Tag: Acoustics

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

By Natalie Nickells, visiting PhD Student, British Antarctic Survey

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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Bibliography

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Sonar savvy: using echo sounders to characterize zooplankton swarms

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

I’m Natalie Chazal, the GEMM Lab’s newest PhD student! This past spring I received my MS in Biological and Agricultural Engineering with Dr. Natalie Nelson’s Biosystems Analytics Lab at North Carolina State University. My thesis focused on using shellfish sanitation datasets to look at water quality trends in North Carolina and to forecast water quality for shellfish farmers in Florida. Now, I’m excited to be studying gray whales in the GEMM Lab!

Since the beginning of the Fall term, I’ve jumped into a project that will use our past 8 years of sonar data collected using a Garmin echo sounder during the GRANITE project work with gray whales off the Newport, OR coast. Echo sounder data is commonly used recreationally to detect bottom depth and for finding fish and my goal is to use these data to assess relative prey abundance at gray whale sightings over time and space. 

There are also scientific grade echo sounders that are built to be incredibly precise and very exact in the projection and reception of the sonar pulses. Both types of echosounders can be used to determine the depth of the ocean floor, structures within the water column, and organisms that are swimming within the sonar’s “cone” of acoustic sensing. The precision and stability of the scientific grade equipment allows us to answer questions related to the specific species of organisms, the substrate type at the sea floor, and even animal behavior. However, scientific grade echo sounders can be expensive, overly large for our small research vessel, and require expertise to operate. When it comes to generalists, like gray whales, we can answer questions about relative prey abundances without the use of such exact equipment (Benoit-Bird 2016; Brough 2019). 

While there are many variations of echo sounders that are specific to their purpose, commercially available, single beam echo sounders generally function in the same way (Fig. 1). First, a “ping” or short burst of sound at a specific frequency is produced from a transducer. The ping then travels downward and once it hits an object, some of the sound energy bounces off of the object and some moves into the object. The sound that bounces off of the object is either reflected or scattered. Sound energy that is either reflected or scattered back in the direction of the source is then received by the transducer. We can figure out the depth of the signal using the amount of travel time the ping took (SeaBeam Instruments 2000).

Figure 1. Diagram of how sound is scattered, reflected, and transmitted in marine environments (SeaBeam Instruments, 2000).

The data produced by this process is then displayed in real-time, on the screen on board the boat. Figure 2 is an example of the display that we see while on board RUBY (the GEMM Lab’s rigid-hull inflatable research boat): 

Figure 2. Photo of the echo sounder display on board RUBY. On the left is a map that is used for navigation. On the right is the real time feed where we can see the ocean bottom shown as the bright yellow area with the distinct boundary towards the lower portion of the screen. The more orange layer above that, with the  more “cloudy” structure  is a mysid swarm.

Once off the boat, we can download this echo sounder data and process it in the lab to recreate echograms similar to those seen on the boat. The echograms are shown with the time on the x-axis, depth on the y-axis, and are colored by the intensity of sound that was returned (Fig. 3). Echograms give us a sort of picture of what we see in the water column. When we look at these images as humans, we can infer what these objects are, given that we know what habitat we were in. Below (Fig. 3) are some example classifications of different fish and zooplankton swarms and what they look like in an echogram (Kaltenberg 2010).

Figure 3. Panel of echogram examples, from Kaltenberg 2010, for different fish and zooplankton aggregations that have been classified both visually (like we do in real time on the boat) as well as statistically (which we hope to do with the mysid aggregations). 

For our specific application, we are going to focus on characterizing mysid swarms, which are considered to be the main prey target of PCFG whales in our study area. With the echograms generated by the GRANITE fieldwork, we can gather relative mysid swarm densities, giving us an idea of how much prey is available to foraging gray whales. Because we have 8 years of GRANITE echosounder data, with 2,662 km of tracklines at gray whale sightings, we are going to need an automated process. This demand is where image segmentation can come in! If we treat our echograms like photographs, we can train models to identify mysid swarms within echograms, reducing our echogram processing load. Automating and standardizing the process can also help to reduce error. 

We are planning to utilize U-Nets, which are a method of image segmentation where the image goes through a series of compressions (encoders) and expansions (decoders), which is common when using convolutional neural nets (CNNs) for image segmentation. The encoder is generally a pre-trained classification network (CNNs work very well for this) that is used to classify pixels into a lower resolution category. The decoder then takes the low resolution categorized pixels and reprojects them back into an image to get a segmented mask. What makes U-Nets unique is that they re-introduce the higher resolution encoder information back into the decoder process through skip connections. This process allows for generalizations to be made for the image segmentation without sacrificing fine-scale details (Brautaset 2020; Ordoñez 2022; Slonimer 2023; Vohra 2023).

Figure 4. Diagram of the encoder, decoder architecture for U-Nets used in biomedical image segmentation. Note the skip connections illustrated by the gray lines connecting the higher resolution image information on the left, with the decoder process on the right (Ronneberger 2015)

What we hope to get from this analysis is an output image that provides us only the parts of the echogram that contain mysid swarms. Once the mysid swarms are found within the echograms, we can use both the intensity and the size of the swarm in the echogram as a proxy for the relative abundance of gray whale prey. We plan to quantify these estimates across multiple spatial and temporal scales, to link prey availability to changing environmental conditions and gray whale health and distribution metrics. This application is what will make our study particularly unique! By leveraging the GRANITE project’s extensive datasets, this study will be one of the first studies that quantifies prey variability in the Oregon coastal system and uses those results to directly assess prey availability on the body condition of gray whales. 

However, I have a little while to go before the data will be ready for any analysis. So far, I’ve been reading as much as I can about how sonar works in the marine environment, how sonar data structures work, and how others are using recreational sonar for robust analyses. There have been a few bumps in the road while starting this project (especially with disentangling the data structures produced from our particular GARMIN echosounder), but my new teammates in the GEMM Lab have been incredibly generous with their time and knowledge to help me set up a strong foundation for this project, and beyond. 

References

  1. Kaltenberg A. (2010) Bio-physical interactions of small pelagic fish schools and zooplankton prey in the California Current System over multiple scales. Oregon State University, Dissertation. https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/z890rz74t
  2. SeaBeam Instruments. (2000) Multibeam Sonar Theory of Operation. L-3 Communications, East Walpole MA. https://www3.mbari.org/data/mbsystem/sonarfunction/SeaBeamMultibeamTheoryOperation.pdf
  3. Benoit-Bird K., Lawson G. (2016) Ecological insights from pelagic habitats acquired using active acoustic techniques. Annual Review of Marine Science. https://doi.org/10.1146/annurev-marine-122414-034001
  4. Brough T., Rayment W., Dawson S. (2019) Using a recreational grade echosounder to quantify the potential prey field of coastal predators. PLoS One. https://doi.org/10.1371/journal.pone.0217013
  5. Brautaset O., Waldeland A., Johnsen E., Malde K., Eikvil L., Salberg A, Handegard N. (2020) Acoustic classification in multifrequency echosounder data using deep convolutional neural networks. ICES Journal of Marine Science 77, 1391–1400. https://doi.org/10.1093/icesjms/fsz235
  6. Ordoñez A., Utseth I., Brautaset O., Korneliussen R., Handegard N. (2022) Evaluation of echosounder data preparation strategies for modern machine learning models. Fisheries Research 254, 106411. https://doi.org/10.1016/j.fishres.2022.106411
  7. Slonimer A., Dosso S., Albu A., Cote M., Marques T., Rezvanifar A., Ersahin K., Mudge T., Gauthier S., (2023) Classification of Herring, Salmon, and Bubbles in Multifrequency Echograms Using U-Net Neural Networks. IEEE Journal of Oceanic Engineering 48, 1236–1254. https://doi.org/10.1109/JOE.2023.3272393
  8. Ronneberger O., Fischer P., Brox T. (2015) U-Net: Convolutional Networks for Biomedical Image Segmentation. https://doi.org/10.48550/arXiv.1505.04597

A Journey From Microbiology to Macrobiology

Mariam Alsaid, University of California Berkeley, GEMM Lab REU Intern

My name is Mariam Alsaid and I am currently a 5th year undergraduate transfer student at the University of California, Berkeley. Growing up on the small island of Bahrain, I was always minutes away from the water and was enraptured by the creatures that lie beneath the surface. Despite my long-standing interest in marine science, I never had the opportunity to explore it until just a few months ago. My professional background up until this point was predominantly in soil microbiology through my work with Lawrence Berkeley National Laboratory, and I was anxious about how I would switch directions and finally be able to pursue my main passion. For this reason, I was thrilled by my acceptance into the OSU Hatfield Marine Science Center’s REU program this year, which led to my exciting collaboration with the GEMM Lab. It was kind of a silly transition to go from studying bacteria, one of the smallest organisms on earth, to whales, who are the largest.

My project this summer focused on sei whale acoustic occurrence off the coast of Oregon. “What’s a sei whale?” is a question I heard a lot throughout the summer and is one that I had to Google myself several times before starting my internship. Believe it or not, sei whales are the third largest rorqual in the world but don’t get much publicity because of their small population sizes and secretive behavior. The commercial whaling industry of the 19th and 20th centuries did a number on sei whale populations globally, rendering them endangered. In consequence, little research has been conducted on their global range, habitat use, and behavior since the ban of commercial whaling in 1986 (Nieukirk et al. 2020). Additionally, sei whales are relatively challenging to study because of their physical similarities to the fin whale, and acoustic similarities to other rorqual vocalizations, most notably blue whale D-calls and fin whale 40 Hz calls. As of today, published literature indicates that sei whale acoustic presence in the Pacific Ocean is restricted to Antarctica, Chile, Hawaii, and possibly British Columbia, Canada (Mcdonald et al. 2005; Espanol-Jiminez et al. 2019; Rankin and Barlow, 2012; Burnham et al. 2019). The idea behind this research project was sparked by sparse visual sightings of sei whales by research cruises conducted by the Marine Mammal Institute (MMI) in recent years (Figure 1). This raised questions about if sei whales are really present in Oregon waters (and not just misidentified fin whales) and if so, how often?

