“What if I’m wrong? What if I make a mistake?” When I began my career after completing my undergraduate degree, these questions echoed constantly in my head as the stakes were raised and my work was taken more seriously. Of course, this anxiety was not new. As a student, my worst fear had been poor performance in class. Post-undergrad, I was facing the possibility of making a mistake that could impact larger research projects and publications.
Gaining greater responsibility and consequences is a fact of life and an intrinsic part of growing up. As I wrap up my third year of graduate school, I’ve been reflecting on how learning to take on this responsibility as a scientist has been a crucial part of my journey thus far.
A scientist’s job is to ask, and try to answer, questions that no one knows the answer to – which is both terrifying and exciting. It feels a bit like realizing that grown-ups don’t have all the answers as a kid. Becoming comfortable with the fact that my work often involves making decisions that no one definitively can say are wrong or right has been one of my biggest challenges of grad school. The important thing to remember, I’ve learned, is that I’m not making wild guesses – I’m being trained to make the best, most informed decisions possible. And, hopefully, with more experience will come greater confidence.
Through grad school I have learned to take on this responsibility both in the field and the lab, although each brings different experiences. In the field, the stakes can feel higher because the decisions we make affect not just the quality of the data, but the safety of the team (which is always the top priority). I felt this most acutely throughout my first summer as a drone pilot. As a pilot, I am responsible for the safety of the team, the drone, and the quality of the data. As a new pilot, I intensely felt this pressure and would come home feeling more exhausted than usual. Now, in my second field season in this role, I’ve become more comfortable and am slowly building confidence in my abilities as I gain more and more experience.
Video 1 – Two gray whales foraging together off Newport, Oregon, USA. I recorded this footage during my first season as a pilot – a flight I’ll never forget! NOAA/NMFS permit #21678.
I have also had a similar experience in the lab. Once it’s time to work on the analysis of a project, I choose how to clean, analyze, and interpret the data. As a young scientist, every step of the process involves learning new skills and making decisions that I don’t feel entirely qualified to make. When I started analysis for my first PhD chapter, I felt overwhelmed by deciding how to standardize my data, what kind of analysis to perform, and what indices to calculate. And, since it’s my first chapter, I felt further overwhelmed by the worry that any decision I made would become a later regret in a future part of my PhD.
Recently, the most daunting decision has been how to standardize my data. For my first chapter, I am investigating individual specialization of gray whale foraging behavior. The results of this question are not only important for conservation, but for my subsequent work (check out these previous blogs from January 2021and April 2022 for more on this research question). While there is a wealth of literature to draw analysis inspiration from, most of these studies use discrete prey capture data, while I am working with continuous behavior data. So, to make my data points comparable to one another, I need to standardize the behavior observation time of each drone flight to account for the potential bias introduced by recording one individual for more time than another. After experiencing an internal roller coaster of having an idea, thinking it through, deciding it was terrible and restarting the cycle, I was reminded that turning to lab mates and collaborators is the best way to work through a problem.
Image 1 – Comic from phdcomics.com, source: https://phdcomics.com/comics/archive.php?comicid=2008
So, I had as many conversations as I could with my advisor, committee members, and peers. My thinking clarified with every conversation, and I gained confidence in the justification behind my decision. I cannot fully express the comfort that comes from hearing a trusted advisor say, “that makes ecological sense to me”. These conversations have also helped me remember that I am not alone in my worry and that I am not failing because I have these doubts. While I may never be 100% convinced that I’ve made the right decision, I feel much better knowing that I’ve talked it through with the brilliant group of scientists around me. And as I enter an analysis-intensive phase of my PhD, I am extremely grateful to have this community around to challenge, advise, and support me.
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Allison Dawn, GEMM Lab Master’s student, OSU Department of Fisheries, Wildlife and Conservation Sciences, Geospatial Ecology of Marine Megafauna Lab
The 27th Annual Markham Research Symposium was hosted at the Hatfield Marine Science Center (HMSC) last week. During the event, students who have been awarded funds and scholarships through HMSC present their research via poster presentations or 5-minute “ignite” talks. Given how isolated and mostly remote academic events have been during the COVID pandemic, it was invigorating to have an in-person research event. The timing of the symposium was also strategically planned to occur during the first week of Hatfield’s REU (Research Experiences for Undergraduates) students’ arrival, and it felt special to have such a diversity of ages and career stages coming together to discuss science. While I was certainly expecting to have good conversations about research and receive feedback on my work, I was most surprised by how much this event inspired me to reflect on my first year as a graduate student. For this week’s blog I’d like to share some of these reflections I had while listening to the excellent keynote address and interacting with students during the poster session.
The symposium began with a keynote address by Dr. Elizabeth Perotti who identifies as a scientist, communicator, and a parent. Dr. Perotti works as the Education and Outreach Coordinator for NOAA’s Ocean Acidification Program (OAP). I was expecting to hear a 45-minute presentation on the latest ocean acidification efforts, but I was surprised and appreciated that Dr. Perotti spent her time mainly focused on discussing career development through the lens of her own winding career path. While I would have been equally excited to hear about her science communication and outreach work, I am glad she took the time to share her story and give advice based on her experiences. As someone who used to feel insecure about my non-linear path to science, it was validating and inspiring to hear about the variety of experiences that prepared her to take on her current position at NOAA. Dr. Perotti describes her career path as “clear as mud”, but acknowledged that there were several key mentors who helped her identify and shape her specific interests.
One of those mentors was the late Dr. Marian Diamond, who is renowned for her work on brain plasticity research. She was the first female science professor at Cornell and is considered one of the founders of modern neuroscience. She and her team pioneered the idea that the brain can change, and even improve, with the right stimulation. Dr. Diamond was the first person to study Einstein’s brain in the hopes of uncovering the secret to his high intelligence. She found that Einstein’s brain had more glial cells (which are now sometimes called “genius cells”) than the average person. These glial cells are known to nourish strong neuron connections and build a more complex brain structure. Dr. Diamond hypothesized that Einstein’s brain had more of these cells due to the high stimulation he put on his neurons. From the synthesis of this study and other fascinating experiments during her life’s work, Dr. Diamond suggested five core things the brain needs to continue development, regardless of age: diet, exercise, challenges, newness, and love. A healthy diet fuels the brain, exercise builds better brain cells, challenges and newness stimulate brain function, and love enriches our lives – each of these factors are shown to contribute to the neuroplasticity of our brains (Diamond, 2001). During the keynote, Dr. Perotti asked the audience to contemplate if they are pursuing a career that is fulfilling at least one of those core requirements. As I contemplated these “brain essentials”, I realized how my experience as a Master’s student in the GEMM lab actually fulfills each one of these, and I am excited by the science that suggests I may be producing more “genius cells” because of it!
