Month: July 2020

Stories from a whale’s life: how whale photo-identification is an essential part of the whale physiology toolkit

By Alejandro Fernandez Ajo, PhD student at the Department of Biology, Northern Arizona University, Visiting scientist in the GEMM Lab working on the gray whale physiology and ecology project  

Two years ago, in August 2018, I came to Newport and visited the Hatfield Marine Science Center for the first time with an NSF/RCN-founded laboratory exchange with the GEMM Lab and met Dr. Leigh Torres. My goals during this exchange where to learn about non-invasive fieldwork techniques for studying free-range whales while interacting, exchanging ideas, and networking with the GEMM Lab members; also, to discuss some projects and thoughts for future collaborations with Dr. Torres. During those two weeks in Newport, I had the opportunity to help with field work on the project “Evaluation of gray whale ecology and physiology in response to variable ambient ocean noise conditions”, which aims to evaluate the hormonal variability and health of the gray whales that forage along the Oregon coast in the context of multiple stressors. I would return during the summers of 2019 and 2020 as a visiting scientist and research assistant to work on this project. This year the experience has been a bit different in terms of interactions with the HMSC community due to COVID-19; however, we were able to successfully start the field season in time and now we are wrapping up our second month of surveys with many new and interesting data gathered, and many new, unforgettable memories to be treasured. Working with these animals is incredibly fascinating because there are so many things we don´t know about them, and the questions can become both overwhelming and exciting.

An essential part of this project, and arguably any research project done with cetaceans, is the identification of individuals. Hence, considerable effort is expended each year attempting to photograph every gray whale possible within our study region and to identify each whale we encounter. The GEMM Lab maintains a catalog of the gray whales that visit the Oregon coast, a sub-population known as the Pacific Coast Feeding Group (PCFG). This catalog currently consists of 173 individuals. which we frequently compare with a larger catalog of gray whales that includes 2060 individuals observed since 1977 (Cascadia Research Collective). These methods allow us to know who is who among the whales we encounter each day at sea.

The different species of cetaceans can be individually identified by markings on their bodies, very much like fingerprints in humans. Some features on these animals are unique and conserved through life. For example, Southern and Northern right whales are identified by the callosity patters in their heads (Picture 1), while humpback whales are mostly identified individually by the shape and the patterns of black and white pigmentation on the underside of their fluke (Picture 2). Gray whales have very mottled skin coloration, so we use a combination of markings and features to identify individuals: pigmentation patterns, scars, shape and pigmentation of their fluke, and sometimes the shape of their knuckles, which are a series of “humps” that gray whales have instead of a dorsal fin on their back. It might sound very difficult to do, and it can be a tedious task, however as you train your eye it becomes easier, and features that at first seemed undistinguishable become recognizable and unique (Picture 3). As a reward, it is such a joy to find a match and recognize old friends when they arrive from their long journeys in the vast ocean each year to the Oregon coast.

The callosity pattern of a southern right whale. Photo by Alejandro Fernández Ajó – Instituto de Conservación de Ballenas.
Three different humpback whales with notably different pigmentation patterns on their flukes. Photographs captured under NOAA/NMFS permit #21678.
The gray whale “Knife” we have observed frequently this summer off the Oregon coast. Can you see how the right pigmentation pattern identified looks like a knife? Photograph captured under NOAA/NMFS permit #21678.

As a result of our photo-identification efforts and the high site-fidelity of the whales we study, the large majority of the gray whales we observe here in Oregon are known individually. For many whales, we also have detailed sightings records that can span years and decades, that document calving history, lactation, appearance of scars indicative of injury or entanglement, minimum age, sex, habitat-use patterns, behaviors, etc. Holding such detailed information of individual whales provides incredible contributions to our understanding of the basic patterns in life history of whales, such as reproduction rates, calving intervals, age of first reproduction, etc. Moreover, when these life history events are linked with physiological sample collection large steps can be made in the development and validation of physiological methods. Many endocrine assays currently in use for whales are based on non-traditional sample types including feces, respiratory vapor, and baleen, which have been validated using the catalogs of well-known individuals to verify that measured hormones reflect patterns expected for various physiological states. For example, we can compare endocrine data of confirmed pregnant females, known mature males, and known-injured whales to learn how whale physiological responses are different during different life history events (e.g., Burgess et al. 2017, 2018, Corkeron et al. 2017, Hunt et al. 2006, 2016, 2018, Lysiak et al. 2018, Rolland et al. 2005).

