Marine Mammals – Page 3 – Geospatial Ecology of Marine Megafauna Laboratory

How big, how blue, how beautiful! Studying the impacts of climate change on big, (and beautiful) blue whales

Dr. KC Bierlich, Postdoctoral Scholar, OSU Department of Fisheries, Wildlife, & Conservation Sciences, Geospatial Ecology of Marine Megafauna Lab

The SAPPHIRE Project is in full swing, as we spend our days aboard the R/V Star Keys searching for krill and blue whales (Figure 1) in the South Taranaki Bight (STB) region of Aotearoa New Zealand. We are investigating how changing ocean conditions impact krill availability and quality, and how this in turn impacts blue whale behavior, health, and reproduction. Understanding the link between changing environmental conditions on prey species and predators is key to understanding the larger implications of climate change on ocean food webs and each populations’ resiliency.

Figure 1. The SAPPHIRE team searching for blue whales. Top left) KC Bierlich, top right) Dawn Barlow, bottom left) Dawn Barlow, Kim Bernard (left to right), bottom right) KC Bierlich, Dawn Barlow, Leigh Torres, Mike Ogle (left to right).

One of the many components of the SAPPHIRE Project is to understand how foraging success of blue whales is influenced by environmental variation (see this recent blog written by Dr. Dawn Barlow introducing each component of the project). When you cannot go to a grocery store or restaurant any time you are hungry, you must rely on stored energy from previous feeds to fuel energy needs. Body condition reflects an individual’s stored energy in the body as a result of feeding and thus represents the foraging success of an individual, which can then affect its potential for reproductive output and the individual’s overall health (see this previous blog). As discussed in a previous blog, drones serve as a valuable tool for obtaining morphological measurements of whales to estimate their body condition. We are using drones to collect aerial imagery of pygmy blue whales to obtain body condition measurements late in the foraging season between years 2024 and 2026 of the SAPPHIRE Project (Figure 2). We are quantifying body condition as Body Area Index (BAI), which is a relative measure standardized by the total length of the whale and well suited for comparing individuals and populations (Figure 3).

The GEMM Lab recently published an article led by Dr. Dawn Barlow where we investigated the differences in BAI between three blue whale populations: Eastern North Pacific blue whales feeding in Monterey Bay, California; Chilean blue whales feeding in the Corcovado Gulf; and New Zealand Pygmy blue whales feeding in the STB (Barlow et al., 2023). These three populations are interesting to compare since blue whales that feed in Monterey Bay and Corcovado Gulf migrate to and from these seasonally productive feeding grounds, while the Pygmy blue whales stay in Aotearoa New Zealand year-round. Interestingly, the Pygmy blue whales had higher BAI (were fatter) compared to the other two regions despite relatively lower productivity in their foraging grounds. This difference in body condition may be due to different life history strategies where the non-migratory Pygmy blue whales may be able to feed as opportunities arrive, while the migratory strategies of the Eastern North Pacific and Chilean blue whales require good timing to access high abundant prey. Another interesting and unexpected result from our blue whale comparison was that Pygmy blue whales are not so “pygmy”; they are actually the same size as Eastern North Pacific and Chilean blue whales, with an average size around 22 m. Our findings from this blue whale comparison leads us to more questions about how environmental conditions that vary from year to year influence body condition and reproduction of these “not so pygmy” blue whales.

Figure 2. An aerial image of a Pygmy blue whale in the South Taranaki Bight region of Aotearoa New Zealand collected during the SAPPHIRE 2024 field season using a DJI Inspire 2 drone.

Figure 3. A drone image of a Pygmy blue whale and the length and body width measurements used to estimate Body Area Index (BAI), represented by the shaded blue region. Width measurements will also be used to help identify pregnant individuals.

The GEMM Lab has been studying this population of Pygmy blue whales in the STB since 2013 and found that years designated as a marine heatwave resulted with a reduction in blue whale feeding activity. Interestingly, breeding activity is also reduced during marine heatwaves in the following season when compared to the breeding season following a more productive, typical foraging season. These findings indicate that fluctuations in the environment, such as marine heatwaves, may affect not only foraging success, but also reproduction in Pygmy blue whales.

To help us better understand reproductive patterns across years, we will use body width measurements from drone images paired with hormone concentrations collected from fecal and biopsy samples to identify pregnant individuals. Progesterone is a hormone secreted in the ovaries of mammals during the estrous cycle and gestation, making it the predominant hormone responsible for sustaining pregnancy. Recently, the GEMM Lab’s Dr. Alejandro Fernandez-Ajo wrote a blog discussing his publication identifying pregnant individual gray whales using drone-based body width measurements and progesterone concentrations from fecal samples (Fernandez et al., 2023). While individuals that were pregnant had higher levels of progesterone compared to when they were not pregnant, the body width at 50% of the body length served as a more reliable method for detecting pregnancy in gray whales. We will use similar methods to help identify pregnancy in Pygmy blue whales for the SAPPHIRE Project where will we examine body width measurement paired with progesterone concentrations collected from fecal and biopsy samples to identify pregnant individuals. We hope our work will help to better understand how climate change will influence Pygmy blue whale body condition and reproduction, and thus the overall health and resiliency of the population. Stay tuned!

References

Barlow, D. R., Bierlich, K. C., Oestreich, W. K., Chiang, G., Durban, J. W., Goldbogen, J. A., Johnston, D. W., Leslie, M. S., Moore, M. J., Ryan, J. P., & Torres, L. G. (2023). Shaped by Their Environment: Variation in Blue Whale Morphology across Three Productive Coastal Ecosystems. Integrative Organismal Biology, 5(1). https://doi.org/10.1093/iob/obad039

Fernandez Ajó, A., Pirotta, E., Bierlich, K. C., Hildebrand, L., Bird, C. N., Hunt, K. E., Buck, C. L., New, L., Dillon, D., & Torres, L. G. (2023). Assessment of a non-invasive approach to pregnancy diagnosis in gray whales through drone-based photogrammetry and faecal hormone analysis. Royal Society Open Science, 10(7), 230452. https://doi.org/10.1098/rsos.230452

Phases and Feelings of the Scientific Journey

Leigh Torres, Associate Professor, PI of the GEMM Lab

There are many phases of a scientific journey, which generally follows a linear path (although I recognize that the process is certainly iterative at times to improve and refine). The scientific journey typically starts with an idea or question, bred from curiosity and passion. The journey hopefully ends with new knowledge, a useful application (e.g., tool or management outcome), and more questions in need of answers, providing a sense of success and pride. But along this path, there are many more phases, with many more emotions. As we begin the four-year SAPPHIRE project, I have already experienced a range of emotions, and I am certain more will come my way as I again wander through the many phases and feeling of science:

PHASE	FEELINGS
Generation of idea or question	Curiosity, passion, wonder
Build the team and develop the funding proposal	Drive, dreaming big, team management, belief in the importance of your proposed work
Notice of funding proposal success	Disbelief, excitement, and pride, followed quickly by feeling daunted, and self-doubt about the ability to pull off what you said you would do.
*Prep for fieldwork/experiment/data collection	Frantic and overwhelmed by the need to remember all the details that make or break the research; lists, lists, lists; pressure to get organized and stay within your budget. Anticipation, exhaustion.
*Outreach/Engagement/Communication	Eagerness to share and connect; Pressure to build relationships and trust; make sure the research is meaningful and accessible to local communities
*Fieldwork/experiment/data collection/data analysis	Sigh of relief to be underway, accompanied by big pressure to achieve: gotta do what you said you would do.
Preparation of scientific publications and reports	Excitement for data synthesis: What will the results say? What are the answers to your burning questions? Were your hypotheses correct? With a good dose of apprehension of peer feedback and critical reviews.
Publications and reports	Satisfaction to see outputs and results from hard work being broadly disseminated.
Project end with final report	Feeling of great accomplishment, but now need to develop the next project and get the funding… the cycle continues.

