Defining Behaviors

Clara Bird, PhD Student, OSU Department of Fisheries and Wildlife, Geospatial Ecology of Marine Megafauna Lab

When I started working on my thesis, I anticipated many challenges related to studying the behavioral ecology of gray whales. From processing five-plus years of drone footage to data analysis, there has been no shortage of anticipated and unexpected issues. I recently hit an unexpected challenge when I started video processing that piqued my interest. As I’ve discussed in a previous blog, ethograms are lists of defined behaviors that help us properly and consistently collect data in a standardized approach. Ethograms form a crucial foundation of any behavior study as the behaviors defined ultimately affect what questions can be asked and what patterns are detected. Since I am working off of the thorough ethogram of Oregon gray whales from Torres et al. (2018), I had not given much thought to the process of adding behaviors to the ethogram. But, while processing the first chunk of drone videos, I noticed some behaviors that were not in the original ethogram and struggled to decide whether or not to add them. I learned that ethogram development can lead down several rabbit holes. The instinct to try and identify every movement is strong but dangerous. Every minute movement does not necessarily need to be included and it’s important to remember the ultimate goal of the analysis to avoid getting bogged down.

Fundamental behavior questions cannot be answered without ethograms. For example, Baker et al. (2017) developed an ethogram for bottlenose dolphins in Ireland in order to conduct an initial quantitative behavior analysis. They did so by reviewing published ethograms for bottlenose dolphins, consulting with multiple experts, and revising the ethogram throughout the study. They then used their data to test inter-observer variability, calculate activity budgets, and analyze how the activity budgets varied across space and time.

Howe et al. (2015) also developed an ethogram in order to conduct quantitative behavior analyses. Their goals were to use the ethogram and subsequent analyses to better understand the behavior of beluga whales in Cook Inlet, AK, USA and to inform conservation. They started by writing down all behaviors they observed in the field, then they consolidated their notes into a formal ethogram that they used and refined during subsequent field seasons. They used their data to analyze how the frequencies of different behaviors varied throughout the study area at different times. This study served as an initial analysis investigating the effect of anthropogenic disturbance and was refined in future studies.

My research is similarly geared towards understanding behavior patterns to ultimately inform conservation. The primary questions of my thesis involve individual specialization, patterns of behavior across space, the relationship between behavior and body condition, and social behavior (check out this blog to learn more). While deciding what behaviors to add to my ethogram I’ve had to remind myself of these main questions and the bigger picture. The drone footage lets us see so much detail that it’s tempting to try to define every movement we can observe. One rabbit hole I’ve had to avoid a few times is locomotion. From the footage, it is possible to document fluke beats and pectoral fin strokes. While it could be interesting to investigate how different whales move in different ways, it could easily become a complicated mess of classifying different movements and take me deep into the world of whale locomotion. Talking through what that work would look like reminded me that we cannot answer every question and trying to assess all exciting side projects can cause us to lose focus on the main questions.

While I avoided going down the locomotion rabbit hole, there were some new behaviors that I did add to my ethogram. I’ll illustrate the process with the examples of two new behaviors I recently added: fluke swish and pass under (Clips 1 and 2). Clip 1 shows a whale rapidly moving its fluke to the side. I chose to add fluke swish because it’s such a distinct movement and I’m curious to see if there’s a pattern across space, time, individual, or nearby human activity that might explain its function. Clip 2 shows a calf passing under its mom.  It’s not nursing because the calf doesn’t spend time under its mom, it just crosses underneath her. The calf pass under behavior could be a type of mom-calf tactile interaction. Analyzing how the frequency of this behavior changes over time could show how a calf’s dependency on its mom changes over as it ages.

In defining these behaviors, I had to consider how many different variations of this behavior would be included in the definition. This process involves considering at what point a variation of that behavior could serve a different function, even without knowing the function of the original behavior. For fluke swish this process involved deciding to only count a behavior as a fluke swish if it was a big, fast movement. A small and slow movement of the fluke a little to the side could serve a different function, such as turning, or be a random movement.

Clip 1: Fluke swish behavior (Video filmed under NOAA/NMFS research permit #16111​​ by certified drone pilot Todd Chandler).
Clip 2: Pass under behavior (Video filmed under NOAA/NMFS research permit #16111​​ by certified drone pilot Todd Chandler).

The next step involved deciding if the behavior would be a ‘state’ or ‘point’ event. A state event is a behavior with a start and stop moment; a point event is instantaneous and assigned to just a point in time. I would categorize a behavior as a state event if I was interested in questions about its duration. For example, I could ask “what percentage of the total observation time was spent in a certain behavior state?” A point event would be a behavior where duration is not applicable, but I could ask a question like “Did whale 1 perform more point event A than whale 2?”. Both fluke swish and pass under are point events because they only happen for an instant. In a pass under the calf is passing under its mom for just a brief point in time, making it a point event. The final step was to name the behavior. As I discussed in this blog, the name of the behavior does not matter as much as the definition but it is important that the name is clear and descriptive. We chose the name fluke swish because the fluke rapidly moves from side to side and pass under because the calf crosses under its mom.

Frankly, in the beginning, I was a bit overwhelmed by the realization that the content of my ethogram would ultimately control the questions I could answer. I could not help but worry that after processing all the videos, I would end up regretting not defining more behaviors. However, after reading some of the literature, chatting with Leigh, and reviewing the initial chunk of videos several times, I am more confidence in my judgment and my ethogram. I have accepted the fact that I can’t anticipate everything, and I am confident that the behaviors I need to answer my research questions are included. The process of reviewing and updating my ethogram has been a rewarding challenge that resulted in a valuable lesson that I will take with me for the rest of my career.

References

Baker, I., O’Brien, J., McHugh, K., & Berrow, S. (2017). An ethogram for bottlenose dolphins (Tursiops truncatus) in the Shannon Estuary, Ireland. Aquatic Mammals, 43(6), 594–613. https://doi.org/10.1578/AM.43.6.2017.594

Howe, M., Castellote, M., Garner, C., McKee, P., Small, R. J., & Hobbs, R. (2015). Beluga, Delphinapterus leucas, ethogram: A tool for cook inlet beluga conservation? Marine Fisheries Review, 77(1), 32–40. https://doi.org/10.7755/MFR.77.1.3

Torres, L. G., Nieukirk, S. L., Lemos, L., & Chandler, T. E. (2018). Drone up! Quantifying whale behavior from a new perspective improves observational capacity. Frontiers in Marine Science, 5(SEP). https://doi.org/10.3389/fmars.2018.00319

Lessons learned from (not) going to sea

By Rachel Kaplan1 and Dawn Barlow2

1PhD student, Oregon State University College of Earth, Ocean, and Atmospheric Sciences and Department of Fisheries and Wildlife, Geospatial Ecology of Marine Megafauna Lab

2PhD Candidate, Oregon State University Department of Fisheries and Wildlife, Geospatial Ecology of Marine Megafauna Lab

“Hurry up and wait.” A familiar phrase to anyone who has conducted field research. A flurry of preparations, followed by a waiting game—waiting for the weather, waiting for the right conditions, waiting for unforeseen hiccups to be resolved. We do our best to minimize unknowns and unexpected challenges, but there is always uncertainty associated with any endeavor to collect data at sea. We cannot control the whims of the ocean; only respond as best we can.

On 15 February 2021, we were scheduled to board the NOAA Ship Bell M. Shimada as marine mammal observers for the Northern California Current (NCC) ecosystem survey, a recurring research cruise that takes place several times each year. The GEMM Lab has participated in this multidisciplinary data collection effort since 2018, and we are amassing a rich dataset of marine mammal distribution in the region that is incorporated into the OPAL project. February is the middle of wintertime in the North Pacific, making survey conditions challenging. For an illustration of this, look no further than at the distribution of sightings made during the February 2018 cruise (Fig. 1), when rough sea conditions meant only a few whales were spotted.

Figure 1. (A) Map of marine mammal survey effort (gray tracklines) and baleen whale sightings recorded onboard the NOAA ship R/V Shimada during each of the NCC research cruises to-date and (B) number of individuals sighted per cruise since 2018. Note the amount of survey effort conducted in February 2018 (top left panel) compared to the very low number of whales sighted. Data summary and figures courtesy of Solene Derville.

Now, this is February 2021 and the world is still in the midst of navigating the global coronavirus pandemic that has affected every aspect of our lives. The September 2020 NCC cruise was the first NOAA fisheries cruise to set sail since the pandemic began, and all scientists and crew followed a strict shelter-in-place protocol among other COVID risk mitigation measures. Similarly, we sheltered in place in preparation for the February 2021 cruise. But here’s where the weather comes in yet again. Not only did we have to worry about winter weather at sea, but the inclement conditions across the country meant our COVID tests were delayed in transit—and we could not board the ship until everyone tested negative. By the time our results were in, the marine forecast was foreboding, and the Captain determined that the weather window for our planned return to port had closed.

So, we are still on shore. The ship never left the dock, and NCC February 2021 will go on the record as “NAs” rather than sightings of marine mammal presence or absence. So it goes. We can dedicate all our energy to studying the ocean and these spectacularly dynamic systems, but we cannot control them. It is an important and humbling reminder. But as we have continued to learn over the past year, there are always silver linings to be found.

Even though we never made it to the ship, it turns out there’s a lot you can get done onshore. Dawn has sailed on several NCC cruises before, and one of the goals this time was to train Rachel for her first stint at marine mammal survey work. This began at Dawn’s house in Newport, where we sheltered in place together for the week prior to our departure date.

