, T. R., Bjorkstedt, E. P., Bograd, S. J., Burke, B. J., et al. 2021. State of the California Current 2019–2020: Back to the Future With Marine Heatwaves? Front. Mar. Sci., 8.

Are Most Whale Entanglements “Out of Sight, Out of Mind?”

By Lindsay Wickman, Postdoctoral Scholar, Oregon State University Department of Fisheries, Wildlife, and Conservation Sciences, Geospatial Ecology of Marine Megafauna Lab

Earlier this month, most of the GEMM Lab and I attended the 25th Biennial Conference on the Biology of Marine Mammals in Perth, Western Australia. This year’s theme, “Fishing for Change,” acknowledged that incidental entanglement in fishing gear is currently the most pervasive threat to marine mammals (e.g., Avila et al., 2018). While many presentations on the prevalence and impacts of entanglement on marine mammals were sobering, it was also inspiring to be surrounded by so many dedicated people working to address this urgent issue. For me, one of the most memorable anecdotes was an incredible whale disentanglement story shared by Paul Cottrell, a Marine Mammal Coordinator at the Department of Fisheries and Oceans Canada (DFO) in British Columbia.

An Incredible Story of Whale Disentanglement

During August 2024, DFO and a local NGO (Straitwatch) responded to a report of two humpback whales entangled in the same fishing gear near Quadra Island, B.C., Canada. Their photo-identification histories revealed that one whale had migrated from Hawaii, while the other had come from Mexico. Now tied together, the two whales’ fates became intertwined, forcing them to coordinate their movements. This situation obviously raised concerns about their welfare and survival, but I also had to silently wonder, “Did the two whales ever argue about where to migrate next? Would they choose Hawaii or Mexico?”

Thanks to the rescuers’ efforts, both whales were freed and able to make their own choice about where to spend the breeding season. As Paul explained, successfully disentangling one whale is challenging and dangerous, so freeing two was an impressive feat. After the rescue, a video showed the whales continuing to swim together synchronously, as if they did not realize they were no longer connected!

Most Entangled Whales are Out of Sight

The story above exemplifies a “confirmed” entanglement—these whales were seen dragging fishing gear and the event was reported by concerned citizens. However, most entanglement events are never witnessed, for several reasons.

When a whale becomes entangled in fishing gear, it rarely remains anchored in place. Instead, the whale often breaks part of the gear, dragging it behind as it swims. The likelihood of observing the entangled whale subsequently depends on both the chance of it being seen and the observer’s awareness and willingness to report the event (Robbins and Mattila, 2004).

*An entangled humpback whale drags gear off of San Diego, California. Credit: Keith Yip, taken under NOAA Permit #18786*.

Once entangled, many become a “dead whale swimming,” eventually succumbing to starvation and/or infections (Dolman and Moore, 2017). Many entanglements involve the mouth, severely impacting the whale’s ability to feed (Moore and van der Hoop, 2012). The additional drag imposed by entanglement is comparable to the energetic costs of migration or reproduction, causing a significant depletion in their energy reserves (van der Hoop et al. 2015). Serious injuries include amputations, hemorrhage, and infections (Cassoff et al., 2011).

Although some carcasses of entangled whales wash ashore, most are lost at sea and never recovered. For example, even with relatively intensive monitoring for North Atlantic right whale (NARW) carcasses, Pace et al. (2021) estimated that recovered carcasses represented just 36% of the total deaths. These recovered carcasses may also underestimate the toll of entanglement; entanglement accounted for 51% of mortality in the carcasses vs. 87% of serious injuries observed in living NARWs (Pace et al., 2021).

For whales that manage to dislodge the gear and survive, scars can provide clues to their past entanglement history. Injuries from the fishing lines can leave indentations where they cut through skin and blubber, and healed wounds often result in white pigmented scars that wrap around the body (especially the flukes and peduncle; e.g., Robbins and Matilla 2004). The widespread prevalence of these scars suggests that in many cases, whales can actually dislodge the gear on their own. For example, a study of entanglement scars on humpback whales in the Gulf of Maine revealed that 10% of adults and 30% of juveniles acquired new entanglement scars between 2009-2010. Without scarring analyses though, most of these entanglements would have been missed; just 7% of these individuals with entanglement-related scars were seen while entangled (Robbins 2012).

*A humpback whale fluke and peduncle showing scarring likely caused by a past entanglement. Credit: GEMM lab, taken under NOAA Permit # 27426 issued to MMI.*

Unfortunately, scars are not the only long-term consequence of non-lethal entanglement events. Previously entangled NARWs have lower survival rates than unaffected individuals (Robbins et al. 2015, Reed et al. 2024), and long-term stress responses can impact their future health and reproductive success (Pettis et al. 2004). It is tempting to assume that only severe entanglements affect future reproduction and survival, but a lack of extensive external injuries doesn’t necessarily mean that the impact of the entanglement event is more minor (Robbins and Matilla, 2004). For example, Reed et al. (2024) found that NARWs with entanglement injuries classified as minor were less likely to transition from a “non-breeder” to “breeder” status than those with severe injuries.

Tracking Unseen Entanglements: Project SLATE

Since reported entanglements and recovered carcasses reveal just a fraction of actual entanglements, researchers are continuing to innovate ways of documenting these “unseen” entanglement events.