*After months of intense preparation for our field research component of the SAPPHIRE project in Aotearoa New Zealand (permits, equipment purchasing, community engagement, gathering supplies, learning how to use new equipment, vessel contracting, overseas shipping, travel arrangements, vessel mobilization, oh the list goes on!), we have just stepped off the vessel after 3 full days collecting data. I have cycled through all these emotions many times, and now I feel both exhausted and elated. We are implementing our plan, and we now have data in-hand. Worry creeps in all the time: we need to do more, do better. But I also know that our team is excellent and with patience, blessings from the weather gods, and our continued hard work, we will succeed, learn, and share. As SAPPHIRE chargers ahead to understand the impacts of climate change on marine prey (krill) and predators (blue whales), I am ready for the continued mix of emotions that comes with science.

Photo montage of our awesome SAPPHIRE team in prep mode and during data collection in the South Taranaki Bight within Aotearoa New Zealand.

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Oceanographic Alchemy: How Winds Become Whale Food in Oregon

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

Here in the GEMM lab, we love the Oregon coast for its amazing animals – the whales we all study, the seabirds we can sometimes spot from the lab, and the critters that come up in net tows when we’re out on the water. Oregonians owe the amazing biological productivity of the Oregon coast to the underlying atmospheric and oceanographic processes, which make our local Northern California Current (NCC) ecosystem one of the most productive places on earth.

While the topographical bumps of the Oregon coastline and vagaries of coastal weather do have a big impact on the physical and biological processes off the coast, the dominant forces shaping the NCC are large-scale, atmospheric heavy hitters. As the northeasterly trade winds blow across the globe, they set up the clockwise-rotating North Pacific Subtropical Gyre, a major feature covering about 20 million square kilometers of the Pacific Ocean. The equatorward-flowing part of the gyre is the California Current. It comprises an Eastern Boundary Upwelling Ecosystem, one of four such global systems that, while occupying only 1% of the global ocean, are responsible for a whopping 11% of its total primary productivity, and 17% of global fish catch.

*Figure 1.* Important features of the California Current System (Checkley and Barth, 2009).

At its core, this incredible ocean productivity is due to atmospheric pressure gradients. Every spring, an atmospheric system called the North Pacific High strengthens, loosening the hold of the stormy Aleutian Low. As a result, the winds begin to blow from the north, pushing the surface water in the NCC with them towards the equator.

This water is subject to the Coriolis effect – an inertial force that acts upon objects moving across a rotating frame of reference, and the same force that airplane pilots must account for in their flight trajectories. As friction transmits the stress of wind acting upon the ocean’s surface downward through the water column, the Coriolis effect deflects deeper layers of water successively further to the right, before the original wind stress finally peters out due to frictional losses.

This process creates an oceanographic feature called an Ekman spiral, and its net effect in the NCC is the offshore transport of surface water. Deep water flows up to replace it, bringing along nutrients that feed the photosynthesizers at the base of the food web. Upwelling ecosystems like the NCC tend to be dominated by food webs full of large organisms, in which energy flows from single-celled phytoplankton like diatoms, to grazers like copepods and krill, to predators like fish, seabirds, and our favorite, whales. These bountiful food webs keep us busy: GEMM Lab research has explored how upwelling dynamics impact gray whale prey off the Oregon coast, as well as parallel questions far from home about blue whale prey in New Zealand.

*Figure 2. The Coriolis effect creates an oceanographic feature called an Ekman Spiral, resulting in water transport perpendicular to the wind direction (Source:* *NOAA*).

Although the process of upwelling lies at the heart of the productive NCC ecosystem, it isn’t enough for it to simply happen – timing matters, too. The seasonality of ecological events, or phenology, can have dramatic consequences for the food web, and individual populations in it. When upwelling is initiated as normal by the “spring transition”, the delivery of freshly upwelled nutrients activates the food web, with reverberations all the way from phytoplankton to predators. When the spring transition is late, however, the surface ocean is warm, nutrients are depleted, primary productivity is low, and the life cycles and abundances of some species can change dramatically. In 2005, for example, the spring transition was delayed by a month, resulting in declines and spatial redistributions of the taxa typically found in the NCC, including hake, rockfish, albacore tuna, and squid. The Cassin’s auklet, which feeds on plankton, suffered its worst year on record, including reproductive failure that may have resulted from a lack of food.

Upwelling is alchemical in its power to transform, modulating physical and atmospheric processes and turning them into ecosystem gold – or trouble. As oceanographers and Oregonians alike wonder how climate change may reshape our coast, changes to upwelling will likely play a big role in determining the outcome. Some expect that upwelling-favorable winds will become more prevalent, potentially increasing primary productivity. Others suspect that the timing of upwelling will shift, and ecological mismatches like those that occurred in 2005 will be increasingly detrimental to the NCC ecosystem. Whatever the outcome, upwelling is inherent to the character of the Oregon coast, and will help shape its future.

*Figure 3.* The GEMM Lab is grateful that the biological productivity generated by upwelling draws humpback whales like this one to the Oregon coast! (photo: Dawn Barlow)

References

Chavez, Francisco & Messié, Monique. (2009). A comparison of Eastern Boundary Upwelling Ecosystems. Progress In Oceanography. 83. 80-96. 10.1016/j.pocean.2009.07.032.

Chavez, F P., and J R Toggweiler, 1995: Physical estimates of global new production: The upwelling contribution. In Dahlem Workshop on Upwelling in the Ocean: Modern Processes and Ancient Records, Chichester, UK, John Wiley & Sons, 313-320.

Checkley, David & Barth, John. (2009). Patterns and processes in the California Current System. Progress In Oceanography. 83. 49-64. 10.1016/j.pocean.2009.07.028.

Wandering whales: what are Pacific gray whales doing in Atlantic?

Clara Bird, PhD Candidate, OSU Department of Fisheries, Wildlife, and Conservation Sciences, Geospatial Ecology of Marine Megafauna Lab

Happy 2024 everyone! The holiday season usually involves a lot of travelling to visit friends and family, but we’re not the only ones. While most gray whales migrate long distances to their wintering grounds in the Pacific Ocean along the Baja Mexico peninsula, a few whales have made even longer journeys. In the past 13 years, there have been four reported observations of gray whales in the Atlantic and Mediterranean. Most recently, a gray whale was seen off south Florida in December 2023. While these reports always inspire some awe for the ability of a whale to travel such an incredible distance, they also inspire questions as to why and how these whales end up so far from home.

While there used to be a population of gray whales in the Atlantic, it was eradicated by whaling in the mid-nineteenth century (Alter et al., 2015), which made the first observation of a gray whale in the Mediterranean in 2010 especially incredible. This whale was first observed in May off the coast of Israel and then Spain (Scheinin et al., 2011). It was estimated to be about 13 m long (a rough visual estimate made through comparison with a boat) and in poor, but not critical, body condition. Scheinin et al. (2011) proposed that the whale likely crossed from the Bering Sea to the North Atlantic and followed the coasts of either North America or Eurasia (Figure 1).

*Figure 1. Figure from Schenin et al. (2011) showing the possible routes the 2010 whale took to reach the Mediterranean and the path it took within.*

A few years later, another gray whale was spotted in the Southern Atlantic, in Namibia’s Walvis Bay in May 2013. The observation report from the Namibian Dolphin Project proposes that the whale could have crossed through the Arctic or swum around the southern tip of South America (Peterson 2013). While they did not estimate the size or condition of whale, the photos in the report indicate that the whale was not in good condition (Figure 2).