First, the diet I’ve had over the past year has certainly been nurturing. During the field season in Port Orford, one of my favorite meals is when we are given locally-sourced and sustainably caught fish from Port Orford Sustainable Seafood in exchange for helping them process orders. When I am back in Newport and Corvallis, my lab mates and peers are always sharing homemade snacks and we frequently get together for meals (and when the weather is nice – picnics!)
Figures 2 & 3: To the left: Locally sourced salmon cooked by Lisa Hildebrand for one of the many 2021 Port Orford team dinners; To the right: Colorful plates on an impromptu sunny day picnic with Rachel Kaplan.
For exercise – it almost goes without saying that the field season in Port Orford is physically demanding. During data collection we are constantly alert and on our feet on the cliff site, or paddling continuously to stay on station to obtain good zooplankton and oceanographic samples.
Figure 4: Lisa Hildebrand and A. Dawn enjoying one of the last days of kayak sampling for the 2021 Port Orford field season.
Challenges – there are a variety of challenges to face as a new graduate student. Not only are there difficult, yet exciting questions to tackle, and new analysis skills to learn, but as Dr. Perotti discussed in her talk, there are also soft skills (communication, time/conflict management, task prioritization) that I am sharpening, which are equally important to master.
Newness – as a graduate student, almost everything feels new. I frequently feel I am out of my comfort zone. Especially during the past three terms, I find myself in the mental “growth zone” consistently. Between my coursework and getting to attend exciting seminars, I consistently learn something new on a daily basis. Despite having completed a field season last year, leading the team this year will also be new, and I anticipate a steep learning curve where I am excited to learn how to be a better scientist and mentor.
Lastly, the love I have experienced since starting my Master’s degree has been one of my most treasured aspects of my life here – love for my lab family and for the opportunity I have to be here. After the symposium I got together with a few lab mates and we journeyed to Nye Beach to watch the sunset. I appreciate that despite our busy schedules, we all make time to connect with each other and explore the beautiful coast we are privileged to call home.
Figure 5: Watching the sunset on Nye Beach never gets old, especially when you are with good friends. Photo credit: C. Bird.
Just as I incorrectly assumed the keynote would be solely research focused, I anticipated answering in-depth questions about my preliminary Master’s thesis analysis results at the poster session. While I did receive great questions and valuable feedback from mentors, which has already helped shape the next steps in my analysis, the interactions I had with the REU student cohort was very different. These budding scientists were more interested in my personal outlook on graduate school, and asked many questions that felt familiar to me. I let the undergraduates know that it was only a year ago that I graduated with my B.S., and shared many of those same, daunting questions about the next chapter of my career: “How do you know if a program is right for you?”, “How do you pick the right advisor?”, “What type of working environment should I be looking for?”. It was fulfilling to be able to echo the great advice Dr. Perotti gave during the keynote address, in which she encouraged students to find mentors, know their talents, learn how to communicate, and take a challenge.
Figure 6: Posing next to my Markam Symposium poster, excited to share my proposed research with peers and mentors. Photo credit: Lisa Hildebrand
I am extremely grateful to have received one of this year’s Mamie Markham awards, and for the opportunity to interact with younger career scientists who I can share my journey and experiences with. The symposium was good practice in communicating my work and stimulating food for thought as I move forward with my second year in graduate school.
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References
Diamond, Marian (2001) Successful Aging of the Healthy Brain. Conference of the American Society on Aging and The National Council on the Aging March 10, 2001, New Orleans, LA
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.
The core GRANITE field team before the May 24th “trial run”. From left to right: Leigh Torres, KC Bierlich, Clara Bird, Lisa Hildebrand, Alejandro Fernández Ajó. Source: L. Torres.
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!
Our superstar whale Solé. Her identifying features are a small white line on her left side (green box) and a white dot in front of her dorsal hump on the right side (red circle). Source: GEMM Lab. Photograph captured under NOAA/NMFS permit #21678
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.
Porcelain crab larvae. Source: GEMM Lab.A happy captain Ale! Source: GEMM Lab.Enrico (right) and myself after collecting a large fecal sample. Source: GEMM Lab.
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.
The GRANITE team from above, waiting & watching for whales, as we will be doing for the rest of the summer! Source: GEMM Lab.
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.
Literature cited
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
I always have a small crisis before heading into the field, whether for a daytrip or a several-month stint. I’m always dying to go – up until the moment when it is actually time to leave, and I decide I’d rather stay home, keep working on whatever has my current focus, and not break my comfortable little routine.
Preparing to leave on the most recent Northern California Current (NCC) cruise was no different. And just as always, a few days into the cruise, I forgot about the rest of my life and normal routines, and became totally immersed in the world of the ship and the places we went. I learned an exponential amount while away. Being physically in the ecosystem that I’m studying immediately had me asking more, and better, questions to explore at sea and also bring back to land.
Many of these questions and realizations centered on predator-prey relationships between krill and whales at fine spatial scales. We know that distributions of prey species are a big factor in structuring whale distributions in the ocean, and one of our goals on this cruise was to observe these relationships more closely. The cruise offered an incredible opportunity to experience these relationships in real time: while my labmates Dawn and Clara were up on the flying bridge looking for whales, I was down in the acoustics lab, watching incoming echosounder data in order to identify krill aggregations.
From left, Clara and Dawn survey for marine mammals on the flying bridge.
We used radios to stay in touch with what we were each seeing in real time, and learned quickly that we tended to spot whales and krill almost simultaneously. Experiencing this coherence between predator and prey distributions felt like a physical manifestation of my PhD. It also affirmed my faith in one of our most basic modeling assumptions: that the backscatter signals captured in our active acoustic data are representative of the preyscape that nearby whales are experiencing.
Being at sea with my labmates also catalyzed an incredible synthesis of our different types of knowledge. Because of the way that I think about whale distributions, I usually just focus on whether a certain type of whale is present or not while surveying. But Clara, with her focus on cetacean behavior, thinks in a completely different way from me. She timed the length of dives and commented on the specific behaviors she noticed, bringing a new level of context to our observations. Dawn, who has been joining these cruises for five years now, shared her depth of knowledge built through returning to these places again and again, helping us understand how the system varies through time.
Observing whale behavior, such as for these humpbacks, provides valuable information on how they are using a given area.
One of the best experiences of the cruise for me was when we conducted a targeted net tow in an area of foraging humpbacks on the Heceta Head Line off the central Oregon coast. The combination of the krill signature I was seeing on the acoustics display, and the radio reports from Dawn and Clara of foraging dives, convinced me that this was an opportunity for a net tow, if possible, to see exactly what zooplankton was in the water near the whales. Our chief scientist, Jennifer Fisher, and the ship’s officers worked together to quickly turn the ship around and get a net in the water, in an effort to catch krill from the aggregation I had seen.
This unique opportunity gave me a chance to test my own interpretation of the acoustics data, and compare what we captured in the net with what I expected from the backscatter signal. It also prompted me to think more about the synchrony and differences between what is captured by net tows and echosounder data, two primary ways for looking at whale prey.
