Classifying cetacean behavior

Clara Bird, Masters Student, OSU Department of Fisheries and Wildlife, Geospatial Ecology of Marine Megafauna Lab

The GEMM lab recently completed its fourth field season studying gray whales along the Oregon coast. The 2019 field season was an especially exciting one, we collected rare footage of several interesting gray whale behaviors including GoPro footage of a gray whale feeding on the seafloor, drone footage of a gray whale breaching, and drone footage of surface feeding (check out our recently released highlight video here). For my master’s thesis, I’ll use the drone footage to analyze gray whale behavior and how it varies across space, time, and individual. But before I ask how behavior is related to other variables, I need to understand how to best classify the behaviors.

How do we collect data on behavior?

One of the most important tools in behavioral ecology is an ‘ethogram’. An ethogram is a list of defined behaviors that the researcher expects to see based on prior knowledge. It is important because it provides a standardized list of behaviors so the data can be properly analyzed. For example, without an ethogram, someone observing human behavior could say that their subject was walking on one occasion, but then say strolling on a different occasion when they actually meant walking. It is important to pre-determine how behaviors will be recorded so that data classification is consistent throughout the study. Table 1 provides a sample from the ethogram I use to analyze gray whale behavior. The specificity of the behaviors depends on how the data is collected.

Table 1. Sample from gray whale ethogram. Based on ethogram from Torres et al. (2018).

In marine mammal ecology, it is challenging to define specific behaviors because from the traditional viewpoint of a boat, we can only see what the individuals are doing at the surface. The most common method of collecting behavioral data is called a ‘focal follow’. In focal follows an individual, or group, is followed for a set period of time and its behavioral state is recorded at set intervals.  For example, a researcher might decide to follow an animal for an hour and record its behavioral state at each minute (Mann 1999). In some studies, they also recorded the location of the whale at each time point. When we use drones our methods are a little different; we collect behavioral data in the form of continuous 15-minute videos of the whale. While we collect data for a shorter amount of time than a typical focal follow, we can analyze the whole video and record what the whale was doing at each second with the added benefit of being able to review the video to ensure accuracy. Additionally, from the drone’s perspective, we can see what the whales are doing below the surface, which can dramatically improve our ability to identify and describe behaviors (Torres et al. 2018).

Categorizing Behaviors

In our ethogram, the behaviors are already categorized into primary states. Primary states are the broadest behavioral states, and in my study, they are foraging, traveling, socializing, and resting. We categorize the specific behaviors we observe in the drone videos into these categories because they are associated with the function of a behavior. While our categorization is based on prior knowledge and critical evaluation, this process can still be somewhat subjective.  Quantitative methods provide an objective interpretation of the behaviors that can confirm our broad categorization and provide insight into relationships between categories.  These methods include path characterization, cluster analysis, and sequence analysis.

Path characterization classifies behaviors using characteristics of their track line, this method is similar to the RST method that fellow GEMM lab graduate student Lisa Hildebrand described in a recent blog. Mayo and Marx (1990) analyzed the paths of surface foraging North Atlantic Right Whales and were able to classify the paths into primary states; they found that the path of a traveling whale was more linear and then paths of foraging or socializing whales that were more convoluted (Fig 1). I plan to analyze the drone GPS track line as a proxy for the whale’s track line to help distinguish between traveling and foraging in the cases where the 15-minute snapshot does not provide enough context.

Figure 1. Figure from Mayo and Marx (1990) showing different track lines symbolized by behavior category.

Cluster analysis looks for natural groupings in behavior. For example, Hastie et al. (2004) used cluster analysis to find that there were four natural groupings of bottlenose dolphin surface behaviors (Fig. 2). I am considering using this method to see if there are natural groupings of behaviors within the foraging primary state that might relate to different prey types or habitat. This process is analogous to breaking human foraging down into sub-categories like fishing or farming by looking for different foraging behaviors that typically occur together.

Figure 2. Figure from Hastie et al. (2004) showing the results of a hierarchical cluster analysis.

Lastly, sequence analysis also looks for groupings of behaviors but, unlike cluster analysis, it also uses the order in which behaviors occur. Slooten (1994) used this method to classify Hector’s dolphin surface behaviors and found that there were five classes of behaviors and certain behaviors connected the different categories (Fig. 3). This method is interesting because if there are certain behaviors that are consistently in the same order then that indicates that the order of events is important. What function does a specific sequence of behaviors provide that the behaviors out of that order do not?

Figure 3. Figure from Slooten (1994) showing the results of sequence analysis.

Think about harvesting fruits and vegetables from a garden: the order of how things are done matters and you might use different methods to harvest different kinds of produce. Without knowing what food was being harvested, these methods could detect that there were different harvesting methods for different fruits or veggies. By then studying when and where the different methods were used and by whom, we could gain insight into the different functions and patterns associated with the different behaviors. We might be able to detect that some methods were always used in certain habitat types or that different methods were consistently used at different times of the year.

Behavior classification methods such as these described provide a more refined and detailed analysis of categories that can then be used to identify patterns of gray whale behaviors. While our ultimate goal is to understand how gray whales will be affected by a changing environment, a comprehensive understanding of their current behavior serves as a baseline for that future study.

References

Burnett, J. D., Lemos, L., Barlow, D., Wing, M. G., Chandler, T., & Torres, L. G. (2019). Estimating morphometric attributes of baleen whales with photogrammetry from small UASs: A case study with blue and gray whales. Marine Mammal Science, 35(1), 108–139. https://doi.org/10.1111/mms.12527

Darling, J. D., Keogh, K. E., & Steeves, T. E. (1998). Gray whale (Eschrichtius robustus) habitat utilization and prey species off Vancouver Island, B.C. Marine Mammal Science, 14(4), 692–720. https://doi.org/10.1111/j.1748-7692.1998.tb00757.x

Hastie, G. D., Wilson, B., Wilson, L. J., Parsons, K. M., & Thompson, P. M. (2004). Functional mechanisms underlying cetacean distribution patterns: Hotspots for bottlenose dolphins are linked to foraging. Marine Biology, 144(2), 397–403. https://doi.org/10.1007/s00227-003-1195-4

Mann, J. (1999). Behavioral sampling methods for cetaceans: A review and critique. Marine Mammal Science, 15(1), 102–122. https://doi.org/10.1111/j.1748-7692.1999.tb00784.x

Slooten, E. (1994). Behavior of Hector’s Dolphin: Classifying Behavior by Sequence Analysis. Journal of Mammalogy, 75(4), 956–964. https://doi.org/10.2307/1382477

Torres, L. G., Nieukirk, S. L., Lemos, L., & Chandler, T. E. (2018). Drone up! Quantifying whale behavior from a new perspective improves observational capacity. Frontiers in Marine Science, 5(SEP). https://doi.org/10.3389/fmars.2018.00319

Mayo, C. A., & Marx, M. K. (1990). Surface foraging behaviour of the North Atlantic right whale, Eubalaena glacialis, and associated zooplankton characteristics. Canadian Journal of Zoology, 68(10), 2214–2220. https://doi.org/10.1139/z90-308

What is that whale doing? Only residence in space and time will tell…

By Lisa Hildebrand, MSc student, OSU Department of Fisheries and Wildlife, Geospatial Ecology of Marine Megafauna Lab

For my research in Port Orford, my field team and I track individual gray whales continuously from a shore-based location: once we spot a whale we will track it for the entire time that it remains in our study site. The time spent tracking a whale can vary widely. In the 2018 field season, our shortest trackline was three minutes, and our longest track was over three hours in duration.

This variability in foraging time is partly what sparked my curiosity to investigate potential foraging differences between individuals of the Pacific Coast Feeding Group (PCFG) gray whales. I want to know why some individuals, like “Humpy” who was our longest tracked individual in 2018, stayed in an area for so long, while others, like “Smokey”, only stayed for three minutes (Figure 1). It is hard to pinpoint just one variable that drives these decisions (e.g., prey, habitat) made by individuals about where they forage and how long because the marine environment is so dynamic. Foraging decisions are likely dictated by several factors acting in concert with one another. As a result, I have many research questions, including (but certainly not limited to):

  1. Does prey density drive length of individual foraging bouts?
  2. Do individual whales have preferences for a particular prey species?
  3. Are prey patches containing gravid zooplankton targeted more by whales?
  4. Do whales prefer to feed closer to kelp patches?
  5. How does water depth factor into all of the above decisions and/or preferences? 

