With the changing of the season, gray whales are starting their southbound migration that will end in the lagoons off the Baja California Mexico. The migration of the gray whale is the longest migration of any mammal—the round trip totals ~10,000 miles (Pike, 1962)!
Like these gray whales, I am also undertaking my own “migration” as I leave Newport to start my post-Master’s journey. However, my migration will be a little shorter than the gray whale’s journey—only ~3,000 miles—as I head back to the east coast. As I talked about in my previous blog, I have finished my thesis studying the energetics of gray whale foraging behaviors and I attended my commencement ceremony at the University of British Columbia last Wednesday. As my time with the GEMM Lab comes to a close, I want to take some time to reflect on my time in Newport.
Many depictions of scientists show them working in isolation but in my time with the GEMM Lab I got to fully experience the collaborative nature of science. My thesis was a part of the GEMM Lab’s Gray whale Response to Ambient Noise Informed by Technology and Ecology (GRANITE) project and I worked closely with the GRANITE team to help achieve the project’s research goals. The GRANITE team has annual meetings where team members give updates on their contributions to the project and flush out ideas in a series of very busy days. I found these collaborative meetings very helpful to ensure that I was keeping the big picture of the gray whale study system in mind while working with the energetics data I explored for my thesis. The collaborative nature of the GRANITE project provided the opportunity to learn from people that have a different skill set from my own and expose me to many different types of analysis.
Outside of the amazing science opportunities, I have thoroughly enjoyed the privilege of exploring Newport and the Oregon coast. I was lucky enough to find lots of agates and enjoyed consistently spotting gray whale blows on my many beach walks. I experienced so many breathtaking views from hikes (God’s thumb was my personal favorite). I got to attend an Oregon State Beavers football game where we crushed Stanford! And most of all, I am so thankful for all the friends I’ve made in my time here. These warm memories, and the knowledge that I can always come back, will help make it a little easier to start my migration away from Newport.
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Pike, G. C. (1962). Migration and feeding of the gray whale (Eschrichtius gibbosus). Journal of the Fisheries Research Board of Canada, 19(5), 815–838. https://doi.org/10.1139/f62-051
As you may remember, last year’s field season was a remarkable summer for our team. We were pleasantly surprised to find an increased number of whales in our study area compared to previous years and were even more excited that many of them were old friends. As we started this field season, we were all curious to know if this year would be a repeat. And it’s my pleasure to report that this season was even better!
We started the season with an exciting day (6 known whales! see Lisa’s blog) and the excitement (and whales) just kept coming. This season we saw 71 individual whales across 215 sightings! Of those 71, 44 were whales we saw last year, and 10 were new to our catalog, meaning that we saw 17 whales this season that we had not seen in at least two years! There is something extra special about seeing a whale we have not seen in a while because it means that they are still alive, and the sighting gives us valuable data to continue studying health and survival. Another cool note is that 7 of our 12 new whales from last year came back this year, indicating recruitment to our study region.
Included in that group of 7 whales are the two calves from last year! Again, indicating good recruitment of new whales to our study area. We saw both Lunita and Manta (previously nick-named ‘Roly-poly’) throughout this season and we were always happy to see them back in our area and feeding on their own.
We had an especially remarkable encounter with Lunita at the end of this season when we found this whale surface feeding on porcelain crab larvae (video 1)! This is a behavior that we rarely observe, and we’ve never seen a juvenile whale use this behavior before, inspiring questions around how Lunita knew how to perform this behavior.
Not only did we resight our one-year-old friends, but we found two new calves born to well-known mature females (Clouds and Spotlight). We had previously documented Clouds with a calf (Cheetah) in 2016 so it was exciting to see her with a new calf and to meet Cheetah’s sibling! Cheetah has become one of our regulars so we’re curious to see if this new calf joins the regular crew as well. We’re also hoping that Spotlight’s calf will stick around; and we’re optimistic since we observed it feeding alone later in the season.
Of course, 71 whales means heaps of data! We spent 226 hours on the water, conducted 132 drone flights (a record!), and collected 61 fecal samples! Those 132 flights were over 64 individual whales, with Casper and Pacman tying for “best whale to fly over” with 10 flights each. We collected 61 fecal samples from 26 individual whales with a three-way tie for “best pooper” between Hummingbird, Scarlett, and Zorro with 6 fecal samples each. And we continued to collect valuable prey and habitat data through 80 GoPro drops and 79 zooplankton net tows.
And if you were about to ask, “but what about tagging?!”, fear not! We continued our suction cup tagging effort with a successful window in July where we were joined by collaborators John Calambokidis from Cascadia Research Collective and Dave Cade from Hopkins Marine Station and deployed four suction-cup tags.
It’s hard to believe all the work we’ve accomplished in the past five months, and I continue to be honored and proud to be on this incredible team. But as this season has come to a close, I have found myself reflecting on something else. Learning. Over the past several years we have learned so much about not only these whales in our study system but about how to conduct field work. And while learning is continuous, this season in particular has felt like an exciting time for both. In the past year our group has published work showing that we can detect pregnancy in gray whales using fecal samples and drone imagery (Fernandez Ajó et al., 2023), that PCFG gray whales are shorter and smaller than ENP whales (Bierlich et al., 2023), and that gray whales are consuming high levels of microplastics (Torres et al., 2023). We also have several manuscripts in review focused on our behavior work from drones and tags. While this information does not directly affect our field work, it does mean that while we’re observing these whales live, we better understand what we’re observing and we can come up with more specific, in-depth questions based on this foundation of knowledge that we’re building. I have enjoyed seeing our questions evolve each year based on our increasing knowledge and I know that our collaborative, inquisitive chats on the boat will only continue inspiring more exciting research.
On top of our gray whale knowledge, we have also learned so much about field work. When I think back to the early days compared to now, there is a stark difference in our knowledge and our confidence. We do a lot on our little boat! And so many steps that we once relied on written lists to remember to do are now just engrained in our minds and bodies. From loading the boat, to setting up at the dock, to the go pro drops, fecal collections, drone operations, photo taking, and photo ID, our team has become quite the well-oiled machine. We were also given the opportunity to reflect on everything we’ve learned over the past years when it was our turn to train our new team member, Nat! Nat is a new PhD student in the GEMM lab who is joining team GRANITE. Teaching her all the ins and outs of our fieldwork really emphasized how much we ourselves have learned.
