Tag: REU

A Summer of Crustacean Investigation

By Matoska Silva, OSU Department of Integrative Biology, CEOAS REU Program

My name is Matoska Silva, and I just finished my first year at Oregon State University studying biology with a focus in ecology. This summer will be my first experience with marine ecology, and I’m eager to dive right in. I’m super excited for the opportunity to research krill due to the huge impacts these tiny organisms have on their surrounding ecosystems. The two weeks I’ve spent in the CEOAS REU so far have been among the most fun and informative of my life, and I can’t wait to see what else the summer has in store for me.

Figure 1. Matoska presents his proposed research to the CEOAS REU program.

I’ve spent most of my life in Oregon, so I was thrilled to learn that my project would focus on krill distribution along the Oregon Coast that I know and love. More specifically, my project focuses on the Northern California Current (NCC, the current found along the Oregon Coast) and the ways that geographic distribution of krill corresponds to climatic conditions in the region. Here is a synopsis of the project:

The NCC system, which spans the west coast of North America from Cape Mendocino, California to southern British Columbia, is notable for seasonal upwelling, a process that brings cool, nutrient-rich water from the ocean depths to the surface. This process provides nutrients for a complex marine food web containing phytoplankton, zooplankton, fish, birds, and mammals (Checkley & Barth, 2009). Euphausiids, commonly known as krill, are among the most ecologically important zooplankton groups in the NCC, playing a vital role in the flow of nutrients through the food web (Evans et al., 2022). Euphausia pacifica and Thysanoessa spinifera are the predominant krill species in the NCC, with T. spinifera mainly inhabiting coastal waters and E. pacifica inhabiting a wider range offshore (Brinton, 1962). T. spinifera individuals are typically physically larger than E. pacifica and are generally a higher-energy food source for predators (Fisher et al., 2020). 

Temperature has been previously established as a major factor impacting krill abundance and distribution in the NCC (Phillips et al., 2022). Massive, ecosystem-wide changes in the NCC have been linked to extreme warming brought on by the 2014-2016 marine heatwave (Brodeur et al., 2019). Both dominant krill species have been shown to respond negatively to warming events in the NCC, with anomalous warm temperatures in 2014-2016 being linked to severe declines in E. pacifica biomass and with T. spinifera nearly disappearing from the Oregon Coast (Peterson et al., 2017). Changes in normal seasonal size variation and trends toward smaller size distributions in multiple age groups have been observed in E. pacifica in response to warming in northern California coastal waters (Robertson & Bjorkstedt, 2020). 

The El Niño-Southern Oscillation (ENSO) is a worldwide climatic pattern that has been linked to warming events and ecosystem disturbances in the California Current System (McGowan et al., 1998). El Niño events of both strong and weak intensity can result in changes in the NCC ecosystem (Fisher et al., 2015). Alterations in the typical zooplankton community accompanying warm water conditions and a decline in phytoplankton have been recorded in the NCC during weak and strong El Niño occurrences (Fisher et al., 2015). A strong El Niño event occurred in 2023 and 2024, with three-month Oceanic Niño Index means reaching above 1.90 from October 2023 to January 2024 (NOAA Climate Prediction Center, https://www.cpc.ncep.noaa.gov/data/indices/oni.ascii.txt).   

Figure 2. A graph of the ONI showing variability across two decades. Retrieved from NOAA at https://www.climate.gov/news-features/understanding-climate/climate-variability-oceanic-nino-index 

While patterns in krill responses to warming have been described from previous years,  the effects of the 2023-2024 El Niño on the spatial distribution of krill off the Oregon coast have not yet been established. As climate models have predicted that strong El Niño events may become more common due to greenhouse warming effects (Cai et al., 2014), continuing efforts to document zooplankton responses to El Niño conditions are vital for understanding how the NCC ecosystem responds to a changing climate. By investigating krill spatial distributions in April 2023, during a period of neutral ENSO conditions following a year of La Niña conditions, and April 2024, during the 2023-2024 El Niño event, we can assess how recent ENSO activity has impacted krill distributions in the NCC. In addition to broader measures of ENSO, we will examine records of localized sea surface temperatures (SST) and measurements of upwelling activity during April 2023 and 2024.