I hope to get to the bottom of these questions through the data analyses I will be undertaking for my second chapter of my Master’s thesis. However, before I can answer those questions, I need to do a little bit of tidying up of my whale tracklines. Now that the 2019 field season is over and I have all of the years of data that I will be analyzing for my thesis (2015-2019), I have spent the past 1-2 weeks diving into the trackline clean-up and analysis preparation.

The first step in this process is to run a speed filter over each trackline. The aim of the speed filter is to remove any erroneous points or outliers that must be wrong based on the known travel speeds of gray whales. Barb Lagerquist, a Marine Mammal Institute (MMI) colleague who has tracked gray whales for several field seasons, found that the fastest individual she ever encountered traveled at a speed of 17.3 km/h (personal communication). Therefore, based on this information,  my tracklines are run through a speed filter set to remove any points that suggest that the whale traveled at 17.3 km/h or faster (Figure 2). 

Fig 3. Trackline of “Humpy” after interpolation. The red points are interpolated.

Next, the speed-filtered tracklines are interpolated (Figure 3). Interpolation fills spatial and/or temporal gaps in a data set by evenly spacing points (by distance or time interval) between adjacent points. These gaps sometimes occur in my tracklines when the tracking teams misses one or several surfacings of a whale or because the whale is obscured by a large rock. 

After speed filtration and interpolation has occurred, the tracklines are ready to be analyzed using Residence in Space and Time (RST; Torres et al. 2017) to assign behavior state to each location. The questions I am hoping to answer for my thesis are based upon knowing the behavioral state of a whale at a given location and time. In order for me to draw conclusions over whether or not a whale prefers to forage by a reef with kelp rather than a reef without kelp, or whether it prefers Holmesimysis sculpta over Neomysis rayii, I need to know when a whale is actually foraging and when it is not. When we track whales from our cliff site, we assign a behavior to each marked location of an individual. It may sound simple to pick the behavior a whale is currently exhibiting, however it is much harder than it seems. Sometimes the behavioral state of a whale only becomes apparent after tracking it for several minutes. Yet, it’s difficult to change behaviors retroactively while tracking a whale and the qualitative assignment of behavior states is not an objective method. Here is where RST comes in.

Those of you who have been following the blog for a few years may recall a post written in early 2017 by Rachael Orben, a former post-doc in the GEMM Lab who currently leads the Seabird Oceanography Lab. The post discussed the paper “Classification of Animal Movement Behavior through Residence in Space Time” written by Leigh and Rachael with two other collaborators, which had just been published a few days prior. If you want to know the nitty gritty of what RST is and how it works, I suggest reading Rachael’s blog, the GEMM lab’s brief description of the project and/or the actual paper since it is an open-access publication. However, in a nut shell, RST allows a user to identify three primary behavioral states in a tracking dataset based on the time and distance the individual spent within a given radius. The three behavioral categories are as follows:

Fig 4. Visualization of the three RST behavioral categories. Taken from Torres et al. (2017).
  • Transit – characterized by short time and distance spent within an area (radius of given size), meaning the individual is traveling.
  • Time-intensive – characterized by a long time spent within an area, meaning the individual is spending relatively more time but not moving much distance (such as resting in one spot). 
  • Time & distance-intensive – characterized by relatively high time and distances spent within an area, meaning the individual is staying within and moving around a lot in an area, such as searching or foraging. 

What behavior these three categories represent depends on the resolution of the data analyzed. Is one point every day for two years? Then the data are unlikely to represent resting. Or is the data 1 point every second for 1 hour? In which case travel segments may cover short distances. On average, my gray whale tracklines are composed of a point every 4-5 minutes for 1-2 hours.  Bases on this scale of tracking data, I will interpret the categories as follows: Transit is still travel, time & distance-intensive points represent locations where the whale was searching because it was moving around one area for a while, and time-intensive points represent foraging behavior because the whale has ‘found what it is looking for’ and is spending lots of time there but not moving around much anymore. The great thing about RST is that it removes the bias that is introduced by my field team when assigning behavioral states to individual whales (Figure 5). RST looks at the tracklines in a very objective way and determines the behavioral categories quantitatively, which helps to remove the human subjectivity.

While it took quite a bit of troubleshooting in R and overcoming error messages to make the codes run on my data, I am proud to have results that are interesting and meaningful with which I can now start to answer some of my many research questions. My next steps are to create interpolated prey density and distance to kelp layers in ArcGIS. I will then be able to overlay my cleaned up tracklines to start teasing out potential patterns and relationships between individual whale foraging movements and their environment. 

Literature cited

Torres, L. G., R. A. Orben, I. Tolkova, and D. R. Thompson. 2017. Classification of animal movement behavior through residence in space and time. PLoS ONE: doi. org/10.1371/journal.pone.0168513.

A Series of Short Stories from A Field Season in Port Orford

By Mia Arvizu, Marine Studies Initiative (MSI) & GEMM Lab summer intern, OSU junior

Part 1: The Green Life Jacket

The swells are churning and for once my stomach is calm. I take advantage of it while I can, and head out on the kayak. Another beautiful day, another good data set. After about three hours in the kayak and a long paddle fighting winds and swells, we arrive at TC1. That’s short for Tichenor Cove Station 1. I’m fairly tired by now but my teammate and I are determined to finish all stations today. GPS says we arrived, and I paddle against any slight movement to keep us on station. It’s getting more difficult though, so I check in with Anthony, one of the high school interns this summer. “Anthony, have you sent the GoPro camera down yet?”  I take a quick look back peering over my green life jacket. Red flash, and I know it’s on. Anthony sends it down, and I watch as it plunges into depths I couldn’t see on my own. I’m confident it’s doing its job. 

Part 2: The GoPro Dive

The green life jacket is familiar, but there’s a different soul, a different face every year. It’s the same month though. August – the month of whales. 

Red flash, I’m on,  and it’s my time to shine. The scientists debrief me on my latest mission, and I’m alive. “Secchi depth .75 meters.” Hmm, low visibility. This may be a tough one. “Station TC1” One of my favorites but challenging no doubt. “Time is 10:36. 5, 6, 7, 8…” I’m ready. A flush of swirling water surrounds me as I plunge into the depths of a different realm. I’m cocooned in the beauty of an ocean so blue, so majestic, so entrancing. Oh, the mission! Right, I need to stay focused. They lurk all around but with sand clouding the water, I can barely see. I just need one good visual of the purple spikes and the swaying green leaves, and the mission will be complete. I glance just to the left and oh my!

Sea urchins actively foraging on kelp at station TC1 in Tichenor Cove. Source: GEMM Lab.

A giant purple spike comes too close. I barely caught a glimpse of it. I need a better shot, but I only have so much control especially with these undercurrents. I’m ready now though. I peer through the sediment and nothing, but one quick swivel to the right shows me what I feared and what the green life jackets predicted: The purple spikes have grown too many and reduced the swaying greens down to half chewed, severed, scared dead masses. I thought their hypothesis was right, but I didn’t expect this degree of damage. It’s so frightening I almost look away.

But I don’t. I have a mission. So, I look straight ahead documenting the scene. I haven’t seen it this bad in the past years. I wonder what the green life jackets will do about this. I feel a tug, and I’m reeled in. I guess I’ll find out.

GoPro video taken from tandem research kayak during 2019 gray whale field season in Tichenor Cove, Port Orford. Source: GEMM Lab.

Part 3: The Science, how I see it

After collecting data in the kayak, I go back to the field station ready to do data processing. I grab the GoPro and take a look at the video from TC1. I’m both amazed and terrified for the surrounding habitat from what I see. Sea urchins seem to have been actively foraging on kelp stalks. 

Last summer, around this time, a previous intern pointed out that he was witnessing damaged kelp and a notable number of urchins in the GoPro videos. Thus, the GEMM Lab is looking into the relationship between kelp health and sea urchin abundance in Port Orford, which can have significant trophic cascades for the rest of the ecosystem, including whales and their zooplankton prey. The hypothesis is that if sea urchin populations increase in number they may actively forage on kelp, reducing the health of that habitat. Many creatures depend on this habitat including zooplankton which whales feed on. I have looked at videos from past years and the temporal difference in the abundance of urchins is stark. A detailed methodology for the project and our pending results will be featured in a later post, but for now this story is unfolding before our eyes and the GoPro’s lens as well. 