On a personal note, this was my third season as a drone pilot, and honestly, I was pleasantly surprised by my experience this season. Since I started piloting, I have experienced pretty intense nerves every time I’ve flown the drone. From stress dreams, to mild nausea, and an elevated heart rate, flying the drone was something that I didn’t necessarily look forward to. Don’t get me wrong – it’s incredibly valuable data and a privilege to watch the whales from a bird’s eye view in real time. But the responsibility of collecting good data, while keeping the drone and my team members safe was something that I felt viscerally. And while I gained confidence with every flight, the nerves were still as present as ever and I was starting to accept that I would never be totally comfortable as a pilot. Until this season, when the nerves finally cleared, and piloting became as innate as all the other field work components. While there are still some stressful moments, the nerves don’t come roaring back. I have finally gone through enough stressful situations to not be fazed by new ones. And while I am fully aware that this is just how learning works, I write this reflection as a reminder to myself and anyone going through the process of learning any new skill to push through that fear. Remember there can be a disconnect between the time when you know how to do something well, or well-enough, and the time when you feel comfortable doing it. I am just as proud of myself for persevering as I am of the team for collecting so much incredible data. And as I look ahead to my next scary challenge (finishing my PhD!), this is a feeling that I am trying to hold on to.
Stay tuned for updates from team GRANITE!
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Bierlich, K. C., Kane, A., Hildebrand, L., Bird, C. N., Fernandez Ajo, A., Stewart, J. D., Hewitt, J., Hildebrand, I., Sumich, J., & Torres, L. G. (2023). Downsized: Gray whales using an alternative foraging ground have smaller morphology. Biology Letters, 19(8), 20230043. https://doi.org/10.1098/rsbl.2023.0043
Fernandez Ajó, A., Pirotta, E., Bierlich, K. C., Hildebrand, L., Bird, C. N., Hunt, K. E., Buck, C. L., New, L., Dillon, D., & Torres, L. G. (2023). Assessment of a non-invasive approach to pregnancy diagnosis in gray whales through drone-based photogrammetry and faecal hormone analysis. Royal Society Open Science, 10(7), 230452. https://doi.org/10.1098/rsos.230452
Torres, L. G., Brander, S. M., Parker, J. I., Bloom, E. M., Norman, R., Van Brocklin, J. E., Lasdin, K. S., & Hildebrand, L. (2023). Zoop to poop: Assessment of microparticle loads in gray whale zooplankton prey and fecal matter reveal high daily consumption rates. Frontiers in Marine Science, 10. https://www.frontiersin.org/articles/10.3389/fmars.2023.1201078
The winds are consistently (and sometimes aggressively) blowing from the north here on the Oregon coast, which can only mean one thing – summer has arrived! Since mid-May, the GRANITE (Gray whale Response to Ambient Noise Informed by Technology and Ecology) team has been looking for good weather windows to survey for gray whales and we have managed to get five great field work days already. In today’s blog post, I am going to share what (and who) we have seen so far.
On our first day of the field season, PI Leigh Torres, postdoc KC Bierlich and myself, were joined by a special guest: Dr. Andy Read. Andy is the director of the Duke University Marine Lab, where he also runs his own lab, which focuses on conservation biology and ecology of marine vertebrates. Andy was visiting the Hatfield Marine Science Center as part of the Lavern Weber Visiting Scientist program and was hosted here by Leigh. For those of you that do not know, Andy was Leigh’s graduate school advisor at Duke where she completed her Master’s and doctoral degrees. It felt very special to have Andy on board our RHIB Ruby for the day and to introduce him to some friends of ours. The first whale we encountered that day was “Pacman”. While we are always excited to re-sight an individual that we know, this sighting was especially mind-blowing given the fact that Leigh had “just” seen Pacman approximately two months earlier in Guerrero Negro, one of the gray whale breeding lagoons in Mexico (read this blog about Leigh and Clara’s pilot project there). Aside from Pacman, we saw five other individuals, all of which we had seen during last year’s field season.
Since that first day on the water, we have conducted field work on four additional days and so far, we have only encountered known individuals in our catalog. This fact is exciting because it highlights the strong site fidelity that Pacific Coast Feeding Group (PCFG) gray whales have to areas within their feeding range. In fact, I am examining the residency and space use of each individual whale we have observed in our GRANITE study for one of my PhD chapters to better understand the level of fidelity individuals have to the central Oregon coast. Furthermore, this site fidelity underpins the unique, replicate data set on individual gray whale health and ecology that the GRANITE project has been able to progressively build over the years. So far during this field season in 2023, we have seen 13 unique individuals, flown the drone over 10 of them and collected four fecal samples from two, which represent critical data points from early on in the feeding season.
Our sightings this year have not only highlighted the high site fidelity of whales to our study area but have also demonstrated the potential for internal recruitment of calves born to “PCFG mothers” into the PCFG. Recruitment to a population can occur in two ways: externally (individuals immigrate into a population from another population) or internally (calves born to females that are part of the population return to, or stay, within their mothers’ population). Three of the whales we have seen so far this year are documented calves from females that are known to consistently use the PCFG range, including our central Oregon coast study area. In fact, we documented one of these calves, “Lunita”, just last year with her mother (see Clara’s recap of the 2022 field season blog for more about Lunita). The average calf survival estimate between 1997-2017 for the PCFG was 0.55 (Calambokidis et al. 2019), though it varied annually and widely (range: 0.34-0.94). Considering that there have been years with calf survival estimates as low as ~30%, it is therefore all the more exciting when we re-sight a documented calf, alive and well!
We have also been collecting data on the habitat and prey in our study system by deploying our paired GoPro/RBR sensor system. We use the GoPro to monitor the benthic substrate type and relative prey densities in areas where whales are feeding. The RBR sensor collects high-frequency, in-situ dissolved oxygen and temperature data, enabling us to relate environmental metrics to relative prey measurements. Furthermore, we also collect zooplankton samples with a net to assess prey community and quality. On our five field work days this year, we have predominantly collected mysid shrimp, including gravid (a.k.a. pregnant) individuals, however we have also caught some Dungeness and porcelain crab larvae. The GEMM Lab is also continuing our collaboration with Dr. Susanne Brander’s lab at OSU and her PhD student Lauren Kashiwabara, who plan on conducting microplastic lab experiments on wild-caught mysid shrimp. Their plan is to investigate the growth rates of mysid shrimp under different temperature, dissolved oxygen, and microplastic load conditions. However, before they can begin their experiments, they need to successfully culture the mysids in the lab, which is why we collect samples for them to use as their ‘starter culture’. Stay tuned to hear more about this project as it develops!
So, all in all, it has been an incredibly successful start to our field season, marked by the return of many familiar flukes and flanks! We are excited to continue collecting rock solid GRANITE data this summer to increase our efforts to understand gray whale ecology and physiology.
Calambokidis, J., Laake, J., and Perez, A. (2019). Updated analyses of abundance and population structure of seasonal gray whales in the Pacific Northwest, 1996-2017. IWC, SC/A17/GW/05 for the Workshop on the Status of North Pacific Gray Whales. La Jolla: IWC.