Figure 1. Map of sei whale visual sightings off the coast of Oregon, colored by MMI Lab research cruise, and the location of the hydrophone at NH45 (white star).

A hydrophone, which is a fancy piece of equipment that records continuous underwater sound, was deployed 45 miles offshore of Newport, OR between October of 2021 and December of 2022. My role this summer was to use this acoustic data to determine whether sei whales are hanging out in Oregon or not. Acoustic data was analyzed using the software Raven Pro, which allowed me to visualize sound in the form of spectrograms (Fig. 2). From there, my task was to select signals that could potentially be sei whale calls. It was a hurdle familiarizing myself with sei whale vocalizations while also keeping in mind that other species (e.g., blue and fin whales) may produce similar sounding (and looking in the spectrograms) calls. For this reason, I decided to establish confidence levels based on published sei whale acoustic research that would help me classify calls with less bias. Vocalizations produced by sei whales are characterized by low frequency, broadband, downsweeps. Sei whales can be acoustically distinguished from other whales because of their tendency to produce uniform groups of calls (typically in doublets and triplets) in a short timeframe. This key finding allowed me to navigate the acoustic data with more ease.

The majority of the summer was spent slowly scanning through the months of data at 5-minute increments. As you can imagine, excitement varied by day. Some days I would find insanely clear signals of blue, fin, and humpback whales and other days I would find nothing. The major discovery and the light at the end of the tunnel was the SEI WHALES!!! I detected numerous high quality sei whale calls throughout the study period with peaks in October and November (but a significantly higher peak in occurrence in 2022 versus 2021). I also encountered a unique vocalization type in fall of 2022, consisting of a very long series of repeated calls that we called “multiplet”, rather than doublets or triplets that is more typical of sei whales (Fig. 3). Lastly, I found no significant diel pattern in sei whale vocalization, indicating that these animals call at any hour of the day. More research needs to go into this project to better estimate sei whale occurrence and understand their behavior in Oregon but this preliminary work provides a great baseline into what sei whales sound like in this part of the world. In the future, the GEMM lab intends on implementing more hydrophone data and work on developing an automated detection system that would identify sei whale calls automatically.

Figure 2. Spectrogram of typical sei whale calls detected in acoustic data
Figure 3. Spectrogram of unique sei whale multiplet call type
Figure 4. My first time conducting fieldwork! I spent a few mornings assisting Dr. Rachel Orben’s group in surveying murre and cormorant nests (thanks to my good friend Jacque McKay :))

My experience this summer was so formative for me. As someone who has been an aspiring marine biologist for so long, I am so grateful for my experience working with the GEMM Lab alongside incredible scientists who are equally passionate about studying the mysteries of the ocean. This experience has also piqued my interest in bioacoustics and I plan on searching for other opportunities to explore the field in the future. Aside from growing professionally, I learned that I am more capable of tackling and overcoming obstacles than I had thought. I was afraid of entering a field that I knew so little about and was worried about failing and not fitting in. My anxieties were overshadowed by the welcoming atmosphere at Hatfield and I could not have asked for better people to work with. As I was searching for sei whale calls this summer, I suppose that I was also unintentionally searching for my voice as a young scientist in a great, blue field.

Figure 5. My mentor, Dr. Dawn Barlow, and I with my research poster at the Hatfield Marine Science Center Coastal Intern Symposium

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References:

Nieukirk, S. L., Mellinger, D. K., Dziak, R. P., Matsumoto, H., & Klinck, H. (2020). Multi-year occurrence of sei whale calls in North Atlantic polar waters. The Journal of the Acoustical Society of America, 147(3), 1842–1850. https://doi.org/10.1121/10.0000931

McDonald, M. A., Calambokidis, J., Teranishi, A. M., & Hildebrand, J. A. (2001). The acoustic calls of blue whales off California with gender data. The Journal of the Acoustical Society of America, 109(4), 1728–1735. https://doi.org/10.1121/1.1353593

Español-Jiménez, S., Bahamonde, P. A., Chiang, G., & Häussermann, V. (2019). Discovering sounds in Patagonia: Characterizing sei whale (<i>Balaenoptera borealis</i>) downsweeps in the south-eastern Pacific Ocean. Ocean Science, 15(1), 75–82. https://doi.org/10.5194/os-15-75-2019

Rankin, S., & Barlow, J. (2007). VOCALIZATIONS OF THE SEI WHALE BALAENOPTERA BOREALIS OFF THE HAWAIIAN ISLANDS. Bioacoustics, 16(2), 137–145. https://doi.org/10.1080/09524622.2007.9753572

Burnham, R. E., Duffus, D. A., & Mouy, X. (2019). The presence of large whale species in Clayoquot Sound and its offshore waters. Continental Shelf Research, 177, 15–23. https://doi.org/10.1016/j.csr.2019.03.004

SST, EKE, SSH: Wading Through the Alphabet Soup of Oceanographic Parameters related to Deep-Dwelling Odontocetes

By: Marissa Garcia, PhD Student, Cornell University, Department of Natural Resources and the Environment, K. Lisa Yang Center for Conservation Bioacoustics

Predator-Prey Inference: A Tale as Old as Time

It’s a tale as old as time: where there’s prey, there’ll be predators.

As apex predators, cetaceans act as top-down regulators of ecosystem function. While baleen whales act as “ecosystem engineers,” facilitating nutrient cycling in the ocean (Roman et al., 2014), toothed whales, or “odontocetes,” can impart keystone-level effects — that is, they disproportionately control the marine community’s food-web structure (Valls, Coll, & Christensen, 2015). The menus of prey vary widely by species — ranging from mircronekton to fish to squid – and by extension, vary widely across trophic levels.

So, it naturally follows the old adage: where there’s an abundance of prey, there’ll be an abundance of cetaceans. Yet, creating models that accurately depict this predator-prey relationship is, perhaps unsurprisingly, not as straightforward.

Detecting the ‘Predator’ Half of the Equation

Scientists have successfully documented cetacean presence drawing upon a myriad of methods, each bearing its unique advantages and limitations.

Visual surveys — spanning viewpoints from land, boats, and air — can attain precise spatial data and species ID. However, this data can be constrained by “availability bias” — that is, scientists can only observe cetaceans visible at the surface, not those obscured by the ocean’s depths. Species that spend less time near the surface are more likely to elude the observer’s line of sight, thereby being missed in the data. Consequently, visual surveys have historically undersampled deep-diving species. For instance, since its discovery by western science in 1945, the Hubb’s beaked whale (Mesoplodon carlshubbi) has only been observed alive twice by OSU MMI’s very own Bob Pitman, once in 1994 and another time in 2021.

Scientists have also been increasingly conducting acoustic surveys to document cetacean presence. Acoustic recorders can “hear” each cetacean species at different ranges. Baleen whales, which bellow low-frequency calls, can be heard as far as across ocean basins (Munk et al., 1994). Toothed whales whistle, echolocate, and buzz at frequencies so high they’re considered ultrasonic. But it comes at a trade-off: high-frequency sounds have shorter wavelengths, meaning they are heard across smaller ranges. This high variability, which scientists refer to as “detection range,” translates to not always knowing where the vocalizing cetacean that was recorded is: as such, acoustic data can lack the high-resolution spatial precision often achieved by visual surveys. Nevertheless, acoustic data triumphs in temporal extent, sometimes managing to record continuously at six months at a time. Additionally, animals can elude visual detection in poor weather conditions or if they have a cryptic surface expression, but detected in acoustic surveys (e.g., North Atlantic right whales (Eubalaena glacialis) (Ganley, Brault, & Mayo, 2019; Clark et. al, 2010). Thus, acoustic surveys may be especially optimal for recording elusive deep-dwellers that occupy the often rough Oregon waters, such as beaked whales, the focus of my research in collaboration with the GEMM Lab.

Figure 1: HALO Project researchers Marissa Garcia (left; Yang Center via Cornell) and Imogen Lucciano (right; OSU MMI) among three Rockhopper acoustic recording units, ahead of deployment off the Oregon coast. Credit: Marissa Garcia.

Detecting the ‘Prey’ Half of the Equation

Prey can be measured by numerous methods. Most directly, prey can be measured “in-situ” — that is, prey is collected directly from the site where the cetaceans are detected or observed. A 2020 study combined fish trawls with a towed hydrophone array to identify which fish species odontocetes along the continental shelf of West Ireland (e.g., pilot whales, sperm whales, and Sowerby’s beaked whales) were feasting; the results found that odontocetes primarily fed upon mesopelagic fish and cephalopods (Breen et al., 2020). While trawls can glean species ID of prey, associating this prey data with depth and biomass can prove challenging.