We walked through the iPad program we use to enter data, looked through field guides, and talked over how to respond in different scenarios we might encounter while surveying for marine mammals at sea. We also joined Solene, a postdoc working on the OPAL project, for a Zoom meeting to edit the distance sampling protocol document. It was great training to discuss the finer points of data collection together, with respect to how that data will ultimately be worked into our species distribution models.

The February NCC cruise is famously rough, and a tough time to sight whales (Fig. 1). This low sighting rate arises from a combination of factors: baleen whales typically spend the winter months on their breeding grounds in lower latitudes so their density in Oregon waters is lower, and the notorious winter sea state makes sighting conditions difficult. Solene signed off our Zoom call with, “Go collect that high-quality absence data, girls!” It was a good reminder that not seeing whales is just as important scientifically as seeing them—though sometimes, of course, it’s not possible to even get out where you can’t see them. Furthermore, all absence data is not created equal. The quality of the absence data we can collect deteriorates along with the weather conditions. When we ultimately use these survey data to fuel species distribution models, it’s important to account for our confidence in the periods with no whale sightings.

In addition to the training we were able to conduct on land, the biggest silver lining came just from sheltering in place together. We had only met over Zoom previously, and spending this time together gave us the opportunity to get to know each other in real life and become friends. The week involved a lot of fabulous cooking, rainy walks, and an ungodly number of peanut butter cups. Even though the cruise couldn’t happen, it was such a rich week. The NCC cruises take place several times each year, and the next one is scheduled for May 2021. We’ll keep our fingers crossed for fair winds and negative COVID tests in May!

Figure 2. Dawn’s dog Quin was a great shelter in place buddy. She was not sad that the cruise was canceled.

Putting Physiological Tools to Work for Whale Conservation

By Alejandro Fernandez Ajo, PhD student at the Department of Biology, Northern Arizona University, Visiting scientist in the GEMM Lab working on the gray whale physiology and ecology project  

About four years ago, I was in Patagonia, Argentina deciding where to focus my research and contribute to whale conservation efforts. At the same time, I was doing fieldwork with the Whale Conservation Institute of Argentina at the “Whale Camp” in Península Valdés. I read tons of papers and talked with my colleagues about different opportunities and gaps in knowledge that I could tackle during my Ph.D. program. One of the questions that caught my attention was about the unknown cause (or causes) for the recurrent high calf mortalities that the Southern Right Whale (SRW) population that breeds at Peninsula Valdés experienced during the 2000s (Rowntree et al. 2013). Still, at that time, I was unsure how to tackle this research question.

Golfo San José, Península Valdés – Argentina. Collecting SRW behavioral data from the cliff’s vantage point. Source: A. Fernandez Ajo.

Between 2003 and 2013, at least 672 SRWs died, of which 91% were calves (Sironi et al. 2014). These mortalities represented an average total whale death per year of 80 individuals in the 2007-2013 period, which vastly exceeded the 8.2 average deaths per year of previous years by a ten-fold increase (i.e., 1993-2002) (Rowntree et al. 2013). In fact, this calf mortality rate was the highest ever documented for any population of large whales. During this period, from 2006 to 2009, I was the Coordinator of the Fauna Area in the Patagonian Coastal Zone Management Plan, and I collaborated with the Southern Right Whale Health Monitoring Program (AKA: The Stranding Program) that conducted field necropsies on stranded whales along the coasts of the Península and collected many different samples including whale baleen.

Southern Right Whale, found stranded in Patagonia Argentina. Source: Instituto de Conservación de Ballenas.

In this process, I learned about the emerging field of Conservation Physiology and the challenges of utilizing traditional approaches to studying physiology in large whales. Basically, the problem is that there is no possible way to obtain blood samples (the gold standard sample type for physiology) from free-swimming whales; whales are just too large! Fortunately, there are currently several alternative approaches for gathering physiological information on large whales using a variety of non-lethal and minimally invasive (or non-invasive) sample matrices, along with utilizing valuable samples recovered at necropsy (Hunt et al. 2013). That is how I learned about Dr. Kathleen Hunt’s novel research studying hormones from whale baleen (Hunt et al., 2018, 2017, 2014). Thus, I contacted Dr. Hunt and started a collaboration to apply these novel methods to understand the case of calf mortalities of the SRW calves in Patagonia utilizing the baleen samples that we recovered with the Stranding program at Península Valdés (see my previous blog post).

What is conservation physiology?

Conservation physiology is a multidisciplinary field of science that utilizes physiological concepts and tools to understand underlying mechanisms of disturbances to solve conservation problems. Conservation physiology approaches can provide sensitive biomarkers of environmental change and allow for targeted conservation strategies. The most common Conservation Physiology applications are monitoring environmental stressors, understanding disease dynamics and reproductive biology, and ultimately reducing human-wildlife conflict, among other applications.

I am now completing the last semester of my Ph.D. program. I have learned much about the amazing field of Conservation Physiology and how much more we need to know to achieve our conservation goals. I am still learning, yet I feel that through my research I have contributed to understanding how different stressors impact the health and wellbeing of whales, and about aspects of their biology that have long been obscured or unknown for these giants. One contribution I am proud of is our recent publication of, “A tale of two whales: putting physiological tools to work for North Atlantic and southern right whales,” which was published in January 2021 as a book chapter in “Conservation Physiology: Applications for Wildlife Conservation and Management” published by Oxford University Press: Oxford, UK.

This book outlines the significant avenues and advances that conservation physiology contributes to the monitoring, management, and restoration of wild animal populations. The book also defines opportunities for further growth in the field and identifies critical areas for future investigation. The text and the contributed chapters illustrate several examples of the different approaches that the conservation physiology toolbox can tackle. In our chapter, “A tale of two whales,” we discuss developments in conservation physiology research of large whales, with the focus on the North Atlantic right whale (Eubalaena glacialis) and southern right whale (Eubalaena australis), two closely related species that differ vastly in population status and conservation pressures. We review the advances in Conservation Physiology that help overcome the challenges of studying large whales via a suite of creative approaches, including photo-identification, visual health assessment, remote methods of assessing body condition, and endocrine research using non-plasma sample types such as feces, respiratory vapor, and baleen. These efforts have illuminated conservation-relevant physiological questions for both species, such as discrimination of acute from chronic stress, identification of likely causes of mortality, and monitoring causes and consequences of body condition and reproduction changes.

Book Overview:

This book provides an overview of the different applications of Conservation Physiology, outlining the significant avenues and advances by which conservation physiology contributes to the monitoring, management, and restoration of wild animal populations. By using a series of global case studies, contributors illustrate how approaches from the conservation physiology toolbox can tackle a diverse range of conservation issues, including monitoring environmental stress, predicting the impact of climate change, understanding disease dynamics, and improving captive breeding, and reducing human-wildlife conflict. The variety of taxa, biological scales, and ecosystems is highlighted to illustrate the far-reaching nature of the discipline and allow readers to appreciate the purpose, value, applicability, and status of the field of conservation physiology. This book is an accessible supplementary textbook suitable for graduate students, researchers, and practitioners in conservation science, ecophysiology, evolutionary and comparative physiology, natural resources management, ecosystem health, veterinary medicine, animal physiology, and ecology.

References

Hunt KE, Fernández Ajó A, Lowe C, Burgess EA, Buck CL. 2021. A tale of two whales: putting physiological tools to work for North Atlantic and southern right whales. In: “Conservation Physiology: Integrating Physiology Into Animal Conservation And Management”, ch. 12. Eds. Madliger CL, Franklin CE, Love OP, Cooke SJ. Oxford University press: Oxford, UK.

Sironi, M., Rowntree, V., Di Martino, M. D., Beltramino, L., Rago, V., Franco, M., and Uhart, M. (2014). Updated information for 2012-2013 on southern right whale mortalities at Península Valdés, Argentina. SC/65b/BRG/06 report presented to the International Whaling Commission Scientific Committee, Portugal. <https://iwc.int/home>.

Rowntree, V.J., Uhart, M.M., Sironi, M., Chirife, A., Di Martino, M., La Sala, L., Musmeci, L., Mohamed, N., Andrejuk, J., McAloose, D., Sala, J., Carribero, A., Rally, H., Franco, M., Adler, F., Brownell, R. Jr, Seger, J., Rowles, T., 2013. Unexplained recurring high mortality of southern right whale Eubalaena australis calves at Península Valdés, Argentina. Marine Ecology Progress Series, 493, 275-289. DOI: 10.3354/meps10506

Hunt KE, Moore MJ, Rolland RM, Kellar NM, Hall AJ, Kershaw J, Raverty SA, Davis CE, Yeates LC, Fauquier DA, et al., 2013. Overcoming the challenges of studying conservation physiology in large whales: a review of available methods. Conserv Physiol 1: cot006–cot006.

Hunt, K.E., Stimmelmayr, R., George, C., Hanns, C., Suydam, R., Brower, H., Rolland, R.M., 2014. Baleen hormones: a novel tool for retrospective assessment of stress and reproduction in bowhead whales (Balaena mysticetus). Conserv. Physiol. 2, cou030. https://doi.org/10.1093/conphys/cou030

Hunt, K.E., Lysiak, N.S., Moore, M.J., Rolland, R.M., 2016. Longitudinal progesterone profiles in baleen from female North Atlantic right whales (Eubalaena glacialis) match known calving history. Conserv. Physiol. 4, cow014. https://doi.org/10.1093/conphys/cow014

Hunt, K.E., Lysiak, N.S., Robbins, J., Moore, M.J., Seton, R.E., Torres, L., Buck, C.L., 2017. Multiple steroid and thyroid hormones detected in baleen from eight whale species. Conserv. Physiol. 5. https://doi.org/10.1093/conphys/cox061

Hunt, K.E., Lysiak, N.S.J., Matthews, C.J.D., Lowe, C., Fernández Ajó, A., Dillon, D., Willing, C., Heide-Jørgensen, M.P., Ferguson, S.H., Moore, M.J., Buck, C.L., 2018. Multi-year patterns in testosterone, cortisol and corticosterone in baleen from adult males of three whale species. Conserv. Physiol. 6, coy049. https://doi.org/10.1093/conphys/coy049

What makes a species, a species?

