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There she blows! Studying blow synchrony in blue and gray whale mother-calf pairs

Maddie Honomichl, CSUMB Undergraduate in Marine Science, 2025  NSF REU and TOPAZ/JASPER Intern

Hi everyone, my name is Maddie Honomichl, and I was one of the two NSF REU interns with the GEMM lab this summer. This fall will be my last semester at California State University, Monterey Bay (CSUMB), where I will receive my undergraduate degree in Marine Science. Growing up in the Arizona desert limited my exposure to large bodies of water but led to memorable family trips to San Diego. With each trip my adoration for the ocean and the vast marine ecosystem emerged, resulting in my choice to go to college at CSU Monterey Bay. During my time at CSUMB, I learned of what internships were and the magnitude of impact these experiences had on my peers. Naturally, I searched online for weeks for future summer internship openings available—eventually leading me to none other than the GEMM Lab’s TOPAZ/JASPER project.

Figure 1. A picture of me, Maddie Honomichl, in Redding, CA.

Celest Sorrentino, my amazing mentor, took me under her wing and helped me complete my very first research project: In sync? Studying blow synchrony in blue and gray whale mother-calf pairs using drone footage. The aim of my project is to understand more about calf development in gray and blue whales by investigating changes in mother-calf blow synchrony. But what is synchrony?

Synchrony can be defined as two individuals attempting to match each other’s behavior (Novotny & Bente 2022) and promote mimicry and learning. For example, humpback whales teaching their calves vocalizations and song patterns to communicate is an instance of synchrony and social learning (Anjara 2018). Another example of synchrony in wildlife is energetic transfer, where a whale calf will swim in alignment with its mother’s slipstream to expend less energy (Norris & Prescott 1961). Just like these behaviors, blow synchrony is a measure we can use in marine mammal mother-calf pairs to evaluate their relationship with each other.

Aside from the TOPAZ/JASPER project, you might already be familiar with two other incredible GEMM lab projects GRANITE and SAPPHIRE. During the years of 2016-2023, drone footage of the Pacific Coast Feeding Group of gray whales was collected along the Oregon coast for the GRANITE project. In 2016, 2017, 2024, and 2025, drone footage for the pygmy blue whales was collected in South Taranaki Bight, New Zealand, for the SAPPHIRE project. Large marine mammals, especially whales, are difficult to study for many reasons including their brief occurrences at the surface and the challenges of studying aquatic animals. However, the use of drones allows for a safer and non-invasive alternative method for marine mammal monitoring in their natural habitat (Álvarez-González et al., 2023).

Figure 2. Two still images taken from GRANITE drone footage. The left is of a mother gray whale blowing and the right is of a gray whale calf blowing

Baleen whale calves only have 6-8 months to learn everything they need to know before they wean and are sent off on their own (Lockyer 1984). I don’t know about you, but if my mom kicked me out after I turned 5 years old, I would be pretty lost. In American culture, the golden age for humans to be considered an adult is around 18 years old, when they finally leave the house and venture on their own. For humans, age is a cultural sign of independence, but not much is known about what factors influence what makes a calf ready to be independent. Blow synchrony between mother-calf pairs during the calf’s weaning period can be used as a metric for calf development, which is important to know more about as calf development and survival rates are critical factors to consider in population dynamics and management efforts.

When do whales eventually leave their mother? We frequently don’t know how old a calf is, so we use three different metrics as proxies of calf maturity. First, we use Total Length (TL), which is the length of the whale from rostrum to fluke (or nose to tail) (Pirotta et. al., 2023) and serves as an indicator of growth. Our next metric is Body Area Index (BAI), similar to BMI in humans, which is a score of body condition to understand how fat or skinny the whale calf is (Burnett et. al., 2019). Total Length and BAI measurements are derived from drone photogrammetry work conducted by the GEMM Lab and CODEX. Our last proxy is Day of Year (DOY), which is the day in the year we sighted the whales.

Figure 3. Demonstrating photogrammetry methods used to measure Total Length and Body Area Index (BAI). On the left is a drone image of a gray whale showing how we calculate Total Length (TL) from rostrum to fluke. This image is also divided into increments which are used to calculate Surface Area (SA), depicted by the green dashed box, and using the equation on the right with TL, BAI is calculated. 

The specific question I addressed was: Does mother-calf blow rate synchrony change as the calf’s Total Length and Body Area Index increase, and Day of Year increases? In other words, does synchrony change as calves become longer, healthier, and the year progresses. Meaning, as the calf grows in length, increases its body condition, and the day of year progresses, the calf will gain independence from its mother and become out of sync.

I analyzed blowhole rates of mother-calf gray and blue whales using  a program called BORIS (Friard & Gamba 2016). BORIS (Behavioral Observation Research Interactive Software) is an online free program where researchers can assign behavior states to animals in video. In BORIS, I watched the drone footage and marked a “blow” event for the mom and calf, recording a specific time stamp per event. I repeated this workflow for each video of both gray and blue whale mom-calf pairs. Once completed, I calculated the average difference of the calf’s timestamp from the mother’s timestamp per pair. The reason behind this approach is that  the larger the average difference, the more asynchronous the calf is with its mother, and the smaller the average difference the more synchronous they will become.

To evaluate the effect of our proxies for age, Total Length, BAI, and Day of Year, on mother-calf blow rate synchrony, I turned to my good friend RStudio. I created a scatterplot and regressions for these relationships (Figure 4). These results indicate that body condition (BAI) may be a better proxy of calf maturity and preparation for weaning in gray whales (p-value = 0.0064), whereas calf Total Length (TL) is more indicative of calf maturity in blue whales (p-value = 0.00097).

Figure 4. Scatterplot describing the relationship between the average difference in breath rate in seconds across our three proxies: (i) Average total length, (ii) Average BAI, (iii) Day of Year. The black line in the linear regression fit to the data produced by the linear model. The error bars around each point are the standard deviation or the variability in their blow synchrony. The bigger the error bars mean the more variation the mother and calf had in their blow rates, and the smaller the error bars means the less variation the mother and calf had in their blow rates. Ultimately to answer my question, for gray whales, blow synchrony between mother and calf decreases with increasing calf Body Area Index (BAI). For our blue whales, mother-calf blow synchrony decreases with increasing calf Total Length (TL).

As I end my 10-week internship summer filled with data collection and analysis, lots of laughs and inside jokes, I am proud to say I have learned so much about the research that goes into a project like mine. As someone who loves marine animals, especially whale sharks, I now have a newfound love for whales that will forever be in my heart. I am so incredibly grateful that I was able to work with the GEMM lab and the amazing team of researchers and scientists it encompasses. Being a first-generation college student comes with its challenges of learning how to navigate higher education without direct guidance of family who had been through the experience. But if there’s one thing I always tell myself, it’s that with a little bit of grit and hard work, you can do anything you put your mind to! Whatever my future holds for me, I hope it is filled with more research opportunities and the chance to work with marine mammals!

Figure 5. An image of Maddie Honomichl, presenting her research poster at the Hatfield summer coastal intern symposium remotely from Port Orford!

References:

Álvarez-González, M., Suarez-Bregua, P., Pierce, G. J., & Saavedra, C. (2023). Unmanned Aerial Vehicles (UAVs) in Marine Mammal Research: A Review of Current Applications and Challenges. Drones, 7(11), 667. https://doi.org/10.3390/drones7110667

Anjara Saloma. Humpback whales (Megaptera novaeangliae) mother-calf interactions. Vertebrate Zoology. Université Paris Saclay (COmUE); Université d’Antananarivo, 2018. English. ⟨NNT : 2018SACLS138⟩. ⟨tel-02869389⟩

Burnett, J. D., Lemos, L., Barlow, D., Wing, M. G., Chandler, T., & Torres, L. G. (2019). Estimating morphometric attributes of baleen whales with photogrammetry from small UASs: A case study with blue and gray whales. Marine Mammal Science, 35(1), 108–139. https://doi.org/10.1111/mms.12527

Friard, O., & Gamba, M. (2016). BORIS: A free, versatile open‐source event‐logging software for video/audio coding and live observations. Methods in Ecology and Evolution, 7(11), 1325–1330. https://doi.org/10.1111/2041-210X.12584

Huetz, C., Saloma, A., Adam, O., Andrianarimisa, A., & Charrier, I. (2022). Ontogeny and synchrony of diving behavior in Humpback whale mothers and calves on their breeding ground. Journal of Mammalogy, 103(3), 576–585. https://doi.org/10.1093/jmammal/gyac010

Lockyer, Christina. (1984). Review of Baleen Whale (Mysticeti) Reproduction and Implications for Management. Reproduction in whales, dolphins and porpoises. Proc. conference, La Jolla, CA, 1981. 6. 27-50.

Norris, K.S., & Prescott, J.H. (1961). Observations of Pacific cetaceans of Californian and Mexican waters. University of California Publications in Zoology, 63, 291- 402.