Alternatively, prey can be detected via active acoustics. Echosounders release an acoustic signal that descends through the water column and then echoes back once it hits a sound-scattering organism. Beaked whales forage within deep scattering layers typically composed of myctophid fish and squid, both of which can echo back echosounder pings (Hazen et al., 2011). Thus, echosounder data can map prey density through the water column. When mapping prey density of beaked whales, Hazen et al. 2011 found a strong positive correlation among prey density, ocean vertical structure, and clicks primarily produced while foraging – suggesting beaked whales forage at depth when encountering large, multi-species aggregations of prey.

Figure 2: An example of prey mapping via a Simrad EK60 120 kHz split-beam echosounder. Credit: Rachel Kaplan (OSU MMI) via the HALO Project.

Most relevant to the HALO Project, prey is measured using proximate indices, which are more easily quantifiable metrics of ocean conditions, such as collected from ships via CTD casts or via satellite imagery, that are indirectly related to prey abundance. CTD data can provide information related to the water column structure, including depth and strength of the thermocline, depth of the mixed layer, depth of the euphotic zone, and total chlorophyll concentration in the euphotic zone (Redfern et al. 2006). Satellite imagery can characterize the dynamic patterns of the surface later, including sea surface temperature (SST), salinity, surface chlorophyll a, sea surface height (SSH), and sea surface currents (Virgili et al., 2022; Redfern et al., 2006). Ocean model data products can, such as the Regional Ocean Modeling System (ROMS) which models how an oceanic region of interest responds to physical processes, can provide water column variables related to eddy kinetic energy (EKE) and average temperature gradients (Virgili et al., 2022). In the case of my research with the HALO Project, we will be using oceanographic data collected through the Ocean Observatories Initiative to inform odontocete species distribution models.

Connecting the Dots: Linking Deep-Dwelling Top Predators and Prey

While scientists have made significant advances with collecting both cetacean and prey data, connecting the dots between the ecology of deep-dwelling odontocetes and the oceanographic parameters indicative of their prey still remains a challenge.

In the absence of in situ sampling, species distribution models of marine top predators often derive proxies for “prey data” from static bathymetric and dynamic surface water variables (Virgili et al., 2022). However, surface variables may be irrelevant to toothed whale prey inhabiting great depths (Virgili et al., 2022). Within the HALO Project, the deepest Rockhopper acoustic recording unit is recording odontocetes at nearly 3,000 m below the surface, putting into question the relevance of oceanographic parameters collected at the surface.

Figure 3: Schematic depicting the variation among different zones in the water column. Conditions at the surface may not represent conditions at depth. Credit: Barbara Ambrose, NOAA via NOAA Ocean Explorer.

In my research, I am setting out to estimate which oceanographic variables are optimal for explaining deep-dwelling odontocete presence. A 2022 study using visual survey data found that surface, subsurface, and static variables best explained beaked whale presence, whereas only surface and deep-water variables – not static – best explained sperm whale presence (Virgili et al., 2022). These results are associated with each species’ distinct foraging ecologies; beaked whales may truly only rely on organisms that live near the seabed, whereas sperm whales also feast upon meso-to-bathypelagic organisms, so they may be more sensitive to changes in water column conditions (Virgili et al., 2022). This study expanded the narrative: deep-water variables can also be key to predicting deep-dwelling odontocete presence. The oceanographic variables must be tailored to the ecology of each species of interest.

In the months ahead, I seek to build on this study by investigating which parameters best predict odontocete presence using an acoustic approach instead — I am looking forward to the results to come!

References

Breen, P., Pirotta, E., Allcock, L., Bennison, A., Boisseau, O., Bouch, P., Hearty, A., Jessopp, M., Kavanagh, A., Taite, M., & Rogan, E. (2020). Insights into the habitat of deep diving odontocetes around a canyon system in the northeast Atlantic ocean from a short multidisciplinary survey. Deep-Sea Research. Part I, Oceanographic Research Papers, 159, 103236. https://doi.org/10.1016/j.dsr.2020.103236

Clark, C.W., Brown, M.W., & Corkeron, P. (2010). Visual and acoustic surveys

for North Atlantic right whales, Eubalaena glacialis, in Cape Cod Bay, Massachusetts, 2001–2005: Management implications. Marine Mammal Science, 26(4), 837-854.

Ganley, L.C., Brault, S., & Mayo, C.A. (2019). What we see is not what there is: Estimating North Atlantic right whale Eubalaena glacialis local abundance. Endangered Species Research, 38, 101-113.

Hazen, E. L., Nowacek, D. P., St Laurent, L., Halpin, P. N., & Moretti, D. J. (2011). The relationship among oceanography, prey fields, and beaked whale foraging habitat in the Tongue of the Ocean. PloS One, 6(4), e19269–e19269.

Munk, W. H., Spindel, R. C., Baggeroer, A., & Birdsall, T. G. (1994). The Heard Island Feasibility Test. The Journal of the Acoustical Society of America, 96(4), 2330–2342. https://doi.org/10.1121/1.410105

Redfern, J. V., Ferguson, M. C., Becker, E. A., Hyrenbach, K. D., Good, C., Barlow, J., Kaschner, K., Baumgartner, M. F., Forney, K. A., Ballance, L. T., Fauchald, P., Halpin, P., Hamazaki, T., Pershing, A. J., Qian, S. S., Read, A., Reilly, S. B., Torres, L., & Werner, F. (2006). Techniques for cetacean–habitat modeling. Marine Ecology. Progress Series (Halstenbek), 310, 271–295.

Roman, J., Estes, J. A., Morissette, L., Smith, C., Costa, D., McCarthy, J., Nation, J., Nicol, S., Pershing, A., & Smetacek, V. (2014). Whales as marine ecosystem engineers. Frontiers in Ecology and the Environment, 12(7), 377–385.

Valls, A., Coll, M., & Christensen, V. (2015). Keystone species: toward an operational concept for marine biodiversity conservation. Ecological Monographs, 85(1), 29–47.

Virgili, A., Teillard, V., Dorémus, G., Dunn, T. E., Laran, S., Lewis, M., Louzao, M., Martínez-Cedeira, J., Pettex, E., Ruiz, L., Saavedra, C., Santos, M. B., Van Canneyt, O., Vázquez Bonales, J. A., & Ridoux, V. (2022). Deep ocean drivers better explain habitat preferences of sperm whales Physeter macrocephalus than beaked whales in the Bay of Biscay. Scientific Reports, 12(1), 9620–9620.

Clicks, buzzes, and rasps: How the MMPA has spurred what we know about beaked whale acoustic repertoire

By Marissa Garcia, PhD Student, Cornell University, Department of Natural Resources and the Environment, K. Lisa Yang Center for Conservation Bioacoustics

In October 1972, the tides turned for U.S. environmental politics: the Marine Mammal Protection Act (MMPA) was passed. Its creation ushered in a new flavor of conservation and management. With phrases like “optimum sustainable population” baked into its statutory language, it marked among the first times that ecosystem-based management — an approach which directly calls upon knowledge of ecology to inform action — was required by law (Ray and Potter 2022). Transitioning from reductionist, species-siloed policies, the MMPA instead placed the interdependency of species at the core of ecosystem function and management. 

Beyond deepening the role of science on Capitol Hill, the MMPA’s greatest influence may have been spurred by the language that prohibited “the taking and importation of marine mammals” (16 U.S.C. 1361). Because the word “taking” is multivalent, it carries on its back many interpretations. “Taking” a marine mammal is not limited to intentionally hunting or killing them, or even accidental bycatch. “Taking” also includes carelessly operating a boat when a marine mammal is present, feeding a marine mammal in the wild, or tagging a marine mammal without the appropriate scientific permit. “Taking” a marine mammal can also extend to the fatal consequences caused by noise pollution — not intent, but incident (16 U.S.C. 1362).

The latter circumstances remain reverberant for the U.S. Navy. To comply with the MMPA, they are granted “incidental, but not intentional, taking of small numbers of marine mammals….[when] engag[ing] in a specified activity (other than commercial fishing)” (87 FR 33113). So, if the sonar activities required for national security exercises adversely impact marine mammals, the Navy has a bit of leeway but is still expected to minimize this impact. To further mitigate this potential harm, the Navy thus invests heavily in marine mammal research. (If you are interested in learning more about how the Navy has influenced the trajectory of oceanographic research more broadly, you may find this book interesting.) 

Beaked whales are an example of a marine mammal we know much about due to the MMPA’s call for research when incidental take occurs. Three decades ago, many beaked whales stranded ashore following a series of U.S. Navy sonar exercises. Since then, the Navy has flooded research dollars toward better understanding beaked whale hearing, vocal behavior, and movements (e.g., Klinck et al. 2012). Through these efforts, a deluge of research charged with developing effective tools to acoustically monitor and conserve beaked whales has emerged.  

These studies have laid the foundation for my Ph.D. research, which is dedicated to the Holistic Assessment of Living marine resources off Oregon (HALO) project. Through both visual and acoustic surveys, the HALO project’s mission is to understand how changes in ocean conditions — driven by global climate change — influence living marine resources in Oregon waters. 

In my research specifically, I aim to learn more about beaked whales off the Oregon coast. Beaked whales represent nearly a fourth of cetacean species alive today, with at least 21 species recorded to date (Roman et al. 2013). Even so, 90% of beaked whales are considered data deficient: we lack enough information about them to confidently describe the state of their populations or decide upon effective conservation action. 

Much remains to be learned about beaked whales, and I aim to do so by eavesdropping on them. By referring to the “acoustic repertoire” of beaked whales — that is, their vocalizations and corresponding behaviors — I aim to tease out their vocalizations from the broader ocean soundscape and understand how their presence in Oregon waters varies over time. 