*Figure 2. Images of the gray whale seen in Namibia. Source:* *http://namibiandolphinproject.blogspot.com/2013/05/a-rare-and-mysterious-visitor-in-walvis.html*

The most covered sighting was in 2021, when a gray whale was repeatedly seen in Mediterranean in May of 2021. This whale was estimated to be about two years old and skinny. Furthermore, it’s body condition continued to decline with each sighting (“Lost in the Mediterranean, a Starving Grey Whale Must Find His Way Home Soon,” 2021). The whale was first spotted off the coast of Morocco, then it appears to have crossed the Mediterranean to the coast of Italy and then traveled to the coast of France. Like the 2010 sighting, it is hypothesized that this whale crossed through the Arctic and then crossed the North Atlantic to the enter the Mediterranean through the Gibraltar Strait.

Image of the 2021 whale in the Mediterranean. Source: REUTERS/Alexandre Minguez, https://www.reuters.com/business/environment/lost-mediterranean-starving-grey-whale-must-find-his-way-home-soon-2021-05-07/

Most recently, a gray whale was seen off the coast of Miami in December 2023 (Rodriguez, 2023). While there is no information on its estimated size or condition, it does not appear to be in critical condition from the video (Video 1). This sighting is interesting because it breaks from the pattern that was forming with all the previous sightings occurring in late spring on the western side of the Atlantic. This recent gray whale was seen in winter on the eastern side of the Atlantic. The May timing suggests that those whales crossed into the Atlantic during the spring migration when leaving the wintering grounds and heading to summer foraging grounds. However, this December sighting indicates that this whale ‘got lost’ on its way to the wintering grounds after a foraging season. Another interesting pattern is the body condition, while condition was not always reported, the spring whales all seemed to be in poor condition, likely due to the long journey and/or the lack of suitable food. The Miami whale is the only one that appeared to be in decent condition, but this arrived just after the foraging season and travelled a shorter distance. Finally, it’s also interesting that there is no clear pattern of age, these sightings are of a mixture of adult (2010), juvenile (2021), and unknown (2013, 2023) age classes.

Video 1: NBC6 news report on the sighting

Another common theme across these sightings, is the proposed passage of the whale across the Arctic. Prior to dramatic declines in ice cover in the Arctic due to climate change which made this an unfeasible route, reduced ice cover in the Arctic over the past couple of decades means that this is now possible (Alter et al., 2015). While these recent sightings could be random, they could also indicate that Pacific gray whales may be exploring the Atlantic more, prey availability in the arctic has been declining (Stewart et al., 2023) in recent years meaning that gray whales may be exploring new areas to find alternative food sources. Interestingly, a study by Alter et al. (2015) used genetic analysis to compare the DNA from Atlantic gray whale fossils and Pacific gray whale samples and found evidence that gray whales have moved between the Atlantic and Pacific several times in the last 1000 years when sea level and climate conditions (including ice cover) allowed them to. Meaning, that we could be seeing a pattern of mixing of whale populations between the two oceans repeating itself.

The possibility that we are observing the very early stages of a new population or group forming is particularly interesting to me in the context of how we think about the Pacific Coast Feeding Group (PCFG) of gray whales. If you’ve read our previous blogs, you know that the GEMM lab spends a lot of time studying this sub-group of the Eastern North Pacific (ENP) population. The PCFG feeds along the coast of the Pacific Northwest, which is different from the typical foraging habitat of the ENP in the Bering Sea. We in the GEMM lab often wonder how this subgroup formed (listen to postdoc KC Bierlich’s recent podcast here to learn more). Did it start like these recent observations? With a few whales leaving the typical feeding grounds in the Arctic in search for alternative prey sources and ending up in the Pacific Northwest? Did those whales also struggle to successfully feed at first but then develop new strategies to target new prey items? While whales may be making it through the Arctic now, there is no evidence that these whales have successfully found enough food to thrive. So, these sightings could be random or failed attempts at finding better foraging areas. Afterall, there have only been four reported gray whale sightings in the Atlantic in 13 years. But these are only the observed sightings, and maybe it’s only a matter of time and multiple tries before enough gray whales find each other and an alternative foraging ground in the Atlantic so that a new population is established. Nonetheless, it’s exciting and fun to think about the parallels between these sightings and the PCFG. As we start our ninth year of PCFG research, we hope to continue learning about the origins of this unique and special group. Stay tuned!

References

Alter, S. E., Meyer, M., Post, K., Czechowski, P., Gravlund, P., Gaines, C., Rosenbaum, H. C., Kaschner, K., Turvey, S. T., van der Plicht, J., Shapiro, B., & Hofreiter, M. (2015). Climate impacts on transocean dispersal and habitat in gray whales from the Pleistocene to 2100. Molecular Ecology, 24(7), 1510–1522. https://doi.org/10.1111/mec.13121

Lost in the Mediterranean, a starving grey whale must find his way home soon. (2021, May 7). Reuters. https://www.reuters.com/business/environment/lost-mediterranean-starving-grey-whale-must-find-his-way-home-soon-2021-05-07/

Rodriguez, G. (2023, December 19). Extremely rare and ‘special’ whale sighting near South Florida coast. NBC 6 South Florida. https://www.nbcmiami.com/news/local/extremely-rare-and-special-whale-sighting-near-south-florida-coast/3187746/

Scheinin, A. P., Kerem, D., MacLeod, C. D., Gazo, M., Chicote, C. A., & Castellote, M. (2011). Gray whale ( Eschrichtius robustus) in the Mediterranean Sea: Anomalous event or early sign of climate-driven distribution change? Marine Biodiversity Records, 4, e28. https://doi.org/10.1017/S1755267211000042

Stewart, J. D., Joyce, T. W., Durban, J. W., Calambokidis, J., Fauquier, D., Fearnbach, H., Grebmeier, J. M., Lynn, M., Manizza, M., Perryman, W. L., Tinker, M. T., & Weller, D. W. (2023). Boom-bust cycles in gray whales associated with dynamic and changing Arctic conditions. Science, 382(6667), 207–211. https://doi.org/10.1126/science.adi1847

El Niño de Navidad: What is atmospheric Santa Claus bringing to Oregon krill and whales?

Early June marked the onset of El Niño conditions in the Pacific Ocean , which have been strengthening through the fall and winter. For Oregonians, this climate event means unseasonably warm December days, less snow and overall precipitation (it’s sunny as I write this!), and the potential for increased wildfires and marine heatwaves next summer.

This phenomenon occurs about every two to seven years as part of the El Niño Southern Oscillation (ENSO), a cyclical rotation of atmospheric and oceanic conditions in the Pacific Ocean that is initiated by departures from and returns to “normal conditions” at the equator. Typically, the trade winds blow warm water west along the equator, and El Niño occurs when these winds weaken or reverse. As a result, the upwelling of cold water at the equator ceases, and warm water flows towards the west coast of the Americas, rather than its typical pathway towards Asia. When the trade winds resume their normal direction, usually after months or a year, the system returns to “normal” conditions – or, it can enter the cool La Niña part of the cycle, in which the trade winds are stronger than normal. “El Niño de Navidad” was named by South American fisherman in the 1600s because this event tends to peak in December – and El Niño is clearly going to be a guest for Christmas this year.

*Figure 1.* Maps of sea surface temperature anomalies show Pacific Ocean conditions during a strong La Niña (top) and El Niño (bottom). Source: NOAA climate.gov

These events at the equator trigger changes in global atmospheric circulation patterns, and they can shape weather around the world. Teleconnection, the coherence between meteorological and environmental phenomena occurring far apart, is to me one of the most incredible things about the natural world. This coherence means that the biological community off the Oregon coast is strongly impacted by events initiated at the equator, with consequences that we don’t yet fully understand.