Part 4: The Transformation from STEM to STEAM

I hope you enjoyed these short stories. As the writer, it was nice to express the ecological phenomena I’ve learned about in the last few weeks between sea urchins and kelp in this creative and artistic outlet. Especially since I feel science can be rigid at times. It can be easy to lose myself in numbers and large datasets. However, by tying together the arts and STEM (Science, Technology, Engineering, Mathematics), there is more space for well-rounded inquiry and expressive results. STEAM, which is STEM with the Arts included, is not a new movement. Examples of STEAM are preserved in the past and is ongoing in present examples. A great example of how the sciences and arts are merged together is in the songs of Aboriginal Australians. These songs can take hours to recite fully and are full of environmental knowledge such as species types, behavior of animals, and edible plants. The combination of art and STEM is also displayed in the modern age and is shown in Leah Heiss’s work to create jewelry that helps measure cardiac data and also helps diabetics administer their insulin.  

This is one of Leah’s feature blends of biotechnology and jewelry. It measures cardiac data and is primarily beneficial for patients at risk of heart attacks. Source: Leah Heiss.

There are many ways in which the two subjects can merge together, making each other stronger and better. As a well-rounded student pursuing Environmental Science and interested dance and writing, I am comforted to know that STEAM can allow me to blend my interests. 

Intricacies of Zooplankton Species Identification

By Donovan Burns, Astoria High School Junior, GEMM Lab summer intern

The term zooplankton is used to describe a large number of creatures; the exact definition is any animal that cannot move against a sustained current in the marine environment. There are two main types of plankton: holoplankton and meroplankton. Meroplankton are organisms that are plankton for only part of their life cycle. So this makes most sea creatures plankton, for instance, salmon, sunfish, tuna, and most other fish are meroplankton because they start out their lives as plankton. Holoplankton are plankton that remain plankton for their whole lives, these include mysid shrimp, most marine worms, and most jellyfish.

I have spent a good deal of time this summer looking through a microscope at the zooplankton we have captured during sampling from our research kayak, trying to distinguish and identify different species. Telsons, the tail of the tail, are what we use to identify different types of mysid shrimp, which are a primary gray whale prey item along the Oregon coast and the most predominant type of zooplankton we capture in our sampling. For instance Neomysis is a genus of mysid shrimp and is one of the two most abundant zooplankton species we get. Their telsons end with two spikes that are somewhat longer than the spikes on the side of the telson.  This look is distinct from Holmesimysis sculpta, the other of the two most abundant zooplankton species we get, which have four-pronged telsons with varying sizes of spikes along the sides of the telson. Alienacanthomysis macropsis is identified by both their long eye stalks and their rather bland rounded telson.

Caprellidae. Source: R. Norman.

However, creatures that are not mysid shrimp cannot be identified this way.  Like gammarids, they look like fleas.  We have only found one kind of gammarid here in Port Orford this year, Atylus tridens. There are other types but that is the only type we have found this year. After that, we have Caprellidae, also known as skeleton shrimp. They are long and stalky, and have claws in every spot where they could have claws.

Copepod. Source: L. Hildebrand.

Then there are copepods. Copepods are tiny and have long antennae that string down to the sides of their bodies. We also have been seeing lots of crab larvae. I have also seen a couple of polychaete worms, which are marine worms with many legs and segments. The only reason I was able to identify them as polychaetes is due to my marine biology class at Astoria High School where we identified these worms using microscopes before.

We also have had some trouble identifying somethings. For instance, we have found a few individuals of a type of mysid shrimp with a rake-like tail that we are still trying to identify.  Also, we have captured some jellyfish that we are not trying to identify. When the kayak team gets back in from gathering samples, we freeze the samples to kill and preserve the critters in them. This process turns the jellyfish to mush, so they are hard to identify.

To identify these zooplankton and other critters, we put them into a Petri dish and under a dissection scope, at which point we use forceps to move and pivot creatures.  If a jellyfish had just eaten another plankton, we have to cut it open to get the plankton out so we can identify it.  

Sometimes we have large samples of thousands of the same creature, in this case, we would normally sub-sample it. Sub-sampling is when we take a portion of a sample and identify and count individual zooplankton in that sub-sample. Then we multiply those counts by the portion of the whole sample to get the approximate total number that are in that sample.  For instance, say we had a rather large sample, we would take a tenth of that sample and count what is in it. Say we count 500 individuals in that tenth. We would then multiply 500 by ten to get the total number in that whole sample.

Then there are some plankton that we do not catch, like large jellyfish.  The kayak team has gotten photos of a giant jellyfish that was nearly a meter long.

Jellyfish seen by the kayak team. Source: L. Hildebrand.

All in all, Port Orford has an amazing and diverse population of marine life. From gray whales to thresher sharks to mysid shrimp to copepods to jellyfish, this little ecosystem has pretty much some of everything. 

Fieldwork experience as a GEMM Lab intern

By Anthony Howe, Astoria High School graduate 2019, GEMM Lab summer intern

Murphy’s Law says that “things will go wrong in any given situation if you give them a chance”. This statement certainly applies to research where you never really know what is going to happen when performing fieldwork. You can only try to be prepared for all of the situations. When I arrived at the Oregon State University (OSU) Field Station in Port Orford, I had no idea that it would harbor some of the best educational experiences I have ever had. I had no idea what a theodolite was, nor did I know how to kayak in the ocean, but I learned fast. When we first started being trained on using a theodolite and the program that processes the data, Pythagoras, we had some problems. The theodolite would not stay level, but just as we were learning how to work the theodolite, we also learned how to work as a team. When we finally managed to level the theodolite, which did take a few days, I began to realize the hard work of doing fieldwork. You can be prepared but there will always be something that goes wrong, and that’s okay. I have learned that mistakes happen and cannot be dwelled on. Only learned from. No one is perfect.

Fig 1. Me holding two zooplankton samples after collecting them on the kayak. Source: L. Hildebrand.

Just two days ago I was on our tandem research kayak with Mia Arvizu, the OSU Marine Studies Initiative (MSI) undergraduate intern. When we go out on the kayak, we paddle around our study area and go to GPS-marked “stations” to collect prey samples of zooplankton, test for water visibility using a Secchi disk, and send a GoPro underwater to have a better understanding of what is going on under the surface. While sampling at Station 15 in Mill Rocks I lowered the GoPro into the water using a downrigger. When the GoPro reached the bottom, I began to pull it up, only to realize it had gotten snagged in a crevice. I gave the line to which the GoPro is attached some slack and began to give Mia instructions to move to different spots to try and retrieve the GoPro out of this tight crevice. Unfortunately, I did not realize all of the lines had wrapped themselves underneath the downrigger and as soon as a swell came up, the line broke. My eyes widened as I realized what had just happened. Thankfully, I managed to grasp the last of the remaining line left connected to the GoPro and pulled it back into the kayak using my hand wrapped in a towel since the line is thin and can cut into your hands easily. Only then did I realize that neither Mia nor I had packed a knife in the event we needed to cut a line. We sat and pondered ideas of how to cut the last of the line so that I could reattach the GoPro to the downrigger. Mia came up with the idea to use a barnacle or a mussel, and it worked perfectly. We were proud of ourselves for being resourceful and using nature to our advantage. But as soon as I finished using the mussel to cut the line, Lisa’s voice came over the VHF radio that we always carry with us in the kayak that there were scissors in the First Aid Kit that is stowed in the dry hatch of the kayak. Mia and I looked at each other and could only laugh. The kayak team can be rough at times but it’s made up by the fact that we get beautiful prey samples and stunning GoPro videos of what is below the water.

Fig 2. Mia and myself paddling the kayak across “The Passage”, the approximately 1 km stretch between Mill Rocks and Tichenor Cove, our two study sites. Red Fish Rocks, which is Oregon’s first Marine Reserve, can be seen in the background. Source: L. Hildebrand.

After all of the kayak sampling is done we organize and store our gear, and then go to the lab. In the lab, one person will clean all tools and devices touched by saltwater while the other sieves all of our zooplankton samples. Each sample is individually sieved and then placed in a sample jar with its station name on it and placed into the freezer. We put them in the freezer to increase the longevity of the samples, as well as euthanizing all zooplankton so that they are easier to identify under a dissection scope. After all of that is done we take a 45-minute break before taking over the cliff team job so they can have a lunch break, as well as a rest from staring at the glare of the water all day searching for whales. 