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

Over the roughly 2.5 years that I have researched the Pacific Coast Feeding Group (PCFG) of gray whales, I have thought more and more about what makes a population, a population. From a management standpoint, the PCFG is currently not considered a separate population or even a sub-population of the Eastern North Pacific (ENP) gray whales. Rather, the PCFG is most commonly referred to as a ‘sub-group’ of the ENP. In my opinion, there are valid arguments both for and against the PCFG being designated as its own population. I will address those arguments briefly at the end of this post, but first, I want you to join on me on a journey that is tangential to my question of ‘what makes a population, a population?’ and one that started at the last Marine Mammal Institute Monthly Meeting (MMIMM).

During 2021’s first MMIMM, our director Dr. Lisa Ballance proposed that we lengthen our monthly meeting duration from 1 hour to 1.5 hours. The additional 30 minutes was to allow for an open-ended, institute-wide discussion of a current hot topic in marine mammal science. This proposal was immediately adopted, and the group dove into a discussion about the discovery of a new baleen whale species in the northeastern Gulf of Mexico: Rice’s whale (Balaenoptera ricei). Let me pause here very briefly to reiterate – the discovery of a new baleen whale species!! The fact that anything as large as 12 m could remain undiscovered in our oceans is really quite fascinating and shows that our scientific quest will likely never run out of discoverable subjects. Anyway, the discovery of this new species is supported by several lines of evidence. Unfortunately (but understandably), MMI’s discussion of these topics had to cease after 30 minutes, however I had more questions. I wanted to know what had sparked the researchers to believe that they had discovered a new cetacean species. 

Scientific illustration of Bryde’s whale. Source: NOAA Fisheries.

I started my research by skimming through some news articles about the Rice’s whale discovery. In a Smithsonian Magazine article, I saw a quote by Dr. Patricia Rosel, the lead author of the study detailing Rice’s whale, that read: “But we didn’t have a skull.”. That quote made me pause. A skull? Is that what it takes to discover and establish a new species? This desired piece of evidence seemed rather puzzling and a little antiquated to me, given that the field of genetics is so advanced now and since it is no longer an accepted practice to kill a wild animal just to study it (i.e., scientific whaling). I backtracked through the article to learn that in the 1990s, renowned marine mammal scientist Dale Rice (after whom Rice’s whale was named) recognized that a small population of baleen whale occurred in the northeastern part of the Gulf of Mexico year-round. At the time, this population was believed to be a sub-population of Bryde’s whale. It wasn’t until 2008, that NOAA scientists were able to conduct a genetic analysis of tissue samples from this population, only to find that these whales were genetically distinct from other Bryde’s whales (Rosel & Wilcox 2014). Yet, this information was not enough for these whales to be established as their own species. A skull really was needed to prove that these whales were in fact a new species. Thankfully (for the scientists) but sadly (for the whale), one of these individuals stranded in Sandy Key, Florida, in 2019, and a dedicated team of stranding responders from Florida Fish and Wildlife, Mote Marine Lab, NOAA, Dolphins Plus, and Marine Animal Rescue Society worked tirelessly in difficult conditions to comprehensively document and preserve this animal. Through the diligent work of this, and previous, stranding response teams, Dr. Rosel and her team were provided the opportunity to examine the skull needed to determine population-status. The science team determined that the bones atop the skull around the blowhole provided evidence that these whales were not only genetically, but also anatomically, different from Bryde’s whales. It was this incident, triggered by that short quote in the Smithsonian article, that brought me to my journey of asking ‘what makes a species, a species?’.

Given that I had just read that Dr. Rosel needed a skull to establish Rice’s whale as its own species, I assumed that my search for ‘how to establish a new species’ would end quickly in me finding a list of requirements, one of which would be ‘must present anatomical/skeletal evidence’. To my surprise, my search did not end quickly, and I did not find a straightforward list of requirements. Instead, I discovered that my question of ‘what makes a species, a species?’ does not have a black-and-white answer and involves a lot of debate.

The skull of this stranded whale was a large piece of evidence in establishing Rice’s whale as its own species. Source: Smithsonian Magazine from NOAA / Florida Fish and Wildlife Commission

Kevin de Queiroz, a vertebrate, evolutionary, and systematic biologist who has published extensively on theoretical and conceptual topics in systematic and evolutionary biology, believes that the issue of species delimitation (‘what makes a species, a species?’) has been made more complicated by a larger issue involving the concept of species itself (‘what is a species?’) (De Queiroz 2007). To date, there are 24 recognized species concepts (Mayden 1997). In other words, there are 24 different definitions of what a species is. Perhaps the most common example is the biological species concept where a species is defined as a group of individuals that are able to produce viable and fertile offspring following natural reproduction. Another example is the ecological species concept whereby a species is a group of organisms adapted to a particular set of resources and conditions, called a niche, in the environment. Problematically, many of these concepts are incompatible with one another, meaning that applying different concepts leads to different conclusions about the boundaries and numbers of species in existence (De Queiroz 2007).

This large number of species concepts is due to the different interests of certain subgroups of biologists. For example, highlighting morphological differences between species is central to paleontologists and taxonomists, whereas ecologists will focus on niche differences. Population geneticists will attribute species differences to genes, while for systematists, monophyly will be paramount. It goes on and on. And so does the debate about the concept of species. It seems that there currently is not one clear, defined consensus on what a species is. Some biologists argue that a species is a species if it is genetically different, while others will insist that skeletal and morphological evidence must be present. From what I can tell, it seems that scientists describe and (attempt to) establish a new species by publishing their lines of evidence, after which experts in the field discuss and evaluate whether a new species should be established. 

In the field of marine mammal science, the Society of Marine Mammalogy’s Taxonomic Committee is charged with maintaining a standard, accepted classification and nomenclature of marine mammals worldwide. The committee annually considers and evaluates new, peer-reviewed literature that proposes changes (including additions) to marine mammal taxonomy. I expect that the case of Rice’s whale will be on the committee’s docket this year. Given that Rosel and co-authors presented geographic, morphological, and genetic evidence to support the establishment of Rice’s whale, I would not be surprised if the committee adds it to their curated list.

After taking this dive into the ‘what makes a species, a species?’ question, let’s see if we can apply some of what we’ve learned to the ‘what makes a population, a population?’ question regarding the PCFG and ENP gray whales. Following the ecological species concept, an argument for the recognition of the PCFG as its own population would be that they occupy an entirely different environment during their summer foraging season than the ENP whales. Not only are the geographic ranges different, but PCFG whales also show behavioral differences in their foraging tactics and targeted prey. The argument against the PCFG being classified as its own population is largely supported by genetic analysis that has revealed ambiguous evidence that the PCFG and ENP are not genetically isolated from one another. While one study has shown that there is maternal cultural affiliation within the PCFG (meaning that calves born to PCFG females tend to return to the PCFG range; Frasier et al. 2011), another has revealed that mixing between ENP and PCFG gray whales on the breeding grounds does occur (Lang et al. 2014). So, even though these two groups feed in areas that are very far apart (ENP: Arctic vs PCFG: US & Canadian west coast) and certain individuals do show a propensity for a specific feeding ground, the genetic evidence suggests that they mix when on their breeding grounds in Baja California, Mexico. Depending on which species concept you align with, you may see better arguments for either side.

PCFG gray whale along the Oregon coast during the GEMM Lab’s 2020 GRANITE summer field season. Image captured under NOAA/NMFS permit #21678. Source: GEMM Lab.

You may be wondering why it is important to even ponder questions like ‘what makes a species, a species?’ and ‘what makes a population, a population?’. Does it really matter if the PCFG are considered their own population? Would anything really change? The answer is, most likely, yes. If the PCFG were to be recognized as their own population, it would likely have an immediate effect on their conservation status and subsequently on how the population needed to be managed. Rather than being under the umbrella of a large, (mostly) stable population of ~25,000 individuals, the PCFG would consist of only ~250 individuals. A group this small would possibly be considered “endangered”, which would require much stricter monitoring and management to ensure that their numbers did not decline from year to year, especially due to anthropogenic activities. 

For a long time, I felt like taxonomy was a bit of an archaic scientific field. In my mind, it was something that biologists had focused their time and energy on in the 18th century (most notably Carl Linnaeus, whose taxonomic classification system is still used today), but something that many biologists have moved on from focusing on in the 21st century. However, as I have developed and grown over the last years as a scientist, I have learned that scientific disciplines are often heavily intertwined and co-dependent on one another. As a result, I am able to see the enormous value and need for taxonomic work as it plays a large part in understanding, managing, and ultimately, conserving species and populations.

Literature cited

De Queiroz, K. 2007. Species concepts and species delimitation. Systematic Biology 56(6):879-886.

Frasier, T. R., Koroscil, S. M., White, B. N., and J. D. Darling. 2011. Assessment of population substructure in relation to summer feeding ground use in the eastern North Pacific gray whale. Endangered Species Research 14:39-48.