Beaked whales are notoriously cryptic, elusive to many visual survey efforts like those aboard HALO cruises. In fact, some species have only been identified via carcasses that have washed ashore (Moore and Barlow 2013). Acoustic studies have elucidated ecological information (beaked whales forage at night at seamounts summits; Johnston et al. 2008) and have also introduced promising population-level monitoring efforts (beaked whales have been acoustically detected in areas with a historical scarcity of sightings; Kowarski et al. 2018). Their deep-diving nature often renders them inconspicuous, and they forage at depths between 1,000 and 2,000 m, on dives as long as 90 minutes (Moore and Barlow 2013; Klinck et al. 2012). Their echolocation clicks are produced at frequencies within the hearing range of killer whales, and previous studies have suggested that Blainville’s beaked whales are only vocally active during deep foraging dives and not at the surface, possibly to prevent being acoustically detected by predatory killer whales. Researchers refer to this phenomenon as “acoustic crypsis,” or when vocally-active marine mammals are strategically silent to avoid being found by potential predators (Aguilar de Soto et al. 2012).

We expect to see evidence of Blainville’s beaked whales in Oregon waters, as well as Baird’s, Cuvier’s, Stejneger’s, Hubb’s, and other beaked whale species. Species-specific echolocation clicks were comprehensively described a decade ago in Baumann-Pickering et al. 2013 (Figure 1). While this study laid the groundwork for species-level beaked whale acoustic detection, much more work is still needed to describe their acoustic repertoire with higher resolution detail. For example, though Hubb’s beaked whales live in Oregon waters, their vocal behavior remains scantly defined.

Figure 1: Baird’s, Blainville’s, Cuvier’s, and Stejneger’s beaked whales are among the most comprehensively acoustically described beaked whales inhabiting central Oregon waters, though more work would improve accuracy in species-specific acoustic detection. Credit: Marissa Garcia. Infographic draws upon beaked whale imagery from NOAA Fisheries and spectrograms and acoustical statistics published in Baumann-Pickering et al. 2013.

The HALO project seeks to add a biological dimension to the historical oceanographic studies conducted along the Newport Hydrographic (NH) line ever since the 1960s (Figure 2). Rockhopper acoustic recording units are deployed at sites NH 25, NH 45, and NH 65. The Rockhopper located at site NH 65 is actively recording on the seafloor about 2,800 m below the surface. Because beaked whales tend to be most vocally active at these deep depths, we will first dive into the acoustic data on NH 65, our deepest unit, in hopes of finding beaked whale recordings there.

Figure 2: The HALO project team conducts quarterly visual surveys along the NH line, spanning between NH 25 and NH 65. Rockhopper acoustic recording units continuously record at the NH 25, NH 45, and NH 65 sites. Credit: Leigh Torres.

Beaked whales’ acoustic repertoire can be broadly split into four primary categories: burst pulses (aka “search clicks”), whistles, buzz clicks, and rasps. Beaked whale search clicks, which are regarded as burst pulses when produced in succession, have distinct qualities: their upswept frequency modulation (meaning the frequency gets higher within the click), their long duration especially when compared to other delphinid clicks, and a consistent interpulse interval  which is the time of silence between signals (Baumann-Pickering et al. 2013). Acoustic analysts can identify different species based on how the frequency changes in different burst pulse sequences (Baumann-Pickering et al. 2013; Figure 1). For this reason, when I conduct my HALO analyses, I intend to automatically detect beaked whale species using burst pulses, as they are the best documented beaked whale signal, with unique signatures for each species. 

In the landscape of beaked whale acoustics, the acoustic repertoire of Blainville’s beaked whales (Mesoplodon densirostris) — a species of focus in my HALO analyses — is especially well defined. Blainville’s beaked whale whistles have been recorded up to 900 m deep, representing the deepest whistle recorded for any marine mammal to date in the literature (Aguilar de Soto et al. 2012). While Blainville’s beaked whales only spend 40% of their time at depths below 170 m, two key vocalizations occur at these depths: whistles and rasps. While they remain surprisingly silent near the surface, beaked whales produce whistles and rasps at depths up to 900 m. The beaked whales dive together in synchrony, and right before they separate from each other, they produce the most whistles and rasps, further indicating that these vocalizations are used to enhance foraging success (Aguilar de Soto et al. 2006). As beaked whales transition to foraging on their own, they predominantly produce frequently modulated clicks and buzzes. Beaked whales produce buzzes in the final stages of prey capture to receive up-to-date information about their prey’s location. The buzzes’ high repetition enables the whale to achieve 300+ updates on their intended prey’s location in the last 3 m before seizing their feast (Johnson et al. 2006; Figure 3). 

Figure 3: Blainville’s beaked whales generally have four categories within their acoustic repertoire, including burst pulses, whistles, buzz clicks, and rasps. Credit: Marissa Garcia.

All of this knowledge about beaked whale acoustics can be linked back to the MMPA, which has also achieved broader success. Since the MMPA’s implementation, marine mammal population numbers have risen across the board. For marine mammal populations with sufficient data, approximately 65% of these stocks are increasing and 17% are stable (Roman et al. 2013). 

Nevertheless, perhaps much of the MMPA’s true success lies in the research it has indirectly fueled, by virtue of the required compliance of governmental bodies such as the U.S. Navy. And the response has proven to be a boon to knowledge: if the U.S. Navy has been the benefactor of marine mammal research, beaked whale acoustics has certainly been the beneficiary. We hope the beaked whale acoustic analyses stemming from the HALO Project can further this expanse of what we know.

References

Aguilar de Soto, N., Madsen, P. T., Tyack, P., Arranz, P., Marrero, J., Fais, A., Revelli, E., & Johnson, M. (2012). No shallow talk: Cryptic strategy in the vocal communication of Blainville’s beaked whales. Marine Mammal Science, 28(2), E75–E92. https://doi.org/10.1111/j.1748-7692.2011.00495.x

Baumann-Pickering, S., McDonald, M. A., Simonis, A. E., Solsona Berga, A., Merkens, K. P. B., Oleson, E. M., Roch, M. A., Wiggins, S. M., Rankin, S., Yack, T. M., & Hildebrand, J. A. (2013). Species-specific beaked whale echolocation signals. The Journal of the Acoustical Society of America, 134(3), 2293–2301. https://doi.org/10.1121/1.4817832

Dawson, S., Barlow, J., & Ljungblad, D. (1998). SOUNDS RECORDED FROM BAIRD’S BEAKED WHALE, BERARDIUS BAIRDIL. Marine Mammal Science, 14(2), 335–344. https://doi.org/10.1111/j.1748-7692.1998.tb00724.x

Johnston, D. W., McDonald, M., Polovina, J., Domokos, R., Wiggins, S., & Hildebrand, J. (2008). Temporal patterns in the acoustic signals of beaked whales at Cross Seamount. Biology Letters (2005), 4(2), 208–211. https://doi.org/10.1098/rsbl.2007.0614

Johnson, M., Madsen, P. T., Zimmer, W. M. X., de Soto, N. A., & Tyack, P. L. (2004). Beaked whales echolocate on prey. Proceedings of the Royal Society. B, Biological Sciences, 271(Suppl 6), S383–S386. https://doi.org/10.1098/rsbl.2004.0208

Johnson, M., Madsen, P. T., Zimmer, W. M. X., de Soto, N. A., & Tyack, P. L. (2006). Foraging Blainville’s beaked whales (Mesoplodon densirostris) produce distinct click types matched to different phases of echolocation. Journal of Experimental Biology, 209(Pt 24), 5038–5050. https://doi.org/10.1242/jeb.02596

Klinck, H., Mellinger, D. K., Klinck, K., Bogue, N. M., Luby, J. C., Jump, W. A., Shilling, G. B., Litchendorf, T., Wood, A. S., Schorr, G. S., & Baird, R. W. (2012). Near-real-time acoustic monitoring of beaked whales and other cetaceans using a Seaglider. PloS One, 7(5), e36128. https://doi.org/10.1371/annotation/57ad0b82-87c4-472d-b90b-b9c6f84947f8

Kowarski, K., Delarue, J., Martin, B., O’Brien, J., Meade, R., Ó Cadhla, O., & Berrow, S. (2018). Signals from the deep: Spatial and temporal acoustic occurrence of beaked whales off western Ireland. PloS One, 13(6), e0199431–e0199431. https://doi.org/10.1371/journal.pone.0199431

Madsen, P. T.,  Johnson, M., de Soto, N. A., Zimmer, W. M. X., & Tyack, P. (2005). Biosonar performance of foraging beaked whales (Mesoplodon densirostris). Journal of Experimental Biology, 208(Pt 2), 181–194. https://doi.org/10.1242/jeb.01327

McCullough, J. L. K., Wren, J. L. K., Oleson, E. M., Allen, A. N., Siders, Z. A., & Norris, E. S. (2021). An Acoustic Survey of Beaked Whales and Kogia spp. in the Mariana Archipelago Using Drifting Recorders. Frontiers in Marine Science, 8. https://doi.org/10.3389/fmars.2021.664292

Moore, J. E. & Barlow, J. P. (2013). Declining abundance of beaked whales (family Ziphiidae) in the California Current large marine ecosystem. PloS One, 8(1), e52770–e52770. https://doi.org/10.1371/journal.pone.0052770

Ray, G. C. & Potter, F. M. (2011). The Making of the Marine Mammal Protection Act of 1972. Aquatic Mammals, 37(4), 522.