As discussed in a previous blog post, photos of entanglement scars on the flukes and peduncles of humpback whales are being utilized in Project SLATE to detect trends in entanglement off the coast of Oregon, USA. Analyzing images of whales for signs of past entanglements is a meticulous process that may not seem as thrilling as responding to an actual disentanglement event. However, in areas with lower population densities, such as the Oregon coast, reported entanglements are undoubtedly an underestimate of the true number of events. Thus, tracking scarring rates can provide more comprehensive data on entanglement prevalence in Oregon than confirmed reports alone.

What to do if you see an entangled whale

If you happen to observe an entangled whale, please do not attempt to disentangle it yourself. Whale disentanglement is dangerous and complex, so best left to the experts! When well-meaning citizens attempt a disentanglement on their own, it can also result in an “incomplete disentanglement,” where some, but not all, gear is removed from the whale. Incomplete disentanglements just make it harder for responders to subsequently find and successfully rescue the whale.

Instead, report the entanglement by promptly calling:

Entanglement Reporting Hotline: 1-877-SOS-WHAL or 1-877-767-9425
or U.S. Coast Guard: VHF Ch. 16

Videos or photos showing the entangling gear is very helpful to trained responders, but remember to stay at least 100 yards from the whale, and beware of snagging your vessel in the lines. Visit NOAA Fisheries for more information.

*A NOAA-led team disentangle a humpback whale near Dutch Harbor, Alaska. Credit: Andy Dietrick/NOAA, taken under NOAA Permit #18786.*

References:

Avila, I.C., Kaschner, K., Dormann, C.F.. (2018). Current global risks to marine mammals: Taking stock of the threats. Biol. Conserv. 221, 44–58.

Cassoff, R.M., Moore, K.M., McLellan, W.A., Barco, S.G., Rotstein, D.S., Moore, M.J. (2011). Lethal entanglement in baleen whales. Dis. Aquat. Organ. 96, 175–185.

Dolman, Sarah J., and Michael J. Moore. (2024). Chapter 4: Welfare implications of cetacean bycatch and entanglements. In A. Butterworth (Ed.) Marine Mammal Welfare: Human Induced Change in the Marine Environment and Its Impacts on Marine Mammal Welfare (pp. 41-65).

Moore, M. J., and van der Hoop, J. M. (2012). The painful side of trap and fixed net fisheries: chronic entanglement of large whales. Journal of Marine Sciences, 2012.

Pace III, R. M., Williams, R., Kraus, S. D., Knowlton, A. R., & Pettis, H. M. (2021). Cryptic mortality of North Atlantic right whales. Conservation Science and Practice, 3(2), e346

Reed, J., New, L., Corkeron, P., Harcourt, R. (2024). Disentangling the influence of entanglement on recruitment in North Atlantic right whales. Proc. R. Soc. B Biol. Sci. 291.

Robbins, J., Mattila, D. (2004). Estimating humpback whale (Megaptera novaeangliae) entanglement rates on the basis of scar evidence. Rep. to Northeast Fish. Sci. Center, Natl. Mar. Fish. Serv. 43EANF030121 22p.

Robbins, J. (2012). Scar-Based Inference Into Gulf of Maine Humpback Whale Entanglement : 2010. Report to the Northeast Fisheries Science Center National Marine Fisheries Service, EA133F09CN0253 Item 0003AB, Task 3.

van der Hoop JM, Corkeron P, Kenney J, Landry S, Morin D, Smith J, Moore MJ. (2015). Drag from fishing gear entangling North Atlantic right whales. Mar Mamm Sci 32(2):619–642.

Hearing Gray: Diving into the Sonic World of the Gray Whale

By Natalie Nickells, visiting PhD Student, British Antarctic Survey

For the last three months, I’ve been lucky enough to be welcomed into the GEMM lab as a visiting PhD student to work on the acoustic data from hydrophones in CATS tags deployed on gray whales. This work has been a huge change for me! I’ve gone from studying Antarctic baleen whale foraging, the topic of my PhD, from a distance at my desk in Cambridge England, to studying PCFG gray whales in Newport- and finally being in the same country, state, and even county to the whales I am studying! Unlike my Antarctic research, where whale blows in the distance become tiny points in a sea of data, listening to the CATS tag data has allowed me to really connect with these animals on an emotional level, as I’ve spent days, weeks and months listening to the world as they hear it.

Humans are fundamentally visual creatures- we take in information through sight first, with hearing probably our second, or for some even third, sense in line. However, for marine mammals, the same cannot be said: their world is auditory first. This fact is an important realisation to get our heads around, highlighted beautifully by the phrase “the ears are the window to the soul of the whale” (Sonic Sea (2017)) or Tim Donaghy’s emotive statement that “a deaf whale is a dead whale”. High levels of ocean noise therefore have a huge impact on baleen whales. Imagine trying to do your groceries or find a friend while blindfolded or in a thick fog– you might struggle to access food or communicate with others, and your stress would certainly be high. To succeed, you would likely need to change your behaviour.

Behavioural changes in response to ocean noise are observed in baleen whales: for example, humpback whales change their foraging behaviour when ship noise increases (Blair et al., 2016), and gray whales have been shown to call more frequently and possibly more loudly in conditions of high ocean noise (Dahlheim & Castellote, 2016). However, even in the absence of notable behaviour change due to ocean noise, North Atlantic right whales may still be experiencing a stress response. When shipping traffic in the Bay of Fundy significantly decreased in the aftermath of 9/11, North Atlantic right whales in the area had decreased chronic stress levels (Rolland et al., 2012).

