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

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

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

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

An Incredible Story of Whale Disentanglement

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

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

Most Entangled Whales are Out of Sight

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

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

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

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

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

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

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

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

Tracking Unseen Entanglements: Project SLATE

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

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

What to do if you see an entangled whale

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

Instead, report the entanglement by promptly calling:

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

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

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


References:

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

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

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

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

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

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

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

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

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

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.

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

By Natalie Nickells, visiting PhD Student, British Antarctic Survey

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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Bibliography

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Toward an enhanced understanding of large whale ecology: a standardized protocol to quantify hormones in whale blubber

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

Whales are exposed to an increasing number of human-induced stressors—ranging from pollution and bycatch to the impacts of climate change on prey quality and distribution. Understanding how these factors affect whale health is critical for their conservation. The use of alternative approaches (i.e., alternative to blood samples) for gathering physiological information on large whales using a variety of non-lethal and non to minimally invasive sample matrices (i.e., blubber biopsies, blow, and fecal samples) provides a window into their endocrine state, allowing researchers to assess how these animals respond to both short-term and long-term stressors, and assess their reproductive and nutritional status. However, a lack of standardized protocols might hinder the comparability of results across studies, making it difficult to draw broad conclusions about the health and reproductive parameters of different whale populations.

Dr. Logan Pallin and I organized a lab exchange, funded by The Company of Biologists, to start a new collaboration aimed at bridging this gap by validating and standardizing methods for endocrine assessments in whale blubber. This is not just a technical exercise; it is a foundational step towards building equity and capacity in laboratories worldwide to conduct reliable and comparable endocrine assessments, enhancing the opportunities for multi-lab collaborations. Through this exchange, we aim to consolidate a standardized approach that will yield consistent results between laboratories, enabling better comparisons across different large whale populations. Hosted by the University of California Santa Cruz Biotelemetry and Behavioral Ecology Lab (UCSC-BTBEL Lab) under the mentorship of Dr. Logan Pallin, this experience is instrumental in advancing my research on large whale ecology and conservation.

Dr. Logan Pallin and Alejandro Fernandez Ajó conducting hormone extractions from gray whale blubber samples (left). Preparing a microtiter assay plate for hormone quantification in blubber (right).

During this exchange at the BBE Lab, I had the privilege of working closely with Dr. Logan Pallin, whose expertise in large whale endocrinology (particularly analyzing blubber biopsies) has been instrumental in shaping modern approaches to whale research. The lab’s cutting-edge equipment and Logan’s extensive experience with hormone extraction and quantification methods provided an ideal setting for refining our protocols. Our work focused on the extraction and quantification of progesterone from gray whale blubber samples provided by the Oregon State University Marine Mammal Stranding Network, part of MMI. These large blubber sections allow for repeated sub-sampling to ensure that the selected immunoassays reliably detect and measure the hormones of interest, while also assessing potential sources of variability when applying a standardized protocol. We initially focused our tests and validations on progesterone, as it is the precursor of all major steroid hormones and serves as an indicator of reproductive state in females.

A fieldwork day off Monterrey Bay, California with Dr. Logan Pallin, and PhD candidate Haley Robb. Blubber. Blubber biopsies can be obtained from free swimming whales with minimally invasive methods. From each sample we can derive multiple information about the reproductive status, genetics and overall health of the individuals.

The broader impact of our work
The successful validation and standardization of these protocols represents a significant advancement in whale conservation physiology. Once these methods are established, we plan to acquire funds to apply them to a larger collection of blubber samples. We hope to expand our work to include other species and regions, building a broader network of researchers dedicated to studying large whales in a rapidly changing world, and to assess hormone profiles in relation to factors like reproductive success, body condition, and exposure to stressors such as vessel traffic and environmental changes.

During our fieldwork in Monterey Bay, we had fascinating encounters with Minke whales (Balaenoptera acutorostrata, top left), a large group of Risso’s dolphins (Grampus griseus, bottom left), playful Humpbacks (Megaptera novaeangliae, top right), and a Blue whale (Balaenoptera musculus, no photo).