The cliff team generally consists of two people. One person will be on the theodolite, and the other will be on the laptop. The idea is that the theodolite uses the Pythagorean Theorem to get the exact coordinates of the whale we are spotting. This allows us to track exactly where the whales are going, what they are doing, how they’re doing it, and the fashion in which they’re doing it. The fixed points will fall on a plotted map on the laptop. The other job of the person on the laptop is to take pictures when possible so we can identify the whales. For instance, there is a whale named Buttons that has been recorded during past summers in Port Orford. By using the photos we take of a whale, combined with previous data about the whale named Buttons, we can cross-reference the body color and patterns of the whale to be able to re-identify Buttons. We now know that we have seen Buttons for 4 consecutive days feeding in our study area. The camera also acts as a tool to take pictures of whales not just for identity but for rare activity. Today while on the cliff Mia and I spotted a whale in Tichenor Cove (one of our sampling sites) that breached four times! These experiences are rare and beautiful. You never think about how big a whale truly is until you see it almost completely leap out of the water – it is beautiful. 

Fig 3. The post-breach splash created by Buttons. Unfortunately we weren’t able to get a good photo from the cliff because we were too stunned by the fact that we were seeing this rare behavior. Source: GEMM Lab.

I’m sure more mistakes will be made but that’s okay. I have many more experiences to witness, and many more memories to make from this internship, as well as challenges. I couldn’t be more than happy with the team I have to share all of these learning experiences and hardships with. 

Introducing Crew Cinco – the Port Orford Gray Whale Foraging Ecology Field Team of 2019

By Lisa Hildebrand, MSc student, OSU Department of Fisheries and Wildlife, Geospatial Ecology of Marine Megafauna Lab

It seems unfathomable to me that one year and two months ago I had never used a theodolite before, never been in an ocean kayak before, never identified zooplankton before, never seen a Time-Depth-Recorder (TDR) before. Now, one year later, it seems like all of those tools, techniques and things are just a couple of old friends with which I am being reunited with again. My second field season as the project team lead of the gray whale foraging ecology project in Port Orford (PO) is slowly getting underway and so many of the lessons I learned from my first field season last year have already helped me tremendously this year. I know how to interpret weather forecasts and determine whether it will be a kayak-appropriate day. I know how to figure out the quirks of Pythagoras, the program we use to interface with our theodolite which helps us track whales from our cliff site. I know how to keep track of a budget and feed a team of hungry researchers after a long day of work. Knowing all of these things ahead of this year’s field season have made me feel a little more prepared and at ease with the training of my team and the work to be done. Nevertheless, there are always new curveballs to be thrown my way and while they can often be frustrating, I enjoy the challenges that being a team leader has to offer as it allows me to continue to grow as a field research scientist. 

Figure 1. Crew Cinco tracks a whale in Tichenor Cove. Source: L Hildebrand.

2019 marks the fifth year that this project has been taking place in PO. Back in the summer of 2015, former GEMM Lab Master’s student Florence Sullivan started this project together with Leigh. That year the research focused more on investigating vessel disturbance to gray whales by comparing sites of heavy (Boiler Bay) to low boat traffic (Port Orford). The effort found that there were significant differences in gray whale activity budgets between the heavy and low boat traffic conditions (Sullivan & Torres 2018). The following year, the focus of the research switched to being more on the foraging ecology side of things and the project was based solely out of Port Orford, as it continues to be to this day. Being in our fifth year means that we are starting to build a humbly-sized database of sightings across multiple years allowing me to investigate potential individual specialization of the whales that we document. Similarly, multiple years of prey sampling is starting to reveal temporal and spatial trends of prey community assemblages.

Figure 2. Buttons (pictured above) is one of the stars of the Port Orford gray whale foraging ecology project as he has been seen every year since 2016. Crew Cinco has already seen him three times since the start of August. Source: L Hildebrand.

It has become a tradition to come up with a name for the field team that spends 6 weeks at the Oregon State University (OSU) Port Orford Field Station to collect the data for the project. It started with Team Ro“buff”stus in 2015, which I believe carried through until 2017. This is understandable since it’s such a clever name. It’s a play on the species name for gray whales, robustus, but the word “Buff” has been substituted in the center. Buffs are pieces of cloth sewn into a cylindrical shape, often with fun patterns or colors, that can be used as face masks, headbands, and scarves, which come in very handy when your face is exposed to the elements. Doing this project, we can be confronted by wind, sun, fog and sea water all in one day, so Buffs have definitely served the team members very well over the years. Last year, as the project’s torch was passed from Florence to myself, I felt a new team name was apt, and so last year’s team decided our name would be Team Whale Storm. I believe it was because we said we would take the whale world by storm with our insanely good theodolite tracking and kayak sampling skills. With a new year and new team upon us, a new team name was in order. As the title of this blog post indicates, this year the team is called Crew Cinco. The reason behind this name is that we are the fifth team to carry out this field work. Since the gray whales breed in the lagoons of Baja California, Mexico, I like to think that their native language is Spanish. Hence, we have decided that instead of being Crew Five, we are Crew Cinco, as cinco is the Spanish word for five (besides, alliteration makes for a much better team name).

Now that you are up to speed on the history of the PO gray whale project, let me tell you a little about who is part of Crew Cinco and what we have been up to already.

This year’s Marine Studies Initiative OSU undergraduate intern is Mia Arvizu. Mia has just finished her sophomore year at OSU and majors in Environmental Science. Besides being my co-captain this year in the field, Mia is also undertaking an independent research project which focuses on the relationship between sea urchin abundance, kelp health and gray whale foraging. She will tell you all about this project in a few weeks when she takes over the GEMM lab blog. Aside from her interest in ecology and the way science can be used to help local communities in a changing environment, Mia is a dancer, having performed in several dances in OSU’s annual luau this year, and she is currently teaching herself Spanish and Hawaiian.

Both of our high school interns this year are from Astoria. Anthony Howe has just graduated from Astoria High School and will be starting at Clatsop Community College in the fall. His plan is to transfer to OSU and to pursue his interest in marine biology. Anthony, like myself, was born in Germany and lived there until he was six, which means that he is able to speak fluent German. He also introduced the team to the wonders of the Instant Pot, which has made cooking for a team of four hungry scientists much simpler.

Donovan Burns is our other high school intern. He will be going into his junior year in the fall. Donovan never ceases to amaze us with the seemingly endless amounts of general knowledge he has, often sharing facts about Astoria’s history to Asimov’s Laws of Robotics to pickling vegetables, specifically carrots, with us during dinner or while scanning for whales on the cliff site. He also named the first whale we saw here this season – Speckles. 

Figure 3. Crew Cinco, from left to right: Anthony Howe, Donovan Burns, Lisa Hildebrand and Mia Arvizu. Source: L Torres.

Crew Cinco has already been in PO for two weeks now. After having a full team meeting with Leigh in Newport and a GEMM lab summer pizza party, we headed south to begin our 6-week field season. It’s hard to believe that the two training weeks are already over. The team worked hard to figure out the subtleties of the theodolite, observe different gray whales and start to understand their dive and foraging patterns, undertake a kayak paddle & safety course, as well as CPR and First Aid training, learn about data processing and management, and how to use a variety of gizmos to aid us in data collection. But it hasn’t all been work. We enjoyed a day in the Californian Redwoods on one of our day’s off and picked blueberries at the Twin Creek Ranch, stocking our freezer with several bags of juicy berries. We have played ‘Sorry!’ perhaps one too many times already (we are in desperate need of some more boardgames if anyone wants to send some our way to the field station!), and enjoyed many walks and runs on beautiful Battle Rock Beach. 

The next four weeks will not be easy – very early mornings, lots of paddling and squinting into the sun, followed by several hours in the lab processing samples and backing up data. But the next four weeks will also be extremely rewarding – learning lots of new skills that will be valuable beyond this 6-week period, revealing ecological trends and relationships, and ultimately (the true reason for why Mia, Anthony, Donovan and myself are more than happy to put in 6 weeks-worth of hard work), the chance to see whales every day up close and personal. Follow Crew Cinco’s journey over the next few weeks as my interns will be posting to the blog for the next three weeks!