Lang, A. R., Calambokidis, J., Scordino, J., Pease, V. L., Klimek, A., Burkanov, V. N., Gearin, P., Litovka, D. I., Robertson, K. M., Mate, B. R., Jacobsen, J. K., and B. L. Taylor. 2014. Assessment of genetic structure among eastern North Pacific gray whales on their feeding grounds. Marine Mammal Science 30(4):1473-1493.

Mayden, R. L. 1997. A hierarchy of species concepts: the denouement of the species problem in The Units of Biodiversity – Species in Practice Special Volume 54 (M. F. Claridge, H. A. Dawah, and M. R. Wilson, eds.). Systematics Association.

Rosel, P. E., and L. A. Wilcox. 2014. Genetic evidence reveals a unique lineage of Bryde’s whale in the northeastern Gulf of Mexico. Endangered Species Research 25:19-34.

The ups and downs of the ocean

By Solène Derville, Postdoc, OSU Department of Fisheries and Wildlife, Geospatial Ecology of Marine Megafauna Lab

As a GEMM lab post-doc working on the OPAL project, my main goal for 2021 will be to produce accurate predictive models of baleen whale distribution off the Oregon coast to reduce entanglement risk. For the past months, I have been compiling, cleaning, and processing about two years of data collected by Leigh Torres and Craig Hayslip during monthly repeat surveys conducted onboard United States Coast Guard (USCG) helicopters. These standardized surveys record where and when whales are observed off the Oregon coast. These presence and absence data may now be modeled in relation to habitat, while accounting for effort and detection (as several parameters, such as weather and sea state, can affect the capacity of observers to detect whales at the surface). Considering that several baleen whale species (namely, humpback, fin, blue and gray whales) are known to feed in the area, prey availability is expected to be a major driver of their distribution.

As prey distribution data are frequently the lacking component in the habitat model equation, whale ecologists often resort to using environmental proxies. Variables such as topography (e.g., the depth or slope of the seafloor), water physical and chemical characteristics (e.g., temperature, salinity, oxygen concentration) or ocean circulation (e.g., currents, turbulence) have proved to be good predictors for fish or krill distribution, and in turn potential predictors for whale suitable habitats. In my search for such environmental variables to be tested in our future OPAL models, I have been focusing my research on a fascinating ocean feature: sea height.

Sea height varies both temporally and spatially under the influence of multiple factors, from internal mass of the solid Earth to the orbital revolution of the moon. After reading this blog you will realize that the flatness of the horizon at sea is a deceiving perspective (Figure 1) …

Figure 1: Flat? Really? (source: Pixabay)

Gravity and the geoid

We all know of Newton’s s discovery of gravity: the attraction force exerted by any object with a given mass on its surroundings. Yet, it is puzzling to think that the rate of acceleration of the apple falling on Newton’s head would have been different if Newton had been anywhere else on Earth.

Why is that and what does it have to do with sea height? On Earth, the standard gravity g is set at 9.80665 m/s2. This constant is called a “standard” because in fact, gravity varies at the surface of our planet, even if estimated at a fixed altitude. Indeed, as gravity is caused by mass, any change in relief or rock composition results in a change in gravity. For instance, magmatic activity in the upper mantle of the Earth and the crust causes a change in rock density and results in a change in gravity measured at the surface.

Gravity therefore is the first reason why the ocean surface is not flat. Gravity shapes an irregular surface called the “geoid”. This hypothetical ocean surface has equal gravitational potential anywhere on Earth and differs from the ellipsoid of reference by as much as 100 m! So to the question whether Earth is round or flat, I would say it is potato shaped (Figure 2)!

Figure 2: Exaggerated view of the gravitational potential of Earth. View a video animation here. (credit: European Space Agency)

The geoid is an essential reference for understanding ocean currents and monitoring changes in sea-level. Hypothetically, if ocean water had equal density everywhere and at any depth, the sea surface should match with the geoid… but that’s not the case. Let’s see why.

Ocean dynamic topography

Not unlike the hills and valleys covering landscapes, the ocean surface also has its highs and lows. Except that in the ocean, the surface topography is ever changing. Sea surface height (SSH) measures the average height difference between the observed sea level and the ellipsoid of reference (Figure 3). SSH is mostly affected by ocean circulation and may vary by as much as ±1 m. Indeed, just like the rocks inside the Earth, the water in the ocean varies in density. The vertical and horizontal physical structuring of the ocean was extensively discussed by Dawn last November while she was preparing for her PhD Qualifying Exams. Temperature clearly is at the core of the processes. As thermal expansion increases the space between warming water particles, the volume of a given amount of liquid water increases with increasing temperature. Warmer waters therefore take up “more space” than cooler waters, resulting in an elevated SSH.

Figure 3: Overview of the different fields used in altimetry (credit: CLS, https://duacs.cls.fr/)

SSH may therefore be used as an indicator of oceanographic phenomena such as upwellings, where warm surface waters are replaced by deep, cooler, and nutrient-rich waters moving upwards. The California Current that moves southwards along the North American coast is known as one of the world’s major currents affiliated with strong upwelling zones, which often triggers increased biological productivity. Several studies conducted in the California Current system have found a link between the variations in SSH and whale abundance or foraging activity (Abrahms et al. 2019; Pardo et al. 2015; Becker et al. 2016; Hazen et al. 2016).⁠

SSH is measured by altimeter satellites and is made freely available by the European Space Agency and the US National Aeronautics and Space Administration. Lucky me! Numerous variables are derived from SSH, as shown in Figure 3. Among other things, I was able to download the daily maps of Sea Surface Height Anomaly (SSHa, also referred to as Sea Level Anomaly: SLA) over the Oregon coast from February 2019 to December 2020. SSHa is the difference between observed SSH at a specific time and place from the mean SSH field of reference calculated over a long period of time. Negative values of SSHa potentially suggest upwellings of cooler waters that could be associated with higher prey availability. Figure 4 shows an example of environmental data mining as I try to match SSHa with whale observations made during OPAL surveys. Figure 4B suggests increased whale occurrence where/when SSHa is lower.

Figure 4: Preliminary exploration of the relationship between sea surface height anomaly (SSHa) and baleen whales (blue, fin, humpback, unidentified) observed during OPAL surveys off Oregon, USA, between February 2019 and December 2020. A) Example covering 3 months of survey during summer 2019. Sightings were grouped over 5-km segments of surveyed trackline and segments with at least one sighting were mapped with colored circles. Dotted grey lines are the repeated survey tracklines for each of the labeled study areas (NB = North Bend). Sightings are symbolized by area (color)
and group size (circle size). Monthly averages of SSHa are represented with a colored gradient. B) Monthly averages of SSHa measured over 5-km segments where whales were detected (presence) or not (absence).

Although encouraging, these preliminary insights are just the tip of the modeling iceberg. Many more testing and modeling steps will be required to determine confounding factors and relevant spatio-temporal scales at which these oceanographic variables may be influencing whale distribution off the Oregon coast. I am only at the start of a long road…

References

Abrahms, Briana, Heather Welch, Stephanie Brodie, Michael G. Jacox, Elizabeth A. Becker, Steven J. Bograd, Ladd M. Irvine, Daniel M. Palacios, Bruce R. Mate, and Elliott L. Hazen. 2019. “Dynamic Ensemble Models to Predict Distributions and Anthropogenic Risk Exposure for Highly Mobile Species.” Diversity and Distributions, no. December 2018: 1–12. https://doi.org/10.1111/ddi.12940.

Becker, Elizabeth, Karin Forney, Paul Fiedler, Jay Barlow, Susan Chivers, Christopher Edwards, Andrew Moore, and Jessica Redfern. 2016. “Moving Towards Dynamic Ocean Management: How Well Do Modeled Ocean Products Predict Species Distributions?” Remote Sensing 8 (2): 149. https://doi.org/10.3390/rs8020149.

Hazen, Elliott L, Daniel M Palacios, Karin A Forney, Evan A Howell, Elizabeth Becker, Aimee L Hoover, Ladd Irvine, et al. 2016. “WhaleWatch : A Dynamic Management Tool for Predicting Blue Whale Density in the California Current.” Journal of Applied Ecology 54 (5): 1415–28. https://doi.org/10.1111/1365-2664.12820.

Pardo, Mario A., Tim Gerrodette, Emilio Beier, Diane Gendron, Karin A. Forney, Susan J. Chivers, Jay Barlow, and Daniel M. Palacios. 2015. “Inferring Cetacean Population Densities from the Absolute Dynamic Topography of the Ocean in a Hierarchical Bayesian Framework.” PLOS One 10 (3): 1–23. https://doi.org/10.1371/journal.pone.0120727.

The past and present truths of “Big Miracle”

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

As we all try to find ways to be together safely this winter, the GEMM Lab has started a fun series of virtual movie nights. Just before the holidays, we watched “Big Miracle,” which tells the story of the historic whale entrapment event in Utqiagvik, Alaska (formerly called “Barrow”) that captured the world’s attention. 

The 2012 film stars Drew Barrymore, who plays a Greenpeace activist, and John Krasinski, a television reporter covering the story.

In late September 1988, three gray whales became trapped in the sea ice just off Point Barrow. Local attempts to free the whales quickly became national news that captured the attention of millions, including President Ronald Reagan, pop legend Michael Jackson – and elementary-schooler Leigh Torres. 

After the movie, Leigh told us about how she had religiously followed television updates on the rescue as a child. Hearing her memories of the event and its part in inspiring her to pursue a career in whale research was one of the best parts of watching the movie together as a lab.   