The effects of El Niño are diverse – floods in some places, droughts in others – and their onset can mean wildly different things for Oregon, Peru, Alaska, and beyond. As we tap our fingers waiting to be able to ski and snowboard in Oregon, what does our current El Niño event mean for the life in the waters off our coast?

*Figure 2.* Anomalous conditions at the equator qualified as an El Niño event in June 2023.

ENSO plays a big role in the variability in our local Northern California Current (NCC) system, and the outcomes of these events can differ based on the strength and how the signal propagates through the ocean and atmosphere (Checkley & Barth, 2009). Large-scale “coastal-trapped” waves flowing alongshore can bring the warm water signal of an El Niño to our ocean backyard in a matter of weeks. One of the first impacts is a deepening of the thermocline, the upper ocean’s steep gradient in temperature, which changes the cycling of important nutrients in the surface ocean. This can result in a decrease in upwelling and primary productivity that sends ramifications through the food web, including consequences for grazers and predators like zooplankton, marine mammals, and seabirds (Checkley & Barth, 2009).

In addition to these ecosystem effects that result from local changes, the ocean community can also receive new visitors from afar, and see others flee . For krill, the shrimp-like whale prey that I spend a lot of my time thinking about, community composition can change as subtropical species typically found off southern and Baja California are displaced by horizontal ocean flow, or as resident species head north (Lilly & Ohman, 2021).

*Figure 3*. This *Euphausia gibboides* krill is typically found in offshore subtropical habitats but moves north and inshore during El Niño events, and tends to persist awhile in these new environments, impacting the local zooplankton community. Source: Solvn Zankl

The two main krill species that occur in the NCC, Euphausia pacifica and Thysanoessa spinifera, favor the cool, coastal waters typical off the coast of Oregon. During El Niño events, E. pacifica tends to contract its distribution inshore in order to continue occupying these conditions, increasing its spatial overlap with T. spinifera (Lilly & Ohman, 2021). In addition, both tend to shift their populations north, toward cooler, upwelling waters (Lilly & Ohman, 2021).

These krill species are a favored prey of rorqual whales, and the coast of Oregon is an important foraging ground for humpback, blue, and fin whales. Predators tend to follow their prey, and shifting distributions of these krill species may cause whales to move, too. During the 2014-2015 “Blob” event in the Pacific Ocean, a marine heatwave was exacerbated by El Niño conditions. Humpback whales in central California shifted their distributions inshore in response to sparse offshore krill, increasing their overlap with fishing gear and leading to an increase in entanglement events (Santora et al., 2020). Further north, these conditions even led humpback whales to forage in the Columbia River!

Figure 4. In September 2015, El Niño conditions led humpback whales to follow their prey and forage in the Columbia River.

As El Niño events compound with the impacts of global climate change, we can expect these distributional shifts – and perhaps surprises – to continue. By the year 2100, the west coast habitat of both T. spinifera and E. pacifica will likely be constrained due to ocean warming – and when El Niños occur, this habitat will decrease even further (Lilly & Ohman, 2021). As a result, the abundances of both species are expected to decrease during El Niño events, beyond what is seen today (Lilly & Ohman, 2021). This decline in prey availability will likely present a problem for future foraging whales, which may already be facing increased environmental challenges.

Understanding connections is inherent to the field of ecology, and although these environmental dependencies are part of what makes life so vulnerable, they can also be a source of resilience. Although humans have known about ENSO for over 400 years, the complex interplay between nature, anthropogenic systems, and climate change means that we are still learning the full implications of these events. Just as waiting for Santa Claus always keeps kids guessing, the dynamic ocean keeps surprising us, too.

References

Checkley, D. M., & Barth, J. A. (2009). Patterns and processes in the California Current System. Progress in Oceanography, 83(1–4), 49–64. https://doi.org/10.1016/j.pocean.2009.07.028

Lilly, L. E., & Ohman, M. D. (2021). Euphausiid spatial displacements and habitat shifts in the southern California Current System in response to El Niño variability. Progress in Oceanography, 193, 102544. https://doi.org/10.1016/j.pocean.2021.102544

Santora, J. A., Mantua, N. J., Schroeder, I. D., Field, J. C., Hazen, E. L., Bograd, S. J., Sydeman, W. J., Wells, B. K., Calambokidis, J., Saez, L., Lawson, D., & Forney, K. A. (2020). Habitat compression and ecosystem shifts as potential links between marine heatwave and record whale entanglements. Nat Commun, 11(1), 536. https://doi.org/10.1038/s41467-019-14215-w

Sonar savvy: using echo sounders to characterize zooplankton swarms

By Natalie Chazal, PhD student, OSU Department of Fisheries, Wildlife, & Conservation Sciences, Geospatial Ecology of Marine Megafauna Lab

I’m Natalie Chazal, the GEMM Lab’s newest PhD student! This past spring I received my MS in Biological and Agricultural Engineering with Dr. Natalie Nelson’s Biosystems Analytics Lab at North Carolina State University. My thesis focused on using shellfish sanitation datasets to look at water quality trends in North Carolina and to forecast water quality for shellfish farmers in Florida. Now, I’m excited to be studying gray whales in the GEMM Lab!

Since the beginning of the Fall term, I’ve jumped into a project that will use our past 8 years of sonar data collected using a Garmin echo sounder during the GRANITE project work with gray whales off the Newport, OR coast. Echo sounder data is commonly used recreationally to detect bottom depth and for finding fish and my goal is to use these data to assess relative prey abundance at gray whale sightings over time and space.

There are also scientific grade echo sounders that are built to be incredibly precise and very exact in the projection and reception of the sonar pulses. Both types of echosounders can be used to determine the depth of the ocean floor, structures within the water column, and organisms that are swimming within the sonar’s “cone” of acoustic sensing. The precision and stability of the scientific grade equipment allows us to answer questions related to the specific species of organisms, the substrate type at the sea floor, and even animal behavior. However, scientific grade echo sounders can be expensive, overly large for our small research vessel, and require expertise to operate. When it comes to generalists, like gray whales, we can answer questions about relative prey abundances without the use of such exact equipment (Benoit-Bird 2016; Brough 2019).

While there are many variations of echo sounders that are specific to their purpose, commercially available, single beam echo sounders generally function in the same way (Fig. 1). First, a “ping” or short burst of sound at a specific frequency is produced from a transducer. The ping then travels downward and once it hits an object, some of the sound energy bounces off of the object and some moves into the object. The sound that bounces off of the object is either reflected or scattered. Sound energy that is either reflected or scattered back in the direction of the source is then received by the transducer. We can figure out the depth of the signal using the amount of travel time the ping took (SeaBeam Instruments 2000).

Figure 1. Diagram of how sound is scattered, reflected, and transmitted in marine environments (SeaBeam Instruments, 2000).

The data produced by this process is then displayed in real-time, on the screen on board the boat. Figure 2 is an example of the display that we see while on board RUBY (the GEMM Lab’s rigid-hull inflatable research boat):

Figure 2. Photo of the echo sounder display on board RUBY. On the left is a map that is used for navigation. On the right is the real time feed where we can see the ocean bottom shown as the bright yellow area with the distinct boundary towards the lower portion of the screen. The more orange layer above that, with the more “cloudy” structure is a mysid swarm.

Once off the boat, we can download this echo sounder data and process it in the lab to recreate echograms similar to those seen on the boat. The echograms are shown with the time on the x-axis, depth on the y-axis, and are colored by the intensity of sound that was returned (Fig. 3). Echograms give us a sort of picture of what we see in the water column. When we look at these images as humans, we can infer what these objects are, given that we know what habitat we were in. Below (Fig. 3) are some example classifications of different fish and zooplankton swarms and what they look like in an echogram (Kaltenberg 2010).