Novotny, E., & Bente, G. (2022). Identifying Signatures of Perceived Interpersonal Synchrony. Journal of nonverbal behavior, 46(4), 485–517. https://doi.org/10.1007/s10919-022-00410-9

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 co

Smultea, M. A., Fertl, D., Bacon, C. E., Moore, M. R., James, V. R., & Würsig, B. (2017). Cetacean mother-calf behavior observed from a small aircraft off Southern California. Animal Behavior and Cognition, 4(1), 1–23. https://doi.org/10.12966/abc.01.02.2017

Zoop Gone Missing: A Whale’s Dinner Dilemma

Dawson Mohney, TOPAZ/JASPER HS Intern, Pacific High School Graduate

My name is Dawson Mohney, I am a high school intern for the 2025 TOPAZ/JASPER team this field season. I first heard about the TOPAZ/JASPER internship from my friend Jonah Lewis, a previous intern from the 2023 field season. Coincidentally, Jonah and I both graduated this year from Pacific High School here on the coast—small world. I have called Port Orford my home for most of my life, and in recent years I discovered that a gray whale research project has been happening in my own backyard. Growing up less than a mile from the Oregon Coast, I’ve spent a lot of time looking out into the water. I always liked how, no matter what happened in my life, the ocean was always there. This interest is what encouraged me to apply for the internship with the hope of discovering more about the ocean, a substantial part of my home and family.

Fig 1: Picture fellow intern Maddie took of me (Dawson) during our trip to Natural Bridges.

A critical part of this project is understanding not only the magnificent gray whales but also the much less apparent zooplankton–after all, the whales need to eat a lot of zooplankton! Many different species of zooplankton—“zoop” for short—call the Oregon coast home. Each day, as we kayak to our 12 sample stations within the gray whale feeding grounds of Mill Rocks and Tichenor’s Cove, I find myself wondering which species of zoop I’ll get to identify later under the microscope.

Throughout the duration of this internship, our team has met to discuss a few research papers published by GEMM Lab members, including research produced from the TOPAZ/JASPER projects. Recently, I read, “Do Gray Whales Count Calories? Comparing Energetic Values of Gray Whale Prey Across Two Different Feeding Grounds in the Eastern North Pacific,” by Hildebrand et al. who describe the caloric content of different zooplankton species. Before reading this paper, I didn’t realize whale prey could vary in nutritional value – much like food for humans. This paper made it clear that each of the different species of zooplankton is just as important as the last, but consuming more of the higher caloric species such as the Neomysis rayii or the Dungeness crab larvae would certainly be a welcome meal. Seeing these “healthy” meals in the area makes me hopeful for the whales.

Fig 2: Image of a crab larvae in their megalopae stage.

From reading previous blog posts, the foraging habits of the whales this season appear to be unusual. In prior TOPAZ/JASPER field seasons, gray whales have often been tracked foraging near or around our Mill Rocks and Tichenor Cove study sites. This season, we haven’t tracked a single whale in Mill Rocks and only two in Tichenor Cove. Could there just not be enough good zoop?

Along with this lack of whales, there does seem to be a lack of these “high calorie zoop species”. Our team has most frequently collected samples primarily comprising of Atylus tridens, a lower calorie prey type. In fact, during one of our earlier kayak training days this field season we collected 2,019 individual A. tridens. However, since this day we have collected sparse amounts of zooplankton in our samples, ranging from zero to 121 in a given sample. Our total zoop count thus far is 2,524 zooplankton, a third of the total zooplankton collected last field season.

Fig 3: Image of an Atylus tridens under a microscope.

As for whale presence, we have been observing many whales blows near Hell’s Gate as mentioned in last week’s blog written by fellow intern Miranda Fowles. From our cliff site, it has been difficult to know whether these are gray whales or a different kind of whale, leading us to venture out to the Heads to get a better look. The persistence of whales in this area is certainly unusual, and perhaps it can be explained by a larger amount of higher calorie zooplankton species in the Hell’s Gate area.

Fig 4: Dawson tracking blows by Hell’s Gate with the theodolite.

Being part of the TOPAZ/JASPER project, I have become exposed to what the true meaning is behind “fieldwork,” including learning how to be flexible and adapt to new challenges every day. What I have most enjoyed is the team’s ability to overcome any new hurdle together as a unit.  My dad often says, “You learn something new every day,” and this internship couldn’t embody this quote more. In just these 5 weeks, it almost feels like my head is now a couple sizes bigger.

Before this experience, I never thought much about how one might track a whale or how different microscopic species could have such a profound impact on a whale’s decision to forage. Now I feel I understand just how important these less than obvious factors are and the effort which goes behind understanding these relationships. I can only hope future opportunities teach me as much as joining the TOPAZ/JASPER legacy has—it’s an experience that, even just a few days into the 2025 field season, I knew would be hard to match.

Fig 4: Dawson (navigator) and Miranda (sampler) during kayak training on their way to Mill Rocks.

Hildebrand, L., Bernard, K. S., & Torres, L. G. (2021). Do Gray Whales Count Calories? Comparing Energetic Values of Gray Whale Prey Across Two Different Feeding Grounds in the Eastern North Pacific. Frontiers in Marine Science, 8, 683634. https://doi.org/10.3389/fmars.2021.683634

Whales Off Course: Theodolite Tracking in an Unpredicted Area

Miranda Fowles, GEMM Lab TOPAZ/JASPER Intern, OSU Fisheries and Wildlife Undergraduate

Hello! My name is Miranda Fowles, and I am the OSU intern for the 2025 TOPAZ/JASPER project this summer! I recently earned my bachelor’s degree – almost, I have one more term, but I walked at commencement in June – from Oregon State University in Fisheries, Wildlife and Conservation Sciences and a minor in Spanish. My interest in whales began at a young age during a visit to SeaWorld. While I didn’t enjoy the killer whale shows for their entertainment aspect, this exposure allowed me to see a whale for the first time. From then on, I knew I wanted to contribute to understanding more about these animals, even if I wasn’t always sure how to make that happen. My decision to pursue Fisheries and Wildlife sciences was set from the beginning, however I wondered if there were actually opportunities to study whales.

Last summer, I was a MACO intern and stayed at the Hatfield Marine Science Center where I met last year’s TOPAZ/JASPER REU student, Sophia Kormann, and she raved all about her experience, so I just had to apply for this year’s internship! I remember feeling so nervous for the interview, but Dr. Leigh Torres and Celest Sorrentino’s kindness and inspiration quickly put me to ease. When I found out I was offered the position, I was just more excited than I’d ever been!

My day-to-day life as a TOPAZ/JASPER intern here at the Port Orford Field Station looks one of two ways: either on the kayak or the cliff site. When we are ocean kayaking, we go to our 12 sampling sites in the Mill Rocks and Tichenor Cove study areas (Fig. 1), where we collect zooplankton samples (Fig. 2) and oceanographic data with our RBR (an oceanographic instrument), as well as GoPro footage. When on the cliff site, we keep our eyes peeled for any whales to take pictures of them and mark their location in the water with a theodolite.

Fig. 1: Map of our study sites (Tichenor Cove and Mill Rocks) and where we have been seeing gray whales (Hell’s Gate) circled in green, and our Cliff Site.
Fig. 2: Miranda Fowles out on the kayak pointing at her zooplankton samples.

A theodolite is an instrument that is used for mapping and engineering; in our case it is used to track where a gray whale blows and surfaces (For more info, please see this blog by previous intern Jonah Lewis). Each time a whale surfaces, we use the theodolite to create a point in space that marks its location. Once we have multiple points, we can draw lines between each point to establish the track of the whale. These tracklines can then be used to make assumptions of the whales’ behavior. For example, if the trackline is straight, and the individual is moving at a consistent speed and direction, we can assume the whale is transiting. Whereas if the trackline is going back and forth in one small area, the whale is likely searching or foraging for food (Hildebrand et al., 2022).

In last week’s blog my peer Nautika Brown showed how photo ID is a critical part in our field methods. When theodolite tracking, we assign a number with each new individual whale observation. If the whale is close enough, we also capture photographs of the whale (Fig. 3) and match it up to its given number, allowing us to link the trackline to an individual whale so we can understand more about individual behavior. Documenting individual specific behavior is important because previous research has shown that age, size and the individual ID of a whale can all influence different foraging tactic use (Bird et al., 2024). Therefore, each season as we collect more and more data, we establish a repertoire of recurring or new behaviors to sieve for trends and patterns.

Fig. 3: Photo of a gray whale surfacing captured from our cliff site.

I find animal behavior to be an integral role in many ecological studies, and I am intrigued to explore this topic more. As marine mammals that spend most of their time underwater, cetaceans are quite an inconspicuous species to study (Bird et al., 2024), but by studying their ecology through photo ID and theodolite tracking we get insight into who they are, how they behave, and where they go.