Tuning in from my parents’ house in Fairbanks, Alaska, the story felt surprisingly close to home for me too. I had never heard Inupiaq spoken in a feature film before, and I was stunned to recognize the landscape around Utqiaġvik and realize that some of the movie was filmed on location. It was also the first movie I’d seen represent the myriad of human dimensions that surround whale research and policy, including Indigenous rights, oil and fishing industry interests, and environmental perspectives. 

Certain elements of the movie also made me uncomfortable, and thus made me wonder about the movie’s accuracy. Why were the main characters in the film people from outside Alaska? How did the rescue logistics and decision-making processes really play out in Utqiaġvik? Why did the whales become trapped in the first place? 

I was curious to learn more about the whales, and how Utqiaġvik experienced both the massive rescue effort and the Hollywood-ized retelling of its story. During a great Zoom conversation, I learned more from Craig George, a whale biologist who has worked in Utqiaġvik since the 1970s and was involved during the entire 1988 rescue mission.

Like all Hollywood movies based on real events, “Big Miracle” mixes facts with a healthy dose of fiction and storytelling. The movie portrays the three entrapped whales as a family unit, given the names Wilma, Fred, and Bam Bam. Craig described them in more scientific terms – three subadult gray whales, all 25-30 feet in length. He and the other biologists onsite collected data throughout the three-week rescue effort, recording the whales’ behavior, dive times, and vocalizations. They calculated that the whales’ respiration rates were double that of typical rates, revealing the whales’ distress. 

The rescue team named the whales Crossbeak, Bone, and Bonnet based on each individual’s notable morphological traits. Photo: Craig George

“The community effort to free the whales was amazing,” Craig said. “Low-tech approaches and local knowledge are typically most effective in the Arctic, and all the best ideas relied on the Inupiaq knowledge of the area.” 

With the aim of leading the whales offshore to safer waters, a team of volunteers cut a series of breathing holes at regular intervals in the sea ice. The approach seemed to work well, and so the ice-breaking crew was puzzled when the whales stopped using the new holes – until they realized the area was underlain by shoals that the whales were unwilling to cross. They began cutting in a new direction, and the whales appeared in the new hole instantly, before the opening was even completed.

“The whales were trying to tell us the direction they wanted to go,” Craig said. “It was really astonishing, because there was definitely a dynamic between us. We tried to train them to work with us, and they also trained us.” 

 A team of volunteers cut holes in the sea ice, creating a path to open water, while journalists document the moment. Photo: Craig George

Over three weeks, the rescue effort grew from local to international. Companies donated chainsaws and fuel, and people following the news outside Alaska flew to Utqiaġvik to volunteer their help. Several attempts to break the ice, including an ice-based pontoon tractor and an ice-breaking helicopter, failed. Working around the clock, and in temperatures below -20F, volunteers continued cutting breathing holes in the ice for the whales.

Finally, one hurdle remained between the whales and open water – a massive pressure ridge of grounded sea ice, about 20 ft high and just as deep. It was impossible to cut through with chainsaws. Two Russian icebreakers, the Vladimir Arseniev and the Admiral Makarov were enlisted to come break the ridge and clear the way to open water – no small diplomatic feat during the Cold War. 

Ultimately, Craig said, the real story’s ending isn’t quite as picture-perfect as the one in “Big Miracle” – no one actually knows whether the whales made it out or not.

“We know that the whales swam out the icebreaker track, because their blood was found on ice shards,” he said. “They might have made it out, but we never saw them again and don’t know for sure.”

This map shows the path of holes cut through the sea ice, icebreaker track, and pressure ridge of ice. “Barrow” is the former name of Utqiaġvik. Source: Geoff Carroll and Craig George

Nearly 40 years later, Craig says the story still comes up often in Utqiaġvik, but in a different context – climate change. In 1988, the sea ice froze up in late September. In 2020, however, there was no shore-fast ice until early December. Craig remembers that, during the rescue, temperatures dropped to -24°F one night — colder than Utqiaġvik had experienced yet in January 2020, when we last spoke. Today’s dramatically different conditions have impacts for the entire Arctic ecosystem, as well as the people who rely on it to survive.

Watching “Big Miracle” sparked so many questions about the past, and talking with Craig gave me just as many questions about the future. How will changing ocean conditions impact gray whales, and other Arctic whales? How will the social and environmental dynamics that “Big Miracle” depicted – environmentalism, resource exploitation, and Indigenous rights – adapt and evolve in a changing Arctic? What will the Alaskan Arctic look like in another 40 years?

The ecologist and the economist: Exploring parallels between disciplines

By Dawn Barlow1 and Johanna Rayl2

1PhD Candidate, Oregon State University Department of Fisheries and Wildlife, Geospatial Ecology of Marine Megafauna Lab

2PhD Student, Northwestern University Department of Economics

The Greek word “oikos” refers to the household and serves as the root of the words ecology and economics. Although perhaps surprising, the common origin reflects a shared set of basic questions and some shared theoretical foundations related to the study of how lifeforms on earth use scarce resources and find equilibrium in their respective “households”. Early ecological and economic theoretical texts drew inspiration from one another in many instances. Paul Samuelson, fondly referred to as “the father of modern economics,” observed in his defining work Foundations of Economic Analysis that the moving equilibrium in a market with supply and demand is “essentially identical with the moving equilibrium of a biological or chemical system undergoing slow change.” Likewise, early theoretical ecologists recognized the strength of drawing on theories previously established in economics (Real et al. 1991). Similar broad questions are central to researchers in both fields; in a large and dynamic system (termed “macro” in economics) scale, ecologists and economists alike work to understand where competitive forces find equilibrium, and an in individual (or micro) scale, they ask how individuals make behavior choices to maximize success given constraints like time, energy, wealth, or physical resources.

The central model economists have in mind when trying to understand human choices involves “constrained optimization”: what decision will maximize a person, family, firm, or other agent’s objectives given their limitations? For example, someone that enjoys relaxing but also seeks a livable income must choose how much time to devote to working versus relaxing, given the constraint of having just 24 hours in the day, and given the wage they receive from working. An economist studying this decision may want to learn about how changes in the wage will affect that person’s choice of working hours, or how much they dislike working relative to relaxing. Along similar lines, early ecologists theorized that organisms could be selected for one of two optimization strategies: minimizing the time spent acquiring a given amount of energy (i.e., calories from food), or maximizing total energy acquisition per unit of time (Real et al. 1991). Foundational work in the field of economics clarified numerous technical details about formulating and solving such optimization problems. Returning to the example of the leisure time decision, economic theory asks: does it matter if we model this decision as maximizing income given wages and limited time, or as minimizing hours spent working given a desired lifetime income?; can we formulate a “utility function” that  describes how well-off someone is with a given income and amount of leisure?; can we solve for the optimal amount of leisure with pen and paper? The toolkit arising from this work serves as a jumping off point for all contemporary economic research, and the kinds of choices understood under this framework is vast, from, where should a child attend school?; to, how should a government allocate its budget across public resources?

Early work in ecology drew from foundational concepts in economics, following the realization that the strategies by which organisms exploit resources most efficiently also involve optimization. This parallel was articulated by MacArthur and Pianka in their foundational 1966 paper Optimal Use of a Patchy Environment, in which they state: “In this paper we undertake to determine in which patches a species would feed and which items would form its diet if the species acted in the most economical fashion. Hopefully, natural selection will often have achieved such optimal allocation of time and energy expenditures.” Subsequently, this idea was refined into what is known in ecology as the marginal value theorem, which states that an animal should remain in a prey patch until the rate of energy gain drops below the expected energy gain in all remaining available patches (Charnov 1976). In other words, if it is more profitable to switch prey patches than to stay, an animal should move on. These optimization models therefore allow ecologists to pose specific evolutionary and behavioral hypotheses, such as examining energy acquisition over time to understand selective forces on foraging behavior.

As the largest animals on the planet, blue whales have massive prey requirements to meet energy demands. However, they must balance their need to feed with costs such as oxygen consumption during breath-holding, the travel time it takes to reach prey patches at depth, the physiological constraints of diving, and the necessary recuperation time at the surface. It has been demonstrated that blue whales forage selectively to optimize this energetic budget. Therefore, blue whales should only feed on krill aggregations when the energetic gain outweighs the cost (Fig. 1), and this pattern has been empirically demonstrated for blue whale populations in the Gulf of St. Lawrence, Canada (Doniol-Valcroze et al. 2011), in the California Current, (Hazen et al. 2015) and in New Zealand (Torres et al. 2020).

Figure 1. Figure reprinted from Hazen et al. 2015, illustrating how a blue whale should theoretically optimize foraging success in two scenarios. Energy gained from feeding is shown by the blue lines, whereas the cost of foraging in terms of declining oxygen stores during a dive is illustrated by the red lines. On the left (panel B), the whale maximizes its energy gain by increasing the number of feeding lunges (shown by black circles) at the expense of declining oxygen stores when prey density is high. On the right (panel C), the whale minimizes oxygen use by reducing the number of feeding lunges when prey density is low.

The notion of the marginal value theorem is likewise at work in countless economic settings. Economic theory predicts that a farmer cultivating two crops would allocate resources into each crop such that the returns to adding more resources into each crop are the same. If not, she should move resources from the less productive crop to the one where marginal gains are larger. A fisherman, according to this notion, continues to fish longer into the season until the marginal value of one additional day at sea equals the marginal cost of their time, effort, and expenses. These predictions are intuitive by the same logic as the blue whale choosing where to forage, and derive from the mathematics of constrained and unconstrained optimization. Reassuringly, empirical work finds evidence of such profit-maximizing behavior in many settings. In a recent working paper, Burlig, Preonas, and Woerman explore how farmers’ water use in California responds to changes in the price of electricity, which effectively makes groundwater irrigation more expensive due to electric pumping. They find that farmers are very responsive to these changes in marginal cost. Farmers achieve this reduction in water use predominantly by switching to less water-intensive crops and fallowing their land (Burlig, Preonas, and Woerman 2020).