References

Sullivan, F.A., & Torres L.G. Assessment of vessel disturbance to gray whales to inform sustainable ecotourism. Journal of Wildlife Management, 2018. 82: 896-905. 

Our GEM(M), Ruby, is back in action!

By Lisa Hildebrand, MSc student, OSU Department of Fisheries and Wildlife, Geospatial Ecology of Marine Megafauna Lab

Every season, or significant period of time, usually has a distinct event that marks its beginning. For example, even though winter officially begins when the winter solstice occurs sometime between December 20 and December 23, many people often associate the first snowfall as the real start of winter. To mark the beginning of schooling, when children start 1stgrade in Germany (which is where I’m from), they receive something called a “Zuckertüte”, which translated means “sugar bag”. It is a large (sometimes as large as the child) cone-shaped container made of cardboard filled with toys, chocolates, sweets, school supplies and various other treats topped with a large bow.

Receiving my Zuckertüte in August of 2001 before starting 1st grade. Source: Ines Hildebrand.

I still remember (and even have) mine – it was almost as tall as I was, had a large Barbie printed on it (and a real one sitting on top of it) and was bright pink. And of course, while at a movie theatre, once the lights dim completely and the curtain surrounding the screen opens just a little further, members of the audience stop chit-chatting or sending text messages, everyone quietens down and puts their devices away – the film is about to start. There are hundreds upon thousands of examples like these – moments, events, days that mark the start of something.

In the past, the beginning of summer has always been tied to two things for me: the end of school and the chance to be outside in the sun for many hours and days. This reality has changed slightly since moving to Oregon. While I don’t technically have any classes during the summer, the work definitely won’t stop. There are still dozens of papers to read, samples to run in the lab, and data points to plot. For anyone from Oregon or the Pacific Northwest (PNW), it’s pretty well known that the weather can be a little unpredictable and variable, meaning that summer might not always be filled with sunny days. Despite somewhat losing these two “summer markers”, I have found a new event to mark the beginning of summer – the arrival of the gray whales.

Their propensity for coastal waters and near-shore feeding is part of what makes gray whales so unique and arguably “easier” to study than some other baleen whale species. Image captured under NOAA/NMFS permit #21678. Source: Leigh Torres.

 

It’s official – the gray whale field season is upon us! As many of you may already know, the GEMM Lab has two active gray whale research projects: investigating the impacts of ocean noise on gray whale physiology and exploring potential individual foraging specialization among the Pacific Coast Feeding Group (PCFG) gray whales. Both projects involve field work, with the former operating out of Newport and the latter taking place in Port Orford, both collecting photographs and a variety of samples and tracklines to study the PCFG, which is a sub-group of the larger Eastern North Pacific (ENP) population. June 1st is the widely accepted “cut-off date” for the PCFG whales, whereby gray whales seen after June 1st along the PNW coastline (specifically northern California, Oregon, Washington and British Columbia) are considered members of the PCFG. While this date is not the only qualifying factor for an individual to be considered a PCFG member, it is a good general rule of thumb. Since last week happened to be the first week of June, PI Leigh Torres, field technician Todd Chandler and myself launched out onto the Pacific Ocean in our trusty RHIB Ruby twice looking for gray whales, and it sure was a successful start to the season!

Even though I have done small boat-based field work before, every project and field team operates a little differently, which is why I was a little nervous at first. There are a lot of components to the Newport-based project as Leigh & co. assess gray whale physiology by collecting fecal samples, drone imagery and taking photographs, observing behavior patterns, as well as assessing local prey through GoPro footage and light traps. I wasn’t worried about the prey components of the research, since there is plenty of prey sampling involved in my Port Orford research, however I was worried about the whale side of things. I wasn’t sure whether I would be able to catch the drone as it returned back home to Ruby, fearing I might fumble and let it slip through my fingers. I also experienced slight déjà vu when handling the net we use to collect the fecal samples as I was forced to think back to some previous field work that involved collecting a biopsy dart with a net as well. During that project, I had somehow managed to get the end of the net stuck in the back of the boat and as I tried to scoop up the biopsy dart with the net-end, the pole became more and more stuck while the water kept dragging the net-end down and eventually the pole ended up snapping in my hands. On top of all this anxiety and work, trying to find your footing in a small RHIB like Ruby packed with lots of gear and a good amount of swell doesn’t make any of those tasks any easier.

However, as it turned out, none of my fears came to fruition. As soon as Todd fired up Ruby’s engine and we whizzed out and under the Newport bridge, I felt exhilarated. I love field work and was so excited to be out on the water again. During the two days I was able to observe multiple individuals of a species of whale that I find unique and fascinating.

Markings and pigmentation on the flukes are also unique to individuals and allow us to perform photo identification to track individuals over months and years. Image captured under NOAA/NMFS permit #21678. Source: Leigh Torres.

I felt back in my natural element and working with Leigh and Todd was rewarding and fun, as I have so much to learn from their years of experience and natural talent in the field dealing with stressful situations and juggling multiple components and gear. Even though I wasn’t out there collecting data for my own project, some of my observations did get me thinking about what I hope to focus on in my thesis – individualization. It is always interesting to see how differently whales will behave, whether due to the substrate we find them over, the water depths we find them in, or what their surfacing patterns are like. Although I still have six weeks to go until my field season starts and feel lucky to have the opportunity to help Leigh and Todd with the Newport field work, I am already looking forward to getting down to Port Orford in mid-July and starting the fifth consecutive gray whale field season down there.

But back to Newport – over the course of two days, we were able to deploy and retrieve one light trap to collect zooplankton, collect two fecal samples, perform two GoPro drops, fly the drone three times, and take hundreds of photos of whales. Leigh and Todd were both glad to be reunited with an old friend while I felt lucky to be able to meet such a famous lady – Scarback. A whale with a long sighting history not just for the GEMM Lab but for various researchers along the coast that study this population. Scarback is well-known (and easily identified) by the large concave injury on her back that is covered in whale lice, or cyamids. While there are stories about how Scarback’s wound came to be, it is not known for sure how she was injured. However, what researchers do know is that the wound has not stopped this female from reproducing and successfully raising several calves over her lifetime. After hearing her story from Leigh, I wasn’t surprised that both she and Todd were so thrilled to get both a fecal sample and a drone flight from her early in the season. The two days weren’t all rosy; most of day 1 was shrouded in a cloud of mist resulting in a thin but continuous layer of moisture forming on our clothes, while on day 2 we battled with some pretty big swells (up to 6 feet tall) and in typical Oregon coast style we were victims of a sudden downpour for about 10 minutes. We had some excellent sightings and some not-so-excellent sightings. Sightings where we had four whales surrounding our boat at the same time and sightings where we couldn’t re-locate a whale that had popped up right next to us. It happens.

 

A local celebrity – Scarback. Image captured under NOAA/NMFS permit #21678. Source: Lisa Hildebrand.

 

An ecstatic Lisa with wild hair standing in the bow pulpit of Ruby camera at the ready. Source: Leigh Torres.

Field work is certainly one of my favorite things in the world. The smell of the salt, the rustling of cereal bar wrappers, the whipping of hair, the perpetual rosy noses and cheeks no matter how many times you apply and re-apply sunscreen, the awkward hilarity of clambering onto the back of the boat where the engine is housed to take a potty break, the whooshing sound of a blow, the sometimes gentle and sometimes aggressive rocking of the boat, the realization that you haven’t had water in four hours only to chug half of your water in a few seconds, the waft of peanut butter and jelly sandwiches, the circular footprint where a whale has just gracefully dipped beneath the surface slipping away from view. I don’t think I will ever tire of any of those things.

 

 

Signs you’re an ecologist – you don’t spend nearly enough time geeking out about your study species…

By Lisa Hildebrand, MSc student, OSU Department of Fisheries and Wildlife, Geospatial Ecology of Marine Megafauna Lab

This past week has been very busy for me as I gave three quite important, yet very different, presentations. The first was on Tuesday at the Pacific High School in Port Orford, near my study site. The aim of the game was recruitment – my quest for two eager local high schoolers to be my interns for this 2019 summer field season has begun (read blogs written by our 2017 HS interns Nathan Malamud and Quince Nye)! I was lucky enough to be given an entire class period to talk to the students and so I hope that the picture I painted of kayaks, gray whales and sun will be enough to entice students to apply to the internship.

