Forecasting blue whale presence: Small steps toward big goals

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).

A blue whale surfaces in the South Taranaki Bight. Photo by Leigh Torres.

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.

Janet the inflatable blue whale accompanies protesters on the lawn in front of Parliament in Wellington, New Zealand. Image credit: Greenpeace.

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?

The transducer pole in the water off the RV Star Keys (left) deployed with the echosounder to collect prey availability data, including this image (right) of krill swarms near feeding blue whales. Photo by Leigh Torres.

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.

A blue whale surfaces in front of a floating production storage and offloading (FPSO) vessel which services the oil rigs in the South Taranaki Bight. Photo by Dawn Barlow.

 

References:

Torres, L. G. (2013). Evidence for an unrecognised blue whale foraging ground in New Zealand. New Zealand Journal of Marine and Freshwater Research47(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. 

The Land of Maps and Charts: Geospatial Ecology

By Alexa Kownacki, Ph.D. Student, OSU Department of Fisheries and Wildlife, Geospatial Ecology of Marine Megafauna Lab

I love maps. I love charts. As a random bit of trivia, there is a difference between a map and a chart. A map is a visual representation of land that may include details like topology, whereas a chart refers to nautical information such as water depth, shoreline, tides, and obstructions.

Map of San Diego, CA, USA. (Source: San Diego Metropolitan Transit System)
Chart of San Diego, CA, USA. (Source: NOAA)

I have an intense affinity for visually displaying information. As a child, my dad traveled constantly, from Barrow, Alaska to Istanbul, Turkey. Immediately upon his return, I would grab our standing globe from the dining room and our stack of atlases from the coffee table. I would sit at the kitchen table, enthralled at the stories of his travels. Yet, a story was only great when I could picture it for myself. (I should remind you, this was the early 1990s, GoogleMaps wasn’t a thing.) Our kitchen table transformed into a scene from Master and Commander—except, instead of nautical charts and compasses, we had an atlas the size of an overgrown toddler and salt and pepper shakers to pinpoint locations. I now had the world at my fingertips. My dad would show me the paths he took from our home to his various destinations and tell me about the topography, the demographics, the population, the terrain type—all attribute features that could be included in common-day geographic information systems (GIS).

Uncle Brian showing Alexa where they were on a map of Maui, Hawaii, USA. (Photo: Susan K. circa 1995)

As I got older, the kitchen table slowly began to resemble what I imagine the set from Master and Commander actually looked like; nautical charts, tide tables, and wind predictions were piled high and the salt and pepper shakers were replaced with pencil marks indicating potential routes for us to travel via sailboat. The two of us were in our element. Surrounded by visual and graphical representations of geographic and spatial information: maps. To put my map-attraction this in even more context, this is a scientist who grew up playing “Take-Off”, a board game that was “designed to teach geography” and involved flying your fleet of planes across a Mercator projection-style mapboard. Now, it’s no wonder that I’m a graduate student in a lab that focuses on the geospatial aspects of ecology.

A precocious 3-year-old Alexa, sitting with the airplane pilot asking him a long list of travel-related questions (and taking his captain’s hat). Photo: Susan K.

So why and how did geospatial ecology became a field—and a predominant one at that? It wasn’t that one day a lightbulb went off and a statistician decided to draw out the results. It was a progression, built upon for thousands of years. There are maps dating back to 2300 B.C. on Babylonian clay tablets (The British Museum), and yet, some of the maps we make today require highly sophisticated technology. Geospatial analysis is dynamic. It’s evolving. Today I’m using ArcGIS software to interpolate mass amounts of publicly-available sea surface temperature satellite data from 1981-2015, which I will overlay with a layer of bottlenose dolphin sightings during the same time period for comparison. Tomorrow, there might be a new version of software that allows me to animate these data. Heck, it might already exist and I’m not aware of it. This growth is the beauty of this field. Geospatial ecology is made for us cartophiles (map-lovers) who study the interdependency of biological systems where location and distance between things matters.

Alexa’s grandmother showing Alexa (a very young cartographer) how to color in the lines. Source: Susan K. circa 1994

In a broader context, geospatial ecology communicates our science to all of you. If I posted a bunch of statistical outputs in text or even table form, your eyes might glaze over…and so might mine. But, if I displayed that same underlying data and results on a beautiful map with color-coded symbology, a legend, a compass rose, and a scale bar, you might have this great “ah-ha!” moment. That is my goal. That is what geospatial ecology is to me. It’s a way to SHOW my science, rather than TELL it.

Would you like to see this over and over again…?

A VERY small glimpse into the enormous amount of data that went into this map. This screenshot gave me one point of temperature data for a single location for a single day…Source: Alexa K.