Previous work by the GEMM lab observed this stress response to ocean noise in gray whales. They found a correlation between high levels of glucocorticoid (a stress indicator) in male gray whale faeces with high vessel noise and vessel counts in the area. Vessel noise was measured using two static hydrophones off the Oregon coast, and it was assumed all animals in the area experienced the same noise (Lemos et al., 2022; Pirotta et al., 2023). However, a static hydrophone is an imperfect measure of the sound levels a mobile animal experiences, particularly as we might expect animals to change behaviour when disturbed (Sullivan & Torres, 2018). This previous work became the starting point for the question I have addressed during my time in the GEMM Lab: can we measure and characterise the sound levels an individual whale was exposed to? Enter CATS tags. These are suction-cup tags fitted with a host of sensors, which have been used by the GEMM lab since 2021 (see Image 1). So far, they have mostly been used for their accelerometry data (Colson et al. (in press), see also Kate’s blog post). However, the GEMM lab had the foresight to put hydrophones on these tags, and as a result I was welcomed into the lab by a bumper-crop of hydrophone data just waiting to be analysed!

*Image 1: A gray whale (“Slush”) being tagged with a CATS tag and Natalie (right) with the same tag.*

This tag data is particularly valuable, not only for its ability to follow the acoustic world of an individual whale, but also due to the whole suite of data that comes with the acoustics: essentially, the acoustic data comes with behavioural data. Or at least, it comes with data from which we can infer behaviour (Colson et al, in press)! Incorporating behaviour into passive acoustics work hugely strengthens its ecological usefulness (Oestreich et al., 2024). We can hear what an individual whale is hearing, and we can also infer what they were doing before, during, and after they heard or made that sound. Having behavioural data also means that we can ground-truth the sounds we hear. When hearing an interesting sound, I can go back to the video data and accelerometer data to check what the whale sees, what its body-position is doing (e.g., is it headstand foraging?) and the speed and direction of its travel. Context is key!

The importance of context was highlighted in my very first week here in the GEMM lab. I became very interested in a sound I could hear frequently when the whale would surface- a distorted bark-like noise, but the whale was surely too far offshore for any barking dog to be heard? And almost every time the whale surfaced? After a few days pondering, I shared my mystery with Leigh, who laughingly revealed that one of the whale-watching boats in this area has a ‘whale-alerting’ dog on board! Sometimes if it sounds like a dog… it’s a dog! Besides my slightly anticlimactic discovery of dogs barking, committing time to listening to the tags and hearing what the whales hear, has been a magical experience. My favourite hydrophone sound, that still gets me excited when I hear it, is the gray whale ‘bongo call’- or as it’s more formally known in the literature, M1 vocalisation (Guazzo et al., 2019). I’ll let you decide which name is more appropriate! I first heard this call when investigating a time on “Scarlett’s” tag when we knew her 14 year-old daughter “Pacman” had been close: about 15 minutes before “Pacman” appears on the video, Scarlett makes this call (you can play the clip below to listen). In “Lunita’s” tag, we even hear this call three times in a row!

Image 2: A ‘bongo call’ made by “Scarlett” when her daughter “Pacman” was nearby.

Relatively little research has been done on gray whale calls compared to other more studied species like humpbacks. Most of this research has taken place on gray whale migratory routes (Guazzo et al., 2019, 2017; Burnham et al. 2018) or in captivity (Fish et. al, 1974 ) so these tag recordings could be a valuable addition to a small sample from the foraging grounds (Clayton et al., 2023; Haver et al., 2023)- as well as being very personally exciting to hear!

We’ve also been able to use the tag hydrophone data to look at close calls with ships. As I was going through the data on “Scarlett’s” tag, I noticed a spike in vessel noise. Looking at the video from the same timestamp, I could see a small vessel passing directly over her as she surfaced. At the time this vessel passed over her, the tag was only 0.8 m under the surface of the water!

Image 3: A close encounter between a small vessel and “Scarlett”, shown both on the video from the CATS tag (top) and the spectrogram (bottom). The close call is outlined in a yellow box, when a greater intensity of noise occurred as illustrated by the brighter colour intensity compared to the white box (quieter vessel noise). Brighter colours denote a louder volume. The red boxes show surfacing noise- this can essentially be ignored when interpreting the echogram for our purposes.

Sometimes vessels may be more distant, but possibly equally harmful: we have seen vessel noise from larger and presumably more distant vessels dominate the soundscape in some of the tag data. Remembering that to a whale, the sonic world is as important as the visual world is to us, this elevated background noise from ships could have major consequences. So, the first step is to try to quantify the gray whales’ exposure to this vessel noise. I’ve been running some systematic sampling on the tag data to try to quantify background noise levels, and how this changes depending on the time of day: do individual whales experience the same daily spikes in ocean noise that were detected on the static hydrophones, at around 6am and noon due to vessel traffic (Haver et al., 2023)? If not, are they taking evasive action to avoid these spikes? These are just some of the questions that these CATS tags can help us answer, although ideally we need longer acoustic data recordings to capture day and night data, as well as potentially improving the hydrophones on the CATS tags themselves to minimise the impacts of tag interference and random noise.

When explaining to the public what it is to be a PhD student, I often refer to myself as a ‘scientist in training’, or to young children, a ‘baby scientist’. As I look toward my departure from the GEMM lab, I hope to have developed into at least a scientific toddler, having gained the ability to walk through reams of acoustic data with (relative) independence. More than that, I’m excited to take home a refreshed sense of curiosity about what drives marine mammals to behave as they do, an openness to collaboration and new approaches, and a large dose of ‘American emotion’! Let’s hope my British colleagues can handle it!