The second was a short presentation in one of the classes I took this term, GEOG 561: GIScience II Analysis and Applications. The class focuses on developing and conducting geospatial analyses in R and throughout the term each student develops a small independent research project using some of their own data. For my research project, I decided to do a small cluster analysis of the zooplankton community data that we have collected from the kayak net samples.

The third and final presentation of the week happened on Thursday and marked one of the big milestones on my Master’s journey: my research review. The research review is a mandatory (and extremely helpful) process in the Department of Fisheries & Wildlife where the student (in this case me), the committee (Dr Leigh Torres, Dr Rachael Orben, Dr Kim Bernard and Dr Susanne Brander) and a department representative (Dr Brian Sidlauskas) all assemble to discuss the student’s research proposal, which lays out the intended work, chapters, analysis and timeline for the students’ thesis. My proposal (which currently bears the title: “Tonight’s specials include mysids, gammarids and more: An examination of the zooplankton prey of Oregon gray whales and its impact on individual foraging patterns”) proposes a two-chapter thesis where the first examines the quality of zooplankton prey, while the second looks at potential individual foraging specialization of gray whales along the Oregon coast. While my entire committee agreed that what I have set forth to do in the next two or so years is ambitious, they provided me with excellent feedback and confidence that I would be able to achieve what I have planned.

Now that it’s the weekend and I’ve had some time to sit back and think about the week, I realized one major commonality between all three presentations I gave. None of the Powerpoints featured more than one image of a gray whale. How could this be?! It is after all my study species and I spend so much of my summer looking at them – how could it be that so little of what I showed and talked about was the thing that I am most passionate about and is so central to my research?

In the course of doing research, it’s easy to get wound up in the nitty gritty and forget about the big picture. While the nitty gritty is also imperative to conducting the research (and ultimately getting results), I sometimes forget about why I do what I do, which is that gray whales are AWESOME. Looking into the past, it seems that some of my lab mates have had the same realizations about their study species before too: see here and here. So for this blog, I want to bring it back to basics and share some of the things that I think are most fascinating about gray whales.

  1. Gray whales are the only baleen whale that feeds benthically. This behavior is facilitated by the shorter and tougher baleen that gray whales possess in comparison to other baleen whale species (Pivorunas 1979). The majority of the Eastern North Pacific (ENP) gray whale population feeds benthically in the Bering Sea where they eat ampeliscid amphipods, which are a type of benthic invertebrates (Nerini 1984). It is estimated that gray whales must regain 11-29% of critical body mass during the feeding season (Villegas-Amtmann et al. 2015) in order to obtain the energy stores they require for the entire year. Besides the personal benefit of sea floor foraging, by using this feeding tactic gray whales create depressions in the soft sediment that benefit other species besides themselves. The highly disruptive nature of this action can increase the biodiversity of the seafloor and initiate scavenging events by lysiannassid amphipods on other infauna (Oliver & Slattery 1985). Furthermore, Grebmeier & Harrison (1992) documented that a variety of seabirds including northern fulmars, black-legged kittiwakes and thick-billed murres feed on benthic amphipods brought to the surface by this unique foraging behavior performed by gray whales.
  1. Gray whales are essentially acrobats. A preference for benthic prey goes hand in hand with a preference for shallow, coastal waters, as for example Pacific Coast Feeding Group gray whales tend to forage within the 5-15 m depth range (Weller et al. 1999). With female adults ranging between 13-15 m in length (females tend to be slightly larger than adult males) and weighing anywhere between 15-33 tons (Jones et al. 1984), I am continuously fascinated by how gracefully and slowly gray whales can navigate extremely shallow waters.

    However, it is more than just simple navigation – the behaviors and moves that some gray whales display while in the shallows is phenomenal too. Last year Torres et al. (2018) documented this agility through unmanned aerial systems (UAS) footage that provided evidence for some novel foraging tactics including headstands, side-swimming, and jaw snapping and flexing.

  1. They sure are resilient. Commercial whaling of gray whales began in 1846 after two commercial whaling vessels first discovered the winter breeding grounds in Baja California, Mexico (Henderson 1984). Following this discovery, the ENP were targeted for roughly a century before receiving full protection under the International Convention for the Regulation of Whaling in 1946 (Reeves 1984). Through genetic analyses, it has been estimated that the pre-whaling abundance of the ENP population was between 76,000 – 118,000 individuals (Alter et al. 2012), which is roughly three to five times larger than current estimates (24,000 – 26,000; Scordino et al. 2018). While the gray whale populations that once existed in the Atlantic Ocean were not as fortunate as those in the Pacific (Atlantic gray whales were declared extinct in the 18thcentury due to extensive whaling; Bryant 1995), the ENP has definitely made a strong comeback. Additionally, gray whale resilience is not only evident on this long temporal scale but it can also be seen annually when gray whale mothers fight relentlessly to keep their calves alive when under attack from killer whales. A study on predation of gray whales by transient killer whales in Alaska reported that attacks were quickly abandoned if calves were aggressively defended by their mothers or if gray whales succeeded in reaching depths of 3 m or less (Barrett-Lennard et al. 2011).
  1. For some unimaginable reason, gray whales appear to feel a strong connection to us. For many, gray whales might be best known for actively seeking out human contact during their breeding season in the Mexican lagoons. I find this actuality particularly interesting because of the bloody history we share with Pacific gray whales.

Those are just some of the things about gray whales that make them so fascinating to me. I look forward to potentially discovering one or two more things that we don’t know about them yet through my research. Even if that doesn’t turn out to be the case, I feel so lucky that I at least get to spend so much time with them during their feeding season here along the Oregon coast.

 

References

Alter, E.S., et al., Pre-whaling genetic diversity and population ecology in Eastern Pacific gray whales: Insights from ancient DNA and stable isotopes.PLoS ONE, 2012. doi.org/10.1371/journal.pone.0035039.

Barrett-Lennard, L.G., et al., Predation on gray whales and prolonged feeding on submerged carcasses by transient killer whales at Unimak Island, Alaska. Marine Ecology Progress Series, 2011. 421: 229-241.

Bryant, P.J., Dating remains of gray whales from the Eastern North Atlantic. Journal of Mammalogy, 1995. 76(3): 857-861.

Grebmeier, J.M., & Harrison, N.M., Seabird feeding on benthic amphipods facilitated by gray whale feeding activity in the northern Bering Sea. Marine Ecology Progress Series, 1992. 80: 125-133.

Henderson, D.A., Nineteenth century gray whaling: Grounds, catches and kills, practices and depletion of the whale population.Pages 159-186 inJones, M.L. et al., eds. The gray whale: Eschrichtius robustus, 1984. Academic Press, Orlando.

Jones, M.L., et al., The gray whale: Eschrichtius robustus. 1984. Academic Press, Orlando.

Nerini, M., A review of the gray whale feeding ecology. Pages 423-448 inJones, M.L. et al., eds. The gray whale: Eschrichtius robustus, 1984. Academic Press, Orlando.

Oliver, J.S., & Slattery, P.N., Destruction and obstruction on the sea floor: effects of gray whale feeding.Ecology, 1985. 66: 1965-1975.

Pivorunas, A., The feeding mechanisms of baleen whales.American Scientist, 1979. 67(4): 432-440.

Reeves, R.R., Modern commercial pelagic whaling for gray whales. Pages 187-200 inJones, M.L. et al., eds. The gray whale: Eschrichtius robustus, 1984. Academic Press, Orlando.

Scordino, J., et al., Report of gray whale implementation review coordination call on 5 December 2018.

Torres, L.G., et al., Drone up! Quantifying whale behavior from a new perspective improves observational capacity.Frontiers in Marine Science, 2018. 5: doi:10.3389/fmars.2018.00319.

Villegas-Amtmann, S., et al., A bioenergetics model to evaluate demographic consequences of disturbance in marine mammals applied to gray whales. Ecosphere, 2015. 6(10): 1-19.

Weller, D.W., et al., Gray whale (Eschrichtius robustus) off Sakhalin Island, Russia: Seasonal and annual patterns of occurrence. Marine Mammal Science, 1999. 15(4): 1208-1227.