By Charles Nye, graduate student, OSU Department of Fisheries, Wildlife, & Conservation Sciences, Cetacean Conservation and Genomics Laboratory
Let’s consider how much stuff organisms shed daily. If you walk down a hallway, you’ll leave a microscopic trail of skin cells, evaporated sweat, and even more material if you so happen to sneeze or cough (as we’ve all learned). The residency of these bits and pieces in a given environment is on the order of days, give or take (Collins et al. 2018). These days, we can extract, amplify, and sequence DNA from leftover organismal material in environments (environmental DNA; eDNA), stomach contents (dietary DNA, dDNA), and other sources (Sousa et al. 2019; Chavez et al. 2021).
You might be familiar with genetic barcoding, where scientists are able to use documented and annotated pieces of a genome to identify a piece of DNA down to a species. Think of these as genetic fingerprints from a crime scene where all (described) species on Earth are prime suspects. With advancements in computing technology, we can barcode many species at the same time—a process known as metabarcoding. In short, you can now do an ecosystem-wide biodiversity survey without even needing to see your species of interest (Ficetola et al. 2008; Chavez et al. 2021).
(Before you ask: yes, people have tried sampling Loch Ness and came up with not a single strand of plesiosaur DNA (University of Otago, 2019).)
I received my crash course on metabarcoding when I was employed at the Monterey Bay Aquarium Research Institute (MBARI), right before grad school. There, I was employed to help refine eDNA survey field and laboratory methods (in addition to some cool robot stuff). Here at OSU, I use metabarcoding to research whale ecology, detection, and even a little bit of forensics work. Cetacean species (or evidence thereof) I’ve worked on include North Atlantic right whales (Eubalaena glacialis), killer whales (Orcinus spp.), and gray whales (Eschrichtius robustus).
Long-time readers of the GEMM Lab Blog are probably quite knowledgeable about the summertime grays—the Pacific Coast Feeding Group (PCFG). All of us here at OSU’s Marine Mammal Institute (MMI) are keenly interested in understanding why these whales hang out in the Pacific Northwest during the summer months and what sets them apart from the rest of the Eastern North Pacific gray whale population. What interests me? Well, I want to double-check what they’re eating—genetically.
“What does my study species eat?” is a straightforward but underappreciated question. It’s also deceptively difficult to address. What if your species live somewhere remote or relatively inaccessible? You can imagine this is a common logistical issue for most research in marine sciences. How many observations do you need to make to account for seasonal or annual changes in prey availability? Do all individuals in your study population eat the same thing? I certainly like to mix and match my diet.
Gray whale foraging ecology has been studied comprehensively over the last several decades, including an in-depth stomach content evaluation by Mary Nerini in 1984 and GEMMer Lisa Hildebrand’s MSc research. PCFG whales seem to prefer shrimpy little creatures called mysids, along with Dungeness crab (Cancer magister) larvae, during their stay in the Pacific Northwest (PNW), most notably the mysid Neomysis rayii (Guerrero 1989; Hildebrand et al. 2021). Indeed, the average energetic values of common suspected prey species in PNW waters rival the caloric richness of Arctic amphipods (Hildebrand et al. 2021). However, despite our wealth of visual foraging observations, metabarcoding may add an additional layer of resolution. For example, the ocean sunfish (Mola mola) was believed to exclusively forage on gelatinous zooplankton, but a metabarcoding approach revealed a much higher diversity of prey items, including other bony fishes and arthropods (Sousa et al. 2016).
Given all this exposition, you may be wondering: “Charles—how do you intend on getting dDNA from gray whales? Are you going to cut them open?”
No. I’m going to extract DNA from their poop.
Well, actually, I’ve been doing that for the last two years. My lab (Cetacean Conservation and Genomics Laboratory, CCGL) and GEMM Lab have been collaborating to make lemonade out of, er…whale poop. An archive of gray whale fecal samples (with ongoing collections every field season) originally collected for hormone analyses presented itself with new life—the genomics kind. In addition to community-level data, we are also able to recover informative DNA from the gray whales, including sex ID from “depositing” individuals, though the recovery rate isn’t perfect.
Because the GEMM Lab/MMI can non-invasively collect multiple samples from the same individuals over time, dDNA metabarcoding is a great way to repeatedly evaluate the diets of the PCFG, just shy of being at the right place at the right time with a GoPro or drone to witness a feeding event. While we can get stomach contents and even usable dDNA from a naturally deceased whale, those data may not be ideal. How representative a stranded whale is of the population is dependent on the cause of death; an emaciated or critically injured individual, for example, is a strong outlier.
Here’s a snapshot of progress to date for this dDNA metabarcoding project. I pulled out twenty random samples from my much larger working dataset (n = 82) for illustrative purposes (and legibility). After some bioinformatic wizardry, we can use a presence/absence approach to get an empirical glimpse at what passes through a PCFG gray whale. While I am able to recover species-level information, using higher-level taxonomic rankings summarizes the dataset in a cleaner fashion (and also, not every identifiable sequence resolves to species).
The title of most commonly observed prey taxa belongs to our friends, the mysids (Mysidae). Surprisingly, crabs and amphipods are not as common in this dataset, instead losing to krill (Euphausiidae) and olive snails (Olividae). The latter has been found in association with gray whale foraging grounds but not documented in a prey study (Jenkinson 2001). We also get an appreciable amount of interference from non-prey taxa, most notably barnacles (Balanidae), with an honorable mention to hydrozoans (Clytiidae, Corynidae). While easy to dismiss as background environmental DNA, as gray whales do forage at the benthos, these taxa were physically present and identifiable in Nerini’s (1984) gray whale stomach content evaluation.
So—can we conclude that barnacles and hydrozoans are an important part of a gray whale’s diet, as much as mysids? From decades of previous observations, we might say…probably not. Gray whales are actively targeting patches of crabby, shrimpy zooplankton things, and even employ novel foraging strategies to do so (Newell & Cowles 2006; Torres et al. 2018). However, the sheer diversity of consumed species does present additional dimensionality to our understanding of gray whale ecology.
The whales are eating these ancillary organisms, whether they intend to or not, and this probably does influence population dynamics, recruitment, and succession in these nearshore benthic habitats. After all, the shallow pits that gray whales leave behind post-feeding provide a commensal trophic link with other predatory taxa, including seabirds and groundfish (Oliver & Slattery 1985). Perhaps the consumption of these collateral species affects gray whale energetics and reflects on their “performance”?
I hope to address all of this and more in some capacity with my published work and graduate chapters. I’m confident to declare that we can document diet composition of PCFG whales using dDNA metabarcoding, but what comes next is where one can get lost in the sea(weeds). How does the diet of individuals compare to one another? What about at differing time points? Age groups? How many calories are in a barnacle? No need to fret—this is where the fun begins!