Up until this point in the season, we have theodolite tracked gray whales for 12 hours and 3 minutes (woohoo). Interestingly, most of these tracks of whales have been near an area called “Hell’s Gate”, which is located around large rocks toward the far west of our study site (Figs. 2 and 4). We can assume, but cannot be sure, that the whales are feeding here because they spend so much time in the area, and return day after day. According to Dr. Torres, the consistent use of this area near Hell’s Gate by gray whales is unusual. In the prior 10 years of the TOPAZ project, few whales have been tracked foraging in this area near Hell’s Gate, but rather most whales have foraged in the Mill Rocks and Tichenor Cove areas. It is interesting to think about why the whales are behaving differently this year. Maybe this is due to variations in prey availability at these different sites. In recent years, Port Orford has been affected by a surge in purple sea urchin density, which have overgrazed the once prominent kelp forests here. A high urchin density decreases the kelp condition, which then leads to less habitat for zooplankton, creating a decline in prey availability for gray whales (Hildebrand et al., 2024). Upon reflection of my time on the kayak, I have noticed minimal kelp and low zooplankton abundance when conducting our zooplankton drops in our Mill Rocks and Tichenor Cove study sites. Additionally, I have also noticed many purple sea urchins in our GoPro videos. With the effects of this trophic cascade in mind, not observing any gray whales in our traditional study sites is understandable. With these gray whales more commonly seen near Hell’s Gate this year, I am curious to know what prey is attracting them there. Perhaps it is a different type of prey species or one that is high in caloric value than what is in the Mill Rocks and Tichenor Cove areas.

Fig. 4: Intern Nautika Brown looking at Hell’s Gate through the binoculars. Hell’s Gate is the passage between the two large boulders in the distance.

From actively observing whales and learning from my mentor, Celest, I have started to understand that behavior is a critical piece to any form of studying gray whales (and all species). By integrating photo-ID and theodolite tracking, we can learn so much about whale behavior, from where they eat, who is spending time where, and how they may adjust their behavior in response to a changing environment. The TOPAZ/JASPER internship has allowed me to truly comprehend what field research is like, how studying the behaviors of an individual is important, and how detail and patience are extremely necessary when collecting data. As this summer is continuing, I wonder if we will continue to see gray whales primarily feeding in the Hell’s Gate area, or if we will start to observe them more in the Mill Rocks and Tichenor Cove sites like previous years. The thrill of seeing gray whales is unlike any other, and I am so ready to see more whales this season!

References:

Bird, C. N., Pirotta, E., New, L., Bierlich, K. C., Donnelly, M., Hildebrand, L., Fernandez Ajó, A., & Torres, L. G. (2024). Growing into it: Evidence of an ontogenetic shift in grey whale use of foraging tactics. Animal Behaviour, 214, 121–135. https://doi.org/10.1016/j.anbehav.2024.06.004

Hildebrand, L., Derville, S., Hildebrand, I., & Torres, L. G. (2024). Exploring indirect effects of a classic trophic cascade between urchins and kelp on zooplankton and whales. Scientific Reports, 14(1), 9815. https://doi.org/10.1038/s41598-024-59964-x

Hildebrand, L, Sullivan, F. A., Orben, R. A., Derville. S., Torres L. G. (2022) Trade-offs in prey quantity and quality in gray whale foraging. Mar Ecol Prog Ser 695:189-201 https://doi-org.oregonstate.idm.oclc.org/10.3354/meps14115

A Nauti(k)al Journey with Photo ID  

Nautika Brown, GEMM Lab TOPAZ/JASPER Intern, recent Lake Roosevelt high school graduate 

Hi everyone! I’m Nautika Brown, a recent graduate at Lake Roosevelt High School in a small town on the Colville Indian Reservation in Washington.  

Growing up in beautiful Eastern Washington, I spent most all my days outside and, from the time I could swim, I was in the water. When I was little, I used to wish I was a fish so I could live underwater and swim every day of my life. And since then, I have always been fascinated by all animals that could live in and around water. This very fascination is what sparked the idea of becoming a marine biologist. Animals AND water, perfect! 

(Left): Nautika holding a fish she caught back home in Buffalo Lake.
(Right) Nautika with a new type of catch (purple sea urchin) while conducting a zooplankton drop at station MR 18.

Although, as you might assume, living on a reservation surrounded by wheat fields and a few lakes, there weren’t a lot of opportunities to explore my passion. Hence, when I came across a flyer for the 2025 TOPAZ/JASPER internship just a few days before the deadline, I submitted my application as soon as I could. I was so thrilled, I couldn’t imagine getting the chance to kayak with whales on the ocean! It was all I could talk about for weeks on end. 

Since starting my internship here in Port Orford, I have learned so many new things. During our first couple weeks at the field station, we went through a few different classes and trainings, one of them being a presentation on photo identification by GEMM Lab PhD candidate Lisa Hildebrand. Prior to this presentation, I had no idea photos were so important in marine mammal science. During this presentation, I learned about the many different identifiers of a whale and how you can apply them when looking at photos to identify a specific individual. For example, Lisa’s rule of three’s: to confidently ascertain an individual’s ID, at least 3 consistent characteristics between photos must be matched. At the end of this presentation, we even played a guessing game to test our new photo ID’ing skills. (I did pretty well – not to brag or anything.) 

Now with my new photo ID skills, I was excited to capture a photo of a gray whale. On our second day of training, we did spot a whale—but thanks to my newly learned photo-ID skills, I quickly realized it wasn’t the gray whale I was expecting. When the whale first surfaced, I noticed the lack of dorsal knuckles and its distinctly darker body—clear signs it wasn’t a gray whale, but a humpback whale! While it is common to see gray whales from shore along the Oregon coast as they feed in the very nearshore habitat, humpback whales are typically found in much deeper waters, further from shore. Over the last week we have seen a humpback whale within our study site across several days—and we’re not the only ones!  When chatting with the local fisherman pre and post kayak, a few have expressed their own excitement about seeing a humpback so close to shore as well. Throughout our conversations, the question of why a humpback would be so close to shore weighed on our minds, leading me to do my own online research.  

To investigate whether these humpback sightings have been of the same individual or multiple different whales, I decided to review the photos we have captured to try and determine a match. Once I conducted a first pass of the photos, I downloaded 10 of the most clear and definite shots and compared the photos using Lisa’s rule of threes. After reviewing the photos, I noticed that the humpback whale’s dorsal hump resembled one from a previous sighting, but I couldn’t find any other distinguishing markings on its body. While I couldn’t confirm we have been observing the same humpback whale, I gained a deeper understanding of the importance of clear, high-quality photos in photo-ID work.

(Left) Nautika getting ready to take pictures of whales with camera on our cliff site. 
(Right) Picture of humpback whale caught on camera on our 2nd day of training

After reading a few articles about humpback whale migration through Oregon, I found a few potential reasons behind this whale’s occurrence close to the shores of Port Orford. During the summer months, humpbacks travel to colder, more nutrient-dense places to feed, often near the shelf break (where the depth of the ocean suddenly gets deeper, around 200 m). Interestingly, the shelf break near Port Orford is not far from shore, and is a known hotspot for foraging humpback whales in the summer (Derville et al. 2022).  Humpback whales filter-feed on krill and small fish, so perhaps enough prey has moved into the waters near Port Orford to attract a humpback so close to shore. Another reason for this humpback to be close to shore could be the effects of climate change. As the waters warm, food distribution changes, causing multiple species, including humpbacks, to change their feeding grounds and migration routes (read more here).  Although the humpback sightings are outside the range of our kayak zooplankton sampling stations, it would be interesting to see what prey is in the water that is keeping them around.

So far, I have learned the importance of photo identification in marine mammal science and the many ways it can be used. I’m especially grateful for Lisa’s fun and insightful presentation at the start of the season and even more surprised by how quickly I was able to put those photo-ID skills into practice. With three weeks left in the field season, I’m excited to keep building on what I’ve learned and to keep growing my skills. And speaking of building, I’m also curious to see how my “kayak muscles” are shaping up by the end of this amazing TOPAZ/JASPER internship!  

  (Left) Nautika and Celest on kayak heading Mill Rocks stations. 
(Right) Miranda and Nautika wrapping up kayak training with a celebratory team dab

Derville, S., D.R. Barlow, C. Hayslip, and L.G. Torres, Seasonal, Annual, and Decadal Distribution of Three Rorqual Whale Species Relative to Dynamic Ocean Conditions Off Oregon, USA. Frontiers in Marine Science, 2022. 9: p. 868566.

A pinch of salty, silly, and science-y: meet Team Dabwich

Celest Sorrentino, GEMM Lab Master’s student, OSU Department of Fisheries, Wildlife and Conservation Sciences, Geospatial Ecology of Marine Megafauna Lab 

As a loyal and trusted GEMM Lab blog reader, I am sure you know just what time of year it is: the beginning of the 11th annual TOPAZ/JASPER field season where we study whales and their prey while also training the next generation of scientists. The start of the season has been kicked into high tail already and we have many updates to share. Fear not, dear reader, as I am here to release you from relentlessly refreshing your inbox for the long-awaited introduction of the TOPAZ/JASPER team that is taking the project into their second decade.

But first, to appreciate the present milestone, it’s worth revisiting the legacy of those who guided us to this moment. The TOPAZ/JASPER  projects began in 2015, with PI. Dr. Leigh Torres and master’s student Florence Sullivan (2015-2018), and continued forward with Lisa Hildebrand (2018-2021), and Allison Dawn (2022-2024). Now, as a new droplet in this stream of brilliant leaders before me, I feel immense gratitude to be the master’s student leading the TOPAZ/JASPER team this summer. Having been trained by Allison Dawn with Team Protein in 2024, and full unwavering support from Leigh and each leader before me, I enter this new role with confidence and excitement for the next six gray-whale-and-zooplankton filled weeks of data collection. Now, let’s meet the young scientist interns for 2025!