My heartfelt thanks to all those who welcomed me so warmly at the GEMM lab and Oregon State University, particularly my mentors Leigh Torres and Samara Haver.

Bibliography

Sonic Sea (2017) Directed by Michelle Dougherty [Film] Distributed by the Natural Resources Defense Council.

Blair, H.B., Merchant, N.D., Friedlaender, A.S., Wiley, D.N. & Parks, S.E. (2016) Evidence for ship noise impacts on humpback whale foraging behaviour. Biology Letters. 12 (8), 20160005. doi:10.1098/rsbl.2016.0005.

Burnham, R., Duffus, D. & Mouy, X. (2018) Gray Whale (Eschrictius robustus) Call Types Recorded During Migration off the West Coast of Vancouver Island. Frontiers in Marine Science. 5, 329. doi:10.3389/fmars.2018.00329.

Colson, K., E. Pirotta L. New, D Cade, J Calambokidis, K. Bierlich, C Bird, A Fernandez Ajó, L. Hildebrand, A. Trites, L. Torres. (in press). Using accelerometry tags to quantify gray whale foraging behavior. Marine Mammal Science.

Clayton, H., Cade, D.E., Burnham, R., Calambokidis, J. & Goldbogen, J. (2023) Acoustic behavior of gray whales tagged with biologging devices on foraging grounds. Frontiers in Marine Science. 10, 1111666. doi:10.3389/fmars.2023.1111666.

Dahlheim, M. & Castellote, M. (2016) Changes in the acoustic behavior of gray whales Eschrichtius robustus in response to noise. Endangered Species Research. 31, 227–242. doi:10.3354/esr00759.

Fish, J.F., Sumich, J.L. & Lingle, G.L. (n.d.) Sounds Produced by the Gray Whale, Eschrichtius robustus.

Guazzo, R., Schulman-Janiger, A., Smith, M., Barlow, J., D’Spain, G., Rimington, D. & Hildebrand, J. (2019) Gray whale migration patterns through the Southern California Bight from multi-year visual and acoustic monitoring. Marine Ecology Progress Series. 625, 181–203. doi:10.3354/meps12989.

Guazzo, R.A., Helble, T.A., D’Spain, G.L., Weller, D.W., Wiggins, S.M. & Hildebrand, J.A. (2017) Migratory behavior of eastern North Pacific gray whales tracked using a hydrophone array S. Li (ed.). PLOS ONE. 12 (10), e0185585. doi:10.1371/journal.pone.0185585.

Haver, S.M., Haxel, J., Dziak, R.P., Roche, L., Matsumoto, H., Hvidsten, C. & Torres, L.G. (2023) The variable influence of anthropogenic noise on summer season coastal underwater soundscapes near a port and marine reserve. Marine Pollution Bulletin. 194, 115406. doi:10.1016/j.marpolbul.2023.115406.

Lemos, L.S., Haxel, J.H., Olsen, A., Burnett, J.D., Smith, A., Chandler, T.E., Nieukirk, S.L., Larson, S.E., Hunt, K.E. & Torres, L.G. (2022) Effects of vessel traffic and ocean noise on gray whale stress hormones. Scientific Reports. 12 (1), 18580. doi:10.1038/s41598-022-14510-5.

Oestreich, W.K., Oliver, R.Y., Chapman, M.S., Go, M.C. & McKenna, M.F. (2024) Listening to animal behavior to understand changing ecosystems. Trends in Ecology & Evolution. S0169534724001459. doi:10.1016/j.tree.2024.06.007.

Pirotta, E., Fernandez Ajó, A., Bierlich, K.C., Bird, C.N., Buck, C.L., Haver, S.M., Haxel, J.H., Hildebrand, L., Hunt, K.E., Lemos, L.S., New, L. & Torres, L.G. (2023) Assessing variation in faecal glucocorticoid concentrations in gray whales exposed to anthropogenic stressors S. Cooke (ed.). Conservation Physiology. 11 (1), coad082. doi:10.1093/conphys/coad082.

Rolland, R.M., Parks, S.E., Hunt, K.E., Castellote, M., Corkeron, P.J., Nowacek, D.P., Wasser, S.K. & Kraus, S.D. (2012) Evidence that ship noise increases stress in right whales. Proceedings of the Royal Society B: Biological Sciences. 279 (1737), 2363–2368. doi:10.1098/rspb.2011.2429.

Sullivan, F.A. & Torres, L.G. (2018) Assessment of vessel disturbance to gray whales to inform sustainable ecotourism. The Journal of Wildlife Management. 82 (5), 896–905. doi:10.1002/jwmg.21462.

Burning Krillories – Determining Krill Caloric Content in New Zealand’s South Taranaki Bight

By Nina Mahalingam, University of California Davis, OSU CEOAS REU program

Hello! I’m Nina Mahalingam, a rising junior at the University of California, Davis studying biochemistry and molecular biology. Growing up in New Hampshire and Massachusetts, the Boston Aquarium was practically in my backyard – and with just one feel of a touch tank, a lifelong affinity for marine sciences began. CEOAS has provided me with a grand opportunity to pursue this passion, and I can’t wait to dip my toes into the salt water!

Figure 1. Nina posing with a Parr Semimicro Calorimeter.