Figure 3. Panel of echogram examples, from Kaltenberg 2010, for different fish and zooplankton aggregations that have been classified both visually (like we do in real time on the boat) as well as statistically (which we hope to do with the mysid aggregations).

For our specific application, we are going to focus on characterizing mysid swarms, which are considered to be the main prey target of PCFG whales in our study area. With the echograms generated by the GRANITE fieldwork, we can gather relative mysid swarm densities, giving us an idea of how much prey is available to foraging gray whales. Because we have 8 years of GRANITE echosounder data, with 2,662 km of tracklines at gray whale sightings, we are going to need an automated process. This demand is where image segmentation can come in! If we treat our echograms like photographs, we can train models to identify mysid swarms within echograms, reducing our echogram processing load. Automating and standardizing the process can also help to reduce error.

We are planning to utilize U-Nets, which are a method of image segmentation where the image goes through a series of compressions (encoders) and expansions (decoders), which is common when using convolutional neural nets (CNNs) for image segmentation. The encoder is generally a pre-trained classification network (CNNs work very well for this) that is used to classify pixels into a lower resolution category. The decoder then takes the low resolution categorized pixels and reprojects them back into an image to get a segmented mask. What makes U-Nets unique is that they re-introduce the higher resolution encoder information back into the decoder process through skip connections. This process allows for generalizations to be made for the image segmentation without sacrificing fine-scale details (Brautaset 2020; Ordoñez 2022; Slonimer 2023; Vohra 2023).

Figure 4. Diagram of the encoder, decoder architecture for U-Nets used in biomedical image segmentation. Note the skip connections illustrated by the gray lines connecting the higher resolution image information on the left, with the decoder process on the right (Ronneberger 2015)

What we hope to get from this analysis is an output image that provides us only the parts of the echogram that contain mysid swarms. Once the mysid swarms are found within the echograms, we can use both the intensity and the size of the swarm in the echogram as a proxy for the relative abundance of gray whale prey. We plan to quantify these estimates across multiple spatial and temporal scales, to link prey availability to changing environmental conditions and gray whale health and distribution metrics. This application is what will make our study particularly unique! By leveraging the GRANITE project’s extensive datasets, this study will be one of the first studies that quantifies prey variability in the Oregon coastal system and uses those results to directly assess prey availability on the body condition of gray whales.

However, I have a little while to go before the data will be ready for any analysis. So far, I’ve been reading as much as I can about how sonar works in the marine environment, how sonar data structures work, and how others are using recreational sonar for robust analyses. There have been a few bumps in the road while starting this project (especially with disentangling the data structures produced from our particular GARMIN echosounder), but my new teammates in the GEMM Lab have been incredibly generous with their time and knowledge to help me set up a strong foundation for this project, and beyond.

References

Kaltenberg A. (2010) Bio-physical interactions of small pelagic fish schools and zooplankton prey in the California Current System over multiple scales. Oregon State University, Dissertation. https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/z890rz74t
SeaBeam Instruments. (2000) Multibeam Sonar Theory of Operation. L-3 Communications, East Walpole MA. https://www3.mbari.org/data/mbsystem/sonarfunction/SeaBeamMultibeamTheoryOperation.pdf
Benoit-Bird K., Lawson G. (2016) Ecological insights from pelagic habitats acquired using active acoustic techniques. Annual Review of Marine Science. https://doi.org/10.1146/annurev-marine-122414-034001
Brough T., Rayment W., Dawson S. (2019) Using a recreational grade echosounder to quantify the potential prey field of coastal predators. PLoS One. https://doi.org/10.1371/journal.pone.0217013
Brautaset O., Waldeland A., Johnsen E., Malde K., Eikvil L., Salberg A, Handegard N. (2020) Acoustic classification in multifrequency echosounder data using deep convolutional neural networks. ICES Journal of Marine Science 77, 1391–1400. https://doi.org/10.1093/icesjms/fsz235
Ordoñez A., Utseth I., Brautaset O., Korneliussen R., Handegard N. (2022) Evaluation of echosounder data preparation strategies for modern machine learning models. Fisheries Research 254, 106411. https://doi.org/10.1016/j.fishres.2022.106411
Slonimer A., Dosso S., Albu A., Cote M., Marques T., Rezvanifar A., Ersahin K., Mudge T., Gauthier S., (2023) Classification of Herring, Salmon, and Bubbles in Multifrequency Echograms Using U-Net Neural Networks. IEEE Journal of Oceanic Engineering 48, 1236–1254. https://doi.org/10.1109/JOE.2023.3272393
Ronneberger O., Fischer P., Brox T. (2015) U-Net: Convolutional Networks for Biomedical Image Segmentation. https://doi.org/10.48550/arXiv.1505.04597

Migrating back east

By: Kate Colson, MSc Oceans and Fisheries, University of British Columbia, Institute for the Oceans and Fisheries, Marine Mammal Research Unit

With the changing of the season, gray whales are starting their southbound migration that will end in the lagoons off the Baja California Mexico. The migration of the gray whale is the longest migration of any mammal—the round trip totals ~10,000 miles (Pike, 1962)!

*Map of the migration route taken by gray whales along the west coast of North America. (Image credit: Angle, Asplund, and Ostrander, 2017* *https://www.slocoe.org/resources/parent-and-public-resources/what-is-a-california-gray-whale/california-gray-whale-migration/*)

Like these gray whales, I am also undertaking my own “migration” as I leave Newport to start my post-Master’s journey. However, my migration will be a little shorter than the gray whale’s journey—only ~3,000 miles—as I head back to the east coast. As I talked about in my previous blog, I have finished my thesis studying the energetics of gray whale foraging behaviors and I attended my commencement ceremony at the University of British Columbia last Wednesday. As my time with the GEMM Lab comes to a close, I want to take some time to reflect on my time in Newport.

*Me in my graduation regalia (right) and my co-supervisor Andrew Trites holding the university mace (left) after my commencement ceremony at the University of British Columbia rose garden.*

Many depictions of scientists show them working in isolation but in my time with the GEMM Lab I got to fully experience the collaborative nature of science. My thesis was a part of the GEMM Lab’s Gray whale Response to Ambient Noise Informed by Technology and Ecology (GRANITE) project and I worked closely with the GRANITE team to help achieve the project’s research goals. The GRANITE team has annual meetings where team members give updates on their contributions to the project and flush out ideas in a series of very busy days. I found these collaborative meetings very helpful to ensure that I was keeping the big picture of the gray whale study system in mind while working with the energetics data I explored for my thesis. The collaborative nature of the GRANITE project provided the opportunity to learn from people that have a different skill set from my own and expose me to many different types of analysis.

*GRANITE team members hard at work thinking about gray whales and their physiological response to noise.*

This summer I also was able to participate in outreach with the partnership of the Oregon State University Marine Mammal Institute and the Eugene Exploding Whales (the alternate identity of the Eugene Emeralds) minor league baseball team to promote the Oregon Gray Whale License plates. It was exciting to talk to baseball fans about marine mammals and be able to demonstrate that the Gray Whale License plate sales are truly making a difference for the gray whales off the Oregon coast. In fact, the minimally invasive suction cup tags used in to collect the data I analyzed in my thesis were funded by the OSU Gray Whale License plate fund!

Photo of the GEMM Lab promoting Oregon Gray Whale License plates at the Eugene Exploding Whales baseball game. If you haven’t already, be sure to “Put a whale on your tail!” to help support marine mammal research off the Oregon Coast.