Chavez F, Min M, Pitz K, Truelove N, Baker J, LaScala-Grunewald D, Blum M, Walz K,
Nye C, Djurhuus A, et al. 2021. Observing Life in the Sea Using Environmental
DNA Oceanog. 34(2):102–119. doi:10.5670/oceanog.2021.218.
By Morgan O’Rourke-Liggett, Master’s Student, Oregon State University, Department of Fisheries, Wildlife, and Conservation Sciences, Geospatial Ecology of Marine Megafauna Lab
Avid readers of the GEMM Lab blog and other scientists are familiar with the incredible amounts of data collected in the field and the informative figures displayed in our publications and posters. Some of the more time-consuming and tedious work hardly gets talked about because it’s the in-between stage of science and other fields. For this blog, I am highlighting some of the behind-the-scenes work that is the subject of my capstone project within the GRANITE project.
For those unfamiliar with the GRANITE project, this multifaceted and non-invasive research project evaluates how gray whales respond to chronic ambient and acute noise to inform regulatory decisions on noise thresholds (Figure 1). This project generates considerable data, often stored in separate Excel files. While this doesn’t immediately cause an issue, ongoing research projects like GRANITE and other long-term monitoring programs often need to refer to this data. Still, when scattered into separate long Excel files, it can make certain forms of analysis difficult and time-consuming. It requires considerable attention to detail, persistence, and acceptance of monotony. Today’s blog will dive into the not-so-glamorous side of science…data management and standardization!
Of the plethora of data collected from the GRANITE project, I work with the GPS trackline data from the R/V Ruby, environmental data recorded on the boat, gray whale sightings data, and survey summaries for each field day. These come to me as individual yearly spreadsheets, ranging from thirty entries to several thousand. The first goal with this data is to create a standardized survey effort conditions table. The second goal is to determine the survey distance from the trackline, using the visibility for each segment, and calculate the actual area surveyed for the segment and day. This blog doesn’t go into how the area is calculated. Still, all these steps are the foundation for finding that information so the survey area can be calculated.
The first step requires a quick run-through of the sighting data to ensure all dates are within the designated survey area by examining the sighting code. After the date is a three-letter code representing a different starting location for the survey, such as npo for Newport and dep for Depoe Bay. If any code doesn’t match the designated codes for the survey extent, those are hidden, so they are not used in the new table. From there, filling in the table begins (Figure 2).
Segments for each survey day were determined based on when the trackline data changed from transit to the sighting code (i.e., 190829_1 for August 29th, 2019, sighting 1). Transit indicated the research vessel was traveling along the coast, and crew members were surveying the area for whales. Each survey day’s GPS trackline and segment information were copied and saved into separate Excel workbook files. A specific R code would convert those files into NAD 1983 UTM Zone 10N northing and easting coordinates.
Those segments are uploaded into an ArcGIS database and mapped using the same UTM projection. The northing and easting points are imported into ArcGIS Pro as XY tables. Using various geoprocessing and editing tools, each segmented trackline for the day is created, and each line is split wherever there was trackline overlap or U shape in the trackline that causes the observation area to overlap. This splitting ensures the visibility buffer accounts for the overlap (Figure 3).
Once the segment lines are created in ArcGIS, the survey area map (Figure 4) is used alongside the ArcGIS display to determine the start and end locations. An essential part of the standardization process is using the annotated locations in Figure 4 instead of the names on the basemap for the location start and endpoints. This consistency with the survey area map is both for tracking the locations through time and for the crew on the research vessel to recognize the locations. The step assists with interpreting the survey notes for conditions at the different segments. The time starts and ends, and the latitude and longitude start and end are taken from the trackline data.
The sighting data includes the number of whales sighted, Beaufort Sea State, and swell height for the locations where whales were spotted. The environmental data from the sighting data is used as a guide when filling in the rest of the values along the trackline. When data, such as wind speed, swell height, or survey condition, is not explicitly given, matrices have been developed in collaboration with Dr. Leigh Torres to fill in the gaps in the data. These matrices and protocols for filling in the final conditions log are important tools for standardizing the environmental and condition data.
The final product for the survey conditions table is the output of all the code and matrices (Figure 5). The creation of this table will allow for accurate calculation of survey effort on each day, month, and year of the GRANITE project. This effort data is critical to evaluate trends in whale distribution, habitat use, and exposure to disturbances or threats.
The process of completing the table can be a very monotonous task, and there are several chances for the data to get misplaced or missed entirely. Attention to detail is a critical aspect of this project. Standardizing the GRANITE data is essential because it allows for consistency over the years and across platforms. In describing this aspect of my project, I mentioned three different computer programs using the same data. This behind-the-scenes work of creating and maintaining data standardization is critical for all projects, especially long-term research such as the GRANITE project.
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Since its start, the GEMM Lab has been interested in the effect of vessel disturbance on whales. From former student Florence’s masters project to Leila’s PhD work, this research has shown that gray whales on their foraging grounds have a behavioral response to vessel presence (Sullivan & Torres, 2018) and a physiological response to vessel noise (Lemos et al., 2022). Presently, our GRANITE project is continuing to investigate the effect of ambient noise on gray whales, with an emphasis on understanding how these effects might scale up to impact the population as a whole (Image 1).
To date, all this work has been focused on gray whales feeding off the coast of Oregon, but I’m excited to share that this is about to change! In just a few weeks, Leigh and I will be heading south for a pilot study looking at the effects of whale watching vessels on gray whale mom/calf pairs in the nursing lagoons of Baja California, Mexico.
We are collaborating with a Fernanda Urrutia Osorio, a PhD candidate at Scripps Institute of Oceanography, to spend a week conducting fieldwork in one of the nursing lagoons. For this project we will be collecting drone footage of mom/calf pairs in both the presence and absence of whale watching vessels. Our goal is to see if we detect any differences in behavior when there are vessels around versus when there are not. Tourism regulations only allow the whale watching vessels to be on the water during specific hours, so we are hoping to use this regulated pattern of vessel presence and absence as a sort of experiment.
The lagoons are a crucial place for mom/calf pairs, this is where calves nurse and grow before migration, and nursing is energetically costly for moms. So, it is important to study disturbance responses in this habitat since any change in behavior caused by vessels could affect both the calf’s energy intake and the mom’s energy expenditure. While this hasn’t yet been investigated for gray whales in the lagoons, similar studies have been carried out on other species in their nursing grounds.
We can use these past studies as blueprints for both data collection and processing. Disturbance studies such as these look for a wide variety of behavioral responses. These include (1) changes in activity budgets, meaning a change in the proportion of time spent in a behavior state, (2) changes in respiration rate, which would reflect a change in energy expenditure, (3) changes in path, which would indicate avoidance, (4) changes in inter-individual distance, and (5) changes in vocalizations. While it’s not necessarily possible to record all of these responses, a meta-analysis of research on the impact of whale watching vessels found that the most common responses were increases in the proportion of time spent travelling (a change in activity budget) and increased deviation in path, indicating an avoidance response (Senigaglia et al., 2016).