Photogrammetry Insights

By Leila Lemos, PhD Candidate, Fisheries and Wildlife Department, Oregon State University

After three years of fieldwork and analyzing a large dataset, it is time to finally start compiling the results, create plots and see what the trends are. The first dataset I am analyzing is the photogrammetry data (more on our photogrammetry method here), which so far has been full of unexpected results.

Our first big expectation was to find a noticeable intra-year variation. Gray whales spend their winter in the warm waters of Baja California, Mexico, period while they are fasting. In the spring, they perform a big migration to higher latitudes. Only when they reach their summer feeding grounds, that extends from Northern California to the Bering and Chukchi seas, Alaska, do they start feeding and gaining enough calories to support their migration back to Mexico and subsequent fasting period.

 

Northeastern gray whale migration route along the NE Pacific Ocean.
Source: https://journeynorth.org/tm/gwhale/annual/map.html

 

Thus, we expected to see whales arriving along the Oregon coast with a skinny body condition that would gradually improve over the months, during the feeding season. Some exceptions are reasonable, such as a lactating mother or a debilitated individual. However, datasets can be more complex than we expect most of the times, and many variables can influence the results. Our photogrammetry dataset is no different!

In addition, I need to decide what are the best plots to display the results and how to make them. For years now I’ve been hearing about the wonders of R, but I’ve been skeptical about learning a whole new programming/coding language “just to make plots”, as I first thought. I have always used statistical programs such as SPSS or Prism to do my plots and they were so easy to work with. However, there is a lot more we can do in R than “just plots”. Also, it is not just because something seems hard that you won’t even try. We need to expose ourselves sometimes. So, I decided to give it a try (and I am proud of myself I did), and here are some of the results:

 

Plot 1: Body Area Index (BAI) vs Day of the Year (DOY)

 

In this plot, we wanted to assess the annual Body Area Index (BAI) trends that describe how skinny (low number) or fat (higher number) a whale is. BAI is a simplified version of the BMI (Body Mass Index) used for humans. If you are interested about this method we have developed at our lab in collaboration with the Aerial Information Systems Laboratory/OSU, you can read more about it in our publication.

The plots above are three versions of the same data displayed in different ways. The first plot on the left shows all the data points by year, with polynomial best fit lines, and the confidence intervals (in gray). There are many overlapping observation points, so for the middle plot I tried to “clean up the plot” by reducing the size of the points and taking out the gray confidence interval range around the lines. In the last plot on the right, I used a linear regression best fit line, instead of polynomial.

We can see a general trend that the BAI was considerably higher in 2016 (red line), when compared to the following years, which makes us question the accuracy of the dataset for that year. In 2016, we also didn’t sample in the month of July, which is causing the 2016 polynomial line to show a sharp decrease in this month (DOY: ~200-230). But it is also interesting to note that the increasing slope of the linear regression line in all three years is very similar, indicating that the whales gained weight at about the same rate in all years.

 

Plot 2: Body Area Index (BAI) vs Body Condition Score (BCS)

 

In addition to the photogrammetry method of assessing whale body condition, we have also performed a body condition scoring method for all the photos we have taken in the field (based on the method described by Bradford et al. 2012). Thus, with this second set of plots, we wanted to compare both methods of assessing whale body condition in order to evaluate when the methods agree or not, and which method would be best and in which situation. Our hypothesis was that whales with a ‘fair’ body condition would have a lower BAI than whales with a ‘good’ body condition.

The plots above illustrate two versions of the same data, with data in the left plot grouped by year, and the data in the right plot grouped by month. In general, we see that no whales were observed with a poor body condition in the last analysis months (August to October), with both methods agreeing to this fact. Additionally, there were many whales that still had a fair body condition in August and September, but less whales in the month of October, indicating that most whales gained weight over the foraging seasons and were ready to start their Southbound migration and another fasting period. This result is important information regarding monitoring and conservation issues.

However, the 2016 dataset is still a concern, since the whales appear to have considerable higher body condition (BAI) when compared to other years.

 

Plot 3:Temporal Body Area Index (BAI) for individual whales

 

In this last group of plots, we wanted to visualize BAI trends over the season (using day of year – DOY) on the x-axis) for individuals we measured more than once. Here we can see the temporal patterns for the whales “Bit”, “Clouds”, “Pearl”, “Scarback, “Pointy”, and “White Hole”.

We expected to see an overall gradual increase in body condition (BAI) over the seasons, such as what we can observe for Pointy in 2018. However, some whales decreased their condition, such as Bit in 2018. Could this trend be accurate? Furthermore, what about BAI measurements that are different from the trend, such as Scarback in 2017, where the last observation point shows a lower BAI than past observation points? In addition, we still observe a high BAI in 2016 at this individual level, when compared to the other years.

My next step will be to check the whole dataset again and search for inconsistencies. There is something causing these 2016 values to possibly be wrong and I need to find out what it is. The overall quality of the measured photogrammetry images was good and in focus, but other variables could be influencing the quality and accuracy of the measurements.

For instance, when measuring images, I often struggled with glare, water splash, water turbidity, ocean swell, and shadows, as you can see in the photos below. All of these variables caused the borders of the whale body to not be clearly visible/identifiable, which may have caused measurements to be wrong.

 

Examples of bad conditions for performing photogrammetry: (1) glare and water splash, (2) water turbidity, (3) ocean swell, and (4) a shadow created in one of the sides of the whale body.
Source: GEMM Lab. Taken under NMFS permit 16111 issued to John Calambokidis.

 

Thus, I will need to check all of these variables to identify the causes for bad measurements and “clean the dataset”. Only after this process will I be able to make these plots again to look at the trends (which will be easy since I already have my R code written!). Then I’ll move on to my next hypothesis that the BAI of individual whales varied by demographics including sex, age and reproductive state.

To carry out robust science that produces results we can trust, we can’t simply collect data, perform a basic analysis, create plots and believe everything we see. Data is often messy, especially when developing new methods like we have done here with drone based photogrammetry and the BAI. So, I need to spend some important time checking my data for accuracy and examining confounding variables that might affect the dataset. Science can be challenging, both when interpreting data or learning a new command language, but it is all worth it in the end when we produce results we know we can trust.

 

 

 

Plastics truly are ubiquitous in the marine environment

By Lisa Hildebrand, MSc student, OSU Department of Fisheries and Wildlife, Geospatial Ecology of Marine Megafauna Lab

As I enter my second term at OSU as a Master’s student, the ideas and structure of my thesis are slowly coming together. As of right now, my plan is to have two data chapters: The first chapter will assess the quality of zooplankton prey gray whales have access to along the Oregon coast, by looking at energetic value and microplastic content. I will contemplate about how my results potentially affect gray whale health. The second chapter will investigate fine-scale foraging and space use of gray whales in the Port Orford area to determine whether individual specialisation exists.

Fig 1. What it feels like when you start a literature review. Source: Harvard Blogs.

When I first started digging into the scientific literature to prepare for writing my thesis proposal (which is still underway but I’m getting close to the end of a first draft…), one sentence that I seemed to stumble across more often than not was “Marine plastics are ubiquitous” or “Plastics have become ubiquitous in the marine environment” or some other, very similar, iteration of that statement (e.g. Machovsky-Capuska et al. 2019; Eriksen et al. 2014; Fendall & Sewell 2009).

Many of the papers I first read were review papers on microplastics that mostly discussed general concepts like dispersal mechanisms, trophic transfer, or how microplastics become degraded. While I often think of review papers as treasure chests, since they neatly and succinctly summarise an often complicated and busy area of research into just a few pages, sometimes the fine-scale detail can go missing. Therefore, when reading these review papers, I wasn’t learning the in depth details about specific studies where microplastics had been detected in a group of individuals, population or species. So I felt the statement “Plastics are ubiquitous” was just a good (and pretty dramatic) opening line for a paper. However, once I delved into the studies on single species, I was overwhelmed by the amount of results that GoogleScholar spit out at me. If you type “microplastics marine” into the search bar, you’ll get about 7,650 results. This amount might not sound like a lot, especially if you compare it to say “gray whale”, which generates 96,600 results. Yet, the microplastic extraction method typically used was only developed in 2004 (Thompson et al. 2004). Hence, in a span of just 15 years, over 7,000 studies have detected microplastics in over 660 marine organisms (Secretariat of the Convention on Biological Diversity 2012) – a fact I find extremely troubling.