Here in Oregon we are learning from the lives of the gray whales we study, and here I want to share with you two of their stories, one happy and one not-so-happy.

Let´s start with the not-so-happy story so we can end with some brighter news. On June 24 this year, we encountered a whale near Cape Foulweather, which is a very tricky area to work as there are many rocks and shallow water that make the sea conditions very choppy even with low swell. We started documenting the sighting as usual, taking pictures of the left side, the right side and ideally also the fluke of the whale. As we approached this whale, we started noting that something was wrong with its fluke. With the challenging sea conditions, it was not easy to approach the whale and the whale was not exposing its fluke when diving. When we put our drone up to collect photogrammetry and behavior data we gained a much better perspective. This whale has a bad injury on it fluke (Picture 4.C). On the boat we started making conjectures about the cause of this terrible injury that had basically amputate most of its left fluke lobe. Once back on shore, we sorted out the photos and compared the field images captured during the day with the photo-ID catalog and we made a match. This whale is known in our catalog as “ROLLER SKATE”, is a female, and was first sighted in 2015, so she is at least 5 years old today.

The story unfolded when we reviewed Roller Skate’s sighting history. Interestingly we observed this same whale in the same location last September 2019. Unfortunately, it was a very brief encounter but enough for photo documentation of the whale and an interesting observation. Here I quote the field notes that Dr. Torres wrote from this sighting: “September 6th, 2019. Sighting 9: Scattered whales feeding and/or traveling across area to north of Cape Foulweather. One whale had recently chopped fluke; tried to re-find to get better photos but could not (looking at photos now, this whale is clearly entangled in line!). Ceiling too low for UAS [drone flight].” (Picture 4.B).

Progressive photos of Roller Skate’s fluke. In 2017, her fluke was healthy (A). In 2019, we observed her fluke with a line entanglement and “chewed up” (B). In 2020, we have observed the resulting wound and healing process (C). Photographs captured under NOAA/NMFS permit #21678.

Roller skate’s story is an example of how essential is to keep an ID catalog. After a close-up examination of the 2019 picture, we can clearly see a rope entanglement (Picture 4.B). Photos from previous years show how beautiful and healthy her fluke was before this event (Picture 4.A). This event is heart breaking to witness, but this whale could be considered lucky because she was able to shed the gear and survive this entanglement, at least in the short term. Additionally, we can learn from Roller Skate’s misfortune to help us understand what the consequences of such an injury (stressor) may be on the physiology of a whale. We have been eager to collect a fecal sample from Roller Skate to analyze how her hormone levels compare to non-injured whales. Fortunately, we got lucky a couple weeks ago and collected this sample, so now we need to get in the lab and analyze the samples. But more questions remain: Will this injury impact her ability to reproduce? If so, for how long? And at a larger scale, what are the population consequences of such events? If we can understand the magnitude of lethal and sublethal human caused impacts on individual whales and their populations from events such as entanglements, we can develop better methods to mitigate and limit such hazards for whales in their environments.

As I promised, there is also some good news to share. A very well-known PCFG whale, almost a celebrity I dear to say, is “Scarback”, or as we like to call her “Scarlett”. Scarlett is a female known since 1996, making her at least 24 years old, and she also has a very bad injury of unknown origin. Scarlett has a terrible scar on her back that is theorized to have been caused by an explosive harpoon, or maybe a bad ship-strike (Picture 5), but we really do not know. However, we do know she survived this injury and this year she brought a new calf into the population (Picture 6). This is the second calf we have documented from Scarlett, with her previous calf sighted during the 2016 field season and we call it “Brown”. Scarlett is an example of how resilient these amazing giants can be; however, it is likely that while she was recovering from this injury, she was unable to reproduce. How many calves from Scarlett did the PCFG population “lose” due to such a tragedy? We can´t know, but we are learning, and her story will also help us understand whale physiology as we will analyze her fecal hormones and body condition during pregnancy, lactation, and resting phases.