Undoubtedly there are fundamental differences between an ecosystem with interacting biotic and abiotic components and the human-economic environment with its many social and political structures. But for certain types of questions, the parallels across the shared optimization problems are striking. The foundational theories discussed here have paved the way for subsequent advances in both disciplines. For example, the field of behavioral ecology explores how competition and cooperation between and within species affects fitness of populations. Reflecting on early seminal work lends some perspective on how an area of research has evolved. Likewise, exploring parallels between disciplines sheds light on common threads, in turn revealing insights into each discipline individually.

References:

Burlig, Fiona, Louis Preonas, and Matt Woerman (2020). Groundwater, energy, and crop choice. Working Paper.

Charnov EL (1976) Optimal foraging: The marginal value theorem. Theoretical Population Biology 9:129–136.

Doniol-Valcroze T, Lesage V, Giard J, Michaud R (2011) Optimal foraging theory predicts diving and feeding strategies of the largest marine predator. Behavioral Ecology 22:880–888.

Hazen EL, Friedlaender AS, Goldbogen JA (2015) Blue whales (Balaenoptera musculus) optimize foraging efficiency by balancing oxygen use and energy gain as a function of prey density. Science Advces 1:e1500469–e1500469.

MacArthur RH, Pianka ER (1966) On optimal use of a patchy environment. The American Naturalist 100:603–609.

Real LA, Levin SA, Brown JH (1991) Part 2: Theoretical advances: the role of theory in the rise of modern ecology. In: Foundations of ecology: classic papers with commentaries.

Samuelson, Paul (1947). Foundations of Economic Analysis. Harvard University Press.

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

Are there picky eaters in the PCFG?

Clara Bird, PhD Student, OSU Department of Fisheries and Wildlife, Geospatial Ecology of Marine Megafauna Lab

As anyone who has ever been, or raised, a picky eater knows, humans have a wide range of food preferences. The diversity of available cuisines is a testament to the fact that we have individual food preferences. While taste is certainly a primary influence, nutritional benefits and accessibility are other major factors that affect our eating choices. But we are not the only species to have food preferences. In cetacean research, it is common to study the prey types consumed by a population as a whole. Narrowing these prey preferences down to the individual level is rare. While the individual component is challenging to study and to incorporate into population models, it is important to consider what the effects of individual foraging specialization might be.

To understand the role and drivers of individual specialization in population ecology, it is important to first understand the concepts of niche variation and partitioning. An animal’s ecological niche describes its role in the ecosystem it inhabits (Hutchinson, 1957). A niche is multidimensional, with dimensions for different environmental conditions and resources that a species requires. One focus of my research pertains to the dimensions of the niche related to foraging. As discussed in a previous blog, niche partitioning occurs when ecological space is shared between competitors through access to resources varies across different dimensions such as prey type, foraging location, and time of day when foraging takes place. Niche partitioning is usually discussed on the scale of different species coexisting in an ecosystem. Pianka’s theory stating that niche partitioning will increase as prey availability decreases uses competing lizard species as the example (Pianka, 1974). Typically, niche partitioning theory considers inter-specific competition (competition between species), but niche partitioning can take place within a species in response to intra-specific competition (competition between individuals of the same species) through individual niche variation.

A species that consumes a multitude of prey types is considered a generalist while one with a specific prey type is considered a specialist. Gray whales are considered generalists (Nerini, 1984). However, we do not know if each individual gray whale is a generalist or if the generalist population is actually composed of individual specialists with different preferences. One way to test for the presence of individual specialization is to compare the niche width of the population to the niche width of each individual (Figure 1, Bolnick et al., 2003).  For example, if a population eats five different types of prey and each individual consumed those prey types, those individuals would be generalists. However, if each individual only consumed one of the prey types, then those individuals would be specialists within a generalist population.

Figure 1. Figure from Bolnick et al. 2003. The thick curve represents the total niche of the population and the thin curves represent individual niches. Note that in both panels the population has the same total niche. In panel A, the individual curves overlap and are all pretty wide. These curves represent individual generalists that make up a generalist population. In panel B, the thin curves are narrower and do not overlap as much as those in panel A. These curves represent individual specialists that make up a generalist population.

If individual specialization is present in a population the natural follow-up question is why? To answer this, we look for common characteristics between the individuals that are similarly specialized. What do all the individuals that feed on the same prey type have in common? Common characterizations that may be found include age, sex, or distinct morphology (such as different beak or body shapes) (Bolnick et al., 2003).

Woo et al. (2008) studied individual specialization in Brünnich’s guillemot, a generalist sea bird species, using diet and tagging data. They found individual specialization in both diet (prey type) and behavior (dive depth, shape, and flight time). Specialization occurred across multiple timescales but was higher over short-time scales. The authors found that it was more common for an individual to specialize in a prey-type/foraging tactic for a few days than for that specialization to continue across years, although a few individuals were specialists for the full 15-year period of the study. Based on reproductive success of the studies birds, the authors concluded that the generalist and specialist strategies were largely equivalent in terms of fitness and survival. The authors searched for common characteristics in the individuals with similar specialization and they found that the differences between sexes or age classes were so small that neither grouping explained the observed individual specialization. This is an interesting result because it suggests that there is some missing attribute, that of the authors did not examine, that might explain why individual specialists were present in the population.

Hoelzel et al. (1989) studied minke whale foraging specialization by observing the foraging behaviors of 23 minke whales over five years from a small boat. They identified two foraging tactics: lunge feeding and bird-associated feeding. Lunge feeding involved lunging up through the water with an open mouth to engulf a group of fish, while bird-associated feeding took advantage of a group of fish being preyed on by sea birds to attack the fish from below while they were already being attacked from above. They found that nine individuals used lunge feeding, and of those nine, six whales used this tactic exclusively. Five of those six whales were observed in at least two years. Seventeen whales were observed using bird-associated feeding, 14 exclusively. Of those 14, eight were observed in at least two years. Interestingly, like Woo et al. (2008), this study did not find any associations between foraging tactic use and sex, age, or size of whale. Through a comparison of dive durations and feeding rates, they hypothesized that lunge feeding was more energetically costly but resulted in more food, while bird-associated feeding was energetically cheaper but had a lower capture rate. This result means that these two strategies might have the similar energetic payoffs.

Both of these studies are examples of questions that I am excited to ask using our data on the PCFG gray whales feeding off the Oregon coast (especially after doing the research for this blog). We have excellent individual-specific data to address questions of specialization because the field teams for  this project always carefully link observed behaviors with individual whale ID.  Using these data, I am curious to find out if the whales in our study group are individual specialists or generalists (or some combination of the two). I am also interested in relating specific tactics to their energetic costs and benefits in order to assess the payoffs of each foraging tactic. I then hope to combine the results of both analyses to assess the payoffs of each individual whale’s strategy.

Figure 2. Example images of two foraging tactics, side swimming (left) and headstanding (right). Images captured under NOAA/NMFS permit #21678.

Studying individual specialization is important for conservation. Consider the earlier example of a generalist population that consumes five prey items but is composed of individual specialists. If the presence of individual specialization is not accounted for in management plans, then regulations may protect certain prey types or foraging tactics/areas of the whales and not others. Such a management plan could be a dangerous outcome for the whale population because only parts of the population would be protected, while other specialists are at risk, thus potentially losing genetic diversity, cultural behaviors, and ecological resilience in the population as a whole. A plan designed to maximize protection for all the specialists would be better for the population because populations with increased ecological resilience are more likely to persist through periods of rapid environmental change. Furthermore, understanding individual specialization could help us better predict how a population might be affected by environmental change. Environmental change does not affect all prey species in the same way. An individual specialization study could help identify which whales might be most affected by predicted environmental changes. Therefore, in addition to being a fascinating and exciting research question, it is important to test for individual specialization in order to improve management and our overall understanding of the PCFG gray whale population.

References

Bolnick, D. I., Svanbäck, R., Fordyce, J. A., Yang, L. H., Davis, J. M., Hulsey, C. D., & Forister, M. L. (2003). The ecology of individuals: Incidence and implications of individual specialization. American Naturalist, 161(1), 1–28. https://doi.org/10.1086/343878

Hoelzel, A. R., Dorsey, E. M., & Stern, S. J. (1989). The foraging specializations of individual minke whales. Animal Behaviour, 38(5), 786–794. https://doi.org/10.1016/S0003-3472(89)80111-3

Hutchinson, G. E. (1957). Concluding Remarks. Cold Spring Harbor Symposia on Quantitative Biology, 22(0), 415–427. https://doi.org/10.1101/sqb.1957.022.01.039

Nerini, M. (1984). A Review of Gray Whale Feeding Ecology. In The Gray Whale: Eschrichtius Robustus (pp. 423–450). Elsevier Inc. https://doi.org/10.1016/B978-0-08-092372-7.50024-8

Pianka, E. R. (1974). Niche Overlap and Diffuse Competition. 71(5), 2141–2145.

