By Dawn Barlow, PhD student, Department of Fisheries & Wildlife, Geospatial Ecology of Marine Megafauna Lab
When people hear that I study blue whales, they often ask me questions about what it’s like to be close to the largest animal on the planet, where we do fieldwork, and what data we are interested in collecting. While I love time at sea, my view on a daily basis is rarely like this:
More often than not, it looks something like this:
In my application letter to Dr. Leigh Torres, I wrote something along the lines of “while I relish remote fieldwork, I also find great satisfaction in the analysis process.” This statement is increasingly true for me as I grow more proficient in statistical modeling and computer programming. When excitedly telling my family about how I am trying to model relationships between oceanography, krill, whales, and satellite imagery, I was asked what I meant by “model”. Put simply, a model is a formula or equation that we can use to describe a pattern. I have been told, “all models are wrong, but some models work.” What does this mean? While we may never know exactly every pattern of whale feeding behavior, we can use the data we have to describe some of the important relationships. If our model performance is very good, then we have likely described most of what drives the patterns we see. If model performance is poor, then there is more to the pattern that we have not yet captured in either our data collection or in our analytical methods. Another common saying about models is, “A model is only ever as good as the data you put into it.” While we worked hard during field seasons to collect a myriad of data about what could be influencing blue whale distribution patterns, we inevitably could not capture everything, nor do we know everything that should be measured.
So, how do you go about finding the ‘best’ model? This question is what I’ve been grappling with over the last several weeks. My goal is to describe the patterns in the krill that drive patterns in whale distribution, the patterns in oceanography that drive patterns in the krill, and the patterns in the oceanography that drive patterns in whale distribution. The thing is, we have many metrics to describe oceanographic patterns (surface temperature, mixed layer depth, strength of the thermocline, integral of fluorescence, to name just a few), as well as several metrics to describe the krill (number of aggregations, aggregation density, depth, and thickness). When I multiplied out how many possible combinations of predictor variables and parameters we’re interested in modeling, I realized this meant running nearly 300 models in order to settle on the best ten. This is where programming comes in, I told myself, and caught my breath.
I’ve always loved languages. When I was much younger, I thought I might want to study linguistics. As a graduate student in wildlife science, the language I’ve spent the most time learning, and come to love, is the statistical programming language R. Just like any other language, R has syntax and structure. Like any other language, there are many ways in which to articulate something, to make a particular point or reach a particular end goal. Well-written code is sometimes described as “elegant”, much like a well-articulated piece of writing. While I certainly do not consider myself “fluent” in R, it is a language I love learning. I like to think that the R scripts I write are an attempt to eloquently uncover and describe ecological patterns.
Rather than running 300 models one by one, I wrote an R script to run many models at a time, and then sort the outputs by model performance. I may look at the five best models of 32 options in order to select one. But this is where Leigh reminds me to step back from the programming for a minute and put my ecologist hat back on. Insight on the part of the modeler is needed in order to discern between what are real ecological relationships and what are spurious correlations in the data. It may not be quite as simple as choosing the model with the highest explanatory power when my goal is to make ecological inferences.
So, where does this leave me? Hundreds of models later, I am still not entirely sure which ones are best, although I’ve narrowed it down considerably. My programming proficiency and confidence continue to grow, but that only goes so far in ecology. Knowledge of my study system is equally important. So my workflow lately goes something like this: write code, try to interpret model outputs, consider what I know about the oceanography of my study region, re-write code, re-interpret the revised results, and so on. Hopefully this iterative process is bringing us gradually closer to an understanding of the ecology of blue whales on a foraging ground… stay tuned.
By Dawn Barlow, PhD student, Department of Fisheries & Wildlife, Geospatial Ecology of Marine Megafauna Lab
As a PhD student studying the ecology of blue whales in New Zealand, my time is occupied by questions such as: When and where are the blue whales? Can we predict where they will be based on environmental conditions? How does their distribution overlap with human activity such as oil and gas exploration?
Leigh and I have just returned from New Zealand, where I gave an oral presentation at the Society for Conservation Biology Oceania Congress entitled “Cloudy with a chance of whales: Forecasting blue whale presence to mitigate industrial impacts based on tiered, bottom-up models”. While the findings I presented are preliminary, an exciting ecological story is emerging, and one with clear management implications.
The South Taranaki Bight (STB) region of New Zealand is an important area for a population of blue whales which are unique to New Zealand. A wind-driven upwelling system brings cold, productive waters into the bight , which sustains high densities of krill , blue whale prey. The region is also frequented by busy shipping traffic, oil and gas drilling and extraction platforms as well as seismic survey effort for subsurface oil and gas reserves, and is the site of a recently-permitted seabed mine for iron sands (Fig. 1). However, a lack of knowledge on blue whale distribution and habitat use patterns has impeded effective management of these potential anthropogenic threats.
Three surveys were conducted in the STB region in the summer months of 2014, 2016, and 2017. During that time, we not only looked for blue whales, we also collected oceanographic data and hydroacoustic backscatter data to map and measure aspects of the krill in the region. These data streams will help us understand the functional, ecological relationships between the environment (oceanography), prey (krill), and predators (blue whales) in the ecosystem (Fig. 2). But in practice these data are costly and time-consuming to collect, while other data sources such as satellite imagery are readily accessible to managers at a variety of spatial and temporal scales. Therefore, another one of my aims is to link the data we collected in the field to satellite imagery, so that managers can have a practical tool to predict when and where the blue whales are most likely to be found in the region.
So what did I find? Here are the highlights from my preliminary analyses:
The majority of the patterns in blue whale distribution can be explained by the density, depth, and thickness of the krill patches.
Patterns in the krill are driven by oceanography.
Those same oceanographic parameters that drive the krill can be used to explain blue whale distribution.
There are tight relationships between the important oceanographic variables and satellite images of sea surface temperature.
Blue whale distribution can, to some degree, be explained using just satellite imagery.