Understanding spatial distribution of krill aggregations is both ecologically and economically relevant, with implications for both marine conservation and management of commercial fisheries. Modeling patterns in the distribution of krill species and their predators has potential to inform marine management decisions to mitigate human impacts on marine mammals like whales (Rockwood et al., 2020). The data used to identify krill distribution were originally collected as part of the Marine Offshore Species Assessments to Inform Clean Energy (MOSAIC) project. The larger MOSAIC initiative centers around monitoring marine mammals and birds in areas identified for possible future development of offshore wind energy infrastructure. The findings of this study could aid in the conservation of krill consumers during the implementation of wind energy expansion projects. Changes in krill spatial distribution are also important for monitoring species that support commercial fisheries. Temperature has been shown to play a role in the overlap in distribution of NCC krill and Pacific hake (Merluccius productus), a commercially valuable fish species in Oregon waters (Phillips et al., 2023). The findings of my project could supplement existing commercial fish abundance surveys by providing ecological insights into factors driving changes in economically important fisheries.

Figure 3. The study area and transect design of the MOSAIC project, during which active acoustic data was collected (MOSAIC Project, https://mmi.oregonstate.edu/marine-mammals-offshore-wind). 

I’m very grateful for the chance to work on a project with such important implications for the future of our Oregon coast ecosystems. My project has a lot of room for additional investigation of climate variables, with limited time being the main constraint on which processes I can explore. There are also unique methodological challenges to address during the project, and I’m ready to do some experimentation to work out solutions. Wherever my project takes me, I know that I will have developed a diverse range of skills and knowledge of krill by the end of the summer.

References

Brinton, E. (1962). The distribution of Pacific euphausiids. Bulletin of the Scripps Institution of Oceanography, 8(2), 51-270. https://escholarship.org/uc/item/6db5n157 

Brodeur, R. D., Auth, T. D., & Phillips, A. J. (2019). Major shifts in pelagic micronekton and macrozooplankton community structure in an upwelling ecosystem related to an unprecedented marine heatwave. Frontiers in Marine Science, 6. https://doi.org/10.3389/fmars.2019.00212 

Cai, W., Borlace, S., Lengaigne, M., van Rensch, P., Collins, M., Vecchi, G., Timmermann, A., Santoso, A., McPhaden, M. J., Wu, L., England, M. H., Wang, G., Guilyardi, E., & Jin, F. F. (2014). Increasing frequency of extreme El Niño events due to greenhouse warming. Nature Climate Change, 4, 111–116. https://doi.org/10.1038/nclimate2100 

Checkley, D. M., & Barth, J. A. (2009). Patterns and processes in the California Current System. Progress in Oceanography, 83, 49–64. https://doi.org/10.1016/j.pocean.2009.07.028 

Evans, R., Gauthier, S., & Robinson, C. L. K. (2022). Ecological considerations for species distribution modelling of euphausiids in the Northeast Pacific Ocean. Canadian Journal of Fisheries and Aquatic Sciences, 79, 518–532. https://doi.org/10.1139/cjfas-2020-0481 

Fisher, J. L., Peterson, W. T., & Rykaczewski, R. R. (2015). The impact of El Niño events on the pelagic food chain in the northern California Current. Global Change Biology, 21, 4401–4414. https://doi.org/10.1111/gcb.13054 

Fisher, J. L., Menkel, J., Copeman, L., Shaw, C. T., Feinberg, L. R., & Peterson, W. T. (2020). Comparison of condition metrics and lipid content between Euphausia pacifica and Thysanoessa spinifera in the Northern California Current, USA. Progress in Oceanography, 188, 102417. https://doi.org/10.1016/j.pocean.2020.102417

McGowan, J. A., Cayan, D. R., & Dorman, L. M. (1998). Climate-ocean variability and ecosystem response in the Northeast Pacific. Science, 281, 210–217. https://doi.org/10.1126/science.281.5374.210 

Phillips, E. M., Chu, D., Gauthier, S., Parker-Stetter, S. L., Shelton, A. O., & Thomas, R. E. (2022). Spatiotemporal variability of Euphausiids in the California Current Ecosystem: Insights from a recently developed time series. ICES Journal of Marine Science, 79,   1312–1326. https://doi.org/10.1093/icesjms/fsac055 