Collecting tiny yet precious krill samples associated with foraging humpbacks!
Throughout the entire cruise, the opportunity to build my intuition and notice ecological patterns was invaluable. Ecosystem modeling gives us the opportunity to untangle incredible complexity and put dynamic relationships in mathematical terms, but being out on the ocean provides the chance to develop a feel for these relationships. I’m so glad to bring this new perspective to my next round of models, and excited to continue trying to tease apart fine-scale dynamics between whales and krill.
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1PhD student, Oregon State University College of Earth, Ocean, and Atmospheric Sciences and Department of Fisheries, Wildlife, and Conservation Sciences, Geospatial Ecology of Marine Megafauna Lab
What do peanut butter m&ms, killer whales, affogatos, tired eyes, and puffins all have in common? They were all major features of the recent Northern California Current (NCC) ecosystem survey cruise.
The science party of the May 2022 Northern California Current ecosystem cruise.
We spent May 6–17 aboard the NOAA vessel Bell M. Shimada in northern California, Oregon, and Washington waters. This fabulously interdisciplinary cruise studies multiple aspects of the NCC ecosystem three times per year, and the GEMM lab has put marine mammal observers aboard since 2018.
This cruise was a bit different than usual for the GEMM lab: we had eyes on both the whales and their prey. While Dawn Barlow and Clara Bird observed from sunrise to sunset to sight and identify whales, Rachel Kaplan collected krill data via an echosounder and samples from net tows in order to learn about the preyscape the whales were experiencing.
From left, Rachel, Dawn, and Clara after enjoying some beautiful sunset sightings.
We sailed out of Richmond, California and went north, sampling as far north as La Push, Washington and up to 200 miles offshore. Despite several days of challenging conditions due to wind, rain, fog, and swell, the team conducted a successful marine mammal survey. When poor weather prevented work, we turned to our favorite hobbies of coding and snacking.
Rachel attends “Clara’s Beanbag Coding Academy”.
Cruise highlights included several fin whales, sperm whales, killer whales, foraging gray whales, fluke slapping and breaching humpbacks, and a visit by 60 pacific white-sided dolphins. While being stopped at an oceanographic sampling station typically means that we take a break from observing, having more time to watch the whales around us turned out to be quite fortunate on this cruise. We were able to identify two unidentified whales as sei whales after watching them swim near us while paused on station.
Marine mammal observation segments (black lines) and the sighting locations of marine mammal species observed during the cruise.
On one of our first survey days we also observed humpbacks surface lunge feeding close to the ship, which provided a valuable opportunity for our team to think about how to best collect concurrent prey and whale data. The opportunity to hone in on this predator-prey relationship presented itself in a new way when Dawn and Clara observed many apparently foraging humpbacks on the edge of Heceta Bank. At the same time, Rachel started observing concurrent prey aggregations on the echosounder. After a quick conversation with the chief scientist and the officers on the bridge, the ship turned around so that we could conduct a net tow in order to get a closer look at what exactly the whales were eating.
Success! Rachel collects krill samples collected in an area of foraging humpback whales.
This cruise captured an interesting moment in time: southerly winds were surprisingly common for this time of year, and the composition of the phytoplankton and zooplankton communities indicated that the seasonal process of upwelling had not yet been initiated. Upwelling brings deep, cold, nutrient-rich waters to the surface, generating a jolt of productivity that brings the ecosystem from winter into spring. It was fascinating to talk to all the other researchers on the ship about what they were seeing, and learn about the ways in which it was different from what they expected to see in May.
Experiencing these different conditions in the Northern California Current has given us a new perspective on an ecosystem that we’ve been observing and studying for years. We’re looking forward to digging into the data and seeing how it can help us understand this ecosystem more deeply, especially during a period of continued climate change.
The total number of each marine mammal species observed during the cruise.
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Pursuing a graduate degree as a member of the Marine Mammal Institute (MMI) comes with many advantages. Developing associations with curious, industrious researchers and working with advanced technological methods are certainly two of them. Particularly, as a member of the HALO project, I have the pleasure of working alongside not only the GEMM’s, but also acoustician Dr. Holger Klinck and his bioacoustics team at the K. Lisa Yang Center for Conservation Bioacoustics at the Cornell Lab (CCB) who have made significant contributions to advance the field for marine mammal research.
When the HALO project kicked off in October, 2021, Holger and graduate student, Marissa Garcia, arrived for our initial voyage off the Oregon coast with three specialized acoustic recording devices, called Rockhoppers. We deployed each Rockhopper at their designated locations, where they will remain and be replaced every six months, to collect continuous passive acoustic data of cetacean vocalizations. These data are significant because they gather information on all vocalizing whales and dolphins within a detectable range of the Rockhoppers, supporting not only my thesis work concerning fin whale distribution in the Northern California Current (NCC) but has the potential to inform multiple other research projects as well.
Figure 1. Craig Hayslip, Holger Klinck, and Marissa Garcia prepare a Rockhopper for deployment during the first HALO cruise off the Oregon coast.
Passive acoustic monitoring (PAM) is a non-invasive underwater method of recording acoustic output of cetaceans (Zimmer, 2011), and the Rockhopper is specialized for this task. The Rockhopper relatively small (each weighing ~90lbs.) and can be easily deployed with a minimal team from almost any vessel (Fig 1). The mooring is a simple system that anchors the Rockhopper to the sea floor after it sinks through the water column, tolerating depths up to 3,500 m (Klinck et al., 2020). The device can stay on the ocean floor for up to seven months continuously collecting high-frequency data (up to 197 kHz, 24 bits; Klinck et al., 2020). To recover the Rockhopper, the mooring system (Fig 2) includes an acoustic release; when the correct acoustic signal is transmitted by scientists from the vessel and received down at the seafloor, the Rockhopper is released. It’s positive buoyancy allows it to float to the surface where it is recovered. By developing the Rockhopper with these capabilities, the bioacoustics team at Cornell University have taken several steps to enhance cetacean research.
Figure 2. Rockhopper mooring system (Klinck et al., 2020).
According to one of it’s designers, David Winiarski, the Rockhopper development team, consisting of himself, Holger Klinck, Raymond Mack, Christopher Tessaglia-Hymes, Dmitri Ponirakis, Peter Dugan, Christopher Jones, and Haru Matsumoto, initiated it’s construction in 2015. Winiarski states that Jones developed the Rockhopper’s initial PAM electronics at Embedded Ocean Systems (EOS), Boston, MA and then the rest of the team developed the remainder of the device in 2017. The Rockhopper contains the electronic system and a 10.8 V Lithium battery pack in an oil-filled Vitrovex 43 cm glass sphere that is encased in hard polyethelene. Two 64 GB memory cards store the collected acoustic data. About every hour the internal processing unit moves the data to two 4 Terabyte solid-state drives in a process that ensures the data is not lost (Klinck et al., 2020). Winiarski attests that it was quite a hectic process to get six complete Rockhoppers ready for their initial deployment, however the team succeeded and in May 2018 they were deployed in the Gulf of Mexico. The Rockhoppers were recovered in 2019 after six months, returning an amazing 21,522 hours of continuous acoustic data (Klinck et al., 2020).