Or see this once…?

Map made in ArcGIS of Coastal common bottlenose dolphin sightings between 1981-1989 with a layer of average sea surface temperatures interpolated across those same years. A picture really is worth a thousand words…or at least a thousand data points…Source: Alexa K.

For many, maps are visually easy to interpret, allowing quick message communication. Yet, there are many different learning styles. From my personal story, I think it’s relatively obvious that I’m, at least partially, a visual learner. When I was in primary school, I would read the directions thoroughly, but only truly absorb the material once the teacher showed me an example. Set up an experiment? Sure, I’ll read the lab report, but I’m going to refer to the diagrams of the set-up constantly. To this day, I always ask for an example. Teach me a new game? Let’s play the first round and then I’ll pick it up. It’s how I learned to sail. My dad described every part of the sailboat in detail and all I heard was words. Then, my dad showed me how to sail, and it came naturally. It’s only as an adult that I know what “that blue line thingy” is called. Geospatial ecology is how I SEE my research. It makes sense to me. And, hopefully, it makes sense to some of you!

Alexa’s dad teaching her how to sail. (Source: Susan K. circa 2000)
Alexa’s first solo sailboat race in Coronado, San Diego, CA. Notice: Alexa’s dad pushing the bow off the dock and the look on Alexa’s face. (Source: Susan K. circa 2000)
Alexa mapping data using ArcGIS in the Oregon State University Library. (Source: Alexa K circa a few minutes prior to posting).

I strongly believe a meaningful career allows you to highlight your passions and personal strengths. For me, that means photography, all things nautical, the great outdoors, wildlife conservation, and maps/charts.  If I converted that into an equation, I think this is a likely result:

Photography + Nautical + Outdoors + Wildlife Conservation + Maps/Charts = Geospatial Ecology of Marine Megafauna

Or, better yet:

📸 + ⚓ + 🏞 + 🐋 + 🗺 =  GEMM Lab

This lab was my solution all along. As part of my research on common bottlenose dolphins, I work on a small inflatable boat off the coast of California (nautical ✅, outdoors ✅), photograph their dorsal fin (photography ✅), and communicate my data using informative maps that will hopefully bring positive change to the marine environment (maps/charts ✅, wildlife conservation✅). Geospatial ecology allows me to participate in research that I deeply enjoy and hopefully, will make the world a little bit of a better place. Oh, and make maps.

Alexa in the field, putting all those years of sailing and chart-reading to use! (Source: Leila L.)

 

What REALLY is a Wildlife Biologist?

By Alexa Kownacki, Ph.D. Student, OSU Department of Fisheries and Wildlife, Geospatial Ecology of Marine Megafauna Lab

The first lecture slide. Source: Lecture1_Population Dynamics_Lou Botsford

This was the very first lecture slide in my population dynamics course at UC Davis. Population dynamics was infamous in our department for being an ultimate rite of passage due to it’s notoriously challenge curriculum. So, when Professor Lou Botsford pointed to his slide, all 120 of us Wildlife, Fish, and Conservation Biology majors, didn’t know how to react. Finally, he announced, “This [pointing to the slide] is all of you”. The class laughed. Lou smirked. Lou knew.

Lou knew that there is more truth to this meme than words could express. I can’t tell you how many times friends and acquaintances have asked me if I was going to be a park ranger. Incredibly, not all—or even most—wildlife biologists are park rangers. I’m sure that at one point, my parents had hoped I’d be holding a tiger cub as part of a conservation project—that has never happened. Society may think that all wildlife biologists want to walk in the footsteps of the famous Steven Irwin and say thinks like “Crikey!”—but I can’t remember the last time I uttered that exclamation with the exception of doing a Steve Irwin impression. Hollywood may think we hug trees—and, don’t get me wrong, I love a good tie-dyed shirt—but most of us believe in the principles of conservation and wise-use A.K.A. we know that some trees must be cut down to support our needs. Helicoptering into a remote location to dart and take samples from wild bear populations…HA. Good one. I tell myself this is what I do sometimes, and then the chopper crashes and I wake up from my dream. But, actually, a scientist staring at a computer with stacks of papers spread across every surface, is me and almost every wildlife biologist that I know.