One of the key phrases in all these possible behavioral responses is “change in ___”. Without control data collected in the absence of whale watching vessels, it impossible to detect a difference. Some studies have conducted controlled exposures, using approaches with the research vessel as proxies for the whale watchers (Arranz et al., 2021; Sprogis et al., 2020), while others use the whale watching operators’ daily schedule and plan their data collection schedule around that (Sprogis et al., 2023). Just as ours will, all these studies collected data using drones to record whale behavior and made sure to collect footage before, during, and after exposure to the vessel(s).
One study focused on humpback mom/calf pairs found a decrease in the proportion of time spent resting and an increase in both respiration rate and swim speed during the exposure (Sprogis et al., 2020). Similarly, a study focused on short-finned pilot whale mom/calf pairs found a decrease in the mom’s resting time and the calf’s nursing time (Arranz et al., 2021). And, Sprogis et al.’s study of Southern right whales found a decrease in resting behavior after the exposure, suggesting that the vessels’ affect lasted past their departure (Sprogis et al., 2023, Image 3). It is interesting that while these studies found changes in different response metrics, a common trend is that all these changes suggest an increase in energy expenditure caused by the disturbance.
However, it is important to note that these studies focused on short term responses. Long term impacts have not been thoroughly estimated yet. These studies provide many valuable insights, not only into the response of whales to whale watching, but also a look at the various methods used. As we prepare for our fieldwork, it’s useful to learn how other researchers have approached similar projects.
I want to note that I don’t write this blog intending to condemn whale watching. I fully appreciate that offering the opportunity to view and interact with these incredible creatures is valuable. After all, it is one of the best parts of my job. But hopefully these disturbance studies can inform better regulations, such as minimum approach distances or maximum engine noise levels.
As these studies have done, our first step will be to establish an ethogram of behaviors (our list of defined behaviors that we will identify in the footage) using our pilot data. We can also record respiration and track line data. An additional response that I’m excited to add is the distance between the mom and her calf. Former GEMM Lab NSF REU intern Celest will be rejoining us to process the footage using the AI method she developed last summer (Image 4). As described in her blog, this method tracks a mom and calf pair across the video frames, and allows us to extract the distance between them. We look forward to adding this metric to the list and seeing what we can glean from the results.
While we are just getting started, I am excited to see what we can learn about these whales and how best to study them. Stay tuned for updates from Baja!
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Arranz, P., Glarou, M., & Sprogis, K. R. (2021). Decreased resting and nursing in short-finned pilot whales when exposed to louder petrol engine noise of a hybrid whale-watch vessel. Scientific Reports, 11(1), 21195. https://doi.org/10.1038/s41598-021-00487-0
Lemos, L. S., Haxel, J. H., Olsen, A., Burnett, J. D., Smith, A., Chandler, T. E., Nieukirk, S. L., Larson, S. E., Hunt, K. E., & Torres, L. G. (2022). Effects of vessel traffic and ocean noise on gray whale stress hormones. Scientific Reports, 12(1), Article 1. https://doi.org/10.1038/s41598-022-14510-5
Senigaglia, V., Christiansen, F., Bejder, L., Gendron, D., Lundquist, D., Noren, D., Schaffar, A., Smith, J., Williams, R., Martinez, E., Stockin, K., & Lusseau, D. (2016). Meta-analyses of whale-watching impact studies: Comparisons of cetacean responses to disturbance. Marine Ecology Progress Series, 542, 251–263. https://doi.org/10.3354/meps11497
Sprogis, K. R., Holman, D., Arranz, P., & Christiansen, F. (2023). Effects of whale-watching activities on southern right whales in Encounter Bay, South Australia. Marine Policy, 150, 105525. https://doi.org/10.1016/j.marpol.2023.105525
Sprogis, K. R., Videsen, S., & Madsen, P. T. (2020). Vessel noise levels drive behavioural responses of humpback whales with implications for whale-watching. ELife, 9, e56760. https://doi.org/10.7554/eLife.56760
Sullivan, F. A., & Torres, L. G. (2018). Assessment of vessel disturbance to gray whales to inform sustainable ecotourism. Journal of Wildlife Management, 82(5), 896–905. https://doi.org/10.1002/jwmg.21462
After my graduation, since I have tropical blood running in my veins, I literally crossed the entire country in search of blue and sunny skies, warm weather and ocean, and of course different opportunities to continue doing research involving stressors and physiological responses in marine mammals and other marine organisms. It didn’t take me long to start a position as a postdoctoral associate with the Institute of Environment at Florida International University. I have learned so much in these past two years while mainly working with toxicology and stress biomarkers in a wide range of marine individuals including corals, oysters, fish, dolphins, and now manatees. I have started a new chapter in my life, and I am very eager to see where it takes me.
These three chapters were “relatively easy” to publish compared to my fourth chapter, which had a long and somewhat stressful process (which is funny as I am trying to report stress responses in gray whales). Changes between journals, titles, analyses, content, and focus had to be made over the past year and a half for it to be accepted for publication. However, I believe that it was worth the extra work and invested time as our research definitely became more robust after all of the feedback provided by the reviewers. This chapter, now entitled “Effects of vessel traffic and ocean noise on gray whale stress hormones” was finally published earlier this month at the Nature Scientific Reports journal, and I’ll describe it further below.
Increased human activities in the last decades have altered the marine ecosystem, leaving us with a noisier, warmer, and more contaminated ocean. The noise caused by the dramatic increase in commercial and recreational shipping and vessel traffic1-3 has been associated with negative impacts on marine wildlife populations4,5. This is especially true for baleen whales, whose frequencies primarily used for communication, navigation, and foraging6,7 are “masked” by the noise generated by this watercraft. Several studies have reported alterations in marine mammal behavioral states8-11, increased group cohesion12-14, and displacement8,15 due to this disturbance, however, just a few studies have considered their physiological responses. Examples of physiological responses reported in marine mammals include altered metabolic rate15,16 and variations in stress-related hormone (i.e., glucocorticoids) concentrations relative to vessel abundance and ambient noise17,18. Based on this context and on the scarcity of such assessments, we attempted to determine the effects of vessel traffic and associated ambient noise, as well as potential confounding variables (i.e., body condition, age, sex, time), on gray whale fecal glucocorticoid concentrations.
In addition to the data used in my previous three chapters collected from gray whales foraging off the Oregon coast, we also collected ambient noise levels using hydrophones, vessel count data from the Oregon Department of Fish and Wildlife (ODFW), and wind data from NOAA National Data Buoy Center (NDBC). Our first finding was a positive correlation between vessel counts and underwater noise levels (Fig. 1A), likely indicating that vessel traffic is the dominant source of noise in the area. To confirm this, we also compared underwater noise levels with wind speed (Fig. 1B), but no correlations were found.