We were able to identify a sea surface temperature range in the satellite imagery of approximately 18°C where the likelihood of finding a blue whale is the highest. Is this because blue whales really like 18° water? Well, more likely this relationship exists because the satellite imagery is reflective of the oceanography, and the oceanography drives patterns in the krill distribution, and the krill drives the distribution of blue whales (Fig. 3). We were able to make each of these functional linkages through our series of models, which is quite exciting.
That’s all well and good, but we were interested in testing these relationships to see if our identified habitat associations hold up even when we do not have field data (oceanographic, krill, and whale data). This past austral summer, we did not have a field season to collect data, but there was a large seismic airgun survey of the STB region. Seismic survey vessels are required to have trained marine mammal observers on board, and we were given access to the blue whale sightings data they recorded during the survey. In December, when the water was right around the preferred temperature identified by our models (18°C), the observers made 52 blue whale sightings (Fig. 4). In January and February, the waters warmed and only two sightings were made in each month. This is not only reassuring because it supports our model results, it also implies that there is the potential to balance industrial use of the area with protection of blue whale habitat, based on our understanding of the ecology. In January and February, very few blue whales were likely disturbed by the industrial activity in the STB, as conditions were not favorable for foraging at the location of the seismic survey. In contrast, the blue whales that were in the STB region in December may have experienced physiological consequences of sustained exposure to airgun noise since the conditions were favorable for foraging in the STB. In other words, the whales may have tolerated the noise exposure to gain access to good food, but this could have significant biological repercussions such as increased stress .
In the first two weeks of July, we presented these latest findings to managers at the New Zealand Department of Conservation, the Minister of Conservation, the CEO and Policy Advisor of a major oil and gas conglomerate, NGOs, advocacy groups, and scientific colleagues. It was valuable to gather feedback from many different stakeholders, and satisfying to see such a clear interest in, and management application of, our work.
What’s next? We’re back in Oregon, and diving back into analysis. We intend to take the modeling work a step further to make the models predictive—for example, can we forecast where the blue whales will be based on the temperature, productivity, and winds two weeks prior? I am excited to see where these next steps lead!
Shirtcliffe TGL, Moore MI, Cole AG, Viner AB, Baldwin R, Chapman B. 1990 Dynamics of the Cape Farewell upwelling plume, New Zealand. New Zeal. J. Mar. Freshw. Res.24, 555–568. (doi:10.1080/00288330.1990.9516446)
Bradford-Grieve JM, Murdoch RC, Chapman BE. 1993 Composition of macrozooplankton assemblages associated with the formation and decay of pulses within an upwelling plume in greater cook strait, New Zealand. New Zeal. J. Mar. Freshw. Res.27, 1–22. (doi:10.1080/00288330.1993.9516541)
Rolland RM, Parks SE, Hunt KE, Castellote M, Corkeron PJ, Nowacek DP, Wasser SK, Kraus SD. 2012 Evidence that ship noise increases stress in right whales. Proc. Biol. Sci.279, 2363–8. (doi:10.1098/rspb.2011.2429)
By Dawn Barlow, M.S. Ph.D. student, Department of Fisheries and Wildlife, Oregon State University
For years, I have said I want to do “applied conservation science”. As an undergraduate student at Pitzer College I was a double major in Biology and Environmental Policy. While I have known that I wanted to study the oceans on some level my whole life, and I have known for about a decade that I wanted to be a scientist, I realized in college that I wanted to learn how science could be a tool for effective conservation of the marine ecosystems that fascinate me.
Just over a week ago, I successfully defended my MS thesis. When Leigh introduced me at the public seminar, she read a line from my initial letter to her expressing my interest in being her graduate student: “My passion for cetacean research lies not only in fascination of the animals but also how to translate our knowledge of their biology and ecological roles into effective conservation and management measures.” I believe I’ve grown and learned a lot in the two and a half years since I crafted that email and nervously hit send, but the statement is still true.
My graduate research in many ways epitomizes what I am passionate about. I am part of a team studying the ecology of blue whales in a highly industrial area of New Zealand. Not only is it a system in which we can address fascinating questions in ecology, it is also a region that experiences extensive pressure from human use and so all of our findings have direct management implications.
We recently published a paper documenting and describing this New Zealand blue whale population, and the findings reached audiences and news outlets far and wide. Leigh and I are headed to New Zealand for the first two weeks in July. During this time we will not only present our latest findings at the Society for Conservation Biology Oceania Conference, we will also meet with managers at the New Zealand Department of Conservation, speak with the Minister of Energy and Resources as well as the Minster of Conservation, meet with the CEO and Policy Advisor of PEPANZ (a representative group of oil and gas companies in New Zealand), and participate in a symposium of scientists and stakeholders aiming to establish goals for the protection of whales in New Zealand. Now, “applied conservation science” extends well beyond a section in the discussion of a paper outlining the implications of the findings for management.
A blue whale surfaces in front of a floating production storage and offloading (FPSO) vessel servicing the oil rigs in the South Taranaki Bight. Photo by Dawn Barlow.
During our 2017 field season in New Zealand, Leigh and I found ourselves musing on the flying bridge of the research vessel about all the research questions still to be asked of this study system and these blue whales. How do they forage? What are their energetic demands? How does disturbance from oil and gas exploration impact their foraging and their energetic demands? Leigh smiled and told me, “You better watch out, or this will turn into your PhD.” I said that maybe it should. Now I am thrilled to immerse myself into the next phase of this research project and the next chapter of my academic journey as a PhD student. This work is applied conservation science, and I am a conservation biologist. Here’s to retaining my passion for ecology and fascination with my study system, while not losing sight of the implications and applications of my work for conservation. I am excited for what is to come!
Dawn Barlow and Dr. Leigh Torres aboard the R/V Star Keys during the 2017 blue whale field season in New Zealand. Photo by Todd Chandler.