Here at OSU, I’m researching how our tiny friends, the krill, can provide a krill-uminating perspective on trophic ecology and the vitality of marine ecosystems by investigating the caloric content of an understudied species of krill off the coast of New Zealand. Nyctiphanes australis serves as a key prey species to numerous higher trophic levels. Limited knowledge exists regarding the distribution of N. australis in the South Taranaki Bight (STB), with only a handful of studies focused exclusively on the species. The majority of recent information available on the species in the STB came out of research on blue whales and their foraging behaviors (e.g., Barlow et al., 2020). However, given that the spatial distribution of N. australis directly influences the distribution of predator species that depend on them for sustenance (Barlow et. al. 2020), studying the krill may yield a more comprehensive understanding of blue whale behavior as well as ecosystem resilience.

Figure 2. Nyctiphances australis. Photo by A. Slotwinski, CSIRO.

Seawater temperatures around New Zealand have been increasing since 1981 (Sutton & Bowen, 2019), and there is a growing concern about the implications to marine life. In particular, increasing ocean temperatures have had significant impacts on local aquaculture and fisheries (Sutton et al. 2005; Bowen et al. 2017). Although warming trends along the North Island, north of East Cape, have been more severe (around 0.4℃ increase per decade), warming has also been observed in the central and western areas of the STB, averaging around 0.15-0.20℃ increase per decade (Sutton & Bowen, 2019). During Marine Heat Waves (MHWs) (data collected between 2002 and 2018), warming anomalies were observed to decrease phytoplankton presence (Chiswell & Sutton, 2020). Being krill’s primary food source, this suggests a consequent decrease in krill health and reproduction. A recent study on blue whale reproductive patterns in the STB found that whale feeding activity decreased during MHWs, leading to a decline in their reproductive activity during the following breeding season (Barlow et al., 2020). Concurrently, the study observed that there were less krill aggregations and that they were less dense on average (Barlow et al., 2020). This is presumed to be a result of less upwelling nutrients, and therefore poor conditions for krill feeding and reproduction. These findings indicate that the absence of their primary food source, krill, during MHWs can lead to severely negative consequences for the blue whale populations (Barlow et al., 2023).

Anthropogenic activity in the STB, including high vessel traffic, as well as petroleum and mineral exploration and extraction activities, has also been identified as a threat to the local blue whale population (Torres et. al., 2013). Given the cultural significance of the blue whales in this region, there is an urgent need for improved, dynamic management practices in the STB that can be achieved using predictive models to forecast blue whale spatial distribution. Using environmental factors to inform predictive spatial distribution models (SDMs) of blue whales (Redfern et al. 2006, Elith & Leathwick 2009), Barlow et al. (2021) designed a blue whale forecasting tool for managers and decision-makers in New Zealand.

Given the ecological and cultural significance of blue whales and their krill prey in the STB, a Project SAPPHIRE (Synthesis of Acoustics, Physiology, Prey, and Habitat in a Rapidly changing Environment) was developed to examine the impacts of climate change on the health of these crucial species. The overarching goal of Project SAPPHIRE is to measure prey (krill) and predator (blue whales) response to environmental change off the coast of New Zealand. Despite forecasts of high probability of occurrence of blue whales in the STB during the first field season conducted in January-February 2024, both the blue whales and their krill prey were scarce, and it is currently unclear why. My research will focus on examining the calorie content of N. australis in order to advance understanding of how they fulfill the energetic needs of blue whales. Thus, this data can inform future SDMs to forecast impacts of climate change on New Zealand’s marine ecosystem.

Figure 3. Map of SAPPHIRE’s survey effort for 2024. Gray lines represent visual tracking, dotted lines represent aerial tracking. Red dots represent whale sightings and purple stars indicate where two hydrophones were deployed.

This project has already proven tricky – but I’m ready to embrace the challenge. I would like to thank the CEOAS REU program as well as my mentors Kim Bernard, Rachel Kaplan, and Abby Tomita for their continued support. I can’t wait to see what this summer brings!

References

Barlow DR, Klinck H, Ponirakis D, Branch TA, Torres LG. 2023. Environmental conditions and marine heatwaves influence blue whale foraging and reproductive effort. Ecol Evol. 2023;13:e9770.

Barlow D, Kim S. Bernard, Pablo Escobar-Flores, Daniel M. Palacios, Leigh G. 2020. Torres Links in the trophic chain: modeling functional relationships between in situ oceanography, krill, and blue whale distribution under different oceanographic regimes. Marine Ecology Progress Series.

Sutton, P.J.H., & Bowen, M. 2019. Ocean temperature change around New Zealand over the last 36 years. New Zealand Journal of Marine and Freshwater Research, 53(3), 305–326.

Sutton P.J.H., Bowen M, Roemmich D. 2005. Decadal temperature changes in the Tasman Sea. New Zealand Journal of Marine and Freshwater Research. 39:1321–1329.

Bowen M, Markham J, Sutton P, Zhang X, Wu Q, Shears N, Fernandez D. 2017. Interannual variability of sea surface temperatures in the Southwest Pacific and the role of ocean dynamics. Journal of Climate.

Stephen M. Chiswell & Philip J. H. Sutton. 2020. Relationships between long-term ocean warming, marine heat waves and primary production in the New Zealand region. New Zealand Journal of Marine and Freshwater Research.

A Summer of Crustacean Investigation

By Matoska Silva, OSU Department of Integrative Biology, CEOAS REU Program

My name is Matoska Silva, and I just finished my first year at Oregon State University studying biology with a focus in ecology. This summer will be my first experience with marine ecology, and I’m eager to dive right in. I’m super excited for the opportunity to research krill due to the huge impacts these tiny organisms have on their surrounding ecosystems. The two weeks I’ve spent in the CEOAS REU so far have been among the most fun and informative of my life, and I can’t wait to see what else the summer has in store for me.