(Left picture) Maddie (right) with Nautika (top) and Celest (left) during their kayak training.
(Right picture) Photo Maddie took of a humpback in the Port Orford Bay.

Madison (Maddie) Honomichl is a senior wrapping up her last  semester of undergrad at CSU Monterrey Bay this fall to gain a degree in Marine Science. As the GEMM Lab’s REU intern this summer, Maddie began her internship in June by joining me in Newport to learn more about gray whale and pymgy blue whale mother-calf relationships. Without spoiling too much (you’ll hear more from her in her blog post in just a few weeks!) her project focuses on capturing mother-calf blow synchrony of gray and blue whales in drone footage. Now in Port Orford, her gifted talent for photography has been excellent in helping capture photos of traveling whales on the cliff.

(Left picture) Nautika finding a purple urchin after a successful zooplankton drop at our station MR 18.
(Right picture) Miranda(front) and Nautika(rear) after their first kayak training, where Nautika accidentally fell into the water but got back on the kayak in record breaking time, still in good spirits to dab!

Nautika Brown is one of our high school interns from Coulee Dam, Washington. Having just graduated, Nautika’s ambition and passion for studying wildlife lead her to apply to our TOPAZ/JASPER project and we are so happy she did. Accidentally hilarious, she has made everything from kayak training to zooplankton identification that much more enjoyable—reminding the team to have some fun while still getting the job done.

(Left picture) Dawson leading the team with the heavy theodolite stand up to the cliff.
(Right picture) The team hyper locked in on tracking a humpback whale in the bay, working together to describe the position of the whale for Dawson on the theodolite.

Dawson Mohney is our Port Orford local, having recently graduated from Pacific High School in May. Though he might not know the best spots around town, Dawson’s demeanor mirrors that of Port Orford itself: kind, welcoming, and always helpful. Always up for any task, he is the first to ask if anyone needs help with carrying equipment up to the cliff or cooking a ground beef refried beans mash for team dinner. Come fall Dawson is excited to start his first semester at Southwestern Oregon Community college.

(Left picture) Miranda enjoying an outdoor stroll of Port Orford beaches.
(Right picture) Miranda stoked on catching so many atylus tridens for her first kayak training day!

Miranda Fowles is a recent graduate at Oregon State University having completed her major in Fisheries, Wildlife, and Conservation Sciences with a minor in Spanish. Originally from Seattle, her childhood memories include kayaking with her family, so ocean kayaking has come naturally. Miranda’s genuine curiosity shines through in her eagerness to ask questions about whale life histories and their social dynamics. She’s expressed a clear passion for continuing her journey in marine science and academia.

We are now T-minus 2 days until the last of the team’s training period, and we couldn’t be more thrilled for the 4 more weeks to come. Through unexpected wildlife sightings and spontaneous team jokes, our team has only grown stronger and more connected. For all of the interns, this experience is not only their first experience with marine fieldwork, but also their longest. Training days have been both rewarding and physically strengthening; we’ve watched harbor seals lounging between Mill Rocks and tracked a particularly active humpback whale that keeps surfacing in the bay—all while developing what we now call our “ultimate kayak muscles.” By the time lunch rolls around, it feels like an ultimate power recharge, to continue forward with data processing. As any marine field scientist will tell you: there’s something deeply satisfying about coming back to shore and sinking your teeth into a handmade sandwich.

And speaking of our absolute craving for sandwiches, this team has unexpectedly brought back the 2010s dab—with such enthusiasm that it was only right to fuse “dab” with our love for chips-in-sandwiches. With this, I share with your our new, very official team name:

Team Dabwich.

With the right amount of salty, silly, and scienc-y, Team Dabwich is ready to crush the 11th TOPAZ/JASPER field season.

Team Dabwich dabbing right before a successful kayak training
ヽ(⌐_⌐ゞ)!

The slow, but ever turning, cycles of science: a look under the hood of the scientific method

Dr. Clara Bird, Postdoctoral Scholar, OSU Department of Fisheries, Wildlife, and Conservation Sciences, GEMM Lab & LABIRINTO

Cycles can be found everywhere in nature and our lives. From tides and seasons to school years and art projects, we’re constantly experiencing cycles of varying scales. Spring on the Oregon coast brings several important cyclical events: more daylight, the oceanographic spring transition, and the return of our beloved gray whales – just to name a few. On my own personal scale, I’ve been thinking about the cycles we experience as scientists a lot lately, since I’ve recently transitioned out of graduate school and into my current position as a postdoctoral scholar.

Starting this new postdoc has been a bit jarring, as it’s felt like starting over. Even though I’m still working at the Marine Mammal Institute and still studying gray whales, I’ve been learning new skills, knowledge and theory, which pushes me to re-start the cycle of the scientific method, the process we follow in research (Figure 1). Broadly, we start by observing a system and asking a question about a potential pattern or event we see. We then come up with a hypothesis (or two or ten) to address our question(s). The next steps are to collect the data we need to answer our question(s) and test our hypotheses, analyze that data (i.e. run some statistical models), and draw some conclusions from the analysis results. While it seems quite linear, the process of data collection and analysis always leads to more questions than answers, and we inevitably start the cycle all over again.

Figure 1. Schematic depicting the scientific method

Throughout my scientific training I’ve gained experience in all these phases, but I’ve also learned just how many add-ons and do-overs there are in this process (Figure 2). Developing questions and hypotheses often requires a long and winding path through the literature, depending on how much you already know. These steps are often some of the first and biggest steps in graduate school. You need to learn as much as you can about the field and questions you are interested in, as this will inform what has already been done, where the knowledge gaps are, and the hypotheses you’re developing. For example, we often back up a hypothesis with references to studies that have answered our question in different systems. The learning curve is steep, and it’s important to not understate the work that goes into this phase. Early in my career, I remember hearing that “asking the good questions” is a critical skill for research. At the time that sounded like some vague, innate characteristic, and working to gain this ability felt ambiguous and overwhelming. I was absolutely wrong. Like most skills, knowing how to ask good questions is more about experience than intelligence. Here, experience is a combination of reading the literature and practice formulating questions based on the literature.

Figure 2. A more realistic version of the scientific method

Beyond this lesson, I also had to learn that what qualifies a question as “good” also depends on the funding source. In many research institutions, including those in the U.S., scientists are responsible for finding the funding to run their research projects. Funding a project includes salary for the scientists (e.g., professors, grad students, post docs), the cost of collecting and analyzing the data (e.g., travel, equipment, boat time), and the cost of publishing and sharing our findings (e.g., publication costs). The programs we solicit funding from often have their own priorities, so a big part of the research cycle is finding a funding source that is interested in the kinds of questions you want to ask and then adjusting your own questions and hypotheses to align with the funding source’s priorities and budget. The actual application includes writing a proposal where we (1) summarize all the background research justifying the novelty and value of the questions we want to ask and backing up our hypotheses and (2) describe how we plan on answering those questions. Funding is competitive and we typically apply multiple times before being successful. Furthermore, we often apply to multiple funding sources to support the same project. Since each source has its own focus, this ends up being an exercise in coming up with multiple ways to frame and justify a project.

Once we have funding (which can be years after the start of the cycle), we can finally start collecting, analyzing, and interpreting the data. But each of these steps has its own sub-cycles and complexities. Data collection can take years and involve all kinds of troubleshooting equipment issues, logistics, and methods. Depending on your question, data processing and analysis may involve developing your own method. For example, our lab asks a lot of questions about the morphology and body condition of whales. But before we could answer those questions, we first had to work out the best way to accurately measure whales from drone imagery while accounting for measurement uncertainty (read more here). This separate cycle of method development involved so many sub-projects and new software tools that Dr. KC Bierlich now leads the Marine Mammal Institute’s Center of Drone Excellence (CODEX).

Data analysis and interpretation brings us back to the literature review part of the cycle. But now we are looking for examples of how similar data have been analyzed previously and for studies to which we can compare our results. Then, after testing out different models and triple checking our analysis, we’re finally ready to share our findings. We share our results through conference presentations, publications (after the peer review cycle), outreach talks, and press releases that lead to media pieces and interviews.

In addition to the excitement of sharing our findings with the world, we’re simultaneously hyper-aware of all the caveats and limitations of our work. We’re always left with a long list of follow-up questions, thus starting the cycle again. From a zoomed-out perspective these results can form a clean, linear story. But zooming in reveals the reality of years and years of multiple overlapping cycles that have had to pass roadblocks and restart countless times. For example, after nine years for research, the GRANITE project has produced an impressive suite of results addressing questions related to Pacific Coast Feeding Group gray whale morphology, health, hormones, space use, and behavior. It took years of data collection, proposal writing, training, and multiple researchers working through their own project cycles to get here (and we’re not done).

Transitioning out of graduate school has meant expanding my scope of attention to multiple cycles running in parallel, re-starting the literature review process for new projects, and spending a lot more time in the proposal writing sub-cycle. While it’s felt overwhelming at times, I’ve also enjoyed digging into new topics and skills. It’s an interesting balance of experiencing the discomfort that comes with being a beginner while simultaneously drawing comfort from the knowledge that I’ve experienced this cycle before and know how to learn something new.