As I conclude this lab exchange, I am filled with excitement for the future. The knowledge and skills gained during this experience will undoubtedly shape the next phase of my research, allowing me to contribute more effectively to the conservation of these incredible animals. I look forward to applying these standardized methods to ongoing and future projects, and to continuing this fruitful collaboration with the BBE Lab. This journey has reinforced the importance of collaboration, standardization, and innovation in the field of conservation physiology. By working together, we can better understand the complex lives of large whales and take meaningful steps towards their protection in an increasingly challenging environment.

Acknowledgments: This exchange was made possible by the support of The Company of Biologists Traveling Fellowship Grant. I would like to thank Dr. Ari Friedlaender (BBE Lab PI) for facilitating this exchange, and Dr. Leigh Torres (GEMM Lab PI) and Dr. Lisa Balance (MMI director) for their support in helping me expand my collaboration network and skillsets. Special thanks to PhD student Haley Robb for her assistance in the laboratory and fieldwork, and a heartfelt thank you to Dr. Logan Pallin for generously sharing his knowledge and time.

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The Beginning of the End

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

I moved to Corvallis exactly four years ago, in the deep, dark midst of the Covid pandemic, and during the added chaos of the 2020 Labor Day Fires, some of the worst in Oregon’s history. I vividly remember attending our virtual lab meeting sitting on the floor surrounded by boxes, while my labmates told me their own stories (many, surprisingly!) of moving during natural disasters. At the time, beginning graduate school represented so many big changes in my life: I had quit my job, sold my furniture, and moved across the country, hoping to explore an area of research that had been calling to me for years, and to gain a new skillset and confidence.

Highlight: A very pandemic cruise. My first day of marine mammal fieldwork in 2021, at sea with (now Dr.) Dawn Barlow.

Now, I’m starting the fifth year of my PhD, thinking about all that has happened and all that is to come. Graduate school is full of milestones to mark time and progress: I’ve taken the courses required for my program, sat for a written exam to test my broad knowledge of oceanography, and written a dissertation proposal. Earlier this year, I spent two months buried in the literature on oceanography, krill, and whale ecology in preparation for my oral qualifying exam. I’ve stared at the water for dozens of hours watching for whales off the Oregon coast, and experienced polar night studying winter krill in Antarctica. I’ve conquered my fear of learning to code, and felt constant, profound gratitude for the amazing people I get to work with.

The last four years have been incredibly busy and active, but now more than ever, it feels like the time to really do. I can see the analytical steps ahead for my final two dissertation chapters more clearly than I’ve been able to see either of the other two chapters that have come before. One of my favorite parts of the process of research is discussing analytical decisions with my labmates and supervisors, and experiencing how their brains work. Much of our work hinges on modeling relationships between animals and their environment. A model, most fundamentally, is a reduced-scale representation of a system. As I’ve learned to use statistical models to understand relationships between krill and whales, I have simultaneously been building a mental model of the Northern California Current (NCC) ecosystem and the ecological relationships within it. Just as I have long admired in my supervisors and labmates, I can now feel my own mind becoming more playful as I think about this ocean environment, the whales and krill that make a living in the NCC, and the best way to approach studying them analytically.

Highlight: Working on my dissertation proposal during a friend’s 2022 wedding celebration in Utah.

Graduate school demands that you learn and work to constantly exceed your own bounds, and pushing to that extent for years is often stressful and even existentially threatening. However, this process is also beautiful. I have spent the last four years growing in the ways that I’ve long wanted to, and reveled in feeling my mind learn to play. I wouldn’t give up a moment of the time I’ve spent in the field, the relationships I’ve built with my labmates, or the confidence I’ve developed along the way.

As I look ahead to this next, final, year of graduate school, I hope to use what I’ve learned every day – and not just about how to conduct research, but about myself. I want to always remember that krill, whales, and the ocean ecosystem are incredible, and that it is a privilege to study them. I hope to work calmly and intentionally, and to continue appreciating this process of research and growth.