The “dry lab” on the R/V Nathaniel B. Palmer en route to Antarctica. This room full of technology is where the majority of the science takes place. Drake Passage, International Waters in August 2015. Source: Alexa Kownacki

There is an illusion that wildlife biologists are constantly in the field doing all the cool, science-y, outdoors-y things while being followed by a National Geographic photojournalist. Well, let me break it to you, we’re not. Yes, we do have some incredible opportunities. For example, I happen to know that one lab member (eh-hem, Todd), has gotten up close and personal with wild polar bear cubs in the Arctic, and that all of us have taken part in some work that is worthy of a cover image on NatGeo. We love that stuff. For many of us, it’s those few, memorable moments when we are out in the field, wearing pants that we haven’t washed in days, and we finally see our study species AND gather the necessary data, that the stars align. Those are the shining lights in a dark sea of papers, grant-writing, teaching, data management, data analysis, and coding. I’m not saying that we don’t find our desk work enjoyable; we jump for joy when our R script finally runs and we do a little dance when our paper is accepted and we definitely shed a tear of relief when funding comes through (or maybe that’s just me).

A picturesque moment of being a wildlife biologist: Alexa and her coworker, Jim, surveying migrating gray whales. Piedras Blancas Light Station, San Simeon, CA in May 2017. Source: Alexa Kownacki.

What I’m trying to get at is that we accepted our fates as the “scientists in front of computers surrounded by papers” long ago and we embrace it. It’s been almost five years since I was a senior in undergrad and saw this meme for the first time. Five years ago, I wanted to be that scientist surrounded by papers, because I knew that’s where the difference is made. Most people have heard the quote by Mahatma Gandhi, “Be the change that you wish to see in the world.” In my mind, it is that scientist combing through relevant, peer-reviewed scientific papers while writing a compelling and well-researched article, that has the potential to make positive changes. For me, that scientist at the desk is being the change that he/she wish to see in the world.

Scientists aboard the R/V Nathaniel B. Palmer using the time in between net tows to draft papers and analyze data…note the facial expressions. Antarctic Peninsula in August 2015. Source: Alexa Kownacki.

One of my favorite people to colloquially reference in the wildlife biology field is Milton Love, a research biologist at the University of California Santa Barbara, because he tells it how it is. In his oh-so-true-it-hurts website, he has a page titled, “So You Want To Be A Marine Biologist?” that highlights what he refers to as, “Three really, really bad reasons to want to be a marine biologist” and “Two really, really good reasons to want to be a marine biologist”. I HIGHLY suggest you read them verbatim on his site, whether you think you want to be a marine biologist or not because they’re downright hilarious. However, I will paraphrase if you just can’t be bothered to open up a new tab and go down a laugh-filled wormhole.

Really, Really Bad Reasons to Want to be a Marine Biologist:

  1. To talk to dolphins. Hint: They don’t want to talk to you…and you probably like your face.
  2. You like Jacques Cousteau. Hint: I like cheese…doesn’t mean I want to be cheese.
  3. Hint: Lack thereof.

Really, Really Good Reasons to Want to be a Marine Biologist:

  1. Work attire/attitude. Hint: Dress for the job you want finally translates to board shorts and tank tops.
  2. You like it. *BINGO*
Alexa with colleagues showing the “cool” part of the job is working the zooplankton net tows. This DOES have required attire: steel-toed boots, hard hat, and float coat. R/V Nathaniel B. Palmer, Antarctic Peninsula in August 2015. Source: Alexa Kownacki.

In summary, as wildlife or marine biologists we’ve taken a vow of poverty, and in doing so, we’ve committed ourselves to fulfilling lives with incredible experiences and being the change we wish to see in the world. To those of you who want to pursue a career in wildlife or marine biology—even after reading this—then do it. And to those who don’t, hopefully you have a better understanding of why wearing jeans is our version of “business formal”.

A fieldwork version of a lab meeting with Leigh Torres, Tom Calvanese (Field Station Manager), Florence Sullivan, and Leila Lemos. Port Orford, OR in August 2017. Source: Alexa Kownacki.

GEMM Lab 2017: A Year in the Life

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!

The New Zealand blue whale team in action aboard the R/V Star Keys. Photo by L. Torres.

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!

A blue whale surfaces just off the bow of R/V Star Keys. Photo by D. Barlow.

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.

red-legged kittiwakes
Rachael releases a kittiwake on St. George Island. Photo by A. Fleishman.

 

The 2017 Port Orford field team. Photo by A. Kownacki.

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 projectFlorence’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 with a humpback whale biopsy sample. Photo by N. Job.

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.

This summer we were joined by two new lab members! Dom Kone will be studying the potential reintroduction of sea otters to the Oregon Coast as a MSc student in the Marine Resource Management program, and Alexa Kownacki will be studying population health of bottlenose dolphins in California as a PhD student in the Department of Fisheries and Wildlife. We are thrilled to have them on the GEMM Lab team, and look forward to seeing their projects develop. Speaking of new projects from this year, Leigh and Rachael have launched into some exciting research on interactions between albatrosses and fishing vessels in the North Pacific, funded by the NOAA Bycatch Reduction Engineering Program.