Roman, J., Altman, I., Dunphy-Daly, M. M., Campbell, C., Jasny, M., & Read, A. J. (2013). The Marine Mammal Protection Act at 40: status, recovery, and future of U.S. marine mammals. Annals of the New York Academy of Sciences, 1286(1), 29–49. https://doi.org/10.1111/nyas.12040

Keeping up with the HALO project: Recovering Rockhopper acoustic recording units and eavesdropping on Northern right whale dolphins

Marissa Garcia, PhD Student, Cornell University, Department of Natural Resources and the Environment, K. Lisa Yang Center for Conservation Bioacoustics

It was a June morning on the Pacific Ocean, and the R/V Pacific Storm had come to a halt on its journey back to shore. The night before, the Holistic Assessment of Living marine resources off Oregon (HALO) project team had disembarked from Newport and began the long transit to NH 65, a site 65 nautical miles offshore along the Newport Hydrographic line (NH line). Ever since the 1960s, researchers have been conducting oceanographic studies along the NH line; the HALO project seeks to add the biological dimension to these historical data collections.

We were on a mission to recover our first set of Rockhoppers that we had deployed in October 2021, just nine months earlier. The Rockhopper is an underwater passive acoustic recording unit developed by K. Lisa Yang Center for Conservation Bioacoustics at Cornell University. Earlier versions of underwater recorders were optimized to record baleen whales. By contrast, the Rockhopper is designed to record both baleen whales and dolphins on longer and deeper deployments, making it apt for research endeavors such as the HALO project. Three units, deployed at NH 25, 45, and 65, continuously recorded the soundscape of the Oregon waters for six months. In June, we were headed out to sea to recover these three units, collect the acoustic data, and deploy three new units.

Figure 1: The HALO project routinely surveys the trackline spanning between NH 25 and NH 65 on the NH line. Credit: Leigh Torres.

With the ship paused, our first task was to recover the Rockhopper we had deployed at NH 65. This Rockhopper deployment at NH 65 was our deepest successful deployment to date, moored at nearly 3,000 m.

So, how does one recover an underwater recording unit that is nearly 3,000 m below the surface? When the Rockhopper was deployed, it was anchored to the seafloor with a 60 kg cast iron anchor. It seems improbable that an underwater recording unit — anchored by such heavy weights — can eventually rise to the surface, but this capability is made possible through a piece of attached equipment called the acoustic release. By sending a signal of a numbered code from a box on the boat deck through the water column to the Rockhopper, the bottom of the acoustic release will begin to spin and detach from the weights. The weights are then left on the seafloor, as the Rockhopper slowly rises to the surface, now unhindered by the weights. Since these weights are composed of iron, they will naturally erode, without additional pollution contributed to the ecosystem. At NH 65, it took approximately an hour for the Rockhopper to reach the surface.

Figure 2: A diagram of the Rockhopper mooring. Of particular importance to this blog post is the acoustic release (Edgtech PORT MFE release) and the 60 kg anchor (Source: Klinck et al., 2020).

The next challenge is finding the Rockhopper bobbing amongst the waves in the vast ocean — much like searching for a needle in a haystack. The color of the Rockhopper helps aid in this quest. It’s imperative anyone out on the boat deck wears a life jacket; if someone goes overboard while wearing a life-jacket, on-board passengers can more easily spot a bright orange spot in an otherwise blue-green ocean with white caps. The design of the Rockhopper functions similarly; the unit is contained in a bright orange hard hat, helping researchers on-board to more easily spot the device, especially in an ocean often characterized by high sea state.

We also use a Yagi antenna to listen for the VHF (Very High Frequency) signal of the recovery gear, a signal the Rockhopper emits once it’s surfaced above the waterline. Pointing the antenna toward the ocean, we can detect the signal, which will become stronger when we point antenna in the direction of the Rockhopper; once we hear that strong signal, we can recommend to the boat captain to start moving the vessel in that direction.

Figure 3: Derek Jaskula, a member of the field operations team at the K. Lisa Yang Center for Conservation Bioacoustics, points the Yagi antenna to detect the signal from the surfaced Rockhopper. Credit: Marissa Garcia.

At that point, all eyes are on the water, binoculars scanning the horizon for the orange. All ears are eager for the exciting news: “I see the Rockhopper!”

Once that announcement is made, the vessel carefully inches toward the Rockhopper until it is just next to the vessel’s side. Using a hook, the Rockhopper is pulled upward and back onto the deck.

What we weren’t expecting, however, during this recovery was to have our boat surrounded by two dolphin species: Pacific white-sided dolphins (Lagenorhynchus obliquidens) and Northern right whale dolphins (Lissodelphis borealis).

One HALO team member shouted, “I see Northern right whale dolphins!”

Charged with excitement, I quickly climbed up the crow’s nest to get a birds-eye look at the ocean bubbling around us with surfacing dolphins. Surely enough, I spotted the characteristic stripe of the Pacific-white sided dolphins zooming beneath the surface, in streaks of white. But what I was even more eager to see were the Northern right whale dolphins, flipping themselves out of the water, unveiling their bright white undersides. Because they lack dorsal fins, we on-board colloquially refer to Northern right whale dolphins as “sea slugs” to describe their appearance as they surface.

Figure 4: The Northern right whale dolphin (Lissodelphis borealis) surfaces during a HALO cruise. Source: HALO Project Team Member. Permit: NOAA/NMFS permit #21678.

In my analysis of the HALO project data for my PhD, I am interested in using acoustics to describe how the distribution of dolphins and toothed whales in Oregon waters varies across space and time. One species I am especially fascinated to study in-depth is the Northern right whale dolphin. To my knowledge, only three papers to date have attempted to describe their acoustics — two of which were published in the 1970s, and the most recent of which was published fifteen years ago (Fish & Turl, 1976; Leatherwood & Walker, 1979; Rankin et al., 2007).

Leatherwood & Walker (1979) proposed that Northern right whale dolphins produced two categories of whistles: a high frequency whistle that turned into burst-pulse vocalizations, and low frequency whistles. However, Rankin et al. (2007) proposed that Northern right whale dolphins may not actually produce whistles, based on two lines of evidence. First, Rankin et al. (2007) combined visual and acoustic survey, and all vocalizations recorded were localized via beamforming methods to verify that recorded vocalizations were produced by the visually observed dolphins. The visual surveying component is key to validating the vocalizations of the species, which also hints that the HALO project’s multi-surveying approach (acoustic and visual) could help arrive at similar results. Second, the Rankin et al. (2007) explored the taxonomy of the Northern right whale dolphin to verify which vocalizations the species is likely to produce based on the vocal repertoire of its close relatives. The right whale dolphin is closely related to dolphins in the genus Lagenorhynchus — which includes white-sided dolphins — and Cephalorhynchus — which includes Hector’s dolphin. The vocal repertoire of these relatives don’t produce whistles, and instead predominantly produced pulsed sounds or clicks (Dawson, 1991; Herman & Tavolga, 1980). Northern right whale dolphins primarily produce echolocation clicks trains and burst-pulses. Although Rankin et al. (2007) claims that the Northern right whale dolphin does not produce whistles, stereotyped burst-pulse series may be unique to individuals, just as dolphin species use stereotyped signature whistles, or they may be relationally shared just as discrete calls of killer whales are.

Figure 5: The Northern right whale dolphin (Lissodelphis borealis) produces burst-pulses. There exists variation in series of burst-pulses. The units marked by (a) and (b) ultimately get replaced by the unit marked by (c). (Source: Rankin et al., 2007).

We have just finished processing the first round of acoustic data for the HALO project, and it is ready now for analysis. Already previewing an hour of data on the Rockhopper by NH 25, we identified potential Northern right whale dolphin recordings . So far, we have only visually observed Northern right whale dolphins nearby Rockhopper units placed at sites NH 65 and NH 45, so it was surprising to acoustically detect this species on the most inshore unit at NH 25. I look forward to demystifying the mystery of Northern right whale dolphin vocalizations as our research on the HALO project continues!

Figure 6: Potential Northern right whale dolphin vocalizations recorded at the Rockhopper deployed at NH 25.

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References

Dawson, S. (1991). Clicks and Communication: The Behavioural and Social Contexts of Hector’s Dolphin Vocalizations. Ethology, 88(4), 265–276. https://doi.org/10.1111/j.1439-0310.1991.tb00281.x

Fish, J. F. & Turl, C. W. (1976). Acoustic Source Levels of Four Species of Small Whales.

Herman, L. M., and Tavolga, W. N. (1980). “The communication systems of cetaceans,” in Cetacean behavior: Mechanisms and functions, edited by L. M. Herman (Wiley, New York), 149–209.

Klinck, H., Winiarski, D., Mack, R. C., Tessaglia-Hymes, C. T., Ponirakis, D. W., Dugan, P. J., 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://doi.org/10.1109/IEEECONF38699.2020.9388970

Leatherwood, S., and Walker, W. A. (1979). “The northern right whale dolphin Lissodelphis borealis Peale in the eastern North Pacific,” in Behavior of marine animals, Vol. 3: Cetaceans, edited by H. E. Winn and B. L. Olla (Plenum, New York), 85–141.