The scar on Scarlett’s back. This significant wound has an unknown origin. Photograph captured under NOAA/NMFS permit #21678.

Scarlett is a survivor. We need to recognize that we are sharing the ocean with different forms of life. We need to acknowledge their existence and understand how our use of the oceans is affecting them, and, more importantly, work toward improving their conditions. I hope that with our research we highlight and communicate how amazing are these animals, and how important are they for marine ecosystems. And ultimately, I hope our work helps minimize the impacts that affect other forms of ocean life that coexist with us, both above and below the surface.

The well-known gray whale “Scarlett” surfaces under her calf while it checks out the GEMM Lab field team. Photo by Alejandro Fernandez Ajo taken under NOAA/NMFS permit #21678.

References:

Burgess, E., Hunt, K. E., Kraus, S. D. and Rolland, R. M. (2016). Get the most out of blow hormones: validation of sampling materials, field storage and extraction techniques for whale respiratory vapor samples. Conservation Physiology, 4, cow024.

Burgess, E. A., Hunt, K. E., Kraus, S. D. and Rolland, R. M. (2018). Quantifying hormones in exhaled breath for physiological assessment of large whales at sea. Scientific Reports, 8, 10031.

Corkeron, P. J., Rolland, R. M., Hunt, K. E. and Kraus, S. D. (2017). A right whale PooTree: Fecal hormones and classification trees identify reproductive states in North Atlantic right whales (Eubalaena glacialis). Conservation Physiology, 5, cox006. DOI: 10.1093/conphys/cox006.

Hunt, K., Lysiak, N., Moore, M. and Rolland, R. (2017). Multi-year longitudinal profiles of cortisol and corticosterone recovered from baleen of North Atlantic right whales (Eubalaena glacialis). General and Comparative Endocrinology, 254, 50-59. DOI: 10.1016/j.ygcen.2017.09.009.

Hunt, K., Lysiak, N. S. J., Matthews, C. J. D., et al. (2018). Multi-year patterns in testosterone, cortisol and corticosterone in baleen from adult males of three whale species. Conservation Physiology, 6, coy049. DOI: 10.1093/conphys/coy049.

Hunt, K. E., Rolland, R. M., Kraus, S. D. and Wasser, S. K. (2006). Analysis of fecal glucocorticoids in the North Atlantic Right Whale (Eubalaena glacialis). General and Comparative Endocrinology, 148, 260-272.

Lysiak, N., Trumble, S., Knowlton, A. and Moore, M. (2018). Characterizing the duration and severity of fishing gear entanglement on a North Atlantic right whale (Eubalaena glacialis) using stable isotopes, steroid and thyroid hormones in baleen. Frontiers in Marine Science. DOI: 10.3389/fmars.2018.00168.

Rolland, R. M., Hunt, K. E., Kraus, S. D. and Wasser, S. K. (2005). Assessing reproductive status of right whales (Eubalaena glacialis) using fecal hormone metabolites. General and Comparative Endocrinology, 142, 308-317.

Dolphin Diets: Common bottlenose dolphin prey preferences off California

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

Humans are fascinated by food. We want to know its source, its nutrient content, when it was harvested and by whom, and so much more. Since childhood, I was the nagging child who interrogated wait staff about the seafood menu because I cared about the sustainability aspect as well as consuming ethically-sourced seafood. Decades later I still do the same: ask a myriad of questions from restaurants and stores in order to eat as sustainably as possible. But in addition to asking these questions about my food, I also question what my study species eats and why. My study populations, common bottlenose dolphins, are described as top opportunistic predators (Norris and Prescott 1961, Shane et al. 1986, Barros and Odell 1990). In my study area off of California, this species exists in two ecotypes. The coastal ecotype off of California, USA are generalist predators, feeding on many different species of fish using different foraging techniques (Ballance 1992, Shane 1990). The offshore ecotype, on the other hand, is less well-studied, but is frequently observed in association with sperm whales, although the reason is still unknown (Díaz-Gamboa et al. 2018). Stable isotope analysis from skin samples from the two ecotypes indicates that the ecotypes exhibit different foraging strategies based on different isotopic carbon and nitrogen levels (Díaz-Gamboa et al. 2018).

Growing up, I kept the Monterey Bay Aquarium’s Seafood Watch