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!

GEMM Lab members present their research. From left to right, top to bottom: Amanda Holdman, Leila Lemos, Solène Derville, Dawn Barlow, Sharon Nieukirk, and Florence Sullivan.

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.

New publications for the GEMM Lab in 2017 include six for Leigh, three for Rachael, and two for Alexa. Highlights include Classification of Animal Movement Behavior through Residence in Space and Time and A sense of scale: Foraging cetaceans’ use of scale-dependent multimodal sensory systems. Next year is bound to be a big one for GEMM Lab publications, as Amanda, Florence, Solene, Leila, Leigh, and I all have multiple papers currently in review or revision, and more in the works from all of us. How exciting!

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!

GEMM Lab members, friends, and families gather for a holiday celebration.

The passion of a researcher

By Quince Nye, GEMM Lab Summer Intern, Pacific High School Junior

I have spent a lot of my life surrounded by nature. I like to backpack, bike, dive, and kayak in these natural environments. I also have the luck of having parents who are always planning to take me on another adventure where I get to see nature and its inhabitants in ways most people don’t get to enjoy.

Through my backyard explorations, I have begun to realize that Port Orford has an amazing ecosystem in the coves and rivers that are very tied into our community. I’ve fished and swam in these rivers, gone on kayaking tours in these coves (with a great kayak company called South Coast Tours that we partner with), and I’ve seen the life that dwells in them.

Nathan and Maggie paddle out to Mill Rocks for early morning sample collection

Growing up in a school of less than 100 kids I have learned to never reject an opportunity to be a part of something bigger and learn from that experience. So when one of my close friends told me about an OSU project (a college I’m interested in attending) that needed interns to help collect data on gray whales, and kayak almost every day, I signed up without a doubt in my mind.

The team gets some good practice tracking Buttons (Whale #3).  Left to right; Quince, Nathan, Maggie, Florence.

Fast forward a month, and I wake up at 5:20 am. I eat breakfast and get to the Port Orford Field Station. We make a plan for the operations of both the kayak team and cliff team. Today, I’m part of the cliff team, so I head up above the station to Fort Point. Florence and I set up the theodolite and computer at the lookout point and start taking half hour watch shifts searching the horizon for the spout of a gray whale.  Sometimes you see one right away, but other times it feels like the whales are actively hiding from you. These are the times I wish Maggie was here with her endless supply of Disney soundtracks to help pass the hours.

Imitating a ship’s captain, Quince points toward our whale while shouting “Mark”.

A whale spouts out at Mill Rocks and starts heading across to the jetty. Hurray, its data collection time! I try to quickly move the cross-hairs of the theodolite onto the position of the whale using a set of knobs like those on an etch-a-sketch. As you may understand, it’s not an easy task at first but I manage to do it because I’ve been practicing for three weeks. I say “Mark!” cueing Florence to click a button in the program Pythagoras on the computer to record the whale’s position.

The left hand side of Buttons – notice the scatter of white markings on the upper back.

Meanwhile, Florence sees that the whale has two white spots where the fluke meets the knuckles. Those are identifying marks of the beloved whale, Buttons. This whale has been seen here since 2016 and is a fan favorite for our on-going research program. Florence gets just as excited every time and texts her eagerly awaiting interns of previous years all about the sighting. Of course Buttons is not the only whale to have identifying marks such as scars and pigmentation marks. This is why we make sure to get photos of the whales we spot, allowing us to do photo-ID analysis on them through comparison to our database of pictures from previous years.

Quince practices CPR protocol on a training mannequin on his first day.

So far I have gained skill after skill in this internship. I got CPR certified, took a kayak training class, learned how to use a theodolite, and have spent many educational (and frustrating) hours entering data in Excel. I joined the program because I was interested in all of these things. It surprised me that I was developing a relationship with the whales I’m researching. By the end of August I’m now sure that I will also know many of the whales by name. I will probably be much better at using an etch-a-sketch, and I will have had my first taste at what being a scientist is like. What I strive for, however, is to have the same look in my eyes that appears in Florence’s whenever a familiar whale decides to browse our kelp beds.

Finding the edge: Preliminary insights into blue whale habitat selection in New Zealand

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).

Figure 1. A map of New Zealand, with the South Taranaki Bight (STB) region delineated by the black box. Farewell Spit is denoted by a star, and Kahurangi point is denoted by an X.

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 and absence 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.