Figure 1. Matoska presents his proposed research to the CEOAS REU program.

I’ve spent most of my life in Oregon, so I was thrilled to learn that my project would focus on krill distribution along the Oregon Coast that I know and love. More specifically, my project focuses on the Northern California Current (NCC, the current found along the Oregon Coast) and the ways that geographic distribution of krill corresponds to climatic conditions in the region. Here is a synopsis of the project:

The NCC system, which spans the west coast of North America from Cape Mendocino, California to southern British Columbia, is notable for seasonal upwelling, a process that brings cool, nutrient-rich water from the ocean depths to the surface. This process provides nutrients for a complex marine food web containing phytoplankton, zooplankton, fish, birds, and mammals (Checkley & Barth, 2009). Euphausiids, commonly known as krill, are among the most ecologically important zooplankton groups in the NCC, playing a vital role in the flow of nutrients through the food web (Evans et al., 2022). Euphausia pacifica and Thysanoessa spinifera are the predominant krill species in the NCC, with T. spinifera mainly inhabiting coastal waters and E. pacifica inhabiting a wider range offshore (Brinton, 1962). T. spinifera individuals are typically physically larger than E. pacifica and are generally a higher-energy food source for predators (Fisher et al., 2020).

Temperature has been previously established as a major factor impacting krill abundance and distribution in the NCC (Phillips et al., 2022). Massive, ecosystem-wide changes in the NCC have been linked to extreme warming brought on by the 2014-2016 marine heatwave (Brodeur et al., 2019). Both dominant krill species have been shown to respond negatively to warming events in the NCC, with anomalous warm temperatures in 2014-2016 being linked to severe declines in E. pacifica biomass and with T. spinifera nearly disappearing from the Oregon Coast (Peterson et al., 2017). Changes in normal seasonal size variation and trends toward smaller size distributions in multiple age groups have been observed in E. pacifica in response to warming in northern California coastal waters (Robertson & Bjorkstedt, 2020).

The El Niño-Southern Oscillation (ENSO) is a worldwide climatic pattern that has been linked to warming events and ecosystem disturbances in the California Current System (McGowan et al., 1998). El Niño events of both strong and weak intensity can result in changes in the NCC ecosystem (Fisher et al., 2015). Alterations in the typical zooplankton community accompanying warm water conditions and a decline in phytoplankton have been recorded in the NCC during weak and strong El Niño occurrences (Fisher et al., 2015). A strong El Niño event occurred in 2023 and 2024, with three-month Oceanic Niño Index means reaching above 1.90 from October 2023 to January 2024 (NOAA Climate Prediction Center, https://www.cpc.ncep.noaa.gov/data/indices/oni.ascii.txt).

Figure 2. A graph of the ONI showing variability across two decades. Retrieved from NOAA at https://www.climate.gov/news-features/understanding-climate/climate-variability-oceanic-nino-index

While patterns in krill responses to warming have been described from previous years, the effects of the 2023-2024 El Niño on the spatial distribution of krill off the Oregon coast have not yet been established. As climate models have predicted that strong El Niño events may become more common due to greenhouse warming effects (Cai et al., 2014), continuing efforts to document zooplankton responses to El Niño conditions are vital for understanding how the NCC ecosystem responds to a changing climate. By investigating krill spatial distributions in April 2023, during a period of neutral ENSO conditions following a year of La Niña conditions, and April 2024, during the 2023-2024 El Niño event, we can assess how recent ENSO activity has impacted krill distributions in the NCC. In addition to broader measures of ENSO, we will examine records of localized sea surface temperatures (SST) and measurements of upwelling activity during April 2023 and 2024.

Understanding spatial distribution of krill aggregations is both ecologically and economically relevant, with implications for both marine conservation and management of commercial fisheries. Modeling patterns in the distribution of krill species and their predators has potential to inform marine management decisions to mitigate human impacts on marine mammals like whales (Rockwood et al., 2020). The data used to identify krill distribution were originally collected as part of the Marine Offshore Species Assessments to Inform Clean Energy (MOSAIC) project. The larger MOSAIC initiative centers around monitoring marine mammals and birds in areas identified for possible future development of offshore wind energy infrastructure. The findings of this study could aid in the conservation of krill consumers during the implementation of wind energy expansion projects. Changes in krill spatial distribution are also important for monitoring species that support commercial fisheries. Temperature has been shown to play a role in the overlap in distribution of NCC krill and Pacific hake (Merluccius productus), a commercially valuable fish species in Oregon waters (Phillips et al., 2023). The findings of my project could supplement existing commercial fish abundance surveys by providing ecological insights into factors driving changes in economically important fisheries.

Figure 3. The study area and transect design of the MOSAIC project, during which active acoustic data was collected (MOSAIC Project, https://mmi.oregonstate.edu/marine-mammals-offshore-wind).

I’m very grateful for the chance to work on a project with such important implications for the future of our Oregon coast ecosystems. My project has a lot of room for additional investigation of climate variables, with limited time being the main constraint on which processes I can explore. There are also unique methodological challenges to address during the project, and I’m ready to do some experimentation to work out solutions. Wherever my project takes me, I know that I will have developed a diverse range of skills and knowledge of krill by the end of the summer.