Highlight: My first in-person oral presentation, at the 2024 ICES-PICES International Zooplankton Production Symposium in Hobart, Tasmania.

The Theme of the Year is Learning New Things!

By Hali Peterson, rising freshman, Western Oregon University

Hello, my name is Hali Peterson and I am a rising freshman in college. Last summer (2023) I was given the opportunity to be a paid high school intern for the OSU Marine Mammal Institute’s very own GEMM Lab (Geospatial Ecology of Marine Megafauna Laboratory) based at the Hatfield Marine Science Center in Newport, Oregon. My time working in the GEMM Lab has been supported by the Oregon Coast STEM Hub. I started my internship in June 2023 and I was one of the two GEMM Lab summer interns. However, my internship did not end when summer did, as I continued to work throughout the school year and even into this summer. 

Figure 1: Leaving work late and accompanied with a beautiful view of the Newport bridge over Yaquina Bay.

June 29, 2023 to September 20, 2024 (1 year, 2 months, and 21 days if anyone is curious) – what did I do and what did I learn during this time…

Initially, I was tasked with helping the GRANITE project (Gray whale Response to Ambient Noise Informed by Technology and Ecology) by processing drone footage of Pacific Coast Feeding Group (PCFG) gray whales and identifying their zooplankton prey. I started off my internship under the mentorship of KC Bierlich and Lisa Hildebrand and I dove into looking at zooplankton underneath a microscope and watching whales in drone footage, both gathered by the GEMM Lab field team. 

KC taught me how to process drone footage, measure whales and calibration boards, test an artificial intelligence model, as well as write a protocol of the drone processing methods that I had worked on. These tasks were a big responsibility as the measurements need to be accurate and precise so that they can be used to effectively assess the body condition of gray whales, which provides crucial insights into population health.

Figure 2: My favorite drone video of moms and calves meeting up for a playdate!

Under Lisa’s mentorship I learned how to identify and process zooplankton prey samples, process underwater GoPro videos, as well as identify and analyze kelp patches from satellite images. Within these tasks, I honed my expertise in zooplankton and habitat analysis and the results of my work will contribute to a deeper understanding of gray whale feeding habits along the Oregon coast.

Figure 3: My favorite zooplankton to see, a juvenile crab larva.

As my main mentors, KC and Lisa taught me so much about the world of science and research. All of these detail-oriented and multi-layered tasks helped me improve some of the skills I already had before I started the internship as well as gift me with skills I didn’t previously possess. For example, I learned how to collaborate and work with a team, pay attention to detail, double and even triple check everything for quality work, problem solve, and learn to ask questions. 

However, as my time in the GEMM Lab extended beyond the summer of 2023, so did my tasks. Later on I received another mentor, Clara Bird. Under Clara I learned how to identify whales from drone footage recorded in Baja, Mexico (an area that is specifically known as the breeding lagoons where the gray whales go in the winter), as well as use the Newport, Oregon drone footage and CATS (Customized Animal Tracking Solution) tag data to measure inhalation duration and bubble blast occurrences. These experiences furthered my knowledge and yet again I learned something new, a common theme throughout my time in the GEMM Lab. 

Just a few months ago, the GEMM Lab hired Laura Flores Hernandez as a new high school student summer intern, and under the guidance of both Lisa Hildebrand and Leigh Torres, I was given the opportunity to develop my own mentoring skills. I used the skills I had obtained over the past year to teach someone else how to do the tasks I once was new to. I taught Laura how to identify zooplankton, process drone footage, and measure calibration boards. Stepping into that mentor role helped me reflect on my own learning and experiences. I had to go back and figure out how I did things, where I struggled, and how I overcame those struggles. Not an easy task but one I was glad to be presented with. 

Figure 4: Matthew Vaughan (chief scientist on the trip) and me (right) looking at a box core sample.

During my time here I was also invited to join a STEM (Science, Technology, Engineering, Mathematics) cruise led by Oregon Sea Grant with fellow high school students. On this science cruise I got to help look at box core samples (a tool used to collect large amounts of sediment off of the ocean floor). Equipped with my previous knowledge on zooplankton identification, I was able to help the chief scientist on the trip to explain to other high school students what we were seeing in the samples. This trip helped me grow my teamwork and identification skills, as well as experience what it is like to collect data while on a moving ship. 