Woo, K. J., Elliott, K. H., Davidson, M., Gaston, A. J., & Davoren, G. K. (2008). Individual specialization in diet by a generalist marine predator reflects specialization in foraging behaviour. Journal of Animal Ecology, 77(6), 1082–1091. https://doi.org/10.1111/j.1365-2656.2008.01429.x

New Zealand blue whale research in the time of COVID

By Grace Hancock, Undergraduate Student at Kalamazoo College MI, GEMM Lab Intern (June 2020 to present)

It feels safe to say that everyone’s plans for the summer of 2020 went through a roller coaster of changes due to the pandemic. Instead of the summer research or travel plans that many undergraduate students, including myself, expected, many of us found ourselves at home, quarantining, and unsure of what to do with our time. Although it was unexpected, all that extra time brought me serendipitously to the virtual doorstep of the GEMM Lab. A few zoom calls and many, many emails later I am now lucky to be a part of the New Zealand Blue Whale photo-ID team. Under Leigh’s and Dawn’s guidance, I picked up the photo identification project where they had left it and am helping to advance this project to its next stage.

The skin of a blue whale is covered by distinct markings similar to a unique fingerprint. Thus, these whales can have a variety of markings that we use to identify them, including mottled pigmentation, pock marks (often caused by cookie cutter sharks), blisters, and even holes in the dorsal fins and flukes.

Figure 1. Examples of skin conditions that help in matching demonstrated on a photo of NZBW052 on the 10/9/2015

True blue blog fans may remember that in 2016 Dawn began the very difficult work of creating a photo ID catalog of all the blue whales that the GEMM Lab had encountered during field work in the South Taranaki Bight in New Zealand. Since that post, the catalog has grown and become an incredibly useful tool. When I came to the lab, I received a hard drive containing all the work Dawn had done to-date with the catalog, as well as two years of photos from various whale watching trips in the Hauraki Gulf of New Zealand. The goal of my internship was to integrate these photos into the GEMM catalog Dawn had created and, hopefully, identify some matches of whales between the two datasets.  If there were any matches – and if I found no matches – we would gain information about whale movement patterns and abundance in New Zealand waters.

Before we could dive into this exciting matching work, there was lots of data organization to be done. Most of the photos I analyzed were provided by the Auckland Whale and Dolphin Safari (AWADS), an eco-tourism company that does regular whale watching trips in the Hauraki Gulf, off the North Island of New Zealand. The photos I worked with were taken by people with no connection to the lab and, because of this, were often filled with pictures of seals, birds, and whatever else caught the whale watcher’s eye. This dataset led to hours of sorting, renaming, and removing photos. Next, I evaluated each photo of a whale to determine photo-quality (focus, angle to the camera, lighting) and then I used the high-quality photos where markings are visible to begin the actual matching of the whales.

Figure 2. The fluke of NZBW013 taken on 2/2/2016 with examples of unique nicks and markings that could be used to match

Blue whales are inarguably massive organisms. For this reason, it can be hard to know what part of the whale you’re looking at. To match the photos to the catalog, I found the clearest pictures that included the whale’s dorsal fin. For each whale I tried to find a photo from the left side, the right side, and (if possible) an image of its fluke. I could then compare these photos to the ones organized in the catalog developed by Dawn.

The results from my matching work are not complete yet, but there are a few interesting tidbits that I can share with our readers today. From the photos submitted by AWADS, I was able to identify twenty-two unique individual whales. We are in the process of matching these whales to the catalog and, once this is done, we will know how many of these twenty-two are whales we have seen before and how many are new individuals. One of the most exciting matches I made so far is of a whale known in our catalog as individual NZBW072. Part of what made this whale so exciting was the fact that it is the calf of NZBW031 who was spotted eight times from 2010-2017, in the Hauraki Gulf, off Kaikoura, and in the South Taranaki Bight. As it turns out, NZBW072 took after her mother and has been spotted a shocking nine times from 2010 to 2019, all in the Hauraki Gulf region. Many of the whales in our catalog have only been spotted once, so encountering two whales with this kind of sighting track record that also happen to be related is like hitting the jackpot.

Figure 3. NZBW072 photographed on 11/8/2010 (top photo taken by Rochelle Constantine in the Hauraki Gulf) and on 10/3/2019 (bottom photo taken by the Auckland Whale and Dolphin Safari) with marks circled in red or yellow to highlight the matched features.

Once I finish comparing and matching the rest of these photos, the catalog will be substantially more up-to-date. But that is not where the work stops. More photos of blue whales in New Zealand are frequently being captured, either by whale watchers in the Hauraki Gulf, fellow researchers on the water, keen workers on oil and gas rigs, or the GEMM Lab. Furthermore, the GEMM Lab contributes these catalog photos to the International Whaling Commission (IWC) Southern Hemisphere Blue Whale Catalog, which compiles all photos of blue whales in the Southern Ocean and enables interesting and critical conservation questions to be addressed, like “How many blue whales are there in the Southern Ocean?” Once I complete the matching of these 22 individuals, I will upload and submit them to this IWC collaborative database on behalf of the GEMM Lab. This contribution will expand the global knowledge of these whales and motivates me to continue this important photo ID work. I am so excited to be a part of this effort, through which I have learned important skills like the basics of science communication (through writing this blog post) and attention to detail (from working very closely with the photos I was matching). I know both of these skills, and everything else I have learned from this process, will help me greatly as I begin my career in the next few years. I can tell big things will come from this catalog and I will forever be grateful for the chance I have had to contribute to it.

GEMM Lab 2020: A Year in the Life

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

Despite the trials and tribulations of 2020, the GEMM Lab has persevered and experienced many successes and high points. Join me, perhaps with a holiday beverage of choice in-hand, for a summary of what the lab and its members have achieved this year.

The GEMM Lab celebrated several milestones this year. We were all extremely excited and proud when halfway through the year, in July, GEMM Lab PI, Dr. Leigh Torres, was promoted to Associate Professor and granted indefinite tenure in the Department of Fisheries & Wildlife. Leigh joined the department in 2014 and has since completed 13 research projects, is leading 10 current research projects, has graduated 7 graduate students, and is currently advising 4 PhD students and a postdoctoral scholar. A big hurrah to Leigh, our inspiring and tireless captain at the GEMM Lab helm!!

Leigh isn’t the only GEMM Lab member to have received a new title. In March, Leila successfully defended her PhD thesis entitled “Body condition and hormone assessment of eastern North pacific gray whales (Eschrichtius robustus) and associations to ambient noise” and thus graduated from being a PhD candidate to being Dr. Leila Soledade Lemos. Leila is currently a postdoctoral associate at Florida International University. I (Lisa Hildebrand) defended my Master’s thesis “Tonight’s specials include mysids, amphipods, and more: An examination of the zooplankton prey of Oregon gray whales and its impact on foraging choices and prey selection” just a few weeks ago and now bear the title of Master of Science. I am excited to announce that I won’t be leaving the GEMM Lab anytime soon as I will continue to  work with Leigh as I pursue my PhD. Our final new title recipient is Dawn who at the start of December advanced to PhD candidacy after successfully passing her written comprehensive exams in mid-November and her oral comprehensive exams in early December.

Summer is a busy time in the GEMM Lab, largely because it is the time when gray whales are distributed along our Oregon coast for their feeding season and therefore when both of our gray whale projects (GRANITE, or Gray whale Response to Ambient Noise Informed by Technology and Ecology, and the Port Orford foraging ecology project) collect another year of data. With the COVID-19 pandemic in its early stages in the spring (when we start to prep for our field seasons), it was uncertain whether we would be able to get into the field at all. However, after weeks of drafting up and submitting COVID-19 safety plans and precautions, Leigh was able to get both of our gray whale field seasons approved to go ahead this summer! This task was not easy since both projects require some form of travel and sampling methods that do not always allow for 6-feet of distance between team members. Furthermore, the Port Orford project requires the whole team to live and work out of OSU’s Port Orford Field Station together. Despite the hurdles, both projects had successful field seasons. If you want to hear more about the specifics of the field seasons, check out the field season summary blog.

Gray whales weren’t the only species to grab our attention in the field this year. OPAL (Overlap Predictions about Large whales) had a successful second year with Leigh and MMI faculty research assistant Craig Hayslip taking to the skies in United States Coast Guard helicopters four times a month. The project seeks to identify co-occurrence between whales and fishing effort in Oregon to reduce entanglement risk. Leigh and Craig documented numerous cetacean species including blue, fin, humpback, sperm whales, and killer whales. To help with this work, we are so excited to officially have Solène Derville back in the GEMM Lab as a postdoctoral scholar who will work on statistical models aimed at predicting habitat use and distribution patterns of whales off the Oregon coast. While our wish to physically welcome Solène back to Oregon this year did not quite pan out, we are hopeful that she will make the journey from New Caledonia to Oregon in 2021!

The data collected during the helicopter flights will be complimented by the marine mammal observer data that various members of the GEMM Lab have collected over the last four years aboard NOAA Ship Bell M. Shimada as part of the Northern California Current Ecosystem survey. These surveys typically occur three times a year (February, May, September). Although the pandemic threw a wrench into the May cruise, the September cruise was able to go ahead with Dawn and Clara on-board as the two marine mammal observers. It was a very successful cruise, with abundant marine mammal sightings and good survey conditions. Read more about those cruises in Clara and Dawn’s blogs.

While the GEMM Lab did not undertake any field work in New Zealand this year, Leigh and Dawn did travel there in February to meet with scientific colleagues, representatives of the oil and gas industry, and environmental managers, including the New Zealand Minister of Conservation, the Honorable Eugenie Sage. The trip allowed Leigh and Dawn to present their research on blue whales and discuss management implications. These meetings have been highly beneficial as they shared their latest research and results to assist with the development of a marine mammal sanctuary within the industrial region where their research is conducted.