By Dawn Barlow, MSc student, Department of Fisheries and Wildlife, Geospatial Ecology of Marine Megafauna Lab
In 2013, Leigh first published a hypothesis that the South Taranaki Bight region between New Zealand’s North and South Islands is important habitat for blue whales (Torres 2013). Since then, we have collected three years of data and conducted dedicated analyses, so we now understand that a unique population of blue whales is found in New Zealand, and that they are present in the South Taranaki Bight year-round (Barlow et al. in press).
This research has garnered quite a bit of political and media attention. A major platform item for the New Zealand Green Party around the last election was the establishment of a marine mammal sanctuary in the South Taranaki Bight. When the world’s largest seismic survey vessel began surveying the South Taranaki Bight this summer for more oil and gas reserves using tremendously loud airguns, there were rallies on the lawn in front of Parliament featuring a large inflatable blue whale that the protesters affectionately refer to as “Janet”. Needless to say, blue whales have made their way into the spotlight in New Zealand.
Now that we know there is a unique population of blue whales in New Zealand, what is next? What’s next for me is an exciting combination of both ecology and conservation. If an effective sanctuary is to be implemented, it needs to be more than a simple box drawn on a map to check off a political agenda item—the sanctuary should be informed by our best ecological knowledge of the blue whales and their habitat.
In July, Leigh and I will attend the Society for Conservation Biology meeting in Wellington, New Zealand, and I’ll be giving a presentation titled “Cloudy with a chance of whales: Forecasting blue whale presence based on tiered, bottom-up models”. I’ll be the first to admit, I am not yet forecasting blue whale presence. But I am working my way there, step-by-step, through this tiered, bottom-up approach. In cetacean habitat modeling, we often assume that whale distribution on a foraging ground is determined by their prey’s distribution, and that satellite images of temperature and chlorophyll-a provide an accurate picture of what is going on below the surface. Is this true? With our three years of data including in situ oceanography, krill hydroacoustics, and blue whale distribution and behavior, we are in a unique position to test some of those assumptions, as well as provide managers with an informed management tool to predict blue whale distribution.
What questions will we ask using our data? Firstly, can in situ oceanography (i.e., thermocline depth and temperature, mixed layer depth) predict the distribution and density of blue whale prey (krill)? Then, can those prey patterns be accurately predicted in the absence of oceanographic measurements, using just satellite images? Next, we’ll bring the blue whales back into the picture to ask: can we predict blue whale distribution based on our in situ measurements of oceanography and prey? And finally, in the absence of in situ measurements (which is most often the case), can we forecast where the whales will be based just on remotely-sensed images of the region?
So, cloudy with a chance of whales? Well, you’ll have to stay tuned for that story in the coming months. In the meantime, I can tell you that as daunting as it is to aggregate so many data streams, each step of the way has a piece of the story to tell. I can’t wait to see how it falls together, both from an ecological modeling perspective and a conservation management objective.
Torres, L. G. (2013). Evidence for an unrecognised blue whale foraging ground in New Zealand. New Zealand Journal of Marine and Freshwater Research, 47(2), 235-248.
Barlow, D. R., Torres, L. G., Hodge, K. B., Steel, D. Baker, C. S., 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. (in press). Documentation of a New Zealand blue whale population based on multiple lines of evidence. Endangered Species Research.
By Dawn Barlow, MSc student, Department of Fisheries and Wildlife
A few weeks ago, my labmate Dom’s blog reminded me that it is important to step back from the data and appreciate the magnificence of the animals we study from time to time. I have the privilege of studying the largest creatures on the planet. When people hear that I study blue whales, I often get a series of questions: Just how big are they, really? How many are there? Where do they migrate? Where do they breed? Despite the fact that humans hunted blue whales nearly to extinction [1,2], we still know next to nothing about these giants. The short answer to many of those questions is, “Well we don’t really know, but we’re working on it!” Which brings me back to taking time to marvel at these animals for a bit. Isn’t it remarkable that the largest animals on earth can be so mysterious?
Last year at this time we were aboard a research vessel in New Zealand surveying for blue whales and collecting a myriad of biological data to try and glean some insight into their lives. This winter I am processing those data and conducting a literature review to get a firm grasp on what others have found before about blue whale foraging and bioenergetics. On any given Tuesday morning Leigh and I can be found musing about the mechanics of a baleen whale jaw, about what oceanographic boundaries in the water column might be meaningful to a blue whale, about how we might quantify the energy expenditure of a foraging whale. Here are some of those musings.
Humans are, for the most part, terrestrial creatures. Even those of us that would prefer to spend most of our time near, on, or in the water are limited in what we can observe of marine life. Much of the early data that was collected on blue whales came from whaling catches. Observations of anatomy and morphology were made once the whales were killed and taken out of their marine environment. This was not long ago—Soviet whaling continued into the 1970’s in New Zealand . Because baleen whales are long lived (exact age unknown for blue whales but a bowhead whale was estimated to be at least 150 years old ) it is entirely possible that blue whales living today remember being hunted by whalers. Observing whales in their natural state is not easy, particularly post-commercial whaling when they are few and far between.
Yet, where there is a challenge, clever people develop creative approaches and new technologies, leading to new insights. High-quality cameras have allowed scientists to photograph whales for individual identification—a valuable first step in figuring out how many there are and where they go . Satellite tags have allowed scientists to track the movement of blue whales in the North Pacific and Indian Oceans, a first step in learning where these whales might go to breed. However, no blue whale breeding ground has definitively been discovered yet…
What does a whale do when it is below the surface, out of sight of our terrestrial eyes? A study from 1986 that attempted to calculate the prey demands of a whale assumed that whenever a whale was submerged, it was feeding . A big assumption, but a starting place without any dive data. By 2002, tags equipped with time-depth recorders (TDR) had already revealed that blue whales make dives of variable depths and shapes . But, what determines a whale’s path underwater, where they must conserve as much oxygen as they can while finding and exploiting patches of prey? The advent of digital acoustic recording tags (DTAGs) in the early 2000s have allowed scientists to measure the fine-scale movements of whales in three dimensions . These tags can capture the kinematic signatures (based on pitch, roll, and yaw) of lunge-feeding events below the surface. And with the addition of echosounder technology that allows us to map the prey field, we can now link feeding events with characteristics of the prey present in the area . With this progression of technology, curiosity and insight we now know that blue whales are not indiscriminate grazers, but instead pass up small patches of krill in favor of large, dense aggregations where they will get the most energetic bang for their buck.