Phillips, E. M., Malick, M. J., Gauthier, S., Haltuch, M. A., Hunsicker, M. E., Parker‐Stetter, S. L., & Thomas, R. E. (2023). The influence of temperature on Pacific hake co‐occurrence with euphausiids in the California Current Ecosystem. Fisheries Oceanography, 32, 267–279. https://doi.org/10.1111/fog.12628

Peterson, W. T., Fisher, J. L., Strub, P. T., Du, X., Risien, C., Peterson, J., & Shaw, C. T. (2017). The pelagic ecosystem in the Northern California Current off Oregon during the 2014–2016 warm anomalies within the context of the past 20 years. Journal of Geophysical Research: Oceans, 122(9), 7267–7290. https://doi.org/10.1002/2017jc012952 

Robertson, R. R., & Bjorkstedt, E. P. (2020). Climate-driven variability in Euphausia pacificasize distributions off Northern California. Progress in Oceanography, 188, 102412.https://doi.org/10.1016/j.pocean.2020.102412

Are You Seeing Scars Too?: Examining Gray Whale Scars and Skin Conditions

By Serina Lane, GEMM Lab NSF REU Intern, Georgia Gwinnett College

Hello, everyone! My name is Serina and I’m a Research Experience for Undergraduates (REU) Intern at the Hatfield Marine Science Center (HMSC) this summer. I’ve had a love for the ocean for as long as I can remember. Honestly, it started off with just dolphins, but I soon started to realize that the ocean is full of fascinating creatures!

How I ended up here…well, I’ve never been to Oregon, I’m escaping the hot weather of Georgia, but I’m also getting to interact with like-minded marine biologists and experienced individuals at an amazing marine laboratory. At the age of 29, I’m also an older undergraduate student, and I will be graduating soon! I took a very long break from academics and coming back was hard, especially switching from business to biology. I have participated in surveys that asked how I felt about the statement “I am a scientist,” along with the degrees of agree and disagree. For most of my undergraduate career, I picked “slightly disagree”. I was getting great grades, but I did not feel like I was ever going to be able to accomplish the type of work scientific papers are written about. I really felt the need to gain more experience in the career path I intended to follow. All of these are the whirlwind ingredients that went into applying for the HMSC REU Internship at OSU! I’m being mentored by the lovely Natalie Chazal and Leigh Torres, and I am grateful for the opportunity and very excited to experience everything Hatfield has to offer. A little over a week of being here, I already feel my answer sliding from “neutral” to even “slightly agree”. There is still so much to learn!

The project I’m helping with is analyzing the scarring and skin conditions of Eastern North Pacific gray whales alongside the GRANITE team. My job will be analyzing over 100,000 pictures from the past eight years to detect various scars and potential skin conditions (yes, the comma is in the correct spot and no, there are no extra 0’s). Scars can come from a variety of sources such as boat propellers, fishing gear, and killer whales! A study conducted by Corsi et al. consisted of documenting killer whale rake marks (bites, essentially) on different types of whales in the eastern North Pacific. Their results showed that gray whales had the highest percentage of observed rake marks in sighted individuals, and provided insight into why body sections of observed marks are important. Most baleen whales had rake marks predominantly on their flukes, because they are often used for defense and if fleeing, are the closest area to bite. Fascinatingly, Corsi et al. consider that the higher occurrences of gray whale rake marks are due to killer whales adopting species-specific hunting approaches. Gray whales have predictable migratory routes, and we already know how intelligent killer whales can be. If I knew a truck had a specific delivery route and I could wait to intercept a fresh delivery of Krispy Kreme donuts, why wouldn’t I? 

Donuts aside, I’ll also be categorizing where the scars/skin conditions are located – for example, certain regions on the tail (like above) or on their left or right back (often due to boat collisions). Then I’ll define what I believe to be the source of scarring and rate my confidence in that decision based on the photo. Now, not all of the photos are clear enough for me to make informed decisions, so realistically I could end up with only a few hundred usable photos. At the end of the summer, we’ll gather the results and compare the different rates of scarring sources and the body parts where they occurred, and analyze any patterns in skin conditions, such as whether a skin condition has worsened or improved on an individual we have sighted multiple times over the years.

 Figure 1. A little look into a table I made to give examples of what scarring from different sources look like.