Outside of the amazing science opportunities, I have thoroughly enjoyed the privilege of exploring Newport and the Oregon coast. I was lucky enough to find lots of agates and enjoyed consistently spotting gray whale blows on my many beach walks. I experienced so many breathtaking views from hikes (God’s thumb was my personal favorite). I got to attend an Oregon State Beavers football game where we crushed Stanford! And most of all, I am so thankful for all the friends I’ve made in my time here. These warm memories, and the knowledge that I can always come back, will help make it a little easier to start my migration away from Newport.

*Me and my friends outside of Reser Stadium for the Oregon State Beavers football game vs Stanford this season. Go Beavs!!!*

*Me and my friends celebrating after my defense.*

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References

Pike, G. C. (1962). Migration and feeding of the gray whale (Eschrichtius gibbosus). Journal of the Fisheries Research Board of Canada, 19(5), 815–838. https://doi.org/10.1139/f62-051

Blue whales, krill, and climate change: introducing the SAPPHIRE project

By Dr. Dawn Barlow, Postdoctoral Scholar, OSU Department of Fisheries, Wildlife, and Conservation Sciences, Geospatial Ecology of Marine Megafauna Lab

The world is warming. Ocean ecosystems are experiencing significant and rapid impacts of climate change. However, the cascading effects on marine life are largely unknown. Thus, it is critical to understand how – not just if – environmental change impacts the availability and quality of key prey species in ocean food webs, and how these changes will impact marine predator health and population resilience. With these pressing knowledge gaps in mind, we are thrilled to launch a new project “Marine predator and prey response to climate change: Synthesis of Acoustics, Physiology, Prey, and Habitat in a Rapidly changing Environment (SAPPHIRE).” We will examine how changing ocean conditions affect the availability and quality of krill, and thus impact blue whale behavior, health, and reproduction. This large-scale research effort is made possible with funding from the National Science Foundation.

The SAPPHIRE project takes place in the South Taranaki Bight (STB) region of Aotearoa New Zealand, and before diving into our new research plans, let’s reflect briefly on what we know so far about this study system based on our previous research. Our collaborative research team has studied blue whales in the STB since 2013 to document the population, understand their ecology and habitat use, and inform conservation management. We conducted boat-based surveys and used hydrophones to record the underwater soundscape, and found the following:

Blue whales in Aotearoa New Zealand are a unique population, genetically distinct from all other known populations in the Southern Hemisphere, with an estimated population size of 718 (95% CI = 279 – 1926).¹
Blue whales reside in the STB region year-round, with feeding and breeding vocalizations detected nearly every day of the year.^2,3
Wind-driven upwelling over Kahurangi shoals moves a plume of cold, nutrient-rich waters into the STB, supporting aggregations of krill, and thereby critical feeding opportunities for blue whales in spring and summer.^4–6
We developed predictive models to forecast blue whale distribution up to three weeks in advance, providing managers with a real-time tool in the form of a desktop application to produce daily forecast maps for dynamic management.⁷
During marine heatwaves, blue whale feeding activity was substantially reduced in the STB. Interestingly, their breeding activity was also reduced in the following season when compared to the breeding season following a more productive, typical foraging season. This finding indicates that shifting environmental conditions, such as marine heatwaves and climate change, may have consequences to not just foraging success, but the population’s reproductive patterns.³

A blue whale comes up for air in the South Taranaki Bight. Photo by Leigh Torres.

Project goals

Building on this existing knowledge, we aim to gain understanding of the health impacts of environmental change on krill and blue whales, which can in turn inform management decisions. Over the next three years (2024-2026) we will use multidisciplinary methods to collect data in the field that will enable us to tackle these important but challenging goals. Our broad objectives are to:

Assess variation in krill quality and availability relative to rising temperatures and different ocean conditions,
Document how blue whale body condition and hormone profiles change relative to variable environmental and prey conditions,
Understand how environmental conditions impact blue whale foraging and reproductive behavior, and
Integrate these components to develop novel Species Health Models to predict predator and prey whale population response to rapid environmental change.

Kicking off fieldwork

This coming January, we will set sail aboard the R/V Star Keys and head out in search of blue whales and krill in the STB! Five of our team members will spend three weeks at sea, during which time we will conduct surveys for blue whale occurrence paired with active acoustic assessment of krill availability, fly Unoccupied Aircraft Systems (UAS; “drones”) over whales to determine body condition and potential pregnancy, collect tissue biopsy samples to quantify stress and reproductive hormone levels, deploy hydrophones to record rates of foraging and reproductive calls by blue whales, and conduct on-board controlled experiments on krill to assess their response to elevated temperature.

The team in action aboard the R/V Star Keys in February 2017. Photo by L. Torres.

The moving pieces are many as we work to obtain research permits, engage in important consultation with iwi (indigenous Māori groups), procure specialized scientific equipment, and make travel and shipping arrangements. The to-do lists seem to grow just as fast as we can check items off; such is the nature of coordinating an international, multidisciplinary field effort. But it will pay off when we are underway, and I can barely contain my excitement to back on the water with this research team.

Our team has not collected data in the STB since 2017. We know so much more now than we did when studies of this blue whale population were just beginning. For example, we are eager to put our blue whale forecast tool to use, which will hopefully enable us to direct survey effort toward areas of higher blue whale density to maximize data collection. We are keen to see what new insights we gain, and what new questions and challenges arise.

Research team

The SAPPHIRE project will only be possible with the expertise and coordination of the many members of our collaborative group. We are all thrilled to begin this research journey together, and eager to share what we learn.

Principal Investigators:

Leigh Torres (Geospatial Ecology of Marine Megafauna Lab, Marine Mammal Institute, OSU)

Research partners and key collaborators:

References:

1. Barlow DR, Torres LG, Hodge KB, Steel D, Baker CS, Chandler TE, Bott N, Constantine R, Double MC, Gill P, Glasgow D, Hamner RM, Lilley C, Ogle M, Olson PA, Peters C, Stockin KA, Tessaglia-Hymes CT, Klinck H. Documentation of a New Zealand blue whale population based on multiple lines of evidence. Endanger Species Res. 2018;36:27–40.

2. Barlow DR, Klinck H, Ponirakis D, Holt Colberg M, Torres LG. Temporal occurrence of three blue whale populations in New Zealand waters from passive acoustic monitoring. J Mammal. 2022;

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

4. Barlow DR, Klinck H, Ponirakis D, Garvey C, Torres LG. Temporal and spatial lags between wind, coastal upwelling, and blue whale occurrence. Sci Rep. 2021;11(6915):1–10.

5. Barlow DR, Bernard KS, Escobar-Flores P, Palacios DM, Torres LG. Links in the trophic chain: Modeling functional relationships between in situ oceanography, krill, and blue whale distribution under different oceanographic regimes. Mar Ecol Prog Ser. 2020;642:207–25.

6. Torres LG, Barlow DR, Chandler TE, Burnett JD. Insight into the kinematics of blue whale surface foraging through drone observations and prey data. PeerJ. 2020;8:e8906.

7. Barlow DR, Torres LG. Planning ahead: Dynamic models forecast blue whale distribution with applications for spatial management. J Appl Ecol. 2021;58(11):2493–504.

A non-invasive approach to pregnancy diagnosis in Gray whales is possible!

Dr. Alejandro A. Fernández Ajó, Postdoctoral Scholar, Marine Mammal Institute – OSU Department of Fisheries, Wildlife, & Conservation Sciences, Geospatial Ecology of Marine Megafauna (GEMM) Lab.