Figure 5: Sea Kayaking through the fjord with the Girls on Icy Fjords team of 2024.

Another amazing opportunity I was selected for was to join the 2024 Girls on Icy Fjords team. This program, in association with OSU, was designed to empower young women in STEM in the backcountry of Alaska. With a team of 3 amazing instructors and 8 girls (all from different parts of the United States of America) we camped in the backcountry for 8 days, learning about glaciers and fjords, surviving in the backcountry, sea kayaking, and working as a team. I would highly recommend any young woman interested in science, art, or just an amazing experience to check out Inspiring Girls Expeditions.

Bonus Image: This is Jeff the Moyebi Shrimp and I love him.

All in all this will be a job that I will not soon forget; interning in the GEMM Lab has been both a learning opportunity as well as a challenge. My internship wasn’t without its challenges, from a computer that seemed determined to shut down whenever I made progress, to endless hours spent staring at a green screen, waiting to count a fish that might eventually swim by. Though the job had its ups and downs, I am so glad I was given this opportunity and was kept on in the lab for as long as I was. In just a few weeks, I will start my Bachelors of Aquarium Science at Western Oregon University and I’m both excited and nervous. I know that without a doubt the skills I learned during this internship will come in handy as I continue my education and pursue a career in the future. 

Thank you to all my mentors, anyone who answered one of the many questions I had, and to the friends I made along the way!

Two Leaders Wearing Two Hats: A wrap-up of the 2024 TOPAZ/JASPER Field Season

Celest Sorrentino, incoming master’s student, OSU Dept of Fisheries, Wildlife and Conservation Sciences, GEMM Lab

Allison Dawn, PhD student, Clemson University Dept of Forestry and Environmental Conservation, GEMM Lab Alum

Allison:

Celest and I were co-leaders this year, so it only feels fitting to co-write our wrap-up blog for the 2024 field season.

This was my first year training the project leader while also leading the field team. I have to say that I think I learned as much as Celest did throughout this process! This hand-off process requires the two team leaders to get comfortable wearing two different hats. For me, I not only made sure the whole team grasped every aspect of the project within the two training weeks, but also ensured Celest knew the reasoning behind those decisions AND got to exercise her own muscles in decision making according to the many moving parts that comprise a field season: shifts in weather, team needs, and of course the dynamics of shared space at a field site with many other teams. With the limited hours of any given day, this is no small task for either of us, and requires foresight to know where to fit these opportunities for the leader-in-training during our day-to-day tasks.

During this summer, I certainly gained even more respect for how Lisa Hildebrand juggled “Team Heck Yeah” in 2021 while she trained me as leader. Lisa made sure to take me aside in the afternoon to let me in on her thought process before the next days work. I brought this model forward for Team Protein this year, with the added bonus that Celest and I got to room together. By the end of the day, our brains would be buzzing with final thoughts, concerns, and excitement. I will treasure many memories from this season, including the memory of our end-of-day debriefs before bed. Overall, it was an incredibly special process to slowly pass the reins to Celest. I leave this project knowing it is ready for its new era, as Celest is full of positive energy, enthusiasm, and most importantly, just as much passion for this project as the preceding leaders.

Fig. 1: Two leaders wearing two (massive) hats. Field season means you have to be adaptable, flexible, and make the most out of any situation, including sometimes having to move your own bed! We had a blast using our muscles for this; we are Team Protein after all!

Celest:

As I sit down in the field station classroom to write this blog, I realize I am sitting in the same seat where just 12 hours ago a room full of community members laughed and divided delicious blueberry crumble with each other.

We kicked the morning of our final day together off with a Team Protein high powered breakfast in Bandon to have some delicious fuel and let the giggles all out before our presentation. When Dr. Torres arrived, the team got a chance to reflect on the field season and share ideas for next season. Finally, the moment we had all been waiting for:  at 5 PM Team Protein wrapped up our 2024 field station with our traditional Community Presentation.