Surprisingly, cetaceans can heal deep wounds on their own without medical intervention. Scientists have discovered that compounds in their blubber layer, such as organohalogens and isovaleric acid, may naturally fight off infections and help wounds heal faster. Unlike humans and other terrestrial animals that form scabs when injured, cetaceans develop a different protective layer over their wounds. This layer consists of degenerative cells mixed with tiny bubbles and covers the injured area. This unique adaptation might help protect the wound from seawater and other environmental factors. While there have been studies on how surface wounds heal in captive dolphins and whales, there’s still much to learn about how these animals heal large, deep wounds. Understanding how wounds heal can help us to more accurately assess the frequency at which whales are wounded, whether it be from fishing gear or boats, to cookie cutter sharks or killer whales.

It seems like a lot, and it is, but our ultimate goal is to assess the effects that scarring and skin conditions can have in the ecology of marine megafauna. Assessing the individual gray whales in the photos can provide a bigger picture of the health of a whole population. We can also look for any patterns of skin conditions between mother and calf, individuals that are around each other often, adults and juveniles, or males and females. Scars may also play a role in a population’s health. If a gray whale had an open wound previously, did it develop into a skin condition? Did a skin condition worsen? Did it leave them more vulnerable to predators? These are the questions we would like to elaborate on with this research. A great read on this topic was conducted by Dawn R. Barlow, Acacia L. Pepper and Leigh G. Torres, which will be in the references below (Barlow et al., 2019). A better understanding of potential patterns is a better assessment of our current marine management practices. Is it enough, or do we need to change and do more?

Okay, lastly, let’s talk about artificial intelligence (AI). Would using AI methods for this project make our lives easier? Yes. If we could train AI to accurately identify specific scars and skin conditions, our 100,000 photos could be done within minutes. For my job security, woo no AI! But on a serious note, this approach could free up time that could be spent on other efforts, or speed up the process of assessing marine management. However, we gain so much by reviewing the photos ourselves which is still important to do when training AI on what specifics to search for. Over the summer, I’m going to get to know different whales and see how they may change over 8 years, just by their pictures. My excitement grew as soon as I looked at my first 3 gray whales and learned their names. It’s forever important to remember that we can always learn from sharing connections with the organisms we study and interact with. We share the same planet and we have to work together to preserve it. I thank you all for taking a trip through our summer research with me and I hope to meet some of you around Hatfield!

References

Barlow, D. R., Pepper, A. L., & Torres, L. G. (2019a). Skin deep: An assessment of New Zealand blue whale skin condition. Frontiers in Marine Science, 6. https://doi.org/10.3389/fmars.2019.00757 

Bradford, A. L., Weller, D. W., Ivashchenko, Y. V., Burdin, A. M., & Brownell, Jr, R. L. (2009). Anthropogenic scarring of Western Gray Whales (Eschrichtius robustus). Marine Mammal Science, 25(1), 161–175. https://doi.org/10.1111/j.1748-7692.2008.00253.x 

Corsi, E., Calambokidis, J., Flynn, K. R., & Steiger, G. H. (2021). Killer whale predatory scarring on Mysticetes: A comparison of rake marks among blue, humpback, and gray whales in the eastern North Pacific. Marine Mammal Science, 38(1), 223–234. https://doi.org/10.1111/mms.12863 

NOAA. (2020, April 4). Fisheries of the United States. https://www.fisheries.noaa.gov/national/sustainable-fisheries/fisheries-united-states

Hamilton, P. K., & Marx, M. K. (2005). Skin lesions on North Atlantic right whales: Categories, prevalence and change in occurrence in the 1990s. Diseases of Aquatic Organisms, 68, 71–82. https://doi.org/10.3354/dao068071 

Pettis, H. M., Rolland, R. M., Hamilton, P. K., Brault, S., Knowlton, A. R., & Kraus, S. D. (2004). Visual health assessment of north atlantic right whales (Eubalaena glacialis) using photographs. Canadian Journal of Zoology, 82(1), 8–19. https://doi.org/10.1139/z03-207 

Silber, G. K., Weller, D. W., Reeves, R. R., Adams, J. D., & Moore, T. J. (2021). Co-occurrence of gray whales and vessel traffic in the North Pacific Ocean. Endangered Species Research, 44, 177–201. https://doi.org/10.3354/esr01093 Sun, L., Engle, C., Kumar, G., & van Senten, J. (2022). Retail market trends for Seafood in the United States. Journal of the World Aquaculture Society, 54(3), 603–624. https://doi.org/10.1111/jwas.12919

A Journey From Microbiology to Macrobiology

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

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

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

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

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

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

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

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

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

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References:

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

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

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

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

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

Following Tracks: A Summer of Research in Quantitative Ecology

**GUEST POST** written by Irina Tolkova from the University of Washington.

R, a programming language and software for statistical analysis, gives me an error message.