GEMM Lab 2016: A Year in the Life

By Dawn Barlow, MSc Student, Department of Fisheries and Wildlife, Oregon State University

The year is rapidly coming to a close, and what a busy year it has been in the Geospatial Ecology of Marine Megafauna Lab! In 2016, our members have traveled to six continents for work (all seven if we can carry Rachael’s South African conference over from the end of 2015…), led field seasons in polar, temperate, and tropical waters, presented at international conferences, processed and analyzed data, and published results. Now winter finds us holed up in our offices in Newport, and various projects are ramping up and winding down. With all of the recent turmoil 2016 has brought, it is a nice to reflect on the good work that was accomplished over the last 12 months. In writing this, I am reminded of how grateful I am to work with this talented group of people!

The year started with a flurry of field activity from our southern hemisphere projects! Erin spent her second season on the Antarctic peninsula, where she contributed to the Palmer Station Long Term Ecological Research Project.

Erin collecting a crabeater seal scat sample.
Erin in action collecting a crabeater seal scat sample along the West Antarctic Peninsula.

 

Aerial image of the research vessel and a pair of blue whales during the 2016 New Zealand survey.
Aerial image of the research vessel and a pair of blue whales during the 2016 New Zealand survey.

The New Zealand blue whale project launched a comprehensive field effort in January and February, and it was a fruitful season to say the least. The team deployed hydrophones, collected tissue biopsy and fecal samples, and observed whales feeding, racing and nursing. The data collected by the blue whale team is currently being analyzed to aid in conservation efforts of these endangered animals living in the constant presence of the oil and gas industry.

Midway atoll is home to one of the largest albatross colony in the world, and Rachael visited during the winter breeding season. In addition to deploying tracking devices to study flight heights and potential conflict with wind energy development, she became acutely aware of the hazards facing these birds, including egg predation by mice and the consumption of plastic debris.

Laysan albatross equipped with a GPS data logger.
Laysan albatross equipped with a GPS data logger.
Fledgling from last year with a stomach full of plastic.
Fledgling from last year with a stomach full of plastic.

Early summertime brought red-legged kittiwakes to the remote Pribilof Islands in Alaska to nest, and Rachael met them there to study their physiology and behavior.

Rachael with a noosepole on St. George Island, Alaska
Rachael with a noosepole on St. George Island, Alaska
Solene with Dr. Claire Garrigue during fieldwork at the Chesterfield Reefs, New Caledonia.
Solene with Dr. Claire Garrigue during fieldwork at the Chesterfield Reefs, New Caledonia.

As the weather warmed for us in the northern hemisphere, Solene spent the austral winter with the humpback whales on their breeding grounds in New Caledonia. Her team traveled to the Chesterfield Reefs, where they collected tissue biopsy samples and photo-IDs, and recorded the whale’s songs. But Solene studies far more than just these whales! She is thoroughly examining every piece of environmental, physical, and oceanographic data she can get her hands on in an effort to build a thorough model of humpback whale distribution and habitat use.

A humpback whale in New Caledonia's South Lagoon.
A humpback whale in New Caledonia’s South Lagoon.

Summertime came to Oregon, and the gray whales returned to these coastal waters. Leigh, Leila, and Todd launched into fieldwork on the gray whale stress physiology project. The poop-scooping, drone-flying team has gotten a fair bit of press recently, follow this link to listen to more!

The overhead drone captures a pair of gray whales surfacing between kelp beds off Cape Blanco, Oregon, with the research vessel nearby. Take under NOAA/NMFS permit #16111 given to John Calambokidis.
The overhead drone captures a pair of gray whales surfacing between kelp beds off Cape Blanco, Oregon, with the research vessel nearby. Take under NOAA/NMFS permit #16111 given to John Calambokidis.

And while Leigh, Leila, and Todd followed the grays from the water, Florence and her team watched them from shore in Port Orford, tracking their movement and behavior. In an effort to gain a better understanding of the foraging ecology of these whales, Florence and crew also sampled their mysid prey from a trusty research kayak.

13
Florence and the summer 2016 gray whale field team.
DSCF0758
Kelli Iddings sampling mysid near Port Orford.

With the influx of gray whales came an influx of new and visiting GEMM Lab members, as Florence’s team of interns joined for the summer season. I was lucky enough to join this group as the lab’s newest graduate student!

All summer 2016 GEMM Lab members.
All of the summer 2016 GEMM Lab members.

Our members have presented their work to audiences far and wide. This summer Leigh, Amanda, and Florence attended the International Marine Conservation Congress, and Amanda was awarded runner-up for the best student presentation award! Erin traveled to Malaysia for the Scientific Convention on Antarctic Research, and Rachael and Leigh presented at the International Albatross and Petrel Conference in Barcelona. With assistance from Florence and Amanda, Leigh led an offshore expedition on OSU’s research vessel R/V Oceanus to teach high school students and teachers about the marine environment.