Fig 2. Graphic explaining how plastics don’t go away. Source: Biotecnika.

Microplastics are most commonly viewed as particles <5 mm in size (though there is some contention on this size classification, e.g. Claessens et al. 2013). Microplastics arise from several sources, including fragmentation of larger plastics by UV photo-degradation, wave action and physical abrasion, loss of pre-production pellets (nurdles) and polystyrene beads from shipping vessels, waste water discharge containing microbeads used in cosmetics and microfibers released during the washing of textiles and run-off from land (Nelms et al. 2018). Their small size makes these persistent particles bioavailable to ingestion by a variety of marine taxa, ranging from small prey organisms such as zooplankton, to large megafauna such as whales.

Zooplankton are at the base of marine food webs and are therefore consumed in large quantities by a large number of consumers. The propensity of zooplankton to feed in surface waters makes them highly susceptible to encountering and ingesting microplastics as this is where these synthetic particles are highly abundant (Botterell et al. 2018). Microplastics have been detected in zooplankton from the Northeast Pacific Ocean (Desforges et al. 2015), northern South China Sea (Sun et al. 2017), and Portuguese coast (Frias et al. 2014). Additionally, there is documented overlap between microplastic and zooplankton occurrence at many more locations (e.g. North Western Mediterranean Sea, Collignon et al. 2012; Baltic Sea, Gorokhova 2015; Arctic Ocean, Lusher et al. 2015a). As microplastics research is still in its relative infancy, the extent to which microplastics are ingested by zooplankton and the consequences of this behaviour are uncertain. Nevertheless, exposure to microplastics could lead to entanglement of particles within feeding appendages and/or block internal organs, which may result in reduced feeding, poor overall health, injury and death (Desforges et al. 2015). Though a lab study has found that microplastics are expelled by zooplankton after ingestion, the gut-retention times varied between species, and there is the potential risk of exposure to toxins that leech off of particles while in the body (Cole et al. 2013; the below video is from the afore-mentioned study showing how plankton eat plastics, which are illuminated in fluorescent green).

The large knowledge gap regarding the health implications indicates a strong need for more laboratory studies that investigate the long-term effects of persistent exposure to microplastics on lower trophic organisms, as well as continued short-term experiments that examine whether different zooplankton species are affected differently, since morphologies and life-histories vary widely.

Let’s take a step back and re-focus our lens onto a marine taxa that is much, much bigger in size than a zooplankton: cetaceans. Plastic debris has been documented in the stomachs of stranded individuals of several cetacean species (See Baulch & Perry 2014 for a review), however findings of microplastics in cetaceans are less common. Since cetaceans consume large amounts of prey a day, up to several tons daily for some baleen whales, the likelihood that they are ingesting microplastics through their prey is relatively high (Nelms et al. 2018). Therefore the low number of reported cases is again likely due to the relative novelty of microplastic detection methods. Despite the paucity of studies, microplastics have been found in a True’s beaked whale (Mesoplodon mirus, Lusher et al. 2015b), a humpback whale (Megaptera novaeangliae, Besseling et al. 2015) and an Indo-Pacific humpback dolphin (Sousa chinensis, Zhu et al. 2018), showing that microplastic ingestion by cetaceans does occur. Whether these individuals actively (i.e. active feeding) or passively (i.e. uptake through prey consumption) consumed the microplastics, or inhaled them at the water-air interface, is unknown. As with zooplankton, the short- and long-term impacts of ingesting microplastics by marine mammals is also unknown, though impacts on survival, feeding and uptake of toxins are all possibilities.

Fig 3. Example of a light trap sample collected off the Newport coast. Source: L. Torres.

The data collection and analysis I am doing for my thesis will hopefully fill small pockets in these large knowledge gaps. I hope to be able to quantify the extent of microplastic pollution among zooplankton species in nearshore Oregon waters. By comparing samples from several years, months and locations, I will determine whether microplastic loads vary spatially and temporally. Since their abundance and presence have been described as being patchy due to the influence of oceanographic and weather conditions (GESAMP 2016), it would seem reasonable to assume that there will be variation. But, results are a ways away as we have not even started our microplastic extraction techniques, which involves digesting samples in potassium hydroxide solution, incubating them at 50ºC for 48-72 hours, sorting through the dissolved material to identify potential plastics and sending them away for analysis. We first have to work our way through jars upon jars of unopened zooplankton light trap samplesthat need to be sorted by species. I am thankfully joined by undergraduate Robyn Norman who has already assisted this project immensely over the last two years with her zooplankton sorting prowess. So in case anyone wants to come looking for us over the next few weeks, you’ll find both Robyn and me sitting in front of a laminar flow hood in the lab of ecotoxicologist Dr. Susanne Brander, with whom we are collaborating on the microplastics portion of my thesis.

 

References

Baulch, S., & Perry, C., Evaluating the impacts of marine debris on cetaceans. Marine Pollution Bulletin, 2014. 80(1-2): 210-221.

Besseling, E., et al., Microplastic in a macro filter feeder: humpback whale Megaptera novaeangliae. Marine Pollution Bulletin, 2015. 95: 248-252.

Botterell, Z.L.R., et al., Bioavailability and effects of microplastics on marine zooplankton: a review. Environmental Pollution, 2018. 245: 98-110.

Claessens, M., et al., New techniques for the detection of microplastics in sediments and field collected organisms. Marine Pollution Bulletin, 2013. 70(1-2): 227-233.

Cole, M., et al., Microplastic ingestion by zooplankton. Environmental Science & Technology, 2013. 47(12): 6646-6655.

Collignon, A., et al., Neustonic microplastic and zooplankton in the North Western Mediterranean Sea. Marine Pollution Bulletin, 2012. 64(4): 861-864.

Desforges, JP.W., et al., Ingestion of microplastics by zooplankton in the Northeast Pacific Ocean. Archives of Environmental Contamination and Toxicology, 2015. 69(3): 320-330.

Eriksen, M., et al., Plastic pollution in the world’s oceans: more than 5 trillion plastic pieces weighing over 250,000 tons afloat at sea. PLoS ONE, 2014. doi.org/10.1371/journal.pone.0111913.

Fendall, L.S., & Sewell, M.A., Contributing to marine pollution by washing your face: microplastics in facial cleansers. Marine Pollution Bulletin, 2009. 58(8): 1225-1228.

Frias, J.P.G.L., et al., Evidence of microplastics in samples of zooplankton from Portuguese coastal waters. Marine Environmental Research, 2014. 95: 89-95.

GESAMP, Sources, fates and effects of microplastics in the marine environment: part 2 of a global assessment. Second United Nations Environment Assembly, 2016. http://www.gesamp.org/site/assets/files/1720/rs93e.pdf

Gorokhova, E., Screening for microplastic particles in plankton samples: how to integrate marine litter assessment into existing monitoring programs? Marine Pollution Bulletin, 2015. 99(1-2): 271-275.

Lusher, A.L., et al., Microplastics in Arctic polar waters: the first reported values of particles in surface and sub-surface samples. Scientific Reports, 2015a. 5: 14947.

Lusher, A.L., et al., Microplastic and macroplastic ingestion by a deep diving, oceanic cetacean: the True’s beaked whales Mesoplodon mirus. Environmental Pollution, 2015b. 199: 185-191.

Machovsky-Capuska, G.E., et al., A nutritional perspective on plastic ingestion in wildlife. Science of the Total Environment, 2019. 656: 789-796.

Nelms, S.E., et al., Investigating microplastic trophic transfer in marine top predators. Environmental Pollution, 2018. 238: 999-1007.

Secretariat of the Convention on Biological Diversity and the Scientific and Technical Advisory Panel – GEF (2012), Impacts of marine debris on biodiversity: current status and potential solutions. Montreal, Technical Series. 67: 1-61.

Sun, X., et al., Ingestion of microplastics by natural zooplankton groups in the northern South China Sea. Marine Pollution Bulletin, 2017. 115(1-2): 217-224.

Thompson, R.C., et al., Lost at sea: where is all the plastic? Science, 2004. 304(5672): 838.

Zhu, J., et al., Cetaceans and microplastics: First report of microplastic ingestion by a coastal delphinid, Sousa chinensis. Science of the Total Environment, 2018. 659: 649-654.