I mull it over. Revise my code. Run it again.

Hey, look! Two error messages.

…

I’m Irina, and I’m working on summer research in quantitative ecology with Dr. Leigh Torres in the GEMM Lab. Ironically, as much as I’m interested in the environment and the life inhabiting it, my background is actually in applied math, and a bit in computer science.

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(Also, my background is the sand dunes of Florence, OR, which are downright amazing.)

When I mention this in the context of marine research, I usually get a surprised look. But from firsthand experience, the mindsets and skills developed in those areas can actually be very useful for ecology. This is partly because both math and computer science develop a problem-solving approach that can apply to many interdisciplinary contexts, and partly because ecology itself is becoming increasingly influenced by technology.

Personally, I’m fascinated by the advancement in environmentally-oriented sensors and trackers, and admire the inventors’ cleverness in the way they extract useful information. I’ve heard about projects with unmanned ocean gliders that fly through the water, taking conductivity, temperature, depth measurements (Seaglider project by APL at the University of Washington), which can be used for oceanographic mapping. Arrays of hydrophones along the coast detect and recognize marine mammals through bioacoustics (OSU Animal Bioacoustics Lab), allowing for analysis of their population distributions and potentially movement. In the GEMM lab, I learned about light and small GPS loggers, which can be put on wildlife to learn about their movement, and even smaller lighter ones that determine the animal’s general position using the time of sunset and sunrise. Finally, scientists even made artificial nest mounds which hid a scale for recording the weight of breeding birds — looking at the data, I could see a distinctive sawtooth pattern, since the birds lost weight as they incubated the egg, and gained weight after coming home from a foraging trip…

On the whole, I’m really hopeful for the ecological opportunities opened up by technology. But the information coming in from sensors can be both a blessing and a curse, because — unlike manually collected data — the sample sizes tend to be massive. For statistical analysis, this is great! For actually working with the data… more difficult. For my project, this trade-off shows as R and Excel crash over the hundreds of thousands of points in my dataset… what dataset, you might ask? Albatross GPS tracking data.

In 2011, 2012, and 2013, a group of scientists (including Dr. Leigh!) tagged grey-headed albatrosses at Campbell Island, New Zealand, with small GPS loggers. This was done in the summer months, when the birds were breeding, so the GPS tracks represent the birds’ flights as they incubated and raised their chicks. A cool fact about albatrosses: they only raise one chick at a time! As a result, the survival of the population is very dependent on chick survival, which means that the health of the albatrosses during the breeding season, and in part their ability to find food, is critical for the population’s sustainability. So, my research question is: what environmental variables determine where these albatrosses choose to forage?

The project naturally breaks up into two main parts.

  • How can we quantify this “foraging effort” over a trajectory?
  • What is the statistical relationship between this “foraging effort metric” and environmental variables?

Luckily, R is pretty good for both data manipulation and statistical analysis, and that’s what I’m working on now. I’ve just about finished part (1), and will be moving on to part (2) in the coming week. For a start, here are some color-coded plots showing two different ways of measuring the “foraging value” over one GPS track:

track89518

Most of my time goes into writing code, and, of course, debugging. This might sound a bit dull, but the anticipation of new results, graphs, and questions is definitely worth it. Occasionally, that anticipation is met with a result or plot that I wasn’t quite expecting. For example, I was recently attempting to draw the predicted spatial distribution of an albatross population. I fixed some bugs. The code ran. A plot window opened up. And showed this:

pretty_circles

I stared at my laptop for a moment, closed it, and got some hot tea from the lab’s electronic kettle, all the while wondering how R came up with this abstract art.

All in all, while I spend most of my time programming, my motivation comes from the wildlife I hope to work for. And as any other ecologist, I love being out there on the Oregon coast, with the sun, the rain, sand, waves, valleys and mountains, cliff swallows and grey whales, and the rest of our fantastic wild outdoors.

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