Fig 2: Team breakfast at SunnySide Cafe in Bandon, which have delicious GF/DF options.

Within a month and a half, I transitioned from learning alongside each of the interns at the start of the season knowing only the basics of TOPAZ/JASPER, to eventually leading the team for the final stretch. The learning spurts were quite rapid and challenging, but I attribute my gained confidence to observing Allison lead. To say I have learned from Allison only the nitty-gritty whats and whys of TOPAZ/JASPER would not suffice, as in truth I observed the qualities needed to empower a team for 6 weeks. I have truly admired the genuine magnetic connection she established with each intern, and I hope to bring forth the same in future seasons to come.

Witnessing each intern (myself included!) begin the season completely new, to now explaining the significance of each task with ease to the very end was unlike any other. Presenting our field season recap to the Port Orford Community side-by-side with Sophia, Eden, Oceana, and Allison provided an incredible sense of pride and I am thrilled for the second TOPAZ/JASPER Decadel party in 2034 when we can uncover where this internship has taken us all.

…Until next season (:

Fig 3: Team Protein all together at the start of season all together.

Fig 4: Team Protein all smiles after wrapping up the season with the Community Presentation.

Fig 4: Our season by numbers for the 2024 TOPAZ/JASPER season!

Speeding Up, Slowing Down, and Choosing My Fig

Celest Sorrentino, incoming master’s student, OSU Dept of Fisheries, Wildlife, and Conservation Sciences, GEMM Lab

It’s late June, a week before I head back to the West Coast, and I’m working one of my last shifts as a server in New York. Summer had just turned on and the humidity was just getting started, but the sun brought about a liveliness in the air that was contagious. Our regulars traded the city heat for beaches in the Hamptons, so I stood by the door, watching the flow of hundreds upon hundreds of people fill the streets of Manhattan. My manager and I always chatted to pass the time between rushes, and he began to ask me how I felt to move across the country and start my master’s program so soon.

“I am so excited!” I beamed, “Also a bit nervous–”

“Nervous? Why? 

“Are you nervous you’ll become the person you’re meant to be?”

As a first-generation Hispanic student, I found solace in working in hospitality. Working in a restaurant for four years was a means to support myself to attain an undergraduate degree–but I’d be lying if I said I didn’t also love it. I found joy in orchestrating a unique experience for strangers, who themselves brought their own stories to share, each day bestowing opportunity for new friendships or new lessons. This industry requires you to be quick on your feet (never mess with a hungry person’s cacio e pepe), exuding a sense of finesse, continuously alert to your client’s needs and desires all the while always exhibiting a specific ambiance.

So why leave to start my master’s degree?

Fig 1: Me as a server with one of my regulars before his trip to Italy. You can never go wrong with Italian!

For anyone I have not had the pleasure yet to meet, my name is Celest Sorrentino, an incoming master’s student in the GEMM Lab this fall. I am currently writing to you from the Port Orford Field Station, located along the charming south coast of Oregon. Although I am new to the South Coast, my relationship with the GEMM Lab is not, but rather has been warmly cultivated ever since the day I first stepped onto the third floor of the Gladys Valley Building, as an NSF REU intern just two summers ago. Since that particular summer, I have gravitated back to the GEMM Lab every summer since: last summer as a research technician and this summer as a co-lead for the TOPAZ/JASPER Project, a program I will continue to spearhead the next two summers. (The GEMM Lab and me, we just have something– what can I say?)

 In the risk of cementing “cornball” to my identity, pursuing a life in whale research had always been my dream ever since I was a little girl. As I grew older, I found an inclination toward education, in particular a specific joy that could only be found when teaching others, whether that meant teaching the difference between “bottom-up” and “top-bottom” trophic cascades to my peers in college, teaching my 11 year old sister how to do fun braids for middle school, or teaching a room full of researchers how I used SLEAP A.I. to track gray whale mother-calf pairs in drone footage.