Rankin, S., Oswald, J., Barlow, J., & Lammers, M. (2007). Patterned burst-pulse vocalizations of the northern right whale dolphin, Lissodelphis borealis. The Journal of the Acoustical Society of America, 121(2), 1213–1218. https://doi.org/10.1121/1.2404919

Different blue whale populations sing different songs

By Dawn Barlow, PhD Candidate, OSU Department of Fisheries, Wildlife, and Conservation Sciences, Geospatial Ecology of Marine Megafauna Lab

In human cultures, how you sound is often an indicator of where you are from. Have you ever taken a linguistics quiz that tries to guess what part of the United States you grew up in? Questions about whether you pronounce the sugary sweet treat caramel as “carr-mul” or “care-a-mel”, whether you say “soda” or “pop”, or whether a certain type of intersection is called a “roundabout”, “rotary”, or “traffic circle” are used to make a guess at where in the country you were raised. I have spent time in the United States, Australia, and New Zealand, I was amused to learn that the shoes you might wear in summertime can be called flip flops, slippers, thongs, or jandals, depending on which English-speaking country you are in. We know that listening to how someone speaks can tell us about their heritage or culture. As it turns out, the same is true for blue whales. We can learn a lot about blue whales by listening to them.

A blue whale comes up for air in the South Taranaki Bight, New Zealand. We catch only a short glimpse of these ocean giants when they are at the surface. By listening to their vocalizations using acoustic recordings, we can gain a whole new perspective on their lives. Photo by D. Barlow.

Sound is an incredibly important sense to marine mammals, particularly since sound waves can efficiently transmit over long distances in the ocean where other senses, such as vision or smell, are limited. Therefore, passive acoustic monitoring—placing hydrophones underwater to listen for an extended period of time and record the sounds of animals and their environment—is a highly effective tool for studying marine mammals, including blue whales. Throughout the world, blue whales sing. In this case, “song” is defined as a limited number of sound types that are produced in succession to form a recognizable pattern (McDonald et al. 2006). These songs are presumed to be produced by males only, most likely used to maintain associations and mediate social interactions, and seem to play a role in reproduction (Oleson et al. 2007, Lewis et al. 2018). Furthermore, these songs are highly stereotyped, and stable over decadal scales (McDonald et al. 2006).

Figure reproduced from McDonald et al. (2006), illustrating the variation and in blue whale songs from different geographic regions, and their stability over time: Recordings from New Zealand (A), the Central North Pacific (B), Australia (C), the Northeast Pacific (D) and North Indian Ocean (E) illustrate the stable character of the blue whale song over long time periods. All song types for which long time spans of recordings are available show some frequency drift through time, but only minor change in character. These examples were chosen because recordings over a significant time span were available to the authors in raw form, and not because these song types are more stable than the others.

Fascinatingly, blue whale songs have acoustic characteristics that are distinct between geographic regions. A blue whale in the northeast Pacific sings a different song than a blue whale in the north Atlantic; the song heard around Australia is distinct from the one sung off the coast of Chile, and so on. Therefore, differences in blue whale songs between areas can be used as a provisional hypothesis about population structure (McDonald et al. 2006, Samaran et al. 2013, Balcazar et al. 2015). Vocalizations may evolve more rapidly than traditional markers such as genetics or morphology that are often used to delineate populations, particularly in long-lived mammalian species such as blue whales (McDonald et al. 2006).

Figure reproduced from McDonald et al. (2006): Blue whale residence and population divisions suggested from their song types. Arrows indicate the direction of seasonal movements.

Despite the general rule of thumb that population-specific blue whale songs occur in separate geographic regions, there are examples throughout the southern hemisphere where songs from different populations overlap and are recorded in the same location (Samaran et al. 2010, 2013, Tripovich et al. 2015, McCauley et al. 2018, Buchan et al. 2020, Leroy et al. 2021). However, these examples may be instances where the populations temporally or ecologically partition their use of the area. For example, there may be differences in the timing of peak occurrence so that overlap is minimized by alternating which population is predominantly present in different seasons (Leroy et al. 2018). Alternatively, whales from different populations may overlap in space and time, but occupy different ecological niches at the same site. In this case, an area may simultaneously be a migratory corridor for one population and a foraging ground for another (Tripovich et al. 2015).

Figure reproduced from Leroy et al. (2021): Distribution of the five blue whale acoustic populations of the Indian Ocean: the Sri Lankan—NIO (yellow); Madagascan—SWIO (orange); Australian—SEIO (blue); and Arabian Sea—NWIO (red) pygmy blue whales; the hypothesized Chagos pygmy blue whale (green); and the Antarctic blue whale (black dashed line). These distributions have been inferred from the acoustic recordings conducted in the area. The long-term recording sites used to infer these distribution areas are indicated by red stars. Blue whale illustration by Alicia Guerrero.

In the South Taranaki Bight (STB) region of New Zealand, where the GEMM lab has been studying blue whales for the past decade (Torres 2013), the New Zealand song type is recorded year-round (Barlow et al. 2018). New Zealand blue whales rely on a productive upwelling system in the STB that supports an important foraging ground (Barlow et al. 2020, 2021). Antarctic blue whales also seasonally pass through New Zealand waters, likely along their migratory pathway between polar feeding grounds and lower latitude areas (Warren et al. 2021). What does it mean in terms of population connectivity or separation when two different populations occasionally share the same waters? How do these different populations ecologically partition the space they occupy? What drives their differing occurrence patterns? These are the sorts of questions I am diving into as we continue to explore the depths of our acoustic recordings from the STB region. We still have a lot to learn about these blue whales, and there is a lot to be learned through listening.

References:

Balcazar NE, Tripovich JS, Klinck H, Nieukirk SL, Mellinger DK, Dziak RP, Rogers TL (2015) Calls reveal population structure of blue whales across the Southeast Indian Ocean and the Southwest Pacific Ocean. J Mammal 96:1184–1193.

Barlow DR, Bernard KS, Escobar-Flores P, Palacios DM, Torres LG (2020) Links in the trophic chain: Modeling functional relationships between in situ oceanography, krill, and blue whale distribution under different oceanographic regimes. Mar Ecol Prog Ser 642:207–225.

Barlow DR, Klinck H, Ponirakis D, Garvey C, Torres LG (2021) Temporal and spatial lags between wind, coastal upwelling, and blue whale occurrence. Sci Rep 11:1–10.

Barlow DR, Torres LG, Hodge KB, Steel D, Baker CS, Chandler TE, Bott N, Constantine R, Double MC, Gill P, Glasgow D, Hamner RM, Lilley C, Ogle M, Olson PA, Peters C, Stockin KA, Tessaglia-hymes CT, Klinck H (2018) Documentation of a New Zealand blue whale population based on multiple lines of evidence. Endanger Species Res 36:27–40.

Buchan SJ, Balcazar-Cabrera N, Stafford KM (2020) Seasonal acoustic presence of blue, fin, and minke whales off the Juan Fernández Archipelago, Chile (2007–2016). Mar Biodivers 50:1–10.

Leroy EC, Royer JY, Alling A, Maslen B, Rogers TL (2021) Multiple pygmy blue whale acoustic populations in the Indian Ocean: whale song identifies a possible new population. Sci Rep 11:8762.

Leroy EC, Samaran F, Stafford KM, Bonnel J, Royer JY (2018) Broad-scale study of the seasonal and geographic occurrence of blue and fin whales in the Southern Indian Ocean. Endanger Species Res 37:289–300.

Lewis LA, Calambokidis J, Stimpert AK, Fahlbusch J, Friedlaender AS, Mckenna MF, Mesnick SL, Oleson EM, Southall BL, Szesciorka AR, Širović A (2018) Context-dependent variability in blue whale acoustic behaviour. R Soc Open Sci 5.

McCauley RD, Gavrilov AN, Jolli CD, Ward R, Gill PC (2018) Pygmy blue and Antarctic blue whale presence , distribution and population parameters in southern Australia based on passive acoustics. Deep Res Part II 158:154–168.

McDonald MA, Mesnick SL, Hildebrand JA (2006) Biogeographic characterisation of blue whale song worldwide: using song to identify populations. J Cetacean Res Manag 8:55–65.

Oleson EM, Wiggins SM, Hildebrand JA (2007) Temporal separation of blue whale call types on a southern California feeding ground. Anim Behav 74:881–894.

Samaran F, Adam O, Guinet C (2010) Discovery of a mid-latitude sympatric area for two Southern Hemisphere blue whale subspecies. Endanger Species Res 12:157–165.

Samaran F, Stafford KM, Branch TA, Gedamke J, Royer J, Dziak RP, Guinet C (2013) Seasonal and Geographic Variation of Southern Blue Whale Subspecies in the Indian Ocean. PLoS One 8:e71561.

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

Tripovich JS, Klinck H, Nieukirk SL, Adams T, Mellinger DK, Balcazar NE, Klinck K, Hall EJS, Rogers TL (2015) Temporal Segregation of the Australian and Antarctic Blue Whale Call Types (Balaenoptera musculus spp.). J Mammal 96:603–610.

Warren VE, Širović A, McPherson C, Goetz KT, Radford CA, Constantine R (2021) Passive Acoustic Monitoring Reveals Spatio-Temporal Distributions of Antarctic and Pygmy Blue Whales Around Central New Zealand. Front Mar Sci 7:1–14.

Learning to Listen for Animals in the Sea

By Rachel Kaplan, PhD 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

Part of what makes being a graduate student so exciting is the way that learning can flip the world around: you learn a new framework or method, and suddenly everything looks a little different. I am experiencing this fabulous phenomenon lately as I learn to collect and process active acoustic data, which can reveal the distribution and biomass of animals in the ocean – including those favored by foraging whales off of Oregon, like the tiny shrimp-like krill.

Krill, like this Thysanoessa spinifera, play a key role in California Current ecosystems. Photo credit: Scripps Institution of Oceanography.