A blue whale lunges on an aggregation of krill. UAS piloted by Todd Chandler.
Through innovative approaches, we are beginning to understand the lives of these mysterious giants. As is true for many things, the more we learn, the more questions we have. Through the GEMM Lab’s blue whale project, we have determined that a unique population of blue whales occupies the South Taranaki Bight region of New Zealand year-round; they do not simply migrate through as their current threat classification status indicates . But what are their distribution patterns? Can we predict when and where whales are most likely to be in the South Taranaki Bight? Does this population have a different foraging strategy than their Californian, Chilean, or Antarctic counterparts? These are the things we are working on unraveling, and that will aid in their conservation. In the meantime, I’ll keep musing about what we don’t know, and remember to keep marveling at what we do know about the largest creatures on earth.
Clapham, P. J., Young, S. B. & Brownell Jr., R. L. Baleen whales: conservation issues and the status of the most endangered populations. Mamm. Rev.29, 37–60 (1999).
Branch, T. a, Matsuoka, K. & Miyashita, T. Evidence for increases in Antarctic blue whales based on baysian modelling. Mar. Mammal Sci.20, 726–754 (2004).
Branch, T. A. et al. Past and present distribution, densities and movements of blue whales Balaenoptera musculus in the Southern Hemisphere and northern Indian Ocean. Mammal Review37, 116–175 (2007).
George, J. C. et al. Age and growth estimates of bowhead whales (Balaena mysticetus) via aspartic acid racemization. Can. J. Zool.77, 571–580 (1998).
Sears, R. et al. Photographic identification of the Blue Whale (Balaenoptera musculus) in the Gulf of St. Lawrence, Canada. Report of the International Whaling Commission Special Issue 335–342 (1990).
Kenney, R. D., Hyman, M. A. M., Owen, R. E., Scott, G. P. & Winn, H. E. Estimation of prey densities required by Western North Atlantic right whales. Mar. Mammal Sci.2, 1–13 (1986).
Acevedo-Gutierrez, A., Croll, D. A. & Tershy, B. R. High feeding costs limit dive time in the largest whales. J. Exp. Biol.205, 1747–1753 (2002).
Johnson, M. P. & Tyack, P. L. A digital acoustic recording tag for measuring the response of wild marine mammals to sound. IEEE J. Ocean. Eng.28, 3–12 (2003).
Hazen, E. L., Friedlaender, A. S. & Goldbogen, J. A. Blue whales (Balaenoptera musculus) optimize foraging efficiency by balancing oxygen use and energy gain as a function of prey density. Sci. Adv.1, e1500469–e1500469 (2015).
Baker, C. S. et al.Conservation status of New Zealand marine mammals, 2013. (2016).
By Dawn Barlow, MSc Student, Department of Fisheries and Wildlife
The days are growing shorter, and 2017 is drawing to a close. What a full year it has been for the GEMM Lab! Here is a recap, filled with photos, links to previous blogs, and personal highlights, best enjoyed over a cup of hot cocoa. Happy Holidays from all of us!
Things started off with a bang in January as the New Zealand blue whale team headed to the other side of the world for another field season. Leigh, Todd and I joined forces with collaborators from Cornell University and the New Zealand Department of Conservation aboard the R/V Star Keys for the duration of the survey. What a fruitful season it was! We recorded sightings of 68 blue whales, collected biopsy and fecal samples, as well as prey and oceanographic data. The highlight came on our very last day when we were able to capture a blue whale surface lunge feeding on krill from an aerial perspective via the drone. This footage received considerable attention around the world, and now has over 3 million views!
In the spring Rachael made her way to the remote Pribilof Islands of Alaska to study the foraging ecology of red-legged kittiwakes. Her objectives included comparing the birds that reproduce successfully and those that don’t, however she was thrown a major curveball: none of the birds in the colony were able to successfully reproduce. In fact, they didn’t even build nests. Further analyses may elucidate some of the reasons for the reproductive failure of this sentinel species of the Bering Sea… stay tuned.
Florence is a newly-minted MSc! In June, Florence successfully defended her Masters research on gray whale foraging and the impacts of vessel disturbance. She gracefully answered questions from the room packed with people, and we all couldn’t have been prouder to say “that’s my labmate!” during the post-defense celebrations. But she couldn’t leave us just yet! Florence stayed on for another season of field work on the gray whale foraging ecology project in Port Orford, this time mentoring local high school students as part of the project. Florence’s M.Sc. defense!
Upon the gray whales’ return to the Oregon Coast for the summer, Leila, Leigh, and Todd launched right back into the stress physiology and noise project. This year, the work included prey sampling and fixed hydrophones that recorded the soundscape throughout the season. The use of drones continues to offer a unique perspective and insight into whale behavior.
Video captured under NOAA/NMFS permit #16111.
Solene spent the austral winter looking for humpback whales in the Coral Sea, as she participated in several research cruises to remote seamounts and reefs around New Caledonia. This field season was full of new experiences (using moored hydrophones on Antigonia seamount, recording dive depths with SPLASH10 satellite tags) and surprises. For the first time, whales were tracked all the way from New Caledonia to the east coast of Australian. As her PhD draws to a close in the coming year, she will seek to understand the movement patterns and habitat preferences of humpback whales in the region.