Onboarding to the TOPAZ/JASPER project was a new world to me, which required me to quickly learn the ins and outs of a program, and eventually being handed the reins of responsibility of the team, all within 1 month and a half. While the TOPAZ/JASPER 2024 team (aka Team Protein!) and I approach our 5th week of field season, to say we have learned “so much” is an understatement.

Our morning data collection commences at 6:30 AM, with each of us alternating daily between the cliff team and kayak team. 

For kayak team, its imperative to assemble all supplies swiftly given that we’re in a race against time, to outrun the inevitable windy/foggy weather conditions. However, diligence is required; if you forget your paddles back at lab or if you run out of charged batteries, that’s less time on the water to collect data and more time for the weather to gain in on you. We speed up against the weather, but also slow down for the details.

Fig 2: Throwback to our first kayak training day with Oceana (left), Sophia(middle), and Eden (right).

For cliff team, we have joined teams with time. At some point within the last few weeks, each of us on the cliff have had to uncover the dexterity within to become true marine mammal observers (for five or six hours straight). Here we survey for any slight shift in a sea of blue that could indicate the presence of a whale– and once we do… its go time. Once a whale blows, miles offshore, the individual manning the theodolite has just a few seconds to find and focus the reticle before the blow dissipates into the wind. If they miss it… its one less coordinate of that whale’s track. We speed up against the whale’s blow, but also slow down for the details. 

Fig 3: Cliff team tracking a whale out by Mill Rocks!

I have found the pattern of speeding up and slowing down are parallels outside of field work as well. In Port Orford specifically, slowing down has felt just as invigorating as the first breath one takes out of the water. For instance, the daily choice we make to squeeze 5 scientists into the world’s slowest elevator down to the lab every morning may not be practical in everyday life, but the extra minute looking at each other’s sleepy faces sets the foundation for our “go” mode. We also sit down after a day of fieldwork, as a team, eating our 5th version of pasta and meatballs while we continue our Hunger Games movie marathon from the night prior. And we chose our “off-day” to stroll among nature’s gentle giants, experiencing together the awe of the Redwoods trees.

Fig 4A & 4B: (A) Team Protein (Sophia, Oceana, Allison, Eden and I) slow morning elevator ride down to the lab. (B) Sophia hugging a tree at the Redwoods!

When my manager asked the above question, I couldn’t help but think upon an excerpt, popularly known as “The Fig Tree” by Sylvia Plath.

Fig 5: The Fig Tree excerpt by Sylvia Plath. Picture credits to @samefacecollective on Instagram.

For my fig tree, I imagine it as grandiose as those Redwood trees. What makes each of us choose one fig over the other is highly variable, just as our figs of possibilities, some of which we can’t make out quite yet. At some point along my life, the fig of owning a restaurant in the Big Apple propped up. But in that moment with my manager, I imagined my oldest fig, with little Celest sitting on the living room floor watching ocean documentaries and wanting nothing more than to conduct whale research, now winking at me as I start my master’s within the GEMM Lab. Your figs might be different from mine but what I believe we share in common is the alternating pace toward our fig. At times we need speeding up while other times we just need slowing down.

Then there’s that sweet spot in between where we can experience both, just as I have being a part of the 2024 TOPAZ/JASPER team.

Fig 6A and 6B: (A) My sister and I excited to go see some dolphins for the first time! (~2008). (B) Taking undergraduate graduation pics with my favorite whale plushy! (2023)

Fig 7: Team Protein takes on Port Orford Minimal Carnival, lots of needed booging after finishing field work!

Little bit of Kayaking, Lot a bit of Zoops

Eden Van Maren, Homeschool Student from Brookings, TOPAZ/JASPER High School Intern

Hey! I’m Eden Van Maren, an upcoming high school senior from Brookings. I am homeschooled and am taking electives at Brookings Harbor High School. 