We know that whales seek out the dense, energy-rich swarms that krill form, and that knowing where to expect krill can give us a leg up in anticipating whale distributions. Project OPAL (Overlap Predictions About Large whales) seeks to model and provide robust predictions of whale distributions off the coast of Oregon, so that managers can make spatially discrete decisions about potential fishery closures, minimizing burdens to fishermen while also maximizing protection of whales. We hope that including prey in our ecosystem models will help this effort, and working on this aim is one of the big tasks of my PhD.

So, how do we know where to expect krill to be off the coast of Oregon? Acoustic tools give us the opportunity to flip the world upside down: we use a tool called an echosounder to eavesdrop on the ocean, yielding visual outputs like the ones below that let us “see” and interpret sound.

Echograms like these reveal features in the ocean that scatter “pings” of sound, and interpreting these signals can show life in the water column.

This is how it works. The echosounder emits pulses of sound at a known frequency, and then it listens for their return after it bounces of the sea floor or things in the water column. Based on sound experiments in the laboratory, we know to expect our krill species, Euphausia pacifica and Thysanoessa spinifera, to return those echoes at a characteristic decibel level. By constantly “pinging” the water column with this sound, we can record a continuous soundscape along the cruise track of a vessel, and analyze it to identify the animals and features recorded.

I had the opportunity to use an echosounder for the first time recently, on the first HALO cruise. We deployed the echosounder soon after sunrise, 65 miles offshore from Newport. After a little fiddling and troubleshooting, I was thrilled to start “listening” to the water; I was able to see the frothy noise at its surface, the contours of the seafloor, and the pixelated patches that indicate prey in between. Although it’s difficult to definitively identify animals only based on the raw output, we saw swarms that looked like our beloved krill, and other aggregations that suggested hake. Sometimes, at the same time that the team of visual observers on the flying bridge of the vessel sighted whales, I also saw potential prey on the echogram.

 I spent much of the HALO cruise monitoring incoming data from the transducer on the SIMRAD EK60. Photo: Marissa Garcia.

I’m excited to keep collecting these data, and grateful that I can also access acoustic data collected by others. Many research vessels use echosounders while they are underway, including the NOAA Ship Bell M. Shimada, which conducts cruises in the Northern California Current several times a year. Starting in 2018, GEMM Lab members have joined these cruises to conduct marine mammal surveys.

This awesome pairing of data types means that we can analyze the prey that was available at the time of marine mammal sightings. I’ve been starting to process acoustic data from past Northern California Current cruises, eavesdropping on the preyscape in places that were jam-packed with whales, such as this echogram from the September 2020 cruise, below.

An echogram from the September 2020 NCC cruise shows a great deal of prey at different depths.

Like a lot of science, listening to animals in the sea comes down to occasional bursts of fieldwork followed by a lot of clicking on a computer screen during data analysis. This analysis can be some pretty fun clicking, though – it’s amazing to watch the echogram unfurl, revealing the preyscape in a swath of ocean. I’m excited to keep clicking, and learn what it can tell us about whale distributions off of Oregon.

Supporting marine life conservation as an outsider: Blue whales and earthquakes

By Mateo Estrada Jorge, Oregon State University undergraduate student, GEMM Lab REU Intern

Introduction

My name is Mateo Estrada and this past summer I had the pleasure of working with Dawn Barlow and Dr. Leigh Torres as a National Science Foundation (NSF) Research Experience for Undergraduates (REU) intern. I had the chance to proactively learn about the scientific method in the marine sciences by studying the acoustic behaviors of pygmy blue whales (Balaenoptera musculus brevicauda) that are documented residents of the South Taranaki Bight region in New Zealand (Torres 2013, Barlow et al. 2018). I’ve been interested in conducting scientific research since I began my undergraduate education at Oregon State University in 2015. Having the opportunity to apply the skills I gained through my education in this REU has been a blessing. I’m a physics and computer science major, but more than anything I’m a scientist and my passion has taken me in new, unexpected directions that I’m going to share in this blog post. My message for any students who feel like they haven’t found their path yet is: hang in there, sometimes it takes time for things to take shape. That has been my experience and I’m sure it’s been the experience of many people interested in the sciences. I’m a Physics and Computer Science student, so why am I studying blue whales, and more specifically, how can I be doing marine science research having only taken intro to biology 101?

My background

I decided to apply for the REU in the Spring 2021 because it was a chance to use my programming skills in the marine sciences. I’m also passionate about conservation and protecting the environment in a pragmatic way, so I decided to find a niche where I could put my technical skills to good use. Finally, I wanted to explore a scientific field outside of my area of expertise to grow as a student and to learn from other researchers. I was mostly inspired by anecdotal tales of Physicist Richard Feynman who would venture out of the physics department at Caltech and into other departments to learn about what other scientists were investigating to inspire his own work. This summer, I ventured into the world of marine science, and what I found in my project was fascinating.

Whale watching tour

Figure 1. Me standing on a boat on the Pacific Ocean off Long Beach, CA.

To get into the research mode, I decided to go on a whale watching tour with the Aquarium of the Pacific. The tour was two hours long and the sunburn was worth it because we got to see four blue whales off the Long Beach coast in California. I got to see the famous blue whale blow and their splashes. It was the first time I was on a big boat in the ocean, so naturally I got seasick (Fig 1). But it was exciting to get a chance to see blue whales in action (luckily, I didn’t actually hurl). The marine biologist onboard also gave a quick lecture on the relative size of blue whales and some of their behaviors. She also pointed out that they don’t use Sonar to locate whales as this has been shown to disturb their calling behaviors. Instead, we looked for a blow and splashing. The tour was a wonderful experience and I’m glad I got to see some whales out in nature. This experience also served as a reminder of the beauty of marine life and the responsibility I feel for trying to understand and help conserving it.

Context of blue whale calling

Sound plays a significant role in the marine environment and is a critical mode of communication for many marine animals including baleen whales. Blue whales produce different vocalizations, otherwise known as calls.  Blue whale song is theorized to be produced by males of the species as a form of reproductive behavior, similar to how male peacocks engage females by displaying their elongated upper tail covert feathers in iridescent colors as a courtship mechanism. Then there are “D calls” that are associated with social mechanisms while foraging, and these calls are made by both female and male blue whales (Lewis et al. 2018) (Fig. 2).

Figure 2. Spectrogram of Pygmy blue whale D calls manually (and automatically) selected, frequency 0-150 Hz.

Understanding research on blue whales

The most difficult part about coming into a project as an outsider is catching up. I learned how anthropogenetic (human made) noise affects blue whale communication. For example, it has been showing that Mid Frequency Active Sonar signals employed by the U.S. Navy affect blue whale D calling patterns (Melcón 2012). Furthermore, noise from seismic airguns used for oil and gas exploration has also impact blue whale calling behavior (Di Lorio, 2010). Understanding the environmental context in which the pygmy blue whales live and the anthropogenic pressures they face is essential in marine conservation. Protecting the areas in which they live is important so they can feed, reproduce and thrive effectively. What began as a slowly falling snowflake at the start of a snowstorm turned into a cascading avalanche of knowledge pouring into my mind in just two weeks.

Figure 3. The white stars show the hydrophone locations (n = 5). A bathymetric scale of the depth is also given.

The research question I set out to tackle in my internship was: do blue whales change their calling behavior in response to natural noise events from earthquake activity? To do this, I used acoustic recordings from five hydrophones deployed in the South Taranaki Bight (Fig. 3), paired with an existing dataset of all recorded earthquakes in New Zealand (GeoNet). I identified known earthquakes in our acoustic recordings, and then examined the blue whale D calls during 4 hours before and after each earthquake event to look for any change in the number of calls, call energy, entropy, or bandwidth.

A great mentor and lab team

The days kept passing and blending into each other, as they often do with remote work. I began to feel isolated from the people I was working with and the blue whales I was studying. The zoom calls, group chats, and working alongside other remote interns kept me afloat as I adapted to a work world fully online. Nevertheless, I was happy to continue working on this project because I felt like I was slowly becoming part of the GEMM Lab. I would meet with my mentor Dawn Barlow at least once a week and we would spend time talking about the project and sorting out the difficult details of data processing. She always encouraged my curiosity to ask questions. Even if they were silly questions, she was happy to ponder them because she is a curious scientist like myself.

What we learned

Pygmy blue whales from the South Taranaki Bight region do not change their acoustic behavior in response to earthquake activity. The energy of the earthquake, magnitude, depth, and distance to the origin all had no influence on the number of blue whale D calls, the energy of their calling, the entropy, and the bandwidth. A likely reason for why the blue whales would have no acoustic response to earthquakes (magnitude < 5) is that the STB region is a seismically active region due to the nearby interface of the Australian and Pacific plates. Because of the plate tectonics, the region averages about 20,000 recorded earthquakes per year (GeoNet: Earthquake Statistics). Given that pygmy blue whales are present in the STB region year-round (Barlow et al. 2018), the blue whales may have adapted to tolerate the earthquake activity (Fig 4).

Figure 4. Earthquake signal from MARU (1, 2, 3, 4, 5) and blue whale D calls, Frequency 0-150 Hz.

Looking at the future

I presented my work at the end of my REU internship program, which was a difficult challenge for me because I am often intimidated by public speaking (who isn’t?). Communicating science has always been a big interest of me. I love reading news articles about new breakthroughs and being a small part of that is a huge privilege for me. Finding my own voice and having new insights to contribute to the scientific world has always been my main objective. Now I will get to deliver a poster presentation of my REU work at the Association for the Sciences of Limnology and Oceanography (ASLO) Conference in March 2022. I am both excited and nervous to take on this new adventure of meeting seasoned professionals, communicating my results, and learning about the ocean sciences. I hope to gain new inspirations for my future academic and professional work.