Amanda with her award!
Amanda with her award!
Science Party musters in the dry lab for safety debrief aboard R/V Oceanus.
Science Party musters in the dry lab for safety debrief aboard R/V Oceanus.

Courtney fledged from the GEMM Lab nest before 2016 began, but the work she did while here was published in Marine Mammal Science this year. Congrats Courtney! And speaking of publications, additional congratulations to Solene for her publication in Marine Ecology Progress Series, Rachael for her four publications this year in PLOS ONE, Marine Ecology Progress Series, Marine Ornithology, and the Journal of Experimental Biology, and Leigh for her five publications this year in Polar Biology, Diversity and Distributions, Marine Ecology Progress Series, and Marine Mammal Science!

Wintertime in Newport has us tucked away indoors with our computers, cranking through analyses and writing, and dreaming about boats, islands, seabirds, and whales… Solene visited from the South Pacific this fall, and graced us with her presence and her coding expertise. It is a wonderful thing to have labmates to share ideas, frustrations, and accomplishments with.

No heat in the lab can't stop us from solving a coding problem together on a wintery evening!
Solving a coding problem together on a wintery evening.

As the year comes to a close, we have two newly-minted Masters of Science! Congratulations to Amanda and Erin on successfully defending their theses, and stay tuned for their upcoming publications!

Amanda's post-defense celebration!
Amanda’s post-defense celebration!
Erin's post-defense celebration!
Erin’s post-defense celebration!

We are looking forward to what 2017 brings for this team of marine megafauna enthusiasts. Happy holidays from the GEMM Lab!

Happy GEMM Lab members.
Happy GEMM Lab members, enjoying one another’s company and playing Evolution.

Assembling a Toolbox

By Dawn Barlow, MSc student, Oregon State University

toolbox
Source: https://www.ohrd.wisc.edu/home/portals/0/toolbox.jpg

The season has shifted since the post I wrote this summer about diving into the world of New Zealand blue whales and the beginnings of my masters research. My fieldwork will take place during the upcoming austral summer, which will require me to miss the winter term here on campus. This quarter, I have put my research on the back burner for the time being in favor of a full load of coursework. But my project is still there, simmering subtly and persistently, and giving relevance to the coursework that I’m focusing my energy on this fall term.

As an undergraduate student, I acquired a broad scientific background and had the opportunity to dabble in the areas of biology that piqued my interest. I arrived here with a basic understanding of chemistry, physics, cell biology, anatomy, marine ecology and conservation biology. I gained experience working in the field with intertidal sea stars, snails, mussels, crabs and barnacles, with bottlenose dolphins and with humpback whales. But now my focus has narrowed as I’ve honed in on the specific questions that I will pursue over the next two years. My passion lies in marine ecology and conservation. Now, as a graduate student studying the ecology of a little-known population in a highly industrial area, this passion can come to fruition. For my masters, I hope to do the following:

A) Use photo-identification analysis to obtain a population abundance estimate for blue whales in New Zealand

B) Investigate blue whale residency and distribution patterns in New Zealand waters

C) Develop a comprehensive blue whale habitat use model for the South Taranaki Bight region of New Zealand, which incorporates physical and biological data

Down the road I hope to have implemented a capture-recapture abundance estimate model that best fits the dynamics of this population of blue whales, to have mapped where sightings have occurred and where the highest densities of blue whales are found in both space and time, and to have paired blue whale presence and absence with prey distribution, remote-sensed environmental data, and in situ oceanographic data. But how does one accomplish these things? I need a toolbox to draw from. And so this fall, I am assembling my toolbox, learning programs and analytical skills. I am taking methods courses—statistics, data management in R, analysis in GIS, methods in physiology and behavior of marine megafauna—that are no longer explorations into the world of natural science, but rather tools for exploring, identifying, and interpreting specific phenomena in ecology. While each comes with its own hiccups and headaches (see Florence’s post about this…), they are powerful tools.

Aside from coursework, the research I’m conducting has gained weight and relevance beyond being an investigation in ecology. My study area lies in the South Taranaki Bight of New Zealand, which is a contentious proposed seabed mining site for iron sands. As an undergraduate student I read case studies and wrote papers on the environmental impacts of industry, and I decided to go graduate school because I want to do research that has direct conservation applications. Last week I compiled all the data I’ve processed on blue whale sightings, seasonal residency, and photo identification for the South Taranaki Bight, which will be included as evidence submitted in environmental court in New Zealand by my advisor, Dr. Leigh Torres. “Applied conservation science” has been an abstract idea that has excited and motivated me for a long time, and now I am partaking in this process, experiencing applied conservation science firsthand.