A consequence of learning the scientific process is growing accustomed to this cyclical nature. As scientists we know that it’s a slow process, that every result is just the start of a new cycle, and that future work building on a result may agree or disagree with the previous finding. But the way scientific findings are shared with the public doesn’t necessarily reflect the process. Catchy headlines and brief summaries often present findings as definitive and satisfying conclusions to a story. Behind those headlines are years of set up, data collection, analysis, and a suite of caveats that we want to dig into in the future. The results of any given study reflect our best current knowledge at that point in the cycle. By design, that knowledge will grow and change as we move forward.

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The Hitchhiker’s Guide to the Gray Whale: Cetacean Cyamid Coverage Explained

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

When most people think about monitoring the health of a 40-ton gray whale, they picture blubber thickness, dive patterns, or perhaps growth rates. But what if some of the most telling signs are found not in the whale’s bulk, but right on the surface–embedded in its skin, and even crawling across it?

As part of the GRANITE project, my research focuses on using a long-term photographic dataset (>347,000 photos from 10 years!) to evaluate epidermal indicators of stress and health in Pacific Coast Feeding Group (PCFG) gray whales (Eschrichtius robustus) foraging off the Oregon coast. My central questions ask:

  • Can we use features visible on the skin like epidermal diseases, lesion severity, scarring from orcas, boats, and fishing gear, and potentially cyamid loads as biomarkers of physiological stress or nutritional status?
  • How do these skin-based indicators correlate with environmental variables, prey availability, fecal hormones, and overall body condition?

By tracking these patterns across individuals and years, my goal is to understand how gray whales are responding to a changing ocean and whether their skin can tell us more about what’s under the surface.

What are cyamids?

Cyamids, more commonly known as “whale lice”, are small crustaceans that live exclusively on marine mammals. Despite their nickname, cyamids are not true lice—they’re actually amphipod ectoparasites, more closely related to beach hoppers than anything you’d find in your hair. For gray whales (Eschrichtius robustus), these tiny passengers are a constant presence throughout their lives.

Figure 1. Gray whale blow hole area covered in barnacles and cyamids. The circle inset shows a zoomed in area where you can see the orange cyamids aggregating near the more yellow barnacles.

Each whale can host thousands of cyamids at a time, with individuals often clustering in specific areas of the body that provide physical refuge from the currents: around the blowhole, in the crevices of flukes, along the rostrum, genital slits, and especially around wounds or skin irregularities (Figure 1). Unlike barnacles, which attach directly to the skin and remain stationary while they feed on nutrients in the passing water, cyamids grasp onto the whale’s body using claw-like appendages, feeding on sloughed skin and bodily fluids. This relationship is generally not thought to be harmful to the whale, but high cyamid loads can be indicative of poor health, injury, or compromised immune function.

There are several species of cyamids, and many are host-specific—meaning they’ve evolved alongside particular whale species. In gray whales, the most common is Cyamus scammoni, which specializes on gray whales and is rarely found elsewhere. Other species found on gray whales include Cyamus kessleri, and the rarer Cyamus ceti. Cyamids are transmitted primarily from mother to calf, which helps explain their host fidelity, but horizontal transmission (between unrelated individuals) may also occur during close contact which can explain some rare occurrences of cyamids that are found outside of their general host species. In fact, Cyamus ceti was only found once on gray whales in 1861 but is generally thought to be specific to bowhead whales, giving us potential insight into interspecies interactions (bowhead and gray whales can spatially overlap on Arctic foraging grounds).

Figure 2. Cyamus scammoni close up photographs of (A) aggregation, (B) juvenile stage, (C) dorsal side of an adult, and (D) ventral side of an adult showcasing the cyamids corkscrew shaped gills (Takeda et al. 2005)

Because cyamids are permanent residents of the whale’s skin, they offer a unique window into both individual whale life histories and broader ecological trends. Their location, abundance, and distribution can potentially inform us about wound healing, residency duration in foraging areas, and even stress or health status—which makes them an unexpectedly valuable focal point in drone and photograph-based monitoring efforts like in the GRANITE project.

Cyamid Life History

Cyamids are obligate ectoparasites, meaning they spend their entire life on a whale and cannot survive independently in the open ocean. Unlike free-swimming crustaceans, cyamids are permanently attached to the skin or embedded within crevices of the whale’s body, often clinging to roughened areas, scars, embedded barnacles, or calloused skin where they can anchor themselves more securely.

They begin life as tiny juveniles, hatching from eggs carried in the brood pouch of a female cyamid. Rather than undergoing a larval phase in the water column like many marine invertebrates, cyamids develop directly into miniature versions of adults and remain on the whale from birth. This direct development is essential because there’s no safe habitat for a larval cyamid in the open ocean: the host whale is both nursery and home.

Most transmission occurs from mother to calf during the close physical contact of early life. Calves born in the warm lagoons of Baja California, Mexico where gray whales calve and nurse during the winter inherit their cyamid colonies during nursing, rubbing, and swimming alongside their mothers. These early colonizers will multiply as the calf grows and can remain with the whale for years, forming the basis of a persistent, host-specific population.

For Cyamus scammoni specifically (our gray whale specific cyamid), adults will breed in the summer just before the southbound migration. Females will have around 1,000 eggs in their brood pouch, although only about a 60% are fertilized (Leung, 1976). These eggs will hatch in the fall while the gray whales take on their southbound migration but they will stay in the safety of the brood pouch for around 2 to 3 months. The juveniles will be released in the winter, when gray whales arrive in the Baja lagoons where they will then find shelter within the crevices of their host gray whale. Juveniles reach maturity during the northbound migration and will be a full-grown brood upon arrival to summer grounds. While the cycle takes about 8 months to complete, there are juveniles found along the gray whales year-round, leading us to believe that there is likely overlap between broods. For our less abundant Cyamus kessleri, the life cycle is very similar, but the juveniles reach maturity before the gray whales northbound migration to summer feeding grounds. Also, there are around 300 eggs in the Cyamus kessleri brood pouches that have a higher rate of fertilization (75-80%) than Cyamus scammoni (60%) (Leung, 1976)

In short, the life of a cyamid is fully bound to the life of a whale. Every migration, dive, foraging event, and scar the whale experiences becomes part of the cyamid’s environment. By studying them, we gain another lens through which to interpret the health, behavior, and ecology of gray whales on the Oregon Coast.

Uses in Cetacean Health Assessments

As we’ve established, cyamids have unique life histories as ectoparasites and may be valuable indicators in cetacean health assessments across multiple whale species. Because they often congregate around wounds, lesions, and areas of poor skin integrity, their presence and distribution can reveal important clues about a whale’s physical condition, injury history, and immune response. However, studies that have made these connections have variable results.

In species like North Atlantic right whales (Pettis et al. 2004, Pirotta et al. 2023), harbor porpoises (Lehnert et al. 2021), and gray whales (Raverty et al. 2024), researchers have used visual surveys and photographic analysis to quantify cyamid loads in living, stranded, and hunted whales. Researchers can score cyamid presence by identifying attachment sites (e.g. blowhole, scar, dorsal ridge) and estimating the relative coverage by using standardized reference images to maintain consistency. In these studies, whales with heavy cyamid coverage, especially in sensitive regions like the blowhole, mouthline, and genital area, often show signs of poor health or stress, such as emaciation, scarring from entanglement, or chronic skin conditions. Cyamid coverage is sometimes used alongside body condition indices and lesion scoring to build a more complete health profile (Pirotta et al. 2023). There are also studies that show no connections, or even positive connections between body condition and cyamid coverage (Von Duyke et al. 2016).

While cyamids are often associated with injured, inflamed, or otherwise damaged skin, there is no evidence that points towards cyamids directly damaging the skin themselves. However, more work needs to be done to assess their role in the healing processes. Additionally, it’s been noted that more work is needed on the role of cyamids and disease spread (Overstreet et al. 2009). For the PCFG, there is an iconic whale we call “Scarlett” (also known as “Scarback”) who has a large scar on the right side of her back that is highly identifiable due to the orange swarm of cyamids that are constantly surrounding the edges of the wound. She has managed to survive and thrive, producing many calves over the years, but questions remain: How are the cyamids affecting the healing process? Are they increasing or decreasing the risk of infection? How does the frequency of large injuries like this on whales contribute to the cyamid population over evolutionary time?

Figure 3. Right side of PCFG icon, “Scarlett” showing her massive scar covered with orange aggregations of cyamids.

Because whales are complex, highly mobile, long-lived creatures with a constant population of cyamid hitchhikers their skin condition is likely representative of specific to life history, phylogeography, and demographic traits of individuals. While we know that cyamids generally eat sloughed or damaged skin on the whale, what this behavior and symbiosis means for each whale’s individual physiology can be highly complex. Through our high-resolution drone and lateral imagery of the same individuals over time paired with other data sources, such as body condition and prey availability, cyamid scores can offer key insights into how environmental stressors and foraging success affect individual and population-level whale health.