We also investigated noise levels by the hour of the day (Fig. 2), and we found that noise levels peaked between 6 and 8 am most days, coinciding with the peak of vessels leaving the harbor to get to fishing grounds. Another smaller peak is seen at 12 pm, which may represent “half-day fishing charter” vessels returning to the harbor. In contrast, wind speeds (in the lower graph) peaked between 3 and 4 pm, thus confirming the absence of correlation between noise and wind and providing more evidence that noise levels are dominated by the vessel activity in the area.
Finally, we assessed the effects of vessel counts, month, year, sex, whale body condition, and other hormone metabolites on glucocorticoid metabolite (GCm; “stress”) concentrations. Since we are working with fecal samples, we needed to consider the whale gut transit time and go back in time to link time of exposure (vessel counts) to response (glucocorticoid concentrations). However, due to uncertainty regarding gut transit time in baleen whales, we compared different time lags between vessel counts and fecal collection. The gut transit time in large mammals is ~12 hours to 4 days3,19,20, so we investigated the influence of vessel counts on whale “stress hormone levels” from the previous 1 to 7 days. The model with the most influential temporal scale included vessel counts from previous day, which showed a significant positive relationship with GCm (the “stress hormone level”) (Fig. 3).
Thus, the “take home messages” of our study are:
The soundscape in our study area is dominated by vessel noise.
Vessel counts are strongly correlated with ambient noise levels in our study area.
Gray whale glucocorticoid levels are positively correlated with vessel counts from previous day meaning that gray whale gut transit time may occur within ~ 24 hours of the disturbance event.
These four chapters were all very important studies not only to advance the knowledge of gray whale and overall baleen whale physiology (as this group is one of the most poorly understood of all mammals given the difficulties in sample collection21), but also to investigate potential sources for the unusual mortality event that is currently happening (2019-present) to the Eastern North Pacific population of gray whales. Such studies can be used to guide future research and to inform population management and conservation efforts regarding minimizing the impact of anthropogenic stressors on whales.
I am very glad to be part of this project, to see such great fruits from our gray whale research, and to know that this project is still at full steam. The GEMM Lab continues to collect and analyze data for determining gray whale body condition and physiological responses in association with ambient noise (Granite, Amber and Diamond projects). The gray whales thank you for this!
1. McDonald, M. A., Hildebrand, J. A. & Wiggins, S. M. Increases in deep ocean ambient noise in the Northeast Pacific west of San Nicolas Island, California. J. Acoust. Soc. Am. 120, 711–718 (2006).
2. Kaplan, M. B. & Solomon, S. A coming boom in commercial shipping? The potential for rapid growth of noise from commercial ships by 2030. Mar. Policy 73, 119–121 (2016).
3. McCarthy, E. International regulation of underwater sound: establishing rules and standards to address ocean noise pollution (Kluwer Academic Publishers, 2004).
4. Weilgart, L. S. The impacts of anthropogenic ocean noise on cetaceans and implications for management. Can. J. Zool. 85, 1091–1116 (2007).
5. Bas, A. A. et al. Marine vessels alter the behaviour of bottlenose dolphins Tursiops truncatus in the Istanbul Strait, Turkey. Endanger. Species Res. 34, 1–14 (2017).
6. Erbe, C., Reichmuth, C., Cunningham, K., Lucke, K. & Dooling, R. Communication masking in marine mammals: a review and research strategy. Mar. Pollut. Bull. 103, 15–38 (2016).
7. Erbe, C. et al. The effects of ship noise on marine mammals: a review. Front. Mar. Sci. 6 (2019).
8. Sullivan, F. A. & Torres, L. G. Assessment of vessel disturbance to gray whales to inform sustainable ecotourism. J. Wildl. Manag. 82, 896–905 (2018).
9. Pirotta, E., Merchant, N. D., Thompson, P. M., Barton, T. R. & Lusseau, D. Quantifying the effect of boat disturbance on bottlenose dolphin foraging activity. Biol. Conserv. 181, 82–89 (2015).
10. Dans, S. L., Degrati, M., Pedraza, S. N. & Crespo, E. A. Effects of tour boats on dolphin activity examined with sensitivity analysis of Markov chains. Conserv. Biol. 26, 708–716 (2012).
11. Christiansen, F., Rasmussen, M. & Lusseau, D. Whale watching disrupts feeding activities of minke whales on a feeding ground. Mar. Ecol. Prog. Ser. 478, 239–251 (2013).
12. Bejder, L., Samuels, A., Whitehead, H. & Gales, N. Interpreting short-term behavioural responses to disturbance within a longitudinal perspective. Anim. Behav. 72, 1149–1158 (2006).
13. Nowacek, S. M., Wells, R. S. & Solow, A. R. Short-term effects of boat traffic on Bottlenose dolphins, Tursiops truncatus, in Sarasota Bay, Florida. Mar. Mammal. Sci. 17, 673–688 (2001).
14. Bejder, L., Dawson, S. M. & Harraway, J. A. Responses by Hector’s dolphins to boats and swimmers in Porpoise Bay, New Zealand. Mar. Mammal Sci. 15, 738–750 (1999).
15. Lusseau, D. Male and female bottlenose dolphins Tursiops spp. have different strategies to avoid interactions with tour boats in Doubtful Sound. New Zealand. Mar. Ecol. Prog. Ser. 257, 267–274 (2003).
16. Sprogis, K. R., Videsen, S. & Madsen, P. T. Vessel noise levels drive behavioural responses of humpback whales with implications for whale-watching. Elife 9, e56760 (2020).
17. Ayres, K. L. et al. Distinguishing the impacts of inadequate prey and vessel traffic on an endangered killer whale (Orcinus orca) population. PLoS ONE 7, e36842 (2012).
18. Rolland, R. M. et al. Evidence that ship noise increases stress in right whales. Proc. R. Soc. B Biol. Sci. 279, 2363–2368 (2012).
19. Wasser, S. K. et al. A generalized fecal glucocorticoid assay for use in a diverse array of nondomestic mammalian and avian species. Gen. Comp. Endocrinol. 120, 260–275 (2000).
20. Hunt, K. E., Trites, A. W. & Wasser, S. K. Validation of a fecal glucocorticoid assay for Steller sea lions (Eumetopias jubatus). Physiol. Behav. 80, 595–601 (2004).
21. Hunt, K. E. et al. Overcoming the challenges of studying conservation physiology in large whales: a review of available methods. Conserv. Physiol. 1, cot006–cot006 (2013).
It’s hard to believe that it’s already been four and half months since we started the field season (check out Lisa’s blog for a recap of where we began), but as of this weekend the GRANITE project’s 8th field season has officially ended! As the gray whales wrap up their foraging season and start heading south for the winter, it’s time for us to put our gear into storage, settle into a new academic year, and start processing the data we spent so much time collecting.