And so my toolbox is growing, and the scope of my work is simultaneously narrowing in focus and expanding in relevance. The more tools I acquire, the more excited I am to apply them to my research. As I build my toolbox this fall, this process is something I look forward to enhancing while I’m in the field, when I dig deeper into data analysis, and as I grow as a conservation scientist.

A blue whale dives in the South Taranaki Bight, New Zealand. Photo by Leigh Torres.
A blue whale dives in the South Taranaki Bight, New Zealand. Photo by Leigh Torres.

Grad School Headaches

By Florence Sullivan, MSc student GEMM lab

Over the past few months I have been slowly (and I do mean SLOWLY – I don’t believe I’ve struggled this much with learning a new skill in a long, long time) learning how to work in “R”.  For those unfamiliar with why a simple letter might cause me so much trouble, R is a programming language and free software environment suitable for statistical computing and graphing.

My goal lately has been to interpolate my whale tracklines (i.e. smooth out the gaps where we missed a whale’s surfacing by inserting artificial locations).  In order to do this I needed to know (1) How long does a gap between fixes need to be to identify a missed surfacing? (2) How many artificial points should be used to fill a given gap?

The best way to answer these queries was to look at a distribution of all of the time steps between fixes.  I started by importing my dataset – the latitude and longitude, date, time, and unique whale identifier for each point (over 5000 of them) we recorded last summer. I converted the locations into x & y coordinates, adjusted the date and time stamp into the proper format, and used the package adehabitatLT  to calculate the difference in times between each fix.  A package known as ggplot2 was useful for creating exploratory histograms – but my data was incredibly skewed (Fig 1)! It appeared that the majority of our fixes happened less than a minute apart from each other. When you recall that gray whales typically take 3-4 short breathes at the surface between dives, this starts to make a lot of sense, but we had anticipated a bimodal distribution with two peaks: one for the quick surfacings, and one for the surfacings between 4-5 minutes dives. Where was this second peak?

Histogram of the difference in time (in seconds) between whale fixes.
Fig. 1.  Histogram of the difference in time (in seconds on x-axis) between whale fixes.

Sometimes, calculating the logarithm of one of your axes can help tease out more patterns in your data  – particularly in a heavily skewed distribution like Fig. 1. When I logged the time interval data, our expected bimodal distribution pattern became evident (Fig. 2). And, when I back-calculate from the center of the two peaks we see that the first peak occurs at less than 20 seconds (e^2.5 = 18 secs) representing the short, shallow blow intervals, or interventilation dives, and that the second peak of dives spans ~2.5 minutes to  ~5 minutes (e^4.9 = 134 secs, e^5.7 = 298 secs). Reassuringly, these dive intervals are in agreement with the findings of Stelle et al. (2008) who described the mean interval between blows as 15.4 ± 4.73 seconds, and overall dives ranging from 8 seconds to 11 minutes.

Fig. 2. Histogram of the log of time difference between whale fixes.
Fig. 2. Histogram of the log of time difference between whale fixes.

So, now that we know what the typical dive patterns in this dataset are, the trick was to write a code that would look through each trackline, and identify gaps of greater than 5 minutes.  Then, the code calculates how many artificial points to create to fill the gap, and where to put them.

Fig. 3. A check in my code to make sure the artificial points are being plotted correctly. The blue points are the originals, and the red ones are new.
Fig. 3. A check in my code to make sure the artificial points are being plotted correctly. The blue points are the originals, and the red ones are new.

One of the most frustrating parts of this adventure for me has been understanding the syntax of the R language.  I know what calculations or comparisons I want to make with my dataset, but translating my thoughts into syntax for the computer to understand has not been easy.  With error messages such as:

Error in match.names(clabs, names(xi)) :

  names do not match previous names

Solution:  I had to go line by line and verify that every single variable name matched, but turned out it was a capital letter in the wrong place throwing the error!

Error in as.POSIXct.default(time1) :

  do not know how to convert ‘time1’ to class “POSIXct”

Solution: a weird case where the data was in the correct time format, but not being recognized, so I had to re-import the dataset as a different file format.

Error in data.frame(Whale.ID = Whale.ID, Site = Site, Latitude = Latitude,  :   arguments imply differing number of rows: 0, 2, 1

Solution: HELP! Yet to be solved….

Is it any wonder that when a friend asks how I am doing, my answer is “R is kicking my butt!”?

Science is a collaborative effort, where we build on the work of researchers who came before us. Rachael, a wonderful post-doc in the GEMM Lab, had already tackled this time-based interpolation problem earlier in the year working with albatross tracks. She graciously allowed me to build on her previous R code and tweak it for my own purposes. Two weeks ago, I was proud because I thought I had the code working – all that I needed to do was adjust the time interval we were looking for, and I could be off to the rest of my analysis!  However, this weekend, the code has decided it doesn’t work with any interval except 6 minutes, and I am lost.