References:

About Earthquake Drums – GeoNet. geonet.Org. Retrieved June 23, 2021, from https://www.geonet.org.nz/about/earthquake/drums

Barlow, D. R., Torres, L. G., Hodge, K. B., Steel, D., Scott Baker, C., Chandler, T. E., Bott, N., Constantine, R., Double, M. C., Gill, P., Glasgow, D., Hamner, R. M., Lilley, C., Ogle, M., Olson, P. A., Peters, C., Stockin, K. A., Tessaglia-Hymes, C. T., & Klinck, H. (2018). Documentation of a New Zealand blue whale population based on multiple lines of evidence. Endangered Species Research, 36, 27–40. https://doi.org/10.3354/esr00891

Di Iorio, L., & Clark, C. W. (2010). Exposure to seismic survey alters blue whale acoustic communication. Biology Letters, 6(3), 334–335. https://doi.org/10.1098/rsbl.2009.0967

Lewis, L. A., Calambokidis, J., Stimpert, A. K., Fahlbusch, J., Friedlaender, A. S., McKenna, M. F., Mesnick, S. L., Oleson, E. M., Southall, B. L., Szesciorka, A. R., & Sirović, A. (2018). Context-dependent variability in blue whale acoustic behaviour. Royal Society Open Science, 5(8). https://doi.org/10.1098/rsos.180241

Melcón, M. L., Cummins, A. J., Kerosky, S. M., Roche, L. K., Wiggins, S. M., & Hildebrand, J. A. (2012). Blue whales respond to anthropogenic noise. PLoS ONE, 7(2), 1–6. https://doi.org/10.1371/journal.pone.0032681

Torres LG. 2013 Evidence for an unrecognised blue whale foraging ground in New Zealand. NZ J. Mar. Freshwater Res. 47, 235–248. (doi:10. 1080/00288330.2013.773919)

Detecting blue whales from acoustic data

By Dawn Barlow, PhD student, OSU Department of Fisheries and Wildlife, Geospatial Ecology of Marine Megafauna Lab

In January of 2016, five underwater recording units were dropped to the seafloor in New Zealand to listen for blue whales (Fig. 1). These hydrophones sat listening for two years, brought to the surface only briefly every six months to swap out batteries and offload the data. Through all seasons and conditions when scientists couldn’t be on the water, they recorded the soundscape, generating a wealth of acoustic data with the potential to greatly expand our knowledge of blue whale ecology. 

Figure 1. Locations of the five Marine Autonomous Recording Units (MARUs) in the South Taranaki Bight region of New Zealand.

We have established that blue whales are present in New Zealand waters year-round 1. However, many questions remain regarding their distribution across daily, seasonal, and yearly scales. Our two-year acoustic dataset from five hydrophones throughout the STB region is a goldmine of information on blue whale occurrence patterns and the soundscape they inhabit. Having year-round occurrence data will allow us to examine what environmental and anthropogenic factors may influence blue whale distribution patterns. The hydrophones were listening for whales around the clock, every day, while we were on the other side of the world awaiting the recovery of the data to answer our questions.

Before any questions of seasonal distribution or anthropogenic impacts and noise can be addressed, however, we need to know something far more basic: when and where did we record blue whale vocalizations? This may seem like a simple, stepping-stone question, but it is actually quite involved, and the reason I spent the last month working with a team of acousticians at Cornell University’s Center for Conservation Bioacoustics. The expert research group here at Cornell, led by Dr. Holger Klinck, have been instrumental in our New Zealand blue whale research, including developing and building the recording units, hydrophone deployment and recovery, data processing, analysis, and advice. I am thrilled to work with all of them, and had an incredibly productive month of learning about acoustics from the best.

Blue whales produce multiple vocalizations that we are interested in documenting. The New Zealand song (Fig. 2A) is highly stereotyped and unique to the Southwest Pacific Ocean 2,3. Low-frequency downsweeps, or “D calls” (Fig. 2B), are far more variable and produced by blue whale populations around the world 4. Furthermore, Antarctic blue whales produce a highly-stereotyped “Z call” (Fig. 2C) and are known to be present in New Zealand waters occasionally 5.

Figure 2. Spectrograms of (A) the New Zealand blue whale song, (B), D calls, and (C) Antarctic Z calls.

One way to determine when blue whales were vocalizing is for an analyst to manually review the entirety of the two years of sound recordings for each of the five hydrophones by hand to scan for and select individual vocalizations. An alternative approach is to develop a detector algorithm to locate calls in the data based on their stereotypical characteristics. Over the past month I built, tested, and ran detectors for each blue whale call type using what is called a data template detector. This technique uses example signals from the data that the analyst selects as templates. The templates should be clear signals, and representative of the variation in calls contained in the dataset. Then, by comparing pixel characteristics between the template spectrograms and the spectrogram of the recording of interest using certain matching criteria (e.g. threshold for spectrogram correlation, detection frequency range), the algorithm searches for other signals like the templates in the full dataset. For example, in Fig. 3 you can see units of blue whale song I selected as templates for my detector.

Figure 3. Spectrogram of selected sound clips of New Zealand blue whale song, with units used as templates for a detector shown inside the teal boxes.

Testing the performance of a detector algorithm is critical. Therefore, a dataset is needed where calls were identified by an analyst and then used as the “ground truth”, to which the detector results are compared. For my ground truth dataset, I took a subset of 52 days and hand-browsed the spectrograms to identify and log New Zealand blue whale song, D calls, and Antarctic Z calls. In evaluating detector performance, there are three important metrics that need to be weighed: precision (the proportion of detections that are true), recall (the proportion of true calls identified by the detector), and false alarm rate (the number of false positive detections per hour). Ideally, the detector should be optimized to maximize precision and recall and minimize the false positives.

The STB region is highly industrial, and our two-year acoustic dataset contains periods of pervasive seismic airgun noise from oil and gas exploration. Ideally, a detector would be able to identify blue whale vocalizations even in the presence of airgun operations that dominate the soundscape for months. For blue whale song, the detector did quite well! With a precision of 0.91 and recall of 0.93, the detector could pick out song units over airgun noise (Fig. 4). A false alarm rate of 8 false positives per hour is a sacrifice worth making to identify song during seismic operations (and the false positives will be removed in a subsequent step). For D calls, seismic survey activity presented a different challenge. While the detector did well at identifying D calls during airgun operation, the first several detector attempts also logged every single airgun blast as a blue whale vocalization—clearly problematic. Through an iterative process of selecting template signals, and adjusting the number of templates used and the correlation threshold, I was able to come up with a detector which selected D calls and missed most airgun blasts. This success felt like a victory.

Figure 4. An example of spectrograms of simultaneous recordings from the five hydrophones illustrating seismic airgun noise (strong broadband signals that appear as repetitive black, vertical lines) overlapping New Zealand blue whale song. The red boxes are detection events selected by the detector, demonstrating its ability to capture song even during airgun operation.

After this detector development and validation process, I ran each detector on the full two-year acoustic dataset for all five recording units. This step was a good exercise in patience as I eagerly awaited the outputs for the many hours they took to run. The next step in the process will be for me to go through and validate each detector event to eliminate any false positives. However, running the detectors on the full dataset has allowed for exciting preliminary examinations of seasonal blue whale acoustic patterns, which need to be refined and expanded upon as the analysis continues. For example, sometimes the New Zealand song dominates the recordings on all hydrophones (Fig. 5), whereas other times of year song is less common. Similarly, there appear to be seasonal patterns in D calls and Antarctic Z calls, with peaks and dips in detections during different times of year.

Figure 5. An example spectrogram of simultaneous recordings from all five hydrophones during a time when New Zealand blue whale song dominated the recordings, with numerous, overlapping calls.

As with many things, the more questions you ask, the more questions you come up with. From preliminary explorations of the acoustic data my head is buzzing with ideas for further analysis and with new questions I hadn’t thought to ask of the data before. My curiosity has been fueled by scrolling through spectrograms, looking, and listening, and I am as excited as ever to continue researching blue whale ecology. I would like to thank the team at the Center for Conservation Bioacoustics for their support and guidance over the past month, and I look forward to digging deeper into the stories being told in the acoustic data!

Figure 6. A pair of blue whales observed in February 2017 in the South Taranaki Bight. Photo: L. Torres.

References

1.          Barlow, D. R. et al. Documentation of a New Zealand blue whale population based on multiple lines of evidence. Endanger. Species Res. 36, 27–40 (2018).

2.          McDonald, M. A., Mesnick, S. L. & Hildebrand, J. A. Biogeographic characterisation of blue whale song worldwide: using song to identify populations. J. Cetacean Res. Manag. 8, 55–65 (2006).

3.          Balcazar, N. E. et al. Calls reveal population structure of blue whales across the Southeast Indian Ocean and the Southwest Pacific Ocean. J. Mammal. 96, 1184–1193 (2015).

4.          Oleson, E. M. et al. Behavioral context of call production by eastern North Pacific blue whales. Mar. Ecol. Prog. Ser. 330, 269–284 (2007).

5.          McDonald, M. A. An acoustic survey of baleen whales off Great Barrier Island, New Zealand. New Zeal. J. Mar. Freshw. Res. 40, 519–529 (2006).