The field season can be quite an intense time (40 days equaling over 255 hours on the water!), so we often don’t take a moment to reflect until the end. But this season has been nothing short of remarkable. As you may remember from past blogs, the past couple years (2020-21) have been a bit concerning, with lower whale numbers than previously observed. Since many of us started working on the project during this time, most of us were expecting another similar season. But we were wrong in the best way. From the very first day, we saw more whales than in previous years and we identified whales from our catalog that we hadn’t seen in several years.
We identified friends – old and new!
This season we had 224 sightings of 63 individual whales. Of those 63, 51 were whales from our catalog (meaning we have seen them in a previous season). Of these 51 known whales, we only saw 20 of them last year! This observation brings up interesting questions such as, where did most of these whales forage last year? Why did they return to this area this year? And, the classic end of season question, what’s going to happen next year?
We also identified 12 whales that were not in our catalog, making them new to the GEMM lab. Two of our new whales are extra exciting because they are not just new to us but new to the population; we saw two calves this year! We were fortunate enough to observe two mom-calf pairs in July. One pair was of a “new” mom in our catalog and her calf. We nicknamed this calf “Roly-poly” because when we found this mom-calf pair, we recorded some incredible drone footage of “roly-poly” continuously performing body rolls while their mom was feeding nearby (video 1).
The other pair includes a known GEMM lab whale, Luna, and her calf (currently nicknamed “Lunita”). We recently found “Lunita” feeding on their own in early October (Image 2), meaning that they are now independent from its mom (for more on mom-calf behavior check out Celest’s recent blog). We’ll definitely be on the lookout for Roly-Poly and Lunita next year!
We flew, we scooped, we collected heaps of data!
From our previous blogs you probably know that in addition to photo-ID images, our other two most important forms of data collection are drone flights (for body condition and behavior data) and fecal samples (for hormone analysis). And this season was a success for both!
We conducted 124 flights over 49 individual whales. The star of these flights was a local favorite Scarlett who we flew over 18 different times. These repeat samples are crucial data for us because we use them to gain insight into how an individual’s body condition changes throughout the season. We also recorded loads of behavior data, collecting footage of different foraging tactics like headstanding, side-swimming, and surfacing feeding on porcelain crab larvae (video 2)!
We also collected 61 fecal samples from 26 individual whales (Image 3). The stars of that dataset were Soléand Peak who tied with 7 samples each. These hard-earned samples provide invaluable insight into the physiology and stress levels of these individuals and are a crucial dataset for the project.
On top of all that amazing data collection we also collected acoustic data with our hydrophones, prey data from net tows, and biologging data from our tagging efforts. Our hydrophones were in the water all summer recording the sounds that the whales are exposed to, and they were successfully recovered just a few weeks ago (Image 4)! We also conducted 69 net tows to sample the prey near where the whales were feeding and identify which prey the whales might be eating (Image 5). Lastly, we had two very successful tagging weeks during which we deployed (and recovered!) a total of 9 tags, which collected over 30 hours of data (Image 6; check out Kate’s blog for more on that).
All in all, it’s been an incredible season. We’ve seen the return of old friends, collected lots of awesome data, and had some record-breaking days (28 whales in one day!). As we look toward the analysis phase of the year, we’re excited to dig into our eight-year dataset and work to understand what might explain the increase in whales this year.
To end on a personal note, looking through photos to put in this blog was the loveliest trip down memory lane (even though it only ended a few days ago) – I am so honored and proud to be a part of this team. The work we do is hard; we spend long hours on a small boat together and it can be a bit grueling at times. But, when I think back on this season, my first thoughts are not of the times I felt exhausted or grumpy, but of all the joy we felt together. From the incredible whale encounters to the revitalizing snacks to the off-key sing alongs, there is no other team I would rather do this work with, and I so look forward to seeing what next season brings. Stay tuned for more updates from team GRANITE!
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By Braden Adam Vigil, Oregon State University Undergraduate, GEMM Lab NSF REU Intern
My name is Braden Vigil, and I am enjoying this summer with the company of Lisa Hildebrand and Dr. Leigh Torres as a National Science Foundation (NSF) Research Experience for Undergraduates (REU) intern. By slicing off a manageable chunk of the GRANITE project to focus on, I’ve had the chance to explore my passion for data visualization. My excitement for biological research was instilled in me by an impactful high school biology teacher (thank you Mr. Villalobos!) and was narrowed to marine biology research after a chance visit to Oregon State University’s Hatfield Marine Science Center. I’ve come all the way from Southern New Mexico to explore this passion of mine, and the REU program has been one of my first chances to get my feet wet. My advice for any students debating taking big leaps for the sake of passion is to do it – it’s scary, but I’d say there’s nothing better than living out what you want to do (and hopefully getting paid for it!). For this project, the GEMM Lab has saved me the trouble of collecting data – this summer, I’m all action.
Where Gray Whales Are and Why It Matters
Just as you might find yourself at a grocery store to buy food or at a coffee shop catching up with an old friend, so too do whales have places to go and reasons for being there. Research concerning gray whale ecology – understanding the who, what, when, where, whys – should then have a lot to do with the “where?” and “why?” That’s what my project is about: investigating where the gray whales off the Oregon coast are, and what features of the environment are related to their presence and other aspects of the population. After all, distribution is considered the foundational unit for the biogeographical understanding of a population’s location and its interactions with other species. An example of an environmental driver may be phytoplankton and – subsequently – zooplankton abundance. It’s been shown that bottom-up trophic cascades based on primary productivity directly influence predator and prey populations in both terrestrial and marine ecosystems (Sinclair and Krebs 2002; Benoit-Bird and McManus 2012). This driver specifically could then inform something as significant as population abundance of a predator, though that’s out of the scope of my project. Instead, I’m studying how these environmental drivers, specifically sea water temperature, affects the variation of the thyroid hormone (tri-iodothyronine, T3) in gray whales, which the GEMM Lab quantifies from fecal samples that they non-invasively and opportunistically collect. In terrestrial mammals, T3 is believed to be associated with thermoregulation, yet it is unclear if T3 has the same function in baleen whales who use blubber insulation to thermoregulate. To estimate blubber insulation, we use a proxy, called body area index (BAI) collected via drone footage (Burnett et al. 2018), which you can read more about in Clara’s blog. Insights into variations in T3 hormone levels as related to changes in the environment may allow researchers to better understand thermoregulatory challenges whales face in warming oceans.
This Sounds Like a Lot of Data About the Environment, Where’s it Coming From?