A humpback whale observed during the 2017 coral sea research cruise. Photo by S. Derville.
During the austral wintertime when most of us were all in Oregon, the New Zealand blue whale project received more and more political and media attention. Leigh was called to testify in court as part of a contentious permit application case for a seabed mine in the South Taranaki Bight. As austral winter turned to austral spring, a shift in the New Zealand government led to an initiative to designate a marine mammal sanctuary in the South Taranaki Bight, and awareness has risen about the potential impacts of seismic exploration for oil and gas reserves. These tangible applications of our research to management decisions is very gratifying and empowers us to continue our efforts.
In the fall, many of us traveled to Halifax, Nova Scotia to present our latest and greatest findings at the 22nd Biennial Conference on the Biology of Marine Mammals. The strength of the lab shone through at the meeting during each presentation, and we all beamed with pride when we said our affiliation was with the GEMM Lab at OSU. In other conference news, Rachael was awarded the runner-up for her presentation at the World Seabird Twitter Conference!
Leigh had a big year in many ways. Along with numerous scientific accomplishments—new publications, new students, successful fieldwork, successful defenses—she had a tremendous personal accomplishment as well. In the spring she was diagnosed with breast cancer, and after a hard fight she was pronounced cancer-free this November. We are all astounded with how gracefully and fearlessly she navigated these times. Look out world, this lab’s Principle Investigator can accomplish anything!
This austral summer we will not be making our way south to join the blue whales. However, we are keenly watching from afar as a seismic survey utilizing the largest seismic survey vessel in the world has launched in the South Taranaki Bight. This survey has been met with considerable resistance, culminating in a rally led by Greenpeace that featured a giant inflatable blue whale in front of Parliament in Wellington. We are eagerly planning our return to continue this study, but that will hopefully be the subject of a future blog.
In our final lab meeting of the year, we went around the table to share what we’ve learned this year. The responses ranged from really grasping the mechanisms of upwelling in the California Current to gaining proficiency in coding and computing, to the importance of having a supportive community in graduate school to trust that the right thing will happen. If you are reading this, thank you for your interest in our work. We are looking forward to a successful 2018. Happy holidays from the GEMM Lab!
Dr. Leigh Torres, Geospatial Ecology of Marine Megafauna Lab, Marine Mammal Institute, Oregon State University
Dr. Holger Klinck, Bioacoustics Research Program, Cornell Lab of Ornithology, Cornell University
For too long the oil and gas industry has polluted the ocean with seismic airgun noise with little consequence. The industry uses seismic airguns in order to find their next lucrative reserve under the seafloor, and because their operations are out of sight and the noise is underwater many have not noticed this deafening (literally1) noise. As terrestrial and vision-dependent animals, we humans have a hard time appreciating the importance of sound in the marine environment. Most of the ocean is a dark place, where vision does not work well, so many animals are dependent on sound to survive. Especially marine mammals like whales and dolphins.
But, hearing is believing, so let’s have a listen to a recording of seismic airguns firing in the South Taranaki Bight (STB) of New Zealand, a known blue whale feeding area. This is a short audio clip of a seismic airgun firing every ~8 seconds (a typical pattern). Before you hit play, close your eyes and imagine you are a blue whale living in this environment.
Now, put that clip on loop and play it for three months straight. Yes, three months. This consistent, repetitive boom is what whales living in a region of oil and gas exploration hear, as seismic surveys often last 1-4 months.
So, how loud is that, really? Your computer or phone speaker is probably not good enough to convey the power of that sound (unless you have a good bass or sub-woofer hooked up). Industrial seismic airgun arrays are among the loudest man-made sources2 and the noise emitted by these arrays can travel thousands of kilometers3. Noise from a single seismic airgun survey can blanket an area of over 300,000 km2, raising local background noise levels 100-fold4.
Now, oil and gas representatives frequently defend their seismic airgun activities with two arguments, both of which are false. You can hear both these arguments made recently in this interview by a representative of the oil and gas industry in New Zealand defending a proposal to conduct a 3 month-long seismic survey in the STB while blue whales will be feeding there.
First, the oil and gas industry claim that whales and dolphins can just leave the area if they choose. But this is their home, where they live, where they feed and breed. These habitats are not just anywhere. Blue whales come to the STB to feed, to sustain their bodies and reproductive capacity. This habitat is special and is not available anywhere else nearby, so if a whale leaves the STB because of noise disturbance it may starve. Similarly, oil and gas representatives have falsely claimed that because whales stay in the area during seismic airgun activity this indicates they are not being disturbed. If you had the choice of starving or listening to seismic booming you might also choose the latter, but this does not mean you are not disturbed (or annoyed and stressed). Let’s think about this another way: imagine someone operating a nail gun for three months in your kitchen and you have nowhere else to eat. You would stay to feed yourself, but your stress level would elevate, health deteriorate, and potentially have hearing damage. During your next home renovation project you should be happy you have restaurants as alternative eateries. Whales don’t.
Second, the oil and gas industry have claimed that the frequency of seismic airguns is out of the hearing range of most whales and dolphins. This statement is just wrong. Let’s look at the spectrogram of the above played seismic airgun audio clip recorded in the STB. A spectrogram is a visual representation of sound (to help us vision-dependent animals interpret sound). Time is on the horizontal axis, frequency (pitch) is on the vertical axis, and the different colors on the image indicate the intensity of sound (loudness) with bright colors illustrating areas of higher noise. Easily seen is that as the seismic airgun blasts every ~8 seconds, there is elevated noise intensity across all frequencies (bright yellow, orange and green bands). This noise intensity is especially high in the 10 – 80 Hz frequency range, which is exactly where many large baleen whales – like the blue whale – hear and communicate.
In the big, dark ocean, whales use sound to communicate, find food, and navigate. So, let’s try to imagine what it’s like for a whale trying to communicate in an environment with seismic airgun activity. First, let’s listen to a New Zealand blue whale call (vocalization) recorded in the STB. [This audio clip is played at 10X the original speed so that it is more audible to the human hearing frequency range. You can see the real time scale in the top plot.]