Learning this information about the acoustic devices that will be responsible for collecting my Master’s thesis data is encouraging. I am eager to see the fin whale energy captured within the Rockhopper records. The HALO team, along with myself, Holger, and Marissa, will head back out off the Oregon coast to retrieve our three HALO-designated Rockhoppers in early June (next month). We will then spend the summer at Cornell reading through our first six months of data.
So, why call this acoustic device, the “Rockhopper”? Winiarski explained that since the CCB is a subsect of the Cornell Lab of Ornithology their projects tend to be named after birds. The Rockhopper team thought that this device should respectively be named after a cool marine megafauna. Hence the rockhopper penguin was chosen. I do agree that such an outstanding device is well suited in relation with an equally remarkable marine species.
Left: Rockhopper penguins on a New Zealand hillside. https://nzbirdsonline.org.nz/species/eastern-rockhopper-penguin Upper right: Chris Tessaglia-Hymes and David Winiarski with a Rockhopper acoustic device. Lower right: The first six complete Rockhopper acoustic devices developed at the Cornell Center of Bioacoustics in 2017.
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References
Klinck, H., Winiarski, D., Mack, R., Tessaglia-Hymes, C., Ponirakis, D., Dugan, P., Jones, C., Matsumoto, H. 2020. The Rockhopper: a compact and extensible marine autonomous passive acoustic recording system,” Global Oceans 2020: Singapore – U.S. Gulf Coast: 1-7. https://ieeexplore.ieee.org/document/9388970.
Zimmer, W. 2011. Passive acoustic monitoring of cetaceans. Cambridge University Press, Cambridge, UK.
In September 2020, I was hired as a postdoc in the GEMM Lab and was tasked to conduct the analyses necessary for the OPAL project. This research project has the ambitious, yet essential, goal to fill a knowledge gap hindering whale conservation efforts locally: where and when do whales occur off the Oregon coast? Understanding and predicting whale distribution based on changing environmental conditions is a key strategy to assess and reduce spatial conflicts with human activities, specifically the risk of entanglement in fixed fishing gear.
Starting a new project is always a little daunting. Learning about a new region and new species, in an alien research and conservation context, is a challenge. As I have specialized in data science over the last couple of years, I have been confronted many times with the prospect of working with massive datasets collected by others, from which I was asked to tease apart the biases and the ecological patterns. In fact, I have come to love that part of my job: diving down the data rabbit hole and making my way through it by collaborating with others. Craig Hayslip, faculty research assistant in MMI, was the observer who conducted the majority of the 102 helicopter surveys that were used for this study. During the analysis stage, his help was crucial to understand the data that had been collected and get a better grasp of the field work biases that I would later have to account for in my models. Similarly, it took hours of zoom discussions with Dawn Barlow, the GEMM lab’s latest Dr, to be able to clean and process the 75 days of survey effort conducted at sea, aboard the R/V Shimada and Oceanus.
Once the data is “clean”, then comes the time for modeling. Running hundreds of models, with different statistical approaches, different environmental predictors, different parameters etc. etc. That is when you realize what a blessing it is to work with a supervisor like Leigh Torres, head of the GEMM Lab. As an early career researcher, I really appreciate working with people who help me take a step back and see the bigger picture within which the whole data wrangling work is included. It is so important to have someone help you stay focused on your goals and the ecological questions you are trying to answer, as these may easily get pushed back to the background during the data analysis process.
And here we are today, with the first scientific publication from the OPAL project published, a little more than three years after Leigh and Craig started collecting data onboard the United States Coast Guard helicopters off the coast of Oregon in February 2019. Entitled “Seasonal, annual, and decadal distribution of three rorqual whale species relative to dynamic ocean conditions off Oregon, USA”, our study published in Frontiers in Marine Science presents modern and fine-scale predictions of rorqual whale distribution off Oregon, as well as a description of their phenology and a comparison to whale numbers observed across three decades in the region (Figure 1). This research focuses on three rorqual species sharing some ecological and biological traits, as well as similar conservation status: humpback whales (Megaptera novaeangliae), blue whales (Balaenoptera musculus musculus), and fin whales (Balaenoptera physallus); all of which migrate and feed over the US West coast (see a previous blog to learn more about these species here).
Figure 1: Graphical abstract of our latest paper published in Frontiers in Marine Science.
We demonstrate (1) an increase in rorqual numbers over the last three decades in Oregon waters, (2) differences in timing of migration and habitat preferences between humpback, blue, and fin whales, and (3) predictable relationships of rorqual whale distribution based on dynamic ocean conditions indicative of upwellings and frontal zones. Indeed, these ocean conditions are likely to provide suitable biological conditions triggering increased prey abundance. Three seasonal models covering the months of December-March (winter model), April-July (spring) and August-November (summer-fall) were generated to predict rorqual whale densities over the Oregon continental shelf (in waters up to 1,500 m deep). As a result, maps of whale densities can be produced on a weekly basis at a resolution of 5 km, which is a scale that will facilitate targeted management of human activities in Oregon. In addition, species-specific models were also produced over the period of high occurrence in the region; that is humpback and blue whales between April and November, and fin whales between August and March.
As we outline in our concluding remarks, this work is not to be considered an end-point, but rather a stepping stone to improve ecological knowledge and produce operational outputs that can be used effectively by managers and stakeholders to prevent spatial conflict between whales and human activities. As of today, the models of fin and blue whale densities are limited by the small number of observations of these two species over the Oregon continental shelf. Yet, we hope that continued data collection via fruitful research partnerships will allow us to improve the robustness of these species-specific predictions in the future. On the other hand, the rorqual models are considered sufficiently robust to continue into the next phase of the OPAL project that aims to assess overlap between whale distribution and Dungeness crab fishing gear to estimate entanglement risk.
The curse (or perhaps the beauty?) of species distribution modeling is that it never ends. There are always new data to be added, new statistical approaches to be tested, and new predictions to be made. The OPAL models are no exception to this rule. They are meant to be improved in future years, thanks to continued helicopter and ship-based survey efforts, and to the addition of new environmental variables meant to better predict whale habitat selection. For instance, Rachel Kaplan’s PhD research specifically aims at understanding the distribution of whales in relation to krill. Her results will feed into the more general efforts to model and predict whale distribution to inform management in Oregon.
This first publication therefore paves the way for more exciting and impactful research!