These tiny crustaceans, clinging to the folds and scars of their hosts, might seem like background noise in a study focused on body condition or foraging ecology—but they’re far from incidental. In my research, I’ve come to see cyamids as part of the bigger story: silent indicators of stress, recovery, movement, and resilience. By pairing imagery of PCFG gray whale skin with data on prey availability and environmental conditions, I’m working to understand how foraging success and anthropogenic stressors (such as vessel traffic and entanglements) manifest not just in a whale’s body condition, but in the skin itself. The presence, distribution, and density of cyamids may offer yet another layer of insight into how gray whales are coping with changing ocean conditions. It’s a reminder that even the smallest details, like a patch of whale lice, can help us ask bigger questions about the health, resilience, and future of these cetaceans.

References

Callahan, C.M., n.d. MOLECULAR SYSTEMATICS AND POPULATION GENETICS OF WHALE LICE (AMPHIPODA: CYAMIDAE) LIVING ON GRAY WHALE ISLANDS.

Lehnert, K., IJsseldijk, L.L., Uy, M.L., Boyi, J.O., van Schalkwijk, L., Tollenaar, E.A.P., Gröne, A., Wohlsein, P., Siebert, U., 2021. Whale lice (Isocyamus deltobranchium & Isocyamus delphinii; Cyamidae) prevalence in odontocetes off the German and Dutch coasts – morphological and molecular characterization and health implications. International Journal for Parasitology: Parasites and Wildlife 15, 22–30. https://doi.org/10.1016/j.ijppaw.2021.02.015

Leung, Y., 1976. Life cycle of cyamus scammoni (amphipoda: cyamidae), ectoparasite of gray whale, with a remark on the associated species. Scientific Reports of the Whales Research Institute 28, 153–160.

Overstreet, R.M., Jovonovich, J., Ma, H., 2009. Parasitic crustaceans as vectors of viruses, with an emphasis on three penaeid viruses. Integrative and Comparative Biology 49, 127–141. https://doi.org/10.1093/icb/icp033

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. Can. J. Zool. 82, 8–19. https://doi.org/10.1139/z03-207

Pirotta, E., Schick, R.S., Hamilton, P.K., Harris, C.M., Hewitt, J., Knowlton, A.R., Kraus, S.D., Meyer-Gutbrod, E., Moore, M.J., Pettis, H.M., Photopoulou, T., Rolland, R.M., Tyack, P.L., Thomas, L., 2023. Estimating the effects of stressors on the health, survival and reproduction of a critically endangered, long-lived species. Oikos 2023, e09801. https://doi.org/10.1111/oik.09801

Raverty, S., Duignan, P., Greig, D., Huggins, J.L., Huntington, K.B., Garner, M., Calambokidis, J., Cottrell, P., Danil, K., D’Alessandro, D., Duffield, D., Flannery, M., Gulland, F.M., Halaska, B., Lambourn, D.M., Lehnhart, T., Urbán R., J., Rowles, T., Rice, J., Savage, K., Wilkinson, K., Greenman, J., Viezbicke, J., Cottrell, B., Goley, P.D., Martinez, M., Fauquier, D., 2024. Gray whale (Eschrichtius robustus) post-mortem findings from December 2018 through 2021 during the Unusual Mortality Event in the Eastern North Pacific. PLoS One 19, e0295861. https://doi.org/10.1371/journal.pone.0295861

Stimmelmayr, R., Gulland, F.M.D., 2020. Gray Whale (Eschrichtius robustus) Health and Disease: Review and Future Directions. Front. Mar. Sci. 7. https://doi.org/10.3389/fmars.2020.588820

Takeda, M., Ogino, M., n.d. Record of a Whale Louse, Cyamus scammoni Dall (Crustacea: Amphipoda: Cyamidae), from the Gray Whale Strayed into Tokyo Bay, the Pacific Coast of Japan.

Von Duyke, A.L., Stimmelmayr, R., Sheffield, G., Sformo, T., Suydam, R., Givens, G.H., George, J.C., 2016. Prevalence and Abundance of Cyamid “Whale Lice” (Cyamus ceti) on Subsistence Harvested Bowhead Whales (Balaena mysticetus). Arctic 69, 331–340.

Würsig, B., Thewissen, J.G.M., Kovacs, K.M., 2017. Encyclopedia of Marine Mammals. Elsevier Science & Technology, Chantilly, UNITED STATES.

The blues are back in town: recap of the SAPPHIRE 2025 field season

By Dr. Dawn Barlow & Dr. Leigh Torres, OSU Department of Fisheries, Wildlife, and Conservation Sciences, Geospatial Ecology of Marine Megafauna Lab

As the sun set on February 16th, the R/V Star Keys pulled into Wellington Harbour, marking the end of the 2025 SAPPHIRE field season. The crew and science team returned to shore after a packed, productive, and successful three weeks at sea studying the impacts of environmental change on blue whales and krill in the South Taranaki Bight, Aotearoa New Zealand.

A blue whale comes up for air in the South Taranaki Bight.

In stark contrast to the 2024 field season, which featured dense and seemingly endless layers of gelatinous salps in the water and no krill or blue whales in the South Taranaki Bight, the 2025 field season was filled with blue whales and krill. In our three weeks aboard our research vessel Star Keys this year, we observed 66 blue whales, most of which were lunge feeding at the surface on dense patches of krill. We also collected krill for on-board respiration experiments and to be frozen to measure their lengths, weights, and caloric content. We recovered two hydrophones that recorded blue whale calls for the past year, and replaced them with two more. We collected identification photos, skin and blubber tissue samples for genetic and hormone analysis, and flew drones over almost all whales we encountered to measure body condition and morphology. We conducted water column profiles to measure the oceanography of the region, and mapped the prey field as we surveyed using a scientific echosounder.

Map of our survey effort (gray tracklines), blue whale sightings (red circles), and hydrophone locations (purple stars).

Around the world, we are currently bearing witness to environmental change. Our survey last year in 2024 was a reminder of the challenges these blue whales face to survive and thrive in an increasingly unpredictable ocean. This year was a poignant example of the vibrant marine life that exists here in the South Taranaki Bight when ocean conditions align more closely with what is expected, and of the incredible resilience of these animals as they navigate changing waters. These contrasting conditions over multiple years are key to our understanding as we study the impacts of climate change on krill and blue whales through the SAPPHIRE project.

Drone image of a blue whale coming to the surface.

The fieldwork we do to collect these data is motivated by scientific questions, management needs, and fascination with this ecosystem. But ultimately, what makes fieldwork possible and memorable is the people. We are deeply grateful for the many partners on the SAPPHIRE project. The 2025 science team was made up of Leigh Torres, Dawn Barlow, KC Bierlich, Kim Bernard (Oregon State University), Mike Ogle, and Ros Cole (Department of Conservation). The outstanding crew of the R/V Star Keys (Western Work Boats), Josh Fowden, Dave Futter, and Jordy Maiden-Drum, kept us safe, sailing, fed, and happy for three intense weeks. We are also grateful for our shore support, including our colleagues at Cornell University’s Yang Center for Conservation Bioacoustics, NIWA, the Marine Mammal Institute at Oregon State University, and the University of Auckland. Importantly, we deeply appreciate our many stakeholders who help us share, learn, and make our findings meaningful, including the Department of Conservation, the people of Aotearoa, and iwi across our study region, especially Ngāruahine who hosted us at the Rangatapu Marae for a profound hui with a powerful pōwhiri and critical wānanga of knowledge sharing.

Drone image of a blue whale mom and calf pair.

Now the next phase of the work begins. We have many terabytes of data to process, analyze, interpret, and share. We will certainly have our hands full. But while we are at our computers back in Oregon, we will be holding the memories of this field season close: The brilliant turquoise glow of a blue whale just below the surface, the sound of the deep exhalation as the whale comes up for air, and the awe of looking into a blue whale’s eye as it engulfs a dense swarm of krill; The golden sunset lighting and moon rise over Cape Farewell, and Mount Taranaki towering over the blue waters of the South Taranaki Bight; The giddy exclamations or silent awe of those of us privileged to spend time in these waters observing these animals, and the visions that linger just behind our eyelids as we fell into an exhausted sleep. We will see what the next year holds for the SAPPHIRE team and the blue whales and krill of the South Taranaki Bight.

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Demystifying AI: a brief overview of Image-Pre-Processing and a Machine Learning Workflow

Celest Sorrentino, MSc student, OSU Dept of Fisheries, Wildlife and Conservation Sciences, GEMM Lab

The first memory I have of A.I. (Artificial Intelligence) stems from one of my favorite movies growing up: I, Robot (2004). Shifting focus from the sci-fi thriller plot, the distinguished notion of a machine integrating into normal everyday life to perform human tasks, such as converse and automate labor, sparks intrigue. In 2014, my own realization of sci-fi fantasy turned reality initiated with the advertisements of self-driving cars by TESLA. But how does one go from a standard tool, like a vehicle, to an automated machine?