Now, let’s look at a spectrogram of seismic airgun pulses and a blue whale call happening at the same time. The seismic airgun blasts are still evident every ~8 seconds, and the blue whale call is also evident at about the 25 Hz frequency (within the pink box). Because blue whales call at such a low frequency humans cannot hear their call when played at normal speed, so you will only hear the airgun pulses if you hit play. But you can see in the spectrogram that five airgun blasts overlapped with the blue whale call.
No doubt this blue whale heard the repetitive seismic airgun blasts, and vocalized in the same frequency range at the same time. Yet, the blue whale’s call was partially drowned out by the intense seismic airgun blasts. Did any other whale hear it? Could this whale hear other whales? Did it get the message across? Maybe, but probably not very well.
Some oil and gas representatives point toward their adherence to seismic survey guidelines and use of marine mammal observers to reduce their impacts on marine life. In New Zealand these guidelines only stop airgun blasting when animals are within 1000 m of the vessel (1.5 km if a calf is present), yet seismic airgun blasts are so intense that the noise travels much farther. So, while these guidelines may be a start, they only prevent hearing damage to whales and dolphins by stopping airguns from blasting right on top of animals.
So, what does this mean for whales and other marine animals living in habitat where seismic airguns are operating? It means their lives are disturbed and dramatically altered. Multiple scientific studies have shown that whales change behavior5, distribution6, and vocalization patterns7 when seismic airguns are active. Other marine life like squid8, spiny lobster9, scallops10, and plankton11 also suffer when exposed to airgun noise. The evidence has mounted. There is no longer a scientific debate: seismic airguns are harmful to marine animals and ecosystems.
What we are just starting to study and understand is the long-term and population level effects of seismic airguns on whales and other marine life. How do short term behavioral changes, movement to different areas, and different calling patterns impact an individual’s ability to survive or a population’s ability to persist? These are the important questions that need to be addressed now.
Seismic airgun surveys to find new oil and gas reserves are so pervasive in our global oceans, that airgun blasts are now heard year round in the equatorial Atlantic3, 12. As reserves shrink on land, the industry expands their search in our oceans, causing severe and persistent consequences to whales, dolphins and other marine life. The oil and gas industry must take ownership of the impacts of their seismic airgun activities. It’s imperative that political, management, scientific, and public pressure force a more complete assessment of each proposed seismic airgun survey, with an honest evaluation of the tradeoff between economic benefits and costs to marine life.
Here are a few ways we can reduce the impact of seismic airguns on marine life and ecosystems:
Restrict seismic airgun operation in and near sensitive environmental areas, such as marine mammal feeding and breeding areas.
Prohibit redundant seismic surveys in the same area. If one group has already surveyed an area, that data should be shared with other groups, perhaps after an embargo period.
Cap the number and duration of seismic surveys allowed each year by region.
Promote the use of renewable energy sources.
Develop new and quieter survey methods.
Even though we cannot hear the relentless booming, this does not mean it’s not happening and harming animals. Please listen one more time to 1 minute of what whales hear for months during seismic airgun operations.
More information on seismic airgun surveys and their impact on marine life:
Gordon, J., et al., A review of the effects of seismic surveys on marine mammals. Marine Technology Society Journal, 2003. 37(4): p. 16-34.
National Research Council (NRC), Ocean Noise and Marine Mammals. 2003, National Academy Press: Washington. p. 204.
Nieukirk, S.L., et al., Sounds from airguns and fin whales recorded in the mid-Atlantic Ocean, 1999–2009. The Journal of the Acoustical Society of America, 2012. 131(2): p. 1102-1112.
Weilgart, L., A review of the impacts of seismic airgun surveys on marine life. 2013, Submitted to the CBD Expert Workshop on Underwater Noise and its Impacts on Marine and Coastal Biodiversity 25-27 February 2014: London, UK. .
Miller, P.J., et al., Using at-sea experiments to study the effects of airguns on the foraging behavior of sperm whales in the Gulf of Mexico. Deep Sea Research Part I: Oceanographic Research Papers, 2009. 56(7): p. 1168-1181.
Castellote, M., C.W. Clark, and M.O. Lammers, Acoustic and behavioural changes by fin whales (Balaenoptera physalus) in response to shipping and airgun noise. Biological Conservation, 2012. 147(1): p. 115-122.
Di lorio, L. and C.W. Clark, Exposure to seismic survey alters blue whale acoustic communication. Biology Letters, 2010. 6(1): p. 51-54.
Fewtrell, J. and R. McCauley, Impact of air gun noise on the behaviour of marine fish and squid. Marine pollution bulletin, 2012. 64(5): p. 984-993.
Fitzgibbon, Q.P., et al., The impact of seismic air gun exposure on the haemolymph physiology and nutritional condition of spiny lobster, Jasus edwardsii. Marine Pollution Bulletin, 2017.
Day, R.D., et al., Exposure to seismic air gun signals causes physiological harm and alters behavior in the scallop Pecten fumatus. Proceedings of the National Academy of Sciences, 2017. 114(40): p. E8537-E8546.
McCauley, R.D., et al., Widely used marine seismic survey air gun operations negatively impact zooplankton. Nature Ecology & Evolution, 2017. 1(7): p. s41559-017-0195.
Haver, S.M., et al., The not-so-silent world: Measuring Arctic, Equatorial, and Antarctic soundscapes in the Atlantic Ocean. Deep Sea Research Part I: Oceanographic Research Papers, 2017. 122: p. 95-104.