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Reference
Derville, S., Barlow, D. R., Hayslip, C. E., and Torres, L. G. (2022). Seasonal, Annual, and Decadal Distribution of Three Rorqual Whale Species Relative to Dynamic Ocean Conditions Off Oregon, USA. Front. Mar. Sci. 9, 1–19. doi:10.3389/fmars.2022.868566.
Acknowledgments
We gratefully acknowledge the immense contribution of the United State Coast Guard sectors North Bend and Columbia River who facilitated and piloted our helicopter surveys. We would like to also thank NOAA Northwest Fisheries Science Center for the ship time aboard the R/V Bell M. Shimada. We thank the R/V Bell M. Shimada (chief scientists J. Fisher and S. Zeman) and R/V Oceanus crews, as well as the marine mammal observers F. Sullivan, C. Bird and R. Kaplan. We give special recognition and thanks to the late Alexa Kownacki who contributed so much in the field and to our lives. We also thank T. Buell and K. Corbett (ODFW) for their partnership over the OPAL project. We thank G. Green and J. Brueggeman (Minerals Management Service), J. Adams (US Geological Survey), J. Jahncke (Point blue Conservation), S. Benson (NOAA-South West Fisheries Science Center), and L. Ballance (Oregon State University) for sharing validation data. We thank J. Calambokidis (Cascadia Research Collective) for sharing validation data and for logistical support of the project. We thank A. Virgili for sharing advice and custom codes to produce detection functions.
Dr. KC Bierlich, Postdoctoral Scholar, OSU Department of Fisheries, Wildlife, & Conservation Sciences, Geospatial Ecology of Marine Megafauna (GEMM) Lab
In a previous blog, I discussed the importance of incorporating measurement uncertainty in drone-based photogrammetry, as drones with different sensors, focal length lenses, and altimeters will have varying levels of measurement accuracy. In my last blog, I discussed how to incorporate photogrammetric uncertainty when combining multiple measurements to estimate body condition of baleen whales. In this blog, I will highlight our recent publication in Frontiers in Marine Science (https://doi.org/10.3389/fmars.2022.867258) led by GEMM Lab’s Dr. Leigh Torres, Clara Bird, and myself that used these methods in a collaborative study using imagery from four different drones to compare gray whale body condition on their breeding and feeding grounds (Torres et al., 2022).
Most Eastern North Pacific (ENP) gray whales migrate to their summer foraging grounds in Alaska and the Arctic, where they target benthic amphipods as prey. A subgroup of gray whales (~230 individuals) called the Pacific Coast Feeding Group (PCFG), instead truncates their migration and forages along the coastal habitats between Northern California and British Columbia, Canada (Fig. 1). Evidence from a recent study lead by GEMM Lab’s Lisa Hildebrand (see this blog) found that the caloric content of prey in the PCFG range is of equal or higher value than the main amphipod prey in the Arctic/sub-Arctic regions (Hildebrand et al., 2021). This implies that greater prey density and/or lower energetic costs of foraging in the Arctic/sub-Arctic may explain the greater number of whales foraging in that region compared to the PCFG range. Both groups of gray whales spend the winter months on their breeding and calving grounds in Baja California, Mexico.
Figure 1. The GEMM Lab field team following a Pacific Coast Feeding Group (PCFG) gray whale swimming in a kelp bed along the Oregon Coast during the summer foraging season.
In January 2019 an Unusual Mortality Event (UME) was declared for gray whales due to the elevated numbers of stranded gray whales between Mexico and the Arctic regions of Alaska. Most of the stranded whales were emaciated, indicating that reduced nutrition and starvation may have been the causal factor of death. It is estimated that the population dropped from ~27,000 individuals in 2016 to ~21,000 in 2020 (Stewart & Weller, 2021).
During this UME period, between 2017-2019, the GEMM Lab was using drones to monitor the body condition of PCFG gray whales on their Oregon coastal feeding grounds (Fig. 1), while Christiansen and colleagues (2020) was using drones to monitor gray whales on their breeding grounds in San Ignacio Lagoon (SIL) in Baja California, Mexico. We teamed up with Christiansen and colleagues to compare the body condition of gray whales in these two different areas leading up to the UME. Comparing the body condition between these two populations could help inform which population was most effected by the UME.
The combined datasets consisted of four different drones used, thus different levels of photogrammetric uncertainty to consider. The GEMM Lab collected data using a DJI Phantom 3 Pro, DJI Phantom 4, and DJI Phantom 4 Pro, while Christiansen et al., (2020) used a DJI Inspire 1 Pro. By using the methodological approach described in my previous blog (here, also see Bierlich et al., 2021a for more details), we quantified photogrammetric uncertainty specific to each drone, allowing cross-comparison between these datasets. We also used Body Area Index (BAI), which is a standardized relative measure of body condition developed by the GEMM Lab (Burnett et al., 2018) that has low uncertainty with high precision, making it easier to detect smaller changes between individuals (see blog here, Bierlich et al., 2021b).
While both PCFG and ENP gray whales visit San Ignacio Lagoon in the winter, we assume that the photogrammetry data collected in the lagoon is mostly of ENP whales based on their considerably higher population abundance. We also assume that gray whales incur low energetic cost during migration, as gray whale oxygen consumption rates and derived metabolic rates are much lower during migration than on foraging grounds (Sumich, 1983).
Interestingly, we found that gray whale body condition on their wintering grounds in San Ignacio Lagoon deteriorated across the study years leading up to the UME (2017-2019), while the body condition of PCFG whales on their foraging grounds in Oregon concurrently increased. These contrasting trajectories in body condition between ENP and PCFG whales implies that dynamic oceanographic processes may be contributing to temporal variability of prey available in the Arctic/sub-Arctic and PCFG range. In other words, environmental conditions that control prey availability for gray whales are different in the two areas. For the ENP population, this declining nutritive gain may be associated with environmental changes in the Arctic/sub-Arctic region that impacted the predictability and availability of prey. For the PCFG population, the increase in body condition across years may reflect recovery of the NE Pacific Ocean from the marine heatwave event in 2014-2016 (referred to as “The Blob”) that resulted with a period of low prey availability. These findings also indicate that the ENP population was primarily impacted in the die-off from the UME.
Surprisingly, the body condition of PCFG gray whales in Oregon was regularly and significantly lower than whales in San Ignacio Lagoon (Fig. 2). To further investigate this potential intrinsic difference in body condition between PCFG and ENP whales, we compared opportunistic photographs of gray whales feeding in the Northeastern Chukchi Sea (NCS) in the Arctic collected from airplane surveys. We found that the body condition of PCFG gray whales was significantly lower than whales in the NCS, further supporting our finding that PCFG whales overall have lower body condition than ENP whales that feed in the Arctic (Fig. 3).