References

Brinton, E. (1962). The distribution of Pacific euphausiids. Bulletin of the Scripps Institution of Oceanography, 8(2), 51-270. https://escholarship.org/uc/item/6db5n157

Brodeur, R. D., Auth, T. D., & Phillips, A. J. (2019). Major shifts in pelagic micronekton and macrozooplankton community structure in an upwelling ecosystem related to an unprecedented marine heatwave. Frontiers in Marine Science, 6. https://doi.org/10.3389/fmars.2019.00212

Cai, W., Borlace, S., Lengaigne, M., van Rensch, P., Collins, M., Vecchi, G., Timmermann, A., Santoso, A., McPhaden, M. J., Wu, L., England, M. H., Wang, G., Guilyardi, E., & Jin, F. F. (2014). Increasing frequency of extreme El Niño events due to greenhouse warming. Nature Climate Change, 4, 111–116. https://doi.org/10.1038/nclimate2100

Checkley, D. M., & Barth, J. A. (2009). Patterns and processes in the California Current System. Progress in Oceanography, 83, 49–64. https://doi.org/10.1016/j.pocean.2009.07.028

Evans, R., Gauthier, S., & Robinson, C. L. K. (2022). Ecological considerations for species distribution modelling of euphausiids in the Northeast Pacific Ocean. Canadian Journal of Fisheries and Aquatic Sciences, 79, 518–532. https://doi.org/10.1139/cjfas-2020-0481

Fisher, J. L., Peterson, W. T., & Rykaczewski, R. R. (2015). The impact of El Niño events on the pelagic food chain in the northern California Current. Global Change Biology, 21, 4401–4414. https://doi.org/10.1111/gcb.13054

Fisher, J. L., Menkel, J., Copeman, L., Shaw, C. T., Feinberg, L. R., & Peterson, W. T. (2020). Comparison of condition metrics and lipid content between Euphausia pacifica and Thysanoessa spinifera in the Northern California Current, USA. Progress in Oceanography, 188, 102417. https://doi.org/10.1016/j.pocean.2020.102417

McGowan, J. A., Cayan, D. R., & Dorman, L. M. (1998). Climate-ocean variability and ecosystem response in the Northeast Pacific. Science, 281, 210–217. https://doi.org/10.1126/science.281.5374.210

Phillips, E. M., Chu, D., Gauthier, S., Parker-Stetter, S. L., Shelton, A. O., & Thomas, R. E. (2022). Spatiotemporal variability of Euphausiids in the California Current Ecosystem: Insights from a recently developed time series. ICES Journal of Marine Science, 79, 1312–1326. https://doi.org/10.1093/icesjms/fsac055

Phillips, E. M., Malick, M. J., Gauthier, S., Haltuch, M. A., Hunsicker, M. E., Parker‐Stetter, S. L., & Thomas, R. E. (2023). The influence of temperature on Pacific hake co‐occurrence with euphausiids in the California Current Ecosystem. Fisheries Oceanography, 32, 267–279. https://doi.org/10.1111/fog.12628

Peterson, W. T., Fisher, J. L., Strub, P. T., Du, X., Risien, C., Peterson, J., & Shaw, C. T. (2017). The pelagic ecosystem in the Northern California Current off Oregon during the 2014–2016 warm anomalies within the context of the past 20 years. Journal of Geophysical Research: Oceans, 122(9), 7267–7290. https://doi.org/10.1002/2017jc012952

Robertson, R. R., & Bjorkstedt, E. P. (2020). Climate-driven variability in Euphausia pacificasize distributions off Northern California. Progress in Oceanography, 188, 102412.https://doi.org/10.1016/j.pocean.2020.102412

Are You Seeing Scars Too?: Examining Gray Whale Scars and Skin Conditions

By Serina Lane, GEMM Lab NSF REU Intern, Georgia Gwinnett College

Hello, everyone! My name is Serina and I’m a Research Experience for Undergraduates (REU) Intern at the Hatfield Marine Science Center (HMSC) this summer. I’ve had a love for the ocean for as long as I can remember. Honestly, it started off with just dolphins, but I soon started to realize that the ocean is full of fascinating creatures!

How I ended up here…well, I’ve never been to Oregon, I’m escaping the hot weather of Georgia, but I’m also getting to interact with like-minded marine biologists and experienced individuals at an amazing marine laboratory. At the age of 29, I’m also an older undergraduate student, and I will be graduating soon! I took a very long break from academics and coming back was hard, especially switching from business to biology. I have participated in surveys that asked how I felt about the statement “I am a scientist,” along with the degrees of agree and disagree. For most of my undergraduate career, I picked “slightly disagree”. I was getting great grades, but I did not feel like I was ever going to be able to accomplish the type of work scientific papers are written about. I really felt the need to gain more experience in the career path I intended to follow. All of these are the whirlwind ingredients that went into applying for the HMSC REU Internship at OSU! I’m being mentored by the lovely Natalie Chazal and Leigh Torres, and I am grateful for the opportunity and very excited to experience everything Hatfield has to offer. A little over a week of being here, I already feel my answer sliding from “neutral” to even “slightly agree”. There is still so much to learn!

The project I’m helping with is analyzing the scarring and skin conditions of Eastern North Pacific gray whales alongside the GRANITE team. My job will be analyzing over 100,000 pictures from the past eight years to detect various scars and potential skin conditions (yes, the comma is in the correct spot and no, there are no extra 0’s). Scars can come from a variety of sources such as boat propellers, fishing gear, and killer whales! A study conducted by Corsi et al. consisted of documenting killer whale rake marks (bites, essentially) on different types of whales in the eastern North Pacific. Their results showed that gray whales had the highest percentage of observed rake marks in sighted individuals, and provided insight into why body sections of observed marks are important. Most baleen whales had rake marks predominantly on their flukes, because they are often used for defense and if fleeing, are the closest area to bite. Fascinatingly, Corsi et al. consider that the higher occurrences of gray whale rake marks are due to killer whales adopting species-specific hunting approaches. Gray whales have predictable migratory routes, and we already know how intelligent killer whales can be. If I knew a truck had a specific delivery route and I could wait to intercept a fresh delivery of Krispy Kreme donuts, why wouldn’t I?