By Dawn Barlow, MSc Student, Department of Fisheries and Wildlife, Geospatial Ecology of Marine Megafauna Lab
Every two years, an international community of scientists gather for one week to discuss the most current and pressing science and conservation issues surrounding marine mammals. The thousands of attendees range from longtime researchers who have truly shaped the field throughout the course of their careers to students who are just beginning to carve out a niche of their own. I was able to attend the last conference, which took place in San Francisco in 2015, as an undergraduate. The experience cemented my desire to pursue marine mammal research in graduate school and beyond, and also solidified my connection with Leigh Torres and the Geospatial Ecology of Marine Megafauna Laboratory, leading to my current enrollment at Oregon State University. This year, the 22nd Biennial Conference on the Biology of Marine Mammals takes place in Halifax, Nova Scotia, Canada. At the end of this week, Florence, Leila, Amanda, Solene, Sharon and I will head northeast to represent the GEMM Lab at the meeting!
As those of you reading this may not be able to attend, I’d like to share an overview of what we will be presenting next week. If you will be in Halifax, we warmly invite you to the following presentations. In order of appearance:
Amanda will present the final results from part of her MSc thesis on Monday in a presentation titled Comparative fine-scale harbor porpoise habitat models developed using remotely sensed and in situ data. It will be great for current GEMM Lab members to catch up with this recent GEMM Lab graduate on the other side of the continent! (Session: Conservation; Time: 4:00 pm)
On Tuesday morning, Leila will share the latest and greatest updates on her research about Oregon gray whales, including photogrammetry from drone images and stress hormones extracted from fecal samples! Her presentation is titled Combining traditional and novel techniques to link body condition and hormone variability in gray whales. This is innovative and cutting-edge work, and it is exciting to think it will be shared with the international research community. (Session: Health; Time: 10:45 am)
Did you think humpback whales have been so well studied that we must know just about everything about them? Think again! Solene will be sharing new and exciting insights from humpback whales tagged in New Caledonia, who appear to spend an intriguing amount of time around seamounts. Her talk Why do humpback whales aggregate around seamounts in South Pacific tropical waters? New insights from diving behaviour and ocean circulation analyses, will take place on Tuesday afternoon. (Session: Habitat and Distribution Speed Talks; Time: 1:30 pm)
I will be presenting the latest findings from our New Zealand blue whale research. Based on multiple data streams, we now have evidence for a unique blue whale population which is present year-round in New Zealand waters! This presentation, titled From migrant to resident: Multiple data streams point toward a resident New Zealand population of blue whales, will round out the oral presentations on Tuesday afternoon. (Session: Population Biology and Abundance; Time: 4:45 pm)
The GEMM Lab is using new technologies and innovative quantitative approaches to measure gray whale body condition and behaviors from an aerial perspective. On Wednesday afternoon, Sharon will present Drone up! Quantifying whale behavior and body condition from a new perspective on behalf of Leigh. With the emerging prevalence of drones, we are excited to introduce these quantitative applications. (Session: New Technology; Time: 11:45 am)
GoPros, kayaks, and gray whales, oh my! A limited budget couldn’t stop Florence from conducting excellent science and gaining new insights into gray whale fine-scale foraging. On Thursday afternoon, she will present Go-Pros, kayaks and gray whales: Linking fine-scale whale behavior with prey distributions on a shoestring budget, and share her findings, which she was able to pull off with minimal funds, creative study design, and a positive attitude. (Session: Foraging Ecology Speed Talks; Time: 1:55 pm)
Additional Oregon State University students presenting at the conference will include Michelle Fournet, Samara Haver, Niki Diogou, and Angie Sremba. We are thrilled to have such good representation at a meeting of this caliber! As you may know, we are all working on building the GEMM Lab’s social media presence and becoming more “twitterific”. So during the conference, please be sure to follow @GEMMLabOSU on twitter for live updates. Stay tuned!
By Dawn Barlow, MSc Student, Department of Fisheries and Wildlife, Geospatial Ecology of Marine Megafauna Lab
In late February, we wrapped up our 2017 blue whale survey of the South Taranaki Bight region. Upon returning to port in Wellington, Leigh and I each located our one remaining clean shirt, drank a cup of coffee, and walked into a room full of lawyers in suits where Leigh testified in front of the Environmental Protection Authority’s (EPA) Decision Making Committee. The hearing was for Trans-Tasman Resources, Ltd. (TTR)’s application for a permit to extract 50 million tons of iron sands per year from the sea floor for a 35-year period. Our reason for being there? Leigh was called as an expert witness to present our findings on blue whale distribution and ecology in the region where the proposed mining operation will be so that the potential impacts could be properly evaluated by the Decision Making Committee. Talk about seeing an immediate application of your research!
Fast forward several months. The decision of whether or not the permit will be granted has been delayed, more evidence has been requested and considered, Leigh has testified again via skype, and the decision has been delayed yet again. It is a contentious case, and people on both sides have grown impatient, concerned, and frustrated. Finally, the date and time of the decision announcement finds me nervously refreshing my browser window until I see the outcome: the mining permit has been approved. It was a split decision by the committee of four, with the committee chair casting the deciding vote.
While the Decision Making Committee was split on whether or not the permit should be approved, the constituency was not. During the hearing process, over 13,700 submissions were received, 99% of which were in opposition to the mining operation. Opposition came from Iwi (Maori tribes), commercial and recreational fishing industries, scientists, and residents of local coastal communities.
What does this mean for New Zealand, for the whales, for the ecosystem, for the future? This decision represents a landmark case that will surely set a new precedent. It is the first of its kind to be approved in New Zealand, and the first commercial scale seabed mining operation in the world. Other permit applications for seabed mines elsewhere will no doubt be submitted in the wake of the approval of TTR’s iron sands mining operation. The groups Kiwis Against Seabed Mining and Greenpeace New Zealand have announced that they will appeal the EPA’s decision in High Court, and TTR cannot begin dredging until all appeals are heard and two years of environmental monitoring have taken place.