Figure 2. Boxplots showing the distribution of Body Area Index (BAI) values for gray whales imaged by drones in San Ignacio Lagoon (SIL), Mexico and Oregon, USA. The data is grouped by phenology group: End of summer feeding season (departure Oregon vs. arrival SIL) and End of wintering season (arrival Oregon vs. departure SIL). The group median (horizontal line), interquartile range (IQR, box), maximum and minimum 1.5*IQR (vertical lines), and outliers (dots) are depicted in the boxplots. The overlaid points represent the mean of the posterior predictive distribution for BAI of an individual and the bars represents the uncertainty (upper and lower bounds of the 95% HPD interval). Note how PCFG whales at then end of the feeding season (dark green) typically have lower body condition (as BAI) compared to ENP whales at the end of the feeding season when they arrive to SIL after migration (light brown).Figure 3. Boxplots showing the distribution of Body Area Index (BAI) values of gray whales from opportunistic images collected from a plane in Northeaster Chukchi Sea (NCS) and from drones collected by the GEMM Lab in Oregon. The boxplots display the group median (horizontal line), interquartile range (IQR box), maximum and minimum 1.5*IQR (vertical lines), and outlies (dots). The overlaid points are the BAI values from each image. Note the significantly lower BAI of PCFG whales on Oregon feeding grounds compared to whales feeding in the Arctic region of the NCS.
This difference in body condition between PCFG and ENP gray whales raises some really interesting and prudent questions. Does the lower body condition of PCFG whales make them less resilient to changes in prey availability compared to ENP whales, and thus more vulnerable to climate change? If so, could this influence the reproductive capacity of PCFG whales? Or, are whales that recruit into the PCFG adapted to a smaller morphology, perhaps due to their specialized foraging tactics, which may be genetically inherited and enables them to survive with reduced energy stores?
These questions are on our minds here at the GEMM Lab as we prepare for our seventh consecutive field season using drones to collect data on PCFG gray whale body condition. As discussed in a previous blog by Dr. Alejandro Fernandez Ajo, we are combining our sightings history of individual whales, fecal hormone analyses, and photogrammetry-based body condition to better understand gray whales’ reproductive biology and help determine what the consequences are for these PCFG whales with lower body condition.
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References
Bierlich, K. C., Hewitt, J., Bird, C. N., Schick, R. S., Friedlaender, A., Torres, L. G., … & Johnston, D. W. (2021). Comparing Uncertainty Associated With 1-, 2-, and 3D Aerial Photogrammetry-Based Body Condition Measurements of Baleen Whales. Frontiers in Marine Science, 1729.
Bierlich, K. C., Schick, R. S., Hewitt, J., Dale, J., Goldbogen, J. A., Friedlaender, A.S., et al. (2021b). Bayesian Approach for Predicting Photogrammetric Uncertainty in Morphometric Measurements Derived From Drones. Mar. Ecol. Prog. Ser. 673, 193–210. doi: 10.3354/meps13814
Burnett, J. D., Lemos, L., Barlow, D., Wing, M. G., Chandler, T., & Torres, L. G. (2018). Estimating morphometric attributes of baleen whales with photogrammetry from small UASs: A case study with blue and gray whales. Marine Mammal Science, 35(1), 108–139.
Christiansen, F., Rodrı́guez-González, F., Martı́nez-Aguilar, S., Urbán, J., Swartz, S., Warick, H., et al. (2021). Poor Body Condition Associated With an Unusual Mortality Event in Gray Whales. Mar. Ecol. Prog. Ser. 658, 237–252. doi:10.3354/meps13585
Hildebrand, L., Bernard, K. S., and Torres, L. G. (2021). Do Gray Whales Count Calories? Comparing Energetic Values of Gray Whale Prey Across Two Different Feeding Grounds in the Eastern North Pacific. Front. Mar. Sci. 8. doi: 10.3389/fmars.2021.683634
Stewart, J. D., and Weller, D. (2021). Abundance of Eastern North Pacific Gray Whales 2019/2020 (San Diego, CA: NOAA/NMFS)
Sumich, J. L. (1983). Swimming Velocities, Breathing Patterns, and Estimated Costs of Locomotion in Migrating Gray Whales, Eschrichtius Robustus. Can. J. Zoology. 61, 647–652. doi: 10.1139/z83-086
Torres, L.G., Bird, C., Rodrigues-Gonzáles, F., Christiansen F., Bejder, L., Lemos, L., Urbán Ramírez, J., Swartz, S., Willoughby, A., Hewitt., J., Bierlich, K.C. (2022). Range-wide comparison of gray whale body condition reveals contrasting sub-population health characteristics and vulnerability to environmental change. Frontiers in Marine Science. 9:867258. https://doi.org/10.3389/fmars.2022.867258
Allison Dawn, GEMM Lab Master’s student, OSU Department of Fisheries, Wildlife and Conservation Sciences, Geospatial Ecology of Marine Megafauna Lab
As the first year of my Master’s is coming to an end, I am excited to have completed the first milestone of writing my research proposal. During the formation of my initial hypotheses, I have been thinking deeply about the potential drivers of zooplankton variability, and how these metrics relate to the Pacific Coast Feeding Group (PCFG) of gray whales foraging in Port Orford. One topic that continues to appear in the literature and throughout my coursework is that of the extreme marine heat wave (MHW) event (2013-2016) in the Pacific Ocean, otherwise known as the “warm blob”. In Dawn’s (now Dr. Barlow!) blog about this MHW, she discusses how whale habitat in California was compressed due to shifts in prey availability, and how this led to an increased number of whale entanglements (Santora et al., 2020). While sea surface temperature (SST) is only one of many factors that influence prey metrics, it is nevertheless an important factor to consider, especially as these heat waves are expected to increase in intensity and duration due to climate change (Joh and Di Lorenzo, 2017). As Lisa mentioned in her last blog, the “warm blob” exacerbated the loss of kelp and sea stars, which is now impacting multiple trophic levels in Port Orford. For my first thesis chapter, I plan to dive into how SST anomalies impact the mosaic of interactions at our study site in Port Orford, and ultimately try to better understand food availability for the PCFG whales.
Cavole et al., 2016 is one of the early comprehensive studies to discuss the impact of the blob on a variety of planktonic marine species. Their sea surface temperature anomaly figure (Figure 1) shows where the anomaly began in 2013 and how it migrated from the Northern Pacific to the Southern Pacific coast.
Figure 1. Plots showing the SST anomalies as the “warm blob” migrated from the Northern Pacific to the Southern Pacific from 2013 until 2016.