In a previous post (link to blog), I discussed the crucial importance of acquiring knowledge on the reproductive parameters of individual animals in wild populations for designing effective strategies in conservation biology. Specifically, the ability to quantify the number of pregnancies within a population offers valuable insights into the health of individual females and the population as a whole [1,2]. This knowledge provides tools to describe important life-history parameters, including the age of sexual maturity, frequency of pregnancy, duration of gestation, timing of reproduction, and population fecundity; all of which are essential components for monitoring trends in reproduction and the overall health of a species [3]. Additionally, I explained some of the challenges inherent in obtaining such information when working with massive wild animals that spend most of their time underwater in vast expanses of the oceans. Yes, I am talking about whales.

As a result of the logistical and methodological challenges that involve the study of large whales, detailed knowledge of the life-history and general reproductive biology of whales is sparse for most species and populations. In fact, much of the available information is derived from whaling records [4], which may be outdated for application in population models [5].

If you are an avid reader of the GEMM Lab blog posts, you might be familiar with the gray whale (Eschrichtius robustus), and with the distinct subgroup of gray whales, known as the Pacific Coast Feeding Group (PCFG). PCFG gray whales are characterized by their shorter migration to spend their feeding season in the coastal waters of Northern California, Oregon, and southeastern Alaska [6], relative to the larger Eastern North Pacific gray whale that forage in the Arctic region.

The GEMM Lab has monitored individual gray whales within the PCFG off the Oregon coast since 2016 (check the GRANITE project). Each individual whale presents a unique pigmentation pattern, or unique marks that we can use to identify who is who among the whales who visit the Oregon coast. In this way, we keep a detailed record of re-sightings of known individuals (visit IndividuWhale to learn more), and we have high individual re-sighting rates, resulting in a long-term data series for individual whales which enables us to monitor their health, body condition, and thus further develop and advance our non-invasive study methods.

Drone-based image of a Gray whale defecating. Source: GEMM Lab, NOAA/NSF permit #16111

In our recently manuscript published in the Royal Society Open Science journal, armed with our robust dataset comprising fecal hormone metabolites, drone-based photogrammetry, and individual sightings, we delved into the strengths and weaknesses of various diagnostic tools for non-invasive pregnancy diagnosis. Ultimately, we propose a methodological approach that can help with the challenging and important task of identifying pregnancies in gray whales. In particular, we explored the variability in fecal progesterone metabolites and body morphology relative to observed reproductive status and estimated the pregnancy probability for mature females using statistical models.

In mammals, the progesterone hormone is secreted in the ovaries during the estrous cycle and gestation, making it the predominant hormone responsible for sustaining pregnancy [7]. As the hormones are cleared from the blood into the gut, they are metabolized and eventually excreted in feces; fecal samples represent a cumulative and integrated concentration of hormone metabolites [8;9], which are useful indicators for endocrine assessments of free-swimming whales. Additionally, our previous studies in this population [10] detected differences in body condition (see KC blog for more details about how we measure whales) that suggest that changes in the whale’s body widths could be useful in detecting pregnancies.

Our exploratory analyses show that in individual whales, the levels of fecal progesterone were elevated when pregnant as compared to when the same whale was not pregnant. But when looking at progesterone levels at the population level, these differences were masked with the intrinsic variability of this measurement. In turn, the body morphometrics, in particular the body width at the 50% of the total body length, helped discriminate pregnancies better, and the statistical models that included this width variable, effectively classified pregnant from non-pregnant females with a commendable accuracy. Thus, our morphometric approach showcased its potential as a reliable alternative for pregnancy diagnosis.

Below, a comparison of body widths at 5% increments along total body length (from 20 % to 70 %) in female gray whales of known reproductive status from UAS-based photogrammetry (example photograph shown at top). Pregnant females (PF; in blue), presumed nonpregnant juvenile females (JF; yellow), and lactating females (LF; orange). Fernandez Ajó et al. 2023.

Notably, when we ran the pregnancy prediction models on data from our 2022 season and compared results with observations of whales in 2023, we identified a known whale from our study area “Clouds” accompanied by a calf, indicating that she was pregnant in 2022. Our model predicted Clouds to be pregnant with a 70% probability. This validation lends strong confidence to our approach to diagnosing pregnancy. Conversely, some whales predicted to be pregnant in 2022 were not observed with a calf during the 2023 season. However, the absence of calves accompanying these females is likely due to the relatively high mortality of newborn calves in gray whales due to predation or other causes [11].

Overall, our findings underscore some limitations of fecal progesterone metabolite in accurately identifying pregnant PCFG gray whales. However, while acknowledging the challenges associated with fecal sample collection and hormone analysis, we advocate for ongoing exploration of alternative hormone quantification methods and antibodies. Our study highlights the importance of continued research in refining these techniques. The unique attributes of our study system, including high individual re-sighting rates and non-invasive fecal hormone analysis, position it as a cornerstone for future advancements in understanding gray whale reproductive health. By improving our ability to monitor reproductive metrics in baleen whale populations, we pave the way for more effective conservation strategies, ensuring the resilience of these magnificent creatures in the face of a changing marine ecosystems.

References

[1] Burgess EA, Lanyon JM, Brown JL, Blyde D, Keeley T. 2012 Diagnosing pregnancy in free-ranging dugongs using fecal progesterone metabolite concentrations and body morphometrics: A population application. Gen Comp Endocrinol 177, 82–92. (doi:10.1016/J.YGCEN.2012.02.008)

[2] Slade NA, Tuljapurkar S, Caswell H. 1998 Structured-Population Models in Marine, Terrestrial, and Freshwater Systems. J Wildl Manage 62. (doi:10.2307/3802363)

[3] Madliger CL, Love OP, Hultine KR, Cooke SJ. 2018 The conservation physiology toolbox: status and opportunities. Conserv Physiol 6, 1–16. (doi:10.1093/conphys/coy029)

[4] Rice DW, Wolman AA. 1971 Life history and ecology of the gray whale (Eschrichtius robustus). Stillwater, Oklahoma: American Society of Mammalogists.

[5] Melicai V, Atkinson S, Calambokidis J, Lang A, Scordino J, Mueter F. 2021 Application of endocrine biomarkers to update information on reproductive physiology in gray whale (Eschrichtius robustus). PLoS One 16. (doi:10.1371/journal.pone.0255368)

[6] Calambokidis J, Darling JD, Deecke V, Gearin P, Gosho M, Megill W, et al. Abundance, range and movements of a feeding aggregation of gray whales (Eschrichtius robustus) from California to south-eastern Alaska in 1998. J Cetacean Res Manag 2002;4:267–76.

[7] Bronson, F. H. (1989). Mammalian reproductive biology. University of Chicago Press.

[8] Wasser SK, Hunt KE, Brown JL, Cooper K, Crockett CM, Bechert U, Millspaugh JJ, Larson S, Monfort SL (2000) A generalized fecal glucocorticoid assay for use in a diverse array of nondomestic mammalian and avian species. Gen Comp Endocrinol120:260–275.

[9] Hunt, K.E., Rolland, R.M., Kraus, S.D., Wasser, S.K., 2006. Analysis of fecal glucocorticoids in the North Atlantic right whale (Eubalaena glacialis). Gen. Comp. Endocrinol. 148, 260–272. https://doi.org/10.1016/j.ygcen.2006.03.01215.