Many of the difficulties encountered when coding can be fixed by judicious use of google, stackoverflow, and the CRAN repository.

But sometimes, when you’ve been staring at the problem for hours, what you really need is a little praise for trying your best. So, if you are an R user, go download this package: praise, load the library, and type praise() into your console. You won’t regret it (See Fig. 4).

Screenshot (74)
Fig. 4. A little compliment goes a long way to solving a headache.

Thank you to Rachael who created the code in the first place, thanks to Solene who helped me trouble shoot, thanks to Amanda for moral support. Go GEMM Lab!

Why do pirates have a hard time learning the alphabet?  It’s not because they love aaaR so much, it’s because they get stuck at “c”!

Stelle, L. L., W. M. Megill, and M. R. Kinzel. 2008. Activity budget and diving behavior of gray whales (Eschrichtius robustus) in feeding grounds off coastal British Columbia. Marine mammal science 24:462-478.

Smile! You’re on Camera!

By Florence Sullivan, MSc. Student, GEMM Lab

Happy Spring everyone!  You may be wondering where the gray whale updates have been all winter – and while I haven’t migrated south to Baja California with them, I have spent many hours in the GEMM Lab processing data, and categorizing photos.

You may recall that one of my base questions for this project is:

Do individual whales have different foraging strategies?

In order to answer this question, we must be able to tell individual gray whales apart. Scientists have many methods for recognizing individuals of different species using tags and bands, taking biopsy samples for DNA analysis, and more. But the method we’re using for this project is perhaps the simplest: Photo-Identification, which relies on the unique markings on individual animals, like fingerprints.  All you need is a camera and rather a lot of patience.

Bottlenose dolphins were some of the first cetaceans to be documented by photo-identification.  Individuals are identified by knicks and notches in their fins. Humpback whales are comparatively easy to identify – the bold black and white patterns on the underside of their frequently displayed flukes are compared.  Orcas, one of the most beloved species of cetaceans, are recognized thanks to their saddle patches – again, unique to each individual. Did you know that the coloration and shape of those patches is actually indicative of the different ecotypes of Orca around the world? Check out this beautiful poster by Uko Gorter to see!

Gray whale photo identification is a bit more subtle since these whales don’t have dorsal fins and do not show the undersides of their fluke regularly.  Because gray whales can have very different patterns on either side of their body, it is also important to get photos of both their right and left sides, as well as the fluke, to be sure of recognizing an individual if it comes around again.   When taking photos of a gray whale, it’s a good idea to include the dorsal hump, where the knuckles start as it dives, as an easy indicator of which side of the body you are looking at when you’re trying to match photos.  Some clues that I often use when identifying an individual include the placement of barnacles, and patterns of pigmentation and scars.  You can see that patience and a talent for pattern recognition come in handy for this sort of work.

While we were in the field, it was important for my team to quickly find reference features to make sure we were always tracking the same whale. If you stopped by to visit our field station, you may have heard use saying things like “68 has white on both fluke-tips”, “70 has a propeller scar on the left side”,  “the barnacles on 54’s head looks like a polyp”, or “27 has a smiley face in front of the first knuckle left side.” Sometimes, if a trait was particularly obvious, and the whale visited our field station more than once, we would give them a name to help us remember them.  These notes were often (but to my frustration, not always!) recorded in our field notebook, and have come in handy this winter as I have systematically gone through the 8000+ photos we took last summer, identifying each individual, and noting whenever one was a repeat visitor. With these individuals labeled, I can now assess their level of behavioral and distribution consistency within and between study sites, and over the course of the summer.

Why don’t you try your luck?  How many individuals are in this photoset? How many repeats?  If I tell you that my team named some of these whales Mitosis, Smiley, Ninja and Keyboard can you figure out which ones they are?

#1
#2
#2
#3
#4
#4
#5
#5
#6
#6
#7
#7
#8
#8
#9
#9
#10
#10

 

Keep scrolling for the answer key ( I don’t want to spoil it too easily!)

 

 

 

 

 

Answers:

There are 7 whales in this photoset. Smiley and Keyboard both have repeat shots for you to find, and Smiley even shows off both left and right sides.

  1. Whale 18 – Mitosis
  2. Whale 70 -Keyboard
  3. Whale 23 -Smiley
  4. Whale 68 – Keyboard
  5. Whale 27 -Smiley
  6. Whale 67
  7. Whale 36 -Ninja
  8. Whale 60 – “60”
  9. Whale 38 – has no nickname even if we’ve seen it 8 times! Have any suggestions? leave it in the comments!
  10. Whale 55 – Smiley