Among many other impacts, this MHW caused a reduction in phytoplankton, the major food source for zooplankton. The decline of this food source subsequently caused significant changes in zooplankton populations. Specifically, studies on copepod diversity and biomass show that in a typical California Current System (CCS) there is a seasonal oscillation between warm-water with subtropical species and cold-water with subarctic species. In the winter, the CCS is characterized by a high diversity of subtropical species, due to a southern water source. In the spring, northern cold water advection brings low-diversity, subarctic copepods. While the timing of these shifts is subject to change due to changes in the Pacific Decadal Oscillation (PDO), it remains that these subtropical copepod species are known to be smaller and less nutritious than subarctic copepod species regardless of arrival time (Kintisch, 2015; Leising et al., 2015). However, in 2015, this shift to cold water copepod species did not occur, but rather coastal sampling along the Oregon coast saw subtropical copepod species prevail. Specifically, there were 17 main subtropical copepod species that dominated the species composition while the nutrient-rich arctic species were rare. This occurrence of major copepod shifts alone points to the overall concern for the ecosystem imbalance, to the detriment of top predators like marine mammals and seabirds (the “losers”), and others gaining advantage (the “winners”) (Figure 2).
Figure 2. Figure showing the “losers” (right column) and “winners” (left column) of MHW impacts. Species are organized by trophic level, with top predators at the bottom. Taken from Cavole et al., 2016.
More recent studies found that in certain areas, impacts from the “warm blob” outlived the duration of the larger scale anomaly. In fact, large, positive SST anomalies have lingered on the Oregon shelf until at least September 2017 (Peterson et al., 2017). During this time period, anomalously high abundances of nearshore larval North Pacific krill (Euphausia pacifica) were collected off of the Newport Hydrographic Station (Morgan et al., 2019). Additionally, Brodeur et al. (2019) demonstrate that while indicator species in the nearshore have consistent annual variability, there were substantial differences between community composition between 2011-2014 (low diversity) and 2015-2016 (high diversity). This work also documented the shift from crustacean species (like krill and mysids) to more low-quality gelatinous taxa. As the authors acknowledge, this change in prey community assemblage could have major negative impacts on trophic interactions. This is especially true in the context of whales, as they are not known to rely on gelatinous taxa for energy.
Just like our summer sampling in Port Orford, these studies only provide a “snapshot” of plankton species abundance and composition during a particular time of year. However, even a snapshot can reveal significant changes in prey variability, which then may help us understand the drivers of PCFG habitat utilization. We are actively investigating whether there have been significant changes in the variability of several zooplankton metrics (abundance, distribution, size class, composition) relative to SST changes in Port Orford over the last 6 years (2016-2021).
We will also consider multiple other static and dynamic factors that could influence zooplankton patterns (e.g., upwelling strength, kelp health, tidal height, topography); however, given these documented strong relationships between the zooplankton community and SST across the North Pacific, we hypothesize similar impacts in our Port Orford study region. For example, in certain sampling years, net tows seemed to be comprised of smaller size classes of zooplankton than usual. We will consider how size class availability has changed and if this was driven by SST variability. Gray whales are drawn to this area for enhanced feeding opportunities, and understanding the drivers of zooplankton, especially high quality prey, is a key step to understanding whale use of the area.
Please stay tuned for more updates as we continue working towards the answer to these pressing questions!
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References
Brodeur, R. D., Auth, T. D., & Phillips, A. J. (2019). Major shifts in pelagic micronekton and macrozooplankton community structure in an upwelling ecosystem related to an unprecedented marine heatwave. Frontiers in Marine Science, 6, 212.
Cavole, L. M., Demko, A. M., Diner, R. E., Giddings, A., Koester, I., Pagniello, C. M., … & Franks, P. J. (2016). Biological impacts of the 2013–2015 warm-water anomaly in the Northeast Pacific: winners, losers, and the future. Oceanography, 29(2), 273-285.
Joh, Y., & Di Lorenzo, E. (2017). Increasing coupling between NPGO and PDO leads to prolonged marine heatwaves in the Northeast Pacific. Geophysical Research Letters, 44(22), 11-663.
Kintisch, E. (2015). ‘The Blob’ invades Pacific, flummoxing climate experts.
Leising, A. W., Schroeder, I. D., Bograd, S. J., Abell, J., Durazo, R., Gaxiola-Castro, G., … & Warybok, P. (2015). State of the California Current 2014-15: Impacts of the Warm-Water” Blob”. California Cooperative Oceanic Fisheries Investigations Reports, 56.
Morgan, C. A., Beckman, B. R., Weitkamp, L. A., & Fresh, K. L. (2019). Recent ecosystem disturbance in the Northern California current. Fisheries, 44(10), 465-474.
NOAA Fisheries. 2015b. California Current Integrated Ecosystem Assessment (CCIEA) State of the California Current Report, 2015. NMFS Report 2. Santora, J. A., Mantua, N. J., Schroeder, I. D., Field, J. C., Hazen, E. L., Bograd, S. J., … & Forney, K. A. (2020). Habitat compression and ecosystem shifts as potential links between marine heatwave and record whale entanglements. Nature communications, 11(1), 1-12.
When I was younger, I aspired to be a marine mammal biologist. I thought it was purely about knowing as much about marine mammal species as possible. However, over time and with experience in this field, I have realized that in order to understand a species, you need to have a holistic understanding of its prey, habitat, and environment. When I first applied to be advised by Leigh in the GEMM Lab, I had no idea how much of my time I would spend looking at tiny zooplankton under a microscope, thinking about the different benefits of different habitat types, or reading about oceanographic processes. But these things have been incredibly vital to my research to date and as a result, I now refer to myself as a marine ecologist. This holistic understanding that I am gaining will only grow throughout my PhD as I am broadly looking at the habitat use, site fidelity, and population dynamics of the Pacific Coast Feeding Group (PCFG) of gray whales for my thesis research.
The PCFG display many foraging tactics and occupy several habitat types along the Oregon coast while they spend their summer feeding seasons here (Torres et al. 2018). Here, I will focus on one of these habitats: kelp. When you hear the word kelp, you probably conjure an image of long, thick stalks that reach from the ocean floor to the surface, with billowing fronds waving around (Figure 1a). However, this type is only one of three basic morphologies (Filbee-Dexter & Scheibling 2014) and it is called canopy kelp, which often forms extensive forests. The other two morphologies are stipitate and prostrate kelps. The former forms midwater stands (Figure 1b) while the latter forms low-lying kelp beds (Figure 1c). All three of these morphologies exist on the Oregon coast and create a mosaic of understory and canopy kelp patches that dot our coastline.
Figure 1. Examples of the three different kelp morphologies. a: bull kelp (Nereocystis luetkeana) is a type of canopy kelp and the dominant kelp on the Oregon coast (Source: Oregon Coast Aquarium); b: sea palm (Postelsia palmaeformis) is a type of stipitate kelp that forms mid-water stands (Source: Oregon Conservation Strategy); c: sea cabbage (Saccharina sessilis) is a type of prostrate kelp that is stipeless and forms low-lying kelp beds (Source: Central Coast Biodiversity).