[10] Soledade Lemos L, Burnett JD, Chandler TE, Sumich JL, Torres LG. 2020 Intra‐ and inter‐annual variation in gray whale body condition on a foraging ground. Ecosphere 11. (doi:10.1002/ecs2.3094)

[11] James L. Sumich, James T. Harvey, Juvenile Mortality in Gray Whales (Eschrichtius robustus), Journal of Mammalogy, Volume 67, Issue 1, 25 February 1986, Pages 179–182, https://doi.org/10.2307/1381019

A smaller sized gray whale: recent publication finds PCFG whales are smaller than ENP whales

Dr. KC Bierlich, Postdoctoral Scholar, OSU Department of Fisheries, Wildlife, & Conservation Sciences, Geospatial Ecology of Marine Megafauna (GEMM) Lab

A recent blog post by GEMM Lab’s PhD Candidate Clara Bird gave a recap of our 8^th consecutive GRANITEfield season this year. In her blog, Clara highlighted that we saw 71 individual gray whales this season, 61 of which we have seen in previous years and identified as belonging to the Pacific Coast Feeding Group (PCFG). With an estimated population size of around 212 individuals, this means that we saw almost 1/3 of the PCFG population this season alone. Since the GEMM Lab first started collecting data on PCFG gray whales in 2016, we have collected drone imagery on over 120 individuals, which is over half the PCFG population. This dataset provides incredible opportunity to get to know these individuals and observe them from year to year as they grow and mature through different life history stages, such as producing a calf. A question our research team has been interested in is what makes a PCFG whale different from an Eastern North Pacific (ENP) gray whale, which has a population size around 16,000 individuals and feed predominantly in the Arctic during the summer months? For this blog, I will highlight findings from our recent publication in Biology Letters (Bierlich et al., 2023) comparing the morphology (body length, skull, and fluke size) between PCFG and ENP populations.

Body size and shape reflect how an animal functions in their environment and can provide details on an individual’s current health, reproductive status, and energetic requirements. Understanding how animals grow is a key component for monitoring the health of populations and their vulnerability to climate change and other stressors in their environment. As such, collecting accurate morphological measurements of individuals is essential to model growth and infer their health. Collecting such morphological measurements of whales is challenging, as you cannot ask a whale to hold still while you prepare the tape measure, but as discussed in a previous blog, drones provide a non-invasive method to collect body size measurements of whales. Photogrammetry is a non-invasive technique used to obtain morphological measurements of animals from photographs. The GEMM Lab uses drone-based photogrammetry to obtain morphological measurements of PCFG gray whales, such as their body length, skull length (as snout-to-blowhole), and fluke span (see Figure 1).

Figure 1. Morphological measurements obtained via photogrammetry of a Pacific Coast Feeding Group (PCFG) gray whale. These measurements were used to compare to individuals from the Eastern North Pacific (ENP) population.

As mentioned in this previous blog, we use photo-identification to identify unique individual gray whales based on markings on their body. This method is helpful for linking all the data we are collecting (morphology, hormones, behavior, new scarring and skin conditions, etc.) to each individual whale. An individual’s sightings history can also be used to estimate their age, either as a ‘minimum age’ based on the date of first sighting or a ‘known age’ if the individual was seen as a calf. By combining the length measurements from drone-based photogrammetry and age estimates from photo-identification history, we can construct length-at-age growth models to examine how PCFG gray whales grow. While no study has previously examined length-at-age growth models specifically for PCFG gray whales, another study constructed growth curves for ENP gray whales using body length and age estimates obtained from whaling, strandings, and aerial photogrammetry (Agbayani et al., 2020). For our study, we utilized these datasets and compared length-at-age growth, snout-to-blowhole length, and fluke span between PCFG and ENP whales. We used Bayesian statistics to account and incorporate the various levels of uncertainty associated with data collected (i.e., measurements from whaling vs. drone, ‘minimum age’ vs. ‘known age’).

We found that while both populations grow at similar rates, PCFG gray whales reach smaller adult lengths than ENP. This difference was more extreme for females, where PCFG females were ~1 m (~3 ft) shorter than ENP females and PCFG males were ~0.5 m (1.5 ft) shorter than ENP males (Figure 2, Figure 3). We also found that ENP males and females have slightly larger skulls and flukes than PCFG male and females, respectively. Our results suggest PCFG whales are shaped differently than ENP whales (Figure 3)! These results are also interesting in light of our previous published study that found PCFG whales are skinnier than ENP whales (see this previous blog post).

Figure 2. Growth curves (von Bertalanffy–Putter) for length-at-age comparing male and female ENP and PCFG gray whales (shading represents 95% highest posterior density intervals). Points represent mean length and median age. Vertical bars represent photogrammetric uncertainty. Dashed horizontal lines represent uncertainty in age estimates.

Figure 3. Schematic highlighting the differences in body size between Pacific Coast Feeding Group (PCFG) and Eastern North Pacific (ENP) gray whales.

Our results raise some interesting questions regarding why PCFG are smaller: Is this difference in size and shape normal for this population and are they healthy? Or is this difference a sign that they are stressed, unhealthy and/or not getting enough to eat? Larger individuals are typically found at higher latitudes (this pattern is called Bergmann’s Rule), which could explain why ENP whales are larger since they feed in the Arctic. Yet many species, including fish, birds, reptiles, and mammals, have experienced reductions in body size due to changes in habitat and anthropogenic stressors (Gardner et al., 2011). The PCFG range is within closer proximity to major population centers compared to the ENP foraging grounds in the Arctic, which could plausibly cause increased stress levels, leading to decreased growth.

The smaller morphology of PCFG may also be related to the different foraging tactics they employ on different prey and habitat types than ENP whales. Animal morphology is linked to behavior and habitat (see this blogpost). ENP whales feeding in the Arctic generally forage on benthic amphipods, while PCFG whales switch between benthic, epibenthic and planktonic prey, but mostly target epibenthic mysids. Within the PCFG range, gray whales often forage in rocky kelp beds close to shore in shallow water depths (approx. 10 m) that are on average four times shallower than whales feeding in the Arctic. The prey in the PCFG range is also found to be of equal or higher caloric value than prey in the Arctic range (see this blog), which is interesting since PCFG were found to be skinnier.

It is also unclear when the PCFG formed? ENP and PCFG whales are genetically similar, but photo-identification history reveals that calves born into the PCFG usually return to forage in this PCFG range, suggesting matrilineal site fidelity that contributes to the population structure. PCFG whales were first documented off our Oregon Coast in the 1970s (Figure 4). Though, from examining old whaling records, there may have been PCFG gray whales foraging off the coasts of Northern California to British Columbia since the 1920s.

Figure 4. First reports of summer-resident gray whales along the Oregon coast, likely part of the Pacific Coast Feeding Group. Capital Journal, August 9, 1976, pg. 2.

Altogether, our finding led us to two hypotheses: 1) the PCFG range provides an ecological opportunity for smaller whales to feed on a different prey type in a shallow environment, or 2) the PCFG range is an ecological trap, where individuals gain less energy due to energetically costly feeding behaviors in complex habitat while potentially targeting lower density prey, causing them to be skinnier and have decreased growth. Key questions remain for our research team regarding potential consequences of the smaller sized PCFG whales, such as does the smaller body size equate to reduced resilience to environmental and anthropogenic stressors? Does smaller size effect fecundity and population fitness? Stay tuned as we learn more about this unique and fascinating smaller sized gray whale.

References

Agbayani, S., Fortune, S. M. E., & Trites, A. W. (2020). Growth and development of North Pacific gray whales (Eschrichtius robustus). Journal of Mammalogy, 101(3), 742–754. https://doi.org/10.1093/jmammal/gyaa028

Bierlich, K. C., Kane, A., Hildebrand, L., Bird, C. N., Fernandez Ajo, 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(8). https://doi.org/10.1098/rsbl.2023.0043

Gardner, J. L., Peters, A., Kearney, M. R., Joseph, L., & Heinsohn, R. (2011). Declining body size: A third universal response to warming? Trends in Ecology and Evolution, 26(6), 285–291. https://doi.org/10.1016/j.tree.2011.03.005

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