The GEMM Lab prides itself on having strong outreach components to our research, ensuring that young students (high school and undergraduate) from diverse backgrounds have an opportunity to learn STEM skills. Some outreach opportunities were not possible in 2020, but the GEMM Lab continued our efforts where possible. Clara taught a photogrammetry workshop for the Marine Studies Initiative student club Ocean11, where students were taught how to measure whales from drone images. The success of the workshop (and earlier iterations of it in 2019) led to Clara turning it into a lab for Dr. Renee Albertson’s FW 469 Physiology/Behavior of Marine Megafauna class. As one of the program coordinators for the Fisheries & Wildlife Mentorship Program, I co-hosted an Intro to R & RStudio workshop this fall. Rachel taught a remote intensive science communication workshop during her first term in grad school. Although COVID-19 meant that one-on-one mentorships had to be a little more distant, over the course of the year, the GEMM Lab still supervised a total of 7 students that assisted our work in a variety of ways (field and/or lab work, data analyses, independent projects) on a number of projects going on in the lab.

In a typical year, GEMM Lab members would have undertaken quite a lot more travel, largely to attend conferences. Due to COVID-19, most conferences were either cancelled or held virtually. Leigh gave the plenary talk at the annual State of the Coast Conference, one of the favorite conferences of the GEMM Lab as it brings together scientists, stakeholders, managers, students, and the public to discuss Oregon-centric topics. Dawn gave an oral presentation at the International Marine Conservation Congress. The talk was titled “Wind, green water, and blue whales: Predictive models forecast blue whale distribution in an upwelling system to mitigate industrial impacts” as part of a symposium focused on evidence-based solutions for the management of large marine vertebrate species. Clara presented at the annual Research Advances in Fisheries, Wildlife & Ecology symposium hosted by the graduate student association in the Department of Fisheries & Wildlife. Clara’s talk, which was about her proposed PhD research, was titled “Drone footage reveals patterns of gray whale behavior across space, time, and the individual”.

While our travel may have been reduced this year, the lab certainly has had a prolific year of writing! The 19 new publications in 16 scientific journals include contributions from Leigh (6), Leila (5), Rachael (4), Solène (3), Clara (3), Dawn (2), and Ale (1). Scroll down to the end of the post to see the full list.

We are also very excited about a new addition to the lab. Rachel Kaplan, who is co-advised by Leigh and Dr. Kim Bernard in the College of Earth, Ocean, and Atmospheric Sciences, started her PhD at OSU in the fall. Rachel is one of this year’s recipients of the highly-competitive National Science Foundation’s Graduate Research Fellowship. Receiving the fellowship allowed Rachel to wrap up her job at the Bigelow Laboratory for Ocean Sciences in Maine and move to Oregon. The journey wasn’t easy (Rachel moved in the midst of the pandemic and during the height of the wildfires that raged across the U.S. West Coast) but she made it here safely! For her PhD, Rachel will try to understand how oceanographic factors and prey patches shape the distribution of whales in Oregon waters (with data collected through the OPAL project) to work towards solutions to the high rates of whale entanglements in fishing gear that have occurred on the West Coast since 2014. Welcome Rachel! 

While we persevered through tough times this year and have been lucky to celebrate many accomplishments, nothing prepared us for the shock that we all felt, and are still feeling deeply, about the loss of our fellow GEMM Lab graduate student Alexa Kownacki just over a month ago. Alexa’s optimism, generosity, and kindness were unparalleled, and the hole that she leaves in the lab and in our lives individually is gaping. The lab wrote a collaborative blog about Alexa a few weeks ago and we have created a website in her honor, where we encourage everyone to post photos, tributes or stories about Alexa. It has been so comforting to us to read people’s memories of Alexa that allow us to learn new things about her and remind us of our own memories. Alexa, we think of you every day and we miss you.

Alexa in her element

If you are reading this post, we would like to say thank you for all the support and interest in our work – we really appreciate it! Our blog’s viewership this year (a whopping 25,588 views!) has increased over a seven-fold since its creation in 2015 (3,462 views). We hope you will continue to join us on our journeys in 2021. Until then, stay safe, mask up & happy holidays from the GEMM Lab!

A GEMM Lab Happy Hour Zoom

Publications

Ajó, A. A. F., Hunt, K. E., Giese, A. C., Sironi, M., Uhart, M., Rowntree, V. J., Marón, C. F., Dillon, D., DiMartino, M., & Buck, C. L. (2020). Retrospective analysis of the lifetime endocrine response of southern right whale calves to gull wounding and harassment: A baleen hormone approach. General and Comparative Endocrinology, 296, 113536.

Albert, C., …, Orben, R. A., et al. (2020). Seasonal variation of mercury contamination in Arctic seabirds: a pan-arctic assessment. Science of the Total Environment, 750, 142201.

Barlow, D. R., Bernard, K. S., Escobar-Flores, P., Palacios, D. M., & Torres, L. G. (2020). Links in the trophic chain: modeling functional relationships between in situ oceanography, krill, and blue whale distribution under different oceanographic regimes. Marine Ecology Progress Series642, 207-225.

Baylis, A. M. M., Tierney, M., Orben, R. A., González de la Peña, D., & Brickle, P. (2020). Non-breeding movements of Gentoo penguins at the Falkland Islands. Ibis, doi:10.1111/ibi.12882.

Bird, C., & Bierlich, K.. (2020).  CollatriX: A GUI to collate MorphoMetriX outputs. Journal of Open Source Software5(51), 2328. doi:10.21105/joss10.21105/joss.02328.

Bird, C., Dawn, A. H., Dale, J., & Johnston, D. W. (2020). A Semi-Automated Method for Estimating Adélie Penguin Colony Abundance from a Fusion of Multispectral and Thermal Imagery Collected with Unoccupied Aircraft Systems. Remote Sensing12(22), 3692. doi:10.3390/rs12223692.

Chero, G., Pradel, R., Derville, S., Bonneville, C., Gimenez, O., & Garrigue, C. (2020). Reproductive capacity of an endangered and recovering population of humpback whales in the Southern Hemisphere. Marine Ecology Progress Series, 643, 219-227.

Derville, S.Torres, L. G., Zerbini, A. N., Oremus, M., & Garrigue, C. (2020). Horizontal and vertical movements of humpback whales inform the use of critical pelagic habitats in the western South Pacific. Scientific Reports, 10, 4871.

DiGiacomo, A. E., Bird, C., Pan, V. G., Dobroski, K., Atkins-Davis, C., Johnston, D. W., & Ridge, J. T.. (2020). Modeling Salt Marsh Vegetation Height Using Unoccupied Aircraft Systems and Structure from Motion. Remote Sensing12(14), 2333. doi:10.3390/rs12142333.

Garrigue, C., Derville, S., Bonneville, C., Baker, C. S., Cheeseman, T., Millet, L., Paton, D., & Steel, D. (2020). Searching for humpback whales in a historical whaling hotspot of the Coral Sea, South Pacific. Endangered Species Research, 42, 67-82.

Hauser-Davis, R. A., Monteiro, F., Chávez da Rocha, R. C., Lemos, L., Duarte Cardoso, M., & Siciliano, S. (2020). Titanium as a contaminant of emerging concern in the aquatic environment and the current knowledge gap regarding seabird contamination. Ornithologia, 11, 7-15.

Hindell, M. A., … Torres, L. G., et al. (2020). Tracking of marine predators to protect Southern Ocean ecosystems. Nature, 580(7801), 87-92.

Jones, K. A., Baylis, A. M. M., Orben, R. A., Ratcliffe, N., Votier, S. C., Newton, J., & Staniland, I. J. (2020). Stable isotope values in South American fur seal pup whiskers as proxies of year-round maternal foraging ecology. Marine Biology, 167(10), 1-11.

Kroeger, C. E., Crocker, D. E., Orben, R. A., Thompson, D. R., Torres, L. G., Sagar, P. M., Sztukowski, L. A., Andriese, T., Costa, D. P., & Shaffer, S. A. (2020). Similar foraging energetics of two sympatric albatrosses despite contrasting life histories and wind-mediated foraging strategies. Journal of Experimental Biology, 223, jeb228585.

Lemos, L. S., Olsen, A., Smith, A., Chandler, T. E., Larson, S., Hunt, K., & Torres, L. G. (2020). Assessment of fecal steroid and thyroid hormone metabolites in eastern North Pacific gray whales. Conservation Physiology, 8, coaa110.

Monteiro, F., Lemos, L. S., et al. (2020). Total and subcellular Ti distribution and detoxification processes in Pontoporia blainvillei and Steno bredanensis dolphins from southeastern Brazil. Marine Pollution Bulletin, 153, 110975.

Quinete, N., Hauser-Davis, R. A., Lemos, L. S., Moura, J. F., Siciliano, S., & Gardinali P. R. (2020). Occurrence and tissue distribution of organochlorinated compounds and polycyclic aromatic hydrocarbons in Magellanic penguins (Spheniscus magellanicus) from the southeastern coast of Brazil. Science of the Total Environment, 749, 141473.

Soledade Lemos, L., Burnett, J. D., Chandler, T. E., Sumich, J. L., & Torres, L. G. (2020). Intra- and inter-annual variation in gray whale body condition on a foraging ground. Ecosphere, 11(4), e03094.

Torres, L. G., Barlow, D. R.Chandler, T. E., & Burnett, J. D. (2020). Insight into the kinematics of blue whale surface foraging through drone observations and prey data. PeerJ8, e8906.