One of the most magnificent things about kelp is that it is not just a species itself, but it provides critical habitat, refuge, and food resources to a myriad of other species due to its high rates of primary production (Dayton 1985). Kelp is often referred to as a foundation species due to all of these critical services it provides. In Oregon, many species of rockfish, which are important commercial and recreational fisheries, use kelp as habitat throughout their life cycle, including as nursery grounds. Lingcod, another widely fished species, forages amongst kelp. A large number of macroinvertebrates can be found in Oregon kelp forests, including anemones, limpets, snails, sea urchins, sea stars, and abalone, to name a fraction of them.
Kelps grow best in cold, nutrient-rich waters (Tegner et al. 1996) and their growth and distribution patterns are highly naturally variable on both temporal and spatial scales (Krumhansl et al. 2016). However, warm water, low nutrient or light conditions, intensive grazing by herbivores, and severe storm activity can lead to the erosion and defoliation of kelp beds (Krumhansl et al. 2016). While these events can occur naturally in cyclical patterns, the frequency of several of these events has increased in recent years, as a result of climate change and anthropogenic impacts. For example, Dawn’s blog discussed increasing marine heatwaves that represent an influx of warm water for a prolonged period of time. In fact, kelps can be useful sentinels of change as they tend to be highly responsive to changes in environmental conditions (e.g., Rogers-Bennet & Catton 2019) and their nearshore, coastal location directly exposes them to human activities, such as pollution, harvesting, and fishing (Bennett et al. 2016).
Due to its foundational role, changes or impacts to kelp can reverberate throughout the ecosystem and negatively affect many other species. As mentioned previously, kelp is naturally highly variable, and like many other ecological processes, undergoes boom and bust cycles. For over four decades, dense, productive kelp forests have been shown to transition to sea urchin barrens, and back again, in natural cycles (Sala et al. 1998;Pinnegar et al. 2000;Steneck et al. 2002; Figure 2). These transitions are called phase shifts. In a healthy, balanced kelp forest, sea urchins typically passively feed on detrital plant matter, such as broken off pieces of kelp fronds that fall to the seafloor. A phase shift occurs when the grazing intensity of sea urchins increases, resulting in them actively feeding on kelp stalks and fronds to a point where the kelp in an area can become greatly reduced, creating an urchin barren. Sea urchin grazing intensity can change for a number of reasons, including reduction in sea urchin predators (e.g., sea otters, sunflower sea stars) or poor kelp recruitment events (e.g., due to warm water temperature). Regardless of the reason, the phases tend to transition back and forth over time. However, there is concern that sea urchin barrens may become an alternative stable state of the subtidal ecosystem from which kelp in an area cannot recover (Filbee-Dexter & Scheibling 2014).
Figure 2. Screenshots from GoPro videos from 2016 (left) and 2018 (right) at the same kayak sampling station in Port Orford showing the difference between a dense kelp forest and what appears to be an urchin barren. (Source: GEMM Lab).
For example, in 2014, bull kelp canopy cover in northern California was reduced by >90% and has not shown signs of recovery since (Rogers-Bennet & Catton 2019; Figure 3). This massive decline was attributed to two major events: 1) the onset of sea star wasting disease (SSWD) in 2013 and 2) the “warm blob” of 2014-2016. SSWD affected over 20 sea star species along the coast from Mexico to Alaska, with the predatory sunflower sea star, which consumes purple sea urchins, most affected, including population declines of 80-100% along the coast (Harvell et al. 2019). Following this SSWD outbreak, the “warm blob”, which was an extreme marine heatwave in the Pacific Ocean, caused ocean temperatures to spike. These two events allowed purple sea urchin populations to grow unchecked by their predators, and created nutrient-poor and warm water conditions, which limited kelp growth and productivity. Intense grazing on bull kelp by growing urchin populations resulted in the >90% reduction in bull kelp canopy cover and has left behind widespread urchin barrens instead (Rogers-Bennet & Catton 2019). Consequently, there have been ecological and economic impacts on the ecosystem and communities in northern California. Without bull kelp, red abalone and red sea urchin populations starved, leading to a subsequent loss of the recreational red abalone (estimated value of $44 million/year) and commercial red urchin fisheries in northern California (Rogers-Bennet & Catton 2019).
Figure 3. Surface kelp canopy area pre- and post-impact from sites in Sonoma and Mendocino counties, northern California from aerial surveys (2008, 2014-2016). Figure and figure caption taken from Rogers-Bennett & Catton (2019).
As I mentioned earlier, while phase shifts between kelp forests and urchin barrens are common cycles, the intensity of the events described above in northern California are an example of sea urchin barrens potentially becoming a stable state of the subtidal ecosystem (Filbee-Dexter & Scheibling 2014). Given that marine heatwaves are only expected to increase in intensity and frequency in the future (Frölicher et al. 2018), the events documented in northern California may not be an isolated incidence.
Considering that parts of the Oregon coast, particularly the southern portion, are very similar to northern California biogeographically, and that it was not exempt from the “warm blob”, similar changes in kelp forests may be occurring along our coast. There are many individuals and groups that are actively working on this issue to examine potential impacts to kelp and the species that depend on the services it provides. For more information, check out the Oregon Kelp Alliance.
Figure 4. A gray whale surfaces in a large kelp bed during a foraging bout along the Oregon coast. (Source: GEMM Lab).
So, what does all of this information have to do with gray whales? Given their affinity for kelp habitats (Figure 4) and their zooplankton prey that aggregates there, changes to kelp ecosystems may affect gray whale health and ecology. This aspect of the complex kelp trophic web has not been examined to date; thus one of my PhD chapters focuses on the response of gray whales to changing kelp ecosystems along the southern Oregon coast. To do this, I am examining 6 years of data collected during the TOPAZ/JASPER project in Port Orford, to look at the relationships between kelp health, sea urchin density, zooplankton abundance, and gray whale foraging effort over space and time. Documenting impacts of changing kelp forests on gray whales is important to assist management efforts as healthy and abundant kelp seems critical in providing ample food opportunities for these iconic Pacific Northwest marine predators.
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References
Bennett S, et al. The ‘Great Southern Reef’: Social, ecological and economic value of Australia’s neglected kelp forests. Marine and Freshwater Research 67:47-56.
Dayton PK (1985) Ecology of kelp communities. Annual Review of Ecology and Systematics 16:215-245.
Filbee-Dexter K, Scheibling RE (2014) Sea uechin barrens as alternative stable states of collapsed kelp ecosystems. Marine Ecology Progress Series 495:1-25.
Frölicher TL, Fischer EM, Gruber N (2018) Marine heatwaves under global warming. Nature 560:360-364.
Harvell CD, et al. (2019) Disease epidemic and a marine heat wave are associated with the continental-scale collapse of a pivotal predator (Pycnopodia helianthoides). Science Advances 5(1) doi:10.1126/sciadv.aau7042.
Krumhansl KA, et al. (2016) Global patterns of kelp forest change over the past half-century. Proceedings of the National Academy of Sciences of the United States of America 113(48):13785-13790.
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