Not only has the GEMM Lab relieved me of the hassle that data collection and fieldwork can be, so too has the Ocean Observatories Initiative (OOI). Starting in 2014, the OOI has set up several buoys off the U.S. West Coast, each equipped with numerous sensors and data-collecting devices. These have been extracting data from the nearby environment since then, including aspects such as dissolved oxygen, pH, and most important to this study, sea temperature. These buoys run deep too! Some devices reach as low as 25 m, which is where we often expect to see whales foraging during surveys. For our interest, there is one specific buoy that is within the GRANITE project’s survey region, the Oregon Inshore Surface Mooring.
The OOI has published, and continues to publish, an unbelievable amount of data. There are many things that would be interesting to investigate, but until we know how much we can bite off versus how much we can chew, we’ve narrowed it down to a few hypotheses we’re currently investigating.
A Hundred and One Data Visualizations
As fun as I find testing correlations between variables and creating satisfying looking plots, I must admit that I’m not even halfway into this project and I’ve made a LOT of plots. Plots can be an easy way to understand big datasets and observations. Since not all of the data-collecting devices on the OOI data are continuously running, I first needed to get an idea of how much data we have to work with, and how much of that data overlaps in time with our annual gray whale survey period (June 1 – October 15). Some of these preliminary plots look like Figure 2. In addition, these plots grant us an idea of how variable sea surface temperatures have been in these past few years. Marine heatwaves have occurred recently in the Pacific Ocean and off the U.S. West Coast, and it is important to know if their effects continue to linger to the present. Other, unexplained peaks might also be worth investigating.
The goal here is to eventually compare the variables of sea temperature to the T3 hormone levels in gray whales foraging off the Oregon coast. Before this step, it is important to decide what depth of temperature readings are most appropriate to assess. I’ve made several correlation plots of sea temperature between varying depths of 1 m, 7 m, and 25 m. One such plot is included below (Figure 3). This plot shows variation of temperature between different depths. If there is strong variation between the depths of 1 m and 25 m, then the water column may be well stratified, meaning that gray whale response to environmental temperature may be distinct between these distances, possibly even between 1 m and 7 m.
As previously described, this study plays part into the larger GRANITE project with the goal to understand and make predictions about the ecology and physiology of the gray whale population off of the U.S. West Coast. This study will investigate the significance of sea temperature on aspects of whale health – so far including BAI and T3 hormone level. I will be pursuing a stronger grasp on the variation of these relationships through ongoing analysis. My results should be used to clarify nodes and the correlation between them in the web of dynamics encircling the population. This project has given me great insight into how raw data can be turned into meaningful understandings and subsequent impacts. The public OOI data is a scattershot of many different measurements using many different devices constantly. The answers/solutions to the conservation of species threatened by the Anthropocene are out there, all that’s required is that we harness them.
Sinclair, A. R. E., & Krebs, C. J. (2002). Complex numerical responses to top–down and bottom–up processes in vertebrate populations. Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences, 357(1425), 1221–1231.https://doi.org/10.1098/rstb.2002.1123.
We are almost halfway through June which means summer has arrived! Although, here on the Oregon coast, it does not entirely feel like it. We have been swinging between hot, sunny days and cloudy, foggy, rainy days that are reminiscent of those in spring or even winter. Despite these weather pendulums, the GEMM Lab’s GRANITE project is off to a great start in its 8th field season! The field team has already ventured out onto the Pacific Ocean in our trusty RHIB Ruby on four separate days looking for gray whales and in this blog post, I am going to share what we have seen so far.
PI Leigh, PhD candidate Clara and I headed out for a “trial run” on May 24th. While the intention for the day was to make sure all our gear was running smoothly and we still remembered how to complete the many tasks associated with our field work (boat loading and trailering, drone flying and catching, poop scooping, data download, to name a few), we could not resist surveying our entire study range given the excellent conditions. It was a day that all marine field scientists hope for – low winds (< 5 kt all day) and a 3 ft swell over a long period. Despite surveying between Waldport and Depoe Bay, we only encountered one whale, but it was a whale that put a smile on each of our faces. After “just” 252 days, we reunited with Solé, the star of our GRANITE dataset, with record numbers of fecal samples and drone flights collected. This record is due to what seems to be a strong habitat or foraging tactic preference by Solé to remain in a relatively small spatial area off the Oregon coast for most of the summer, rather than traveling great swaths of the coast in search for food. Honest truth, on May 24th we found her exactly where we expected to find her. While we did not collect a fecal sample from her on that day, we did perform a drone flight, allowing us to collect a critical early feeding season data point on body condition. We hope that Solé has a summer full of mysids on the Oregon coast and that we will be seeing her often, getting rounder each time!
Just a week after this trial day, we had our official start to the field season with back-to-back days on the water. On our first day, postdoc Alejandro, Clara and I were joined by St. Andrews University Research Fellow Enrico Pirotta, who is another member of the GRANITE team. Enrico’s role in the GRANITE project is to implement our long-term, replicate dataset into a framework called Population consequences of disturbance (PCoD; you can read all about it in a previous blog). We were thrilled that Enrico was able to join us on the water to get a sense for the species and system that he has spent the last several months trying to understand and model quantitatively from a computer halfway across the world. Luckily, the whales sure showed up for Enrico, as we saw a total of seven whales, all of which were known individuals to us! Several of the whales were feeding in water about 20 m deep and surfacing quite erratically, making it hard to get photos of them at times. Our on-board fish finder suggested that there was a mid-water column prey layer that was between 5-7 m thick. Given the flat, sandy substrate the whales were in, we predicted that these layers were composed of porcelain crab larvae. Luckily, we were able to confirm our hypothesis immediately by dropping a zooplankton net to collect a sample of many porcelain crab larvae. Porcelain crab larvae have some of the lowest caloric values of the nearshore zooplankton species that gray whales likely feed on (Hildebrand et al. 2021). Yet, the density of larvae in these thick layers probably made them a very profitable meal, which is likely the reason that we saw another five whales the next day feeding on porcelain crab larvae once again.
On our most recent field work day, we only encountered Solé, suggesting that the porcelain crab swarms had dissipated (or had been excessively munched on by gray whales), and many whales went in search for food elsewhere. We have done a number of zooplankton net tows across our study area and while we did collect a good amount of mysid shrimp already, they were all relatively small. My prediction is that once these mysids grow to a more profitable size in a few days or weeks, we will start seeing more whales again.
So far we have seen nine unique individuals, flown the drone over eight of them, collected fecal samples from five individuals, conducted 10 zooplankton net tows and seven GoPro drops in just four days of field work! We are certainly off to a strong start and we are excited to continue collecting rock solid GRANITE data this summer to continue our efforts to understand gray whale ecology and physiology.
Hildebrand L, Bernard KS, Torres LGT. 2021. Do gray whales count calories? Comparing energetic values of gray whale prey across two different feeding grounds in the Eastern North Pacific. Frontiers in Marine Science 8. doi: 10.3389/fmars.2021.683634