Growing up in rural Oregon, the outdoors have always been more than just my backyard. It’s been both my classroom and my playground. When Oceana (the other high school intern) and I were homeschooled together as children, Fridays meant her mom would take us up the Chetco River. One Friday, we took our snorkels to observe mature salmon migrating upstream. I remember being so amazed by the size and quantity of the salmon, my young brain could not understand why such large fish would want to swim up to such a small area to lay eggs. The next year when we returned to try and see if the salmon would swim upstream again, we found only one salmon swimming around. This river became my classroom, planting my initial interest in science. 

However. Let’s be clear: Being outside in nature was never “all work, no play” – Definitely lots of play! Summers were filled with sunsets on the beach, some foggy day hikes, but most importantly kayaking on the river. I have many fun memories of waking up early on a weekend to pack food for a long day of kayaking in a tandem with my dad and a bunch of other friends. As I’ve gotten older, my passion for both the environment and science have only grown.

Fig 1: My dad and I kayaking with my dog on the Chetco River.

After going on a college tour at the University of Oregon in January, I suddenly started thinking that I should begin planning for college and future career options. On that tour, I met Ma’yet, the Youth Program Education Coordinator at Curry Watershed Partnership who had worked with Allison. Ma’yet was familiar with the TOPAZ/JASPER program run by the GEMM Lab and, while we were discussing possible summer opportunities in science, they suggested that I would be a great fit.  

In early March, when I discovered there would be someone from the program coming to present at school, I had already been scheduled to work a shift at Dutch Bros. I managed last minute to have one of my coworkers cover the last few hours of my shift so I would be able to get there. He arrived late, so I ran to get there on time, but I made it! Upon arriving, I sat down for the presentation, and, within minutes, Allison confirmed my desire to be a part of this program. I always knew that science is where I wanted to focus my studies. When I came across this program, I was very interested because it involved exciting outdoor activities while learning and experiencing scientific field work. I was thrilled to meet Allison in person to ask questions and share my enthusiasm about the project. 


Before working at the Port Orford field station, I had never given much thought to zooplankton. I had known they were the primary prey for whales, but other than that, I hadn’t considered that there was much else to think about. After starting the work associated with zooplankton on this project, I learned through Sophia how zooplankton can be affected by water temperature and kelp abundance, among other things. Along with learning more about zooplankton ecology, part of the program includes collecting zooplankton samples from 12 different stations (using a kayak) out along the Port Orford coastal area. On my very first training day of zooplankton sampling, I pulled up a ridiculous number of zooplankton in the net (much more than the last few seasons).

Fig 2: Me pulling up my first net of zoops! Look at all that zoop!

Once we return to the lab after a morning of zoop collection, we observe these samples under a microscope, identify their species, and count how many species we collected from each station. Just two weeks into our data collection, we have collected 4291 individual zoops, which already surpasses the total amount of zooplankton collected in 2023 and 2022 combined! That’s a lot of zoops! But how do we do it? 

In our team, I am considered the zoop expert, but I couldn’t do it without a handful of Welch’s fruit snacks and my playlist full of bangers. Zoop processing can be very tedious, but I really enjoy the peace that comes with finishing a giant sample by myself. I love being able to blast AJR in the background while ID’ing each zooplankton even though my team loves to tease me for it (but really, I’m totally putting them on). As I’ve gotten better at ID’ing zooplankton, I started brainstorming about what could help teach other interns in the future. Allison and Lisa, the previous TOPAZ/JASPER leaders, created very useful guides used to train me but I felt that there could be other interactive methods to help interns learn about zoop. Having used Quizlet in the past, I thought it would be a great resource to introduce the zooplankton basics to new interns, so I created an online Zooplankton Identification quiz!

Fig 3A & 3B: Me processing a giant sample of Atylus Tridens.

Despite having only completed three weeks of our data collection season so far, I have already learned so much! From waking up at 5:30 ten days in a row, to kayaking for four hours straight, to even counting 995 (not 1000!) zooplankton in one sitting, this internship has been amazing. It’s been a great introduction to working in the scientific field as many of the responsibilities we have been taught are completely new to me. I am excited to share this internship experience as I apply to colleges and add to my list of skills “Zoop expert.”

Fig 4: My favorite zooplankton! A Dungeness Crab Larvae.