Donuts aside, I’ll also be categorizing where the scars/skin conditions are located – for example, certain regions on the tail (like above) or on their left or right back (often due to boat collisions). Then I’ll define what I believe to be the source of scarring and rate my confidence in that decision based on the photo. Now, not all of the photos are clear enough for me to make informed decisions, so realistically I could end up with only a few hundred usable photos. At the end of the summer, we’ll gather the results and compare the different rates of scarring sources and the body parts where they occurred, and analyze any patterns in skin conditions, such as whether a skin condition has worsened or improved on an individual we have sighted multiple times over the years.

*Figure 1.* A little look into a table I made to give examples of what scarring from different sources look like.

Surprisingly, cetaceans can heal deep wounds on their own without medical intervention. Scientists have discovered that compounds in their blubber layer, such as organohalogens and isovaleric acid, may naturally fight off infections and help wounds heal faster. Unlike humans and other terrestrial animals that form scabs when injured, cetaceans develop a different protective layer over their wounds. This layer consists of degenerative cells mixed with tiny bubbles and covers the injured area. This unique adaptation might help protect the wound from seawater and other environmental factors. While there have been studies on how surface wounds heal in captive dolphins and whales, there’s still much to learn about how these animals heal large, deep wounds. Understanding how wounds heal can help us to more accurately assess the frequency at which whales are wounded, whether it be from fishing gear or boats, to cookie cutter sharks or killer whales.

It seems like a lot, and it is, but our ultimate goal is to assess the effects that scarring and skin conditions can have in the ecology of marine megafauna. Assessing the individual gray whales in the photos can provide a bigger picture of the health of a whole population. We can also look for any patterns of skin conditions between mother and calf, individuals that are around each other often, adults and juveniles, or males and females. Scars may also play a role in a population’s health. If a gray whale had an open wound previously, did it develop into a skin condition? Did a skin condition worsen? Did it leave them more vulnerable to predators? These are the questions we would like to elaborate on with this research. A great read on this topic was conducted by Dawn R. Barlow, Acacia L. Pepper and Leigh G. Torres, which will be in the references below (Barlow et al., 2019). A better understanding of potential patterns is a better assessment of our current marine management practices. Is it enough, or do we need to change and do more?

Okay, lastly, let’s talk about artificial intelligence (AI). Would using AI methods for this project make our lives easier? Yes. If we could train AI to accurately identify specific scars and skin conditions, our 100,000 photos could be done within minutes. For my job security, woo no AI! But on a serious note, this approach could free up time that could be spent on other efforts, or speed up the process of assessing marine management. However, we gain so much by reviewing the photos ourselves which is still important to do when training AI on what specifics to search for. Over the summer, I’m going to get to know different whales and see how they may change over 8 years, just by their pictures. My excitement grew as soon as I looked at my first 3 gray whales and learned their names. It’s forever important to remember that we can always learn from sharing connections with the organisms we study and interact with. We share the same planet and we have to work together to preserve it. I thank you all for taking a trip through our summer research with me and I hope to meet some of you around Hatfield!

References

Barlow, D. R., Pepper, A. L., & Torres, L. G. (2019a). Skin deep: An assessment of New Zealand blue whale skin condition. Frontiers in Marine Science, 6. https://doi.org/10.3389/fmars.2019.00757

Bradford, A. L., Weller, D. W., Ivashchenko, Y. V., Burdin, A. M., & Brownell, Jr, R. L. (2009). Anthropogenic scarring of Western Gray Whales (Eschrichtius robustus). Marine Mammal Science, 25(1), 161–175. https://doi.org/10.1111/j.1748-7692.2008.00253.x

Corsi, E., Calambokidis, J., Flynn, K. R., & Steiger, G. H. (2021). Killer whale predatory scarring on Mysticetes: A comparison of rake marks among blue, humpback, and gray whales in the eastern North Pacific. Marine Mammal Science, 38(1), 223–234. https://doi.org/10.1111/mms.12863

NOAA. (2020, April 4). Fisheries of the United States. https://www.fisheries.noaa.gov/national/sustainable-fisheries/fisheries-united-states

Hamilton, P. K., & Marx, M. K. (2005). Skin lesions on North Atlantic right whales: Categories, prevalence and change in occurrence in the 1990s. Diseases of Aquatic Organisms, 68, 71–82. https://doi.org/10.3354/dao068071

Pettis, H. M., Rolland, R. M., Hamilton, P. K., Brault, S., Knowlton, A. R., & Kraus, S. D. (2004). Visual health assessment of north atlantic right whales (Eubalaena glacialis) using photographs. Canadian Journal of Zoology, 82(1), 8–19. https://doi.org/10.1139/z03-207

Silber, G. K., Weller, D. W., Reeves, R. R., Adams, J. D., & Moore, T. J. (2021). Co-occurrence of gray whales and vessel traffic in the North Pacific Ocean. Endangered Species Research, 44, 177–201. https://doi.org/10.3354/esr01093 Sun, L., Engle, C., Kumar, G., & van Senten, J. (2022). Retail market trends for Seafood in the United States. Journal of the World Aquaculture Society, 54(3), 603–624. https://doi.org/10.1111/jwas.12919

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