Fig 1: Tesla Self-Driving car, image by Bloomberg.com

For my first thesis chapter, I am applying a machine learning model to our lab’s drone video dataset to understand whale mother-calf associations, which is in continuation of my previous internship in 2022. A.I. has absolutely skyrocketed in marine science and hundreds of papers have confirmed the advantage in using machine learning models, such as in species abundance estimates (Boulent et al 2023), whale morphometrics (Bierlich et al 2024), and even animal tracking (Periera et al 2022). Specifically, Dr. KC Bierlich recently led a publication on an incredible A.I. model that can extract still images from drone footage to be subsequently used for body morphometric analysis. Earlier this year my lab mate Nat wrote an insightful blog introducing the history of A.I. and how she uses A.I. for image segmentation to quantify mysid swarms. For those of us who study animal behavior and utilize video-based tools for observation, A.I. is a sweet treat we’ve been craving to speed up and improve our analyses —but where do we start?

With a Venn Diagram and definitions of course!

Figure 1: Venn diagram demonstrating the relationships of 4 subsets of AI (Machine learning, Deep-learning, Computer Vision, and Natural Language Processing) and how they relate to one another.

Good terms to know:

Artificial Intelligence: a machine/model built to mimic human intelligence.

Machine Learning: a subset of A.I. that uses statistical algorithms to recognize patterns and form predictions, usually requiring human intervention for correction.

Deep-learning: a specific form of machine learning that is meant to mimic human neural networks through artificial neural networks (ANN) by recognizing hierarchal patterns with minimal to no human-intervention to correct.

Computer Vision: a type of machine learning that enables a machine/model to gather and retain information from images, video, etc.

Natural Language Processing: a subset of machine learning in which a machine/model to identify, understand, and create text and speech.

(Still a bit confused? A great example of the difference between machine learning and deep-learning can be found here)

So, you have a dataset, what’s the pipeline?

Figure 2: How to go from your research question and use your dataset to using an A.I. model.

First, we must consider what type of data we have and our question. In fact, you might find these two questions are complimentary: What type of questions does our dataset inspire and/or what type of dataset is needed to answer our question?

Responses to these questions can guide whether A.I. is beneficial to invest in and which type to pursue. In my case, we have an imagery dataset (i.e., drone videos) and our question explores the relationship of mom-calf proximity as an indicator of calf-independence. Therefore, a model that employs Computer Vision is a sensible decision because we need a model that extracts information from imagery. From that decision, I then selected SLEAP A.I. as the deep-learning model I’ll use to identify and track animals in video (Pereira et al 2022).

Figure 3: A broad schematic of the workflow utilizing a computer vision* model. As detailed above, a computer vision model is a machine learning model that uses images/videos as a dataset to retain information.

Why is image pre-processing important?

Image pre-processing is an essential step in “cleaning” the imagery data into a functional and insightful format for the machine learning model to extract information. Although tedious to some, I find this to be an exciting yet challenging step to push my ability to reframe my own perspective into another, a trait I believe all researchers share.

A few methods for image/video preprocessing include Resizing, Grayscaling, Noise Reduction, Normalization, Binarization, and Contrast enhancement. I found the following definitions and Python code by Maahi Patel to be incredibly concise and helpful. (Medium.com)

• Resizing: Resizing images to a uniform size is important for machine learning algorithms to function properly. We can use OpenCV’s resize() method to resize images.
• Grayscaling: Converting color images to grayscale can simplify your image data and reduce computational needs for some algorithms. The cvtColor() method can be used to convert RGB to grayscale.
• Noise reduction: Smoothing, blurring, and filtering techniques can be applied to remove unwanted noise from images. The GaussianBlur () and medianBlur () methods are commonly used for this.
• Normalization: Normalization adjusts the intensity values of pixels to a desired range, often between 0 to 1. This step can improve the performance of machine learning models. Normalize () from scikit-image can be used for this.
• Binarization: Binarization converts grayscale images to black and white by thresholding. The threshold () method is used to binarize images in OpenCV.
• Contrast enhancement: The contrast of images can be adjusted using histogram equalization. The equalizeHist () method enhances the contrast of images.

When deciding which between these techniques is best to apply to a dataset, it can be useful to think ahead about how you ultimately intend to deploy this model.

Image/Video Pre-Processing Re-framing

Notice the deliberate selection of the word “mimic” in the above definition for A.I. Living in an expeditiously tech-hungry world, losing sight of A.I. as a mimicry of human intelligence, not a replica, is inevitable. However, our own human intelligence derives from years of experience and exposure, constantly evolving – a machine learning model** does not have this same basis. As a child, we began with phonetics, which lead to simple words, subsequently achieving strings of sentences to ultimately formulate conversations. In a sense, you might consider these steps as “training” as we had more exposure to “data.” Therefore, when approaching image-preprocessing for the initial training dataset for an A.I. model, it’s integral to recognize the image from the lens of a computer, not as a human researcher. With each image, reminding ourselves: What is and isn’t necessary in this image? What is extra “noise”? Do all the features within this image contribute to getting closer to my question?

Model Workflow: What’s Next?

Now that we have our question, model, and “cleaned” dataset, the next few steps are: (II) Image/Video Processing, (III) Labeling, (IV) Model Training, (V) Model Predictions, and (VI) Model Corrections, which leads us to the ultimate step of (VII) A.I. Model Deployment. Labeling is the act of annotating images/videos with classifications the annotator (me or you) deems important for the model to recognize. Next, Model Training, Model Predictions, and Model Corrections can be considered an integrated part of the workflow broken down into steps. Model Training takes place once all labeling is complete, which begins the process for the model to perform the task assigned (i.e., object detection, image segmentation, pose estimation, etc.). After training, we provide the model with new data to test its performance, entering the stage of Model Predictions. Once Predictions have been made, the annotator reviews these attempts and corrects any misidentifications or mistakes, resulting in another round of Model Training. Finally, once satisfied with the model’s Performance, Model Deployment begins, which integrates the model into a “real-world” application.

In the ceaselessly advancing field of A.I., sometimes it can feel like the learning never ends. However, I encourage you to welcome the uncharted territory with a curious mind. Just like with any field of science, errors can happen but, with the right amount of persistence, so can success. I hope this blog has helped as a step forward toward understanding A.I. as an asset and how you can utilize it too!

**granted you are using a machine learning model that is not a foundation model. A foundation model is one that has been pre-trained on a large diverse dataset that one can use as a basis (or foundation) to perform specialized tasks. (i.e. Open A.I. ChatGPT).

References:

Bierlich, K. C., Karki, S., Bird, C. N., Fern, A., & Torres, L. G. (2024). Automated body length and body condition measurements of whales from drone videos for rapid assessment of population health. Marine Mammal Science, 40(4). https://doi.org/10.1111/mms.13137

Boulent, J., Charry, B., Kennedy, M. M., Tissier, E., Fan, R., Marcoux, M., Watt, C. A., & Gagné-Turcotte, A. (2023). Scaling whale monitoring using deep learning: A human-in-the-loop solution for analyzing aerial datasets. Frontiers in Marine Science, 10. https://doi.org/10.3389/fmars.2023.1099479

Deep Learning vs Machine Learning: The Ultimate Battle. (2022, May 2). https://www.turing.com/kb/ultimate-battle-between-deep-learning-and-machine-learning

Jain, P. (2024, November 28). Breakdown: Simplify AI, ML, NLP, deep learning, Computer vision. Medium. https://medium.com/@jainpalak9509/breakdown-simplify-ai-ml-nlp-deep-learning-computer-vision-c76cd982f1e4

Pereira, T.D., Tabris, N., Matsliah, A. et al. SLEAP: A deep learning system for multi-animal pose tracking. Nat Methods 19, 486–495 (2022). https://doi.org/10.1038/s41592-022-01426-1

Patel, M. (2023, October 23). The Complete Guide to Image Preprocessing Techniques in Python. Medium. https://medium.com/@maahip1304/the-complete-guide-to-image-preprocessing-techniques-in-python-dca30804550c

Team, I. D. and A. (2024, November 25). AI vs. Machine learning vs. Deep learning vs. Neural networks. IBM/Think. https://www.ibm.com/think/topics/ai-vs-machine-learning-vs-deep-learning-vs-neural-networks

The Tesla Advantage: 1.3 Billion Miles of Data. (2016). Bloomberg.Com. https://www.bloomberg.com/news/articles/2016-12-20/the-tesla-advantage-1-3-billion-miles-of-data?embedded-checkout=true

Wolfewicz, A. (2024, September 30). Deep Learning vs. Machine Learning – What’s The Difference? https://levity.ai/blog/difference-machine-learning-deep-learning

From coast to coast: assessing impacts of human threats and climate change from dolphins to blue whales

By Nicole Principe, first-year PhD student, OSU Dept of Fisheries, Wildlife and Conservation Sciences, GEMM Lab

Humans rely on oceans and coastal ecosystems for a variety of resources, such as tourism and recreation, fishing and aquaculture, transport of goods, and resource extraction. However, each use is contributing to new and cumulative stressors that are impacting marine mammals.  The health of marine mammal populations can often serve as indicators of overall environmental health. Therefore, studying the stressors they face can help provide insights into the broader impacts on marine ecosystems and determine if conservation or management measures are necessary. As a master’s student at the College of Charleston in South Carolina and subsequently the stranding and research technician with the Lowcountry Marine Mammal Network (LMMN), I saw first-hand how some of these stressors affect local marine mammal populations.

In my role as the stranding and research technician with LMMN, I led the response and recovery of all deceased marine mammals, mainly bottlenose dolphins (Tursiops erebennus), in South Carolina to determine cause of death and identify main sources of mortality. Threats to these cetaceans can be environmental or anthropogenic in origin. Carefully examining and sampling every individual during a necropsy was critical to determine the presence of infectious disease, the contaminant and microplastic load, and any sign human interaction. While deaths from environmental causes can be more challenging for humans to mitigate, direct threats from human activity can be lessened with conservation actions and increased education to the public. LMMN responds to several strandings of dolphins each year that are the result of entanglement or boat strike. South Carolina has one of the highest rates of crab pot entanglements. In some cases, the call came quick enough that a disentanglement was possible, but in others, we found the animal already deceased with rope and gear still attached. Hundreds, if not thousands, of commercial and recreational crab pots are deployed within South Carolina estuaries, yet there are currently no regulations in place to help mitigate the threat of entanglement.

Images: Conducting a necropsy in the lab (left) and doing a preliminary examination in the field (right) on stranded bottlenose dolphins. Photo credit: Lowcountry Marine Mammal Network

LMMN also conducts land and boat-based surveys to better understand strand feeding, which is a unique foraging strategy utilized by a small number of dolphins in South Carolina. When dolphins strand feed, they herd and trap fish up onto mudbanks or shorelines. The dolphins chase after the fish, briefly stranding themselves as they try to catch them. It is an incredible behavior to witness and because of this, it has become highly publicized as a tourist activity. There are areas where the public can walk right up as dolphins are attempting to hunt and many instances of people trying to touch, feed, or otherwise harass the dolphins have been reported. I also conducted a small study where I used drones to identify human interferences towards dolphins strand feeding and found that boaters and kayakers were often approaching the animals too closely, following them, or speeding through the inlet when animals were present. The write up on that project can be found here. High levels of human disturbance towards dolphins strand feeding could lead individuals to abandon otherwise suitable habitat, causing them to expend more energy to look for food elsewhere.

Images: Bottlenose dolphins strand feeding (left) and an instance of a beachgoer illegally harassing dolphins while they hunt (right). Photo credit: Glen Cox & Lucy Grierson.

To help mitigate threats to dolphins from entanglements, boat strikes, and illegal harassment, the LMMN team and I created an educational workshop called W.A.V.E., which stands for Wildlife Awareness and Viewing Etiquette. These half-day workshops are tailored to both recreational boaters/public and commercial tour operators and fishermen and cover topics ranging from the importance of marine mammals in our ecosystem, the Marine Mammal Protection Act, global and local threats, and ways we can view marine wildlife that reduce disturbance. It is my hope that with more education and awareness about how humans use our waterways and interact with wildlife in negative ways, it can lead to positive changes. For more information about LMMN’s W.A.V.E. Workshops, head to their website.

Image: Successful W.A.V.E. Workshop with local eco-tour operators. Photo credit: Lowcountry Marine Mammal Network

In addition to cumulative stressors from human interactions, I also began to contemplate the role of climate change as a threat to the lives of marine mammals during my master’s research on dolphin distribution within the Charleston Estuary System (CES). A main question I was investigating was if and why some dolphins travel into low salinity waters high in the estuarine system.  Bottlenose dolphins have evolved in marine and estuarine environments where salinity levels are typically ~30 parts per thousand (ppt). While dolphins can withstand short durations of exposure to low salinity (defined as 15 ppt), prolonged exposure to freshwater can result in negative health consequences, such as sloughing of skin and ulcerative lesions, changes in pathophysiology, and eventual mortality (Ewing et al., 2017). Over the past 20 years, many intermittent dolphin sightings and strandings occurred in riverine areas of the CES where salinity levels were below 10 ppt. To better understand how and why dolphins use this risky habitat, I conducted drone surveys across the CES for a year. I did find dolphin groups traveling and feeding in low salinity waters, however, the encounters were only during months with warmer water temperatures (Principe et al., 2023). We hypothesize that environmental conditions during those months may lead to decreased prey availability in the lower, more suitable parts of the estuary, forcing dolphins to travel further up the rivers to access higher abundances of prey (especially mullet). Other studies in different regions have found similar results of dolphins traveling into low salinity water during warmer months potentially in response to prey (Mintzer and Fazioli, 2021; Takeshita et al., 2021).

Images: Drone snapshot of six bottlenose dolphins traveling together (left) and a dolphin observed with skin lesions in low salinity habitat (right). Photo credit: Nicole Principe, NMFS Permit 21938

These results lead to questions as to how prey and dolphin movements will shift under future climate change scenarios. Increasing warm water temperatures may lead to further shifts in prey distribution, potentially driving more estuarine dolphins to utilize upper riverine habitats to find food. Just since 2022, four dolphins were observed in freshwater habitat for several weeks. Two were eventually found and confirmed deceased and two went missing and are presumed deceased. If more dolphins use and remain in these low salinity habitats for extended periods, negative health consequences could lead to population impacts and signal a need for more conservation and management actions.

It is quickly becoming evident that climate change is threatening marine mammals, at both local and global scales. More research is needed to better understand how changing environmental conditions is impacting the availability and quality of prey and how large marine predators are shifting in response. For my PhD, I am working with the GEMM Lab on the SAPPHIRE (Synthesis of Acoustics, Physiology, Prey, and Habitat in a Rapidly changing Environment) project, where we are researching how changing ocean conditions affect the availability of krill, and blue whale behavior, health, and reproduction in New Zealand. The South Taranaki Bight (STB) region experiences a productive coastal upwelling system that supports enhanced primary productivity (Chiswell et al. 2017) and dense aggregations of prey (Bradford-Grieve et al., 1993). Pygmy blue whales (Balaenoptera musculus brevicauda) in this region are not known to migrate and instead use the STB region year-round for foraging and reproduction (Torres, 2013; Barlow et al., 2022).  After a marine heatwave in the Tasman Sea in 2015-2016, there were less krill aggregations due to lessened upwelling (Barlow et al., 2020), which caused reduced foraging effort, and subsequently reduced reproductive activity by blue whales (Barlow et al. 2023). Continued field work and data analysis will help us to develop Species Health Models that will predict how these prey and predator populations will respond to future environmental change. 

Overall, it is clear that human activity is leading to direct and indirect impacts on marine mammal populations at many different scales, from an individual human harassing a foraging dolphin to global climate change impacts on blue whale population dynamics. Ongoing research is essential in understanding these impacts better and thus inform development of effective conservation strategies to protect both marine mammals and the environment.

References

Barlow DR, Bernard KS, Escobar-Flores P, Palacios DM, Torres LG (2020) 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 642:207–225.

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 13:e9770.

Barlow DR, Klinck H, Ponirakis D, Holt Colberg M, Torres LG (2022) Temporal occurrence of three blue whale populations in New Zealand waters from passive acoustic monitoring. J Mammal 104(1): 29–38.

Bradford-Grieve JM, Murdoch RC, Chapman BE (1993) Composition of macrozooplankton assemblages associated with the formation and decay of pulses within an upwelling plume in greater cook strait, New Zealand. New Zeal J Mar Freshw Res 27(1): 1–22.

Chiswell SM, Zeldis JR, Hadfield MG, Pinkerton MH (2017) Wind-driven upwelling and surface chlorophyll blooms in greater Cook Strait. New Zeal J Mar Fresw Res 51(4): 465–489.

Ewing RY, Mase-Guthrie B, McFee W, Townsend F, Manire CA, Walsh M,

Borkowski R, Bossart GD, Schaefer AM (2017). Evaluation of serum for pathophysiological effects of prolonged low salinity water exposure in displaced bottlenose dolphins (Tursiops truncatus). Front Vet Sci 4

Hornsby F, McDonald T, Balmer BC, Speakman T, Mullin K, Rosel P, Wells R, Telander A, Marcy P, Schwacke L (2017) Using salinity to identify common bottlenose dolphin habitat in Barataria Bay, Louisiana, USA. Endanger Species Res 33: 833–192.

Mintzer VJ, Fazioli KL (2021) Salinity and water temperature as predictors of bottlenose dolphin (Tursiops truncatus) encounter rates in upper Galveston Bay, Texas. Front Mar Sci 8

Principe N, McFee W, Levine N, Balmer B, Ballenger J (2023). Using Unoccupied Aerial Systems (UAS) to Determine the Distribution Patterns of Tamanend’s Bottlenose Dolphins (Tursiops erebennus) across Varying Salinities in Charleston, South Carolina. Drones 7(12): 10.3390/drones7120689. 

Takeshita R, Balmer BC, Messina F, Zolman ES, Thomas L, Wells RS, Smith CR, Rowles TK, Schwacke LH (2021). High site-fidelity in common bottlenose dolphins despite low salinity exposure and associated indicators of compromised health. PLoS ONE, 16(9), e0258031.

Torres LG (2013) Evidence for an unrecognised blue whale foraging ground in New Zealand. New Zeal J Mar Freshw Res 47:235–248.