So for the time being, life continues as usual for the blue whales. They will carry on feeding and raising their young in the South Taranaki Bight, where they already are surrounded by oil rigs, vessel traffic, and seismic airguns. In the meantime, above the water’s surface, many dedicated individuals are prepared to fight hard for environmental conservation. The blue whales will likely continue to unknowingly play a role in the decision-making process as our data demonstrate the importance of this region to their ecology, and the New Zealand public and media continue to learn about these iconic animals. The research effort I am part of has the potential to immediately and concretely influence policy decisions, and I sincerely hope that our findings will not fall on deaf ears in the appeal process. While we continue to provide biological evidence, politicians, the media, and the public need to emphasize the value of preserving biodiversity. These blue whales can be a figurehead for a more sustainable future for the region.
If you are interested in learning more, I invite you to take a minute to visit the web pages listed below.
Kiwis against seabed mining (KASM), the group leading the effort to stop seabed mining in New Zealand: http://kasm.org.nz/
By Dawn Barlow, MSc student, OSU Department of Fisheries and Wildlife, Geospatial Ecology of Marine Megafauna Lab
I was fortunate enough to spend the Austral summer in the field, and so while the winter rain poured down on Oregon I found myself on the water with the sun and wind on my face, looking for blue whales in New Zealand. This spring I switched gears and spent time taking courses to build my analytical toolbox. In a course on technical writing and communication, I was challenged to present my research using only pictures and words with no written text, and to succinctly summarize the importance of my research in an introduction to a technical paper. I attended weekly seminars to learn about the diverse array of marine science being conducted at Oregon State University and beyond. I also took a course entitled “Advanced Spatial Statistics and Geographic Information Science”. In this skill-building course, we were given the opportunity to work with our own data. Even though my primary objective was to expand the tools in my toolbox, I was excited to explore preliminary results and possible insight into blue whale habitat selection in my study area, the South Taranaki Bight region (STB) of New Zealand (Figure 1).
Despite the recent documentation of a foraging ground in the STB, blue whale distribution remains poorly understood in New Zealand. The STB is New Zealand’s most industrially active marine region, and the site of active oil and gas extraction and exploration, busy shipping traffic, and proposed seabed mining. This potential space-use conflict between endangered whales and industry warrants further investigation into the spatial and temporal extent of blue whale habitat in the region. One of my research objectives is to investigate the relationship between blue whales and their environment, and ultimately to build a model that can predict blue whale presence based on physical and biological oceanographic features. For this spring term, the question I asked was:
Is the number of blue whales present in an area correlated with remotely-sensed sea surface temperature and chlorophyll-a concentration?
For the purposes of this exploration, I used data from our 2017 survey of the STB. This meant importing our ship’s track and our blue whale sighting locations into ArcGIS, so that the data went from looking like this:
… to this:
The next step was to get remote-sensed images for sea surface temperature (SST) and chlorophyll-a (chl-a) concentration. I downloaded monthly averages from the NASA Moderate Resolution Imaging Spectrometer (MODIS aqua) website for the month of February 2017 at 4 km2 resolution, when our survey took place. Now, my images looked something more like this:
But, I can’t say anything reliable about the relationships between blue whales and their environment in the places we did not survey. So next I extracted just the portions of my remote-sensed images where we conducted survey effort. Now my maps looked more like this one:
The above map shows SST along our ship’s track, and the locations where we found whales. Just looking at this plot, it seems like the blue whales were observed in both warmer and colder waters, not exclusively in one or the other. There is a productive plume of cold, upwelled water in the STB that is generated off of Kahurangi point and curves around Farewell Spit and into the bight (Figure 1). Most of the whales we saw appear to be near that plume. But how can I find the edges of this upwelled plume? Well, I can look at the amount of change in SST and chl-a across a spatial area. The places where warm and cold water meet can be found by assessing the amount of variability—the standard deviation—in the temperature of the water. In ArcGIS, I calculated the deviation in SST and chl-a concentration across the surrounding 20 km2 for each 4 km2 cell.
Now, how do I tie all of these qualitative visual assessments together to produce a quantitative result? With a statistical model! This next step gives me the opportunity to flex some other analytical muscles, and practice using another computational tool: R. I used a generalized additive model (GAM) to investigate the relationships between the number of blue whales observed in each 4 km2 cell our ship surveyed and the remote-sensed variables. The model can be written like this:
Number of blue whales ~ SST + chl-a + sd(SST) + sd(chl-a)
In other words, are SST, chl-a concentration, deviation in SST, and deviation in chl-a concentration correlated with the number of blue whales observed within each 4 km2 cell on my map?
This model found that the most important predictor was the deviation in SST. In other words, these New Zealand blue whales may be seeking the edges of the upwelling plume, honing in on places where warm and cold water meet. Thinking back on the time I spent in the field, we often saw feeding blue whales diving along lines of mixing water masses where the water column was filled with aggregations of krill, blue whale prey. Studies of marine mammals in other parts of the world have also found that eddies and oceanic fronts—edges between warm and cold water masses—are important habitat features where productivity is increased due to mixing of water masses. The same may be true for these New Zealand blue whales.
These preliminary findings emphasize the benefit of having both presence andabsence data. The analysis I have presented here is certainly strengthened by having environmental measurements for locations where we did not see whales. This is comforting, considering the feelings of impatience generated by days on the water spent like this with no whales to be seen:
Moving forward, I will include the blue whale sighting data from our 2014 and 2016 surveys as well. As I think about what would make this model more robust, it would be interesting to see if the patterns become clearer when I incorporate behavior into the model—if I look at whales that are foraging and traveling separately, are the results different? I hope to explore the importance of the upwelling plume in more detail—does the distance from the edge of the upwelling plume matter? And finally, I want to adjust the spatial and temporal scales of my analysis—do patterns shift or become clearer if I don’t use monthly averages, or if I change the grid cell sizes on my maps?
I feel more confident in my growing toolbox, and look forward to improving this model in the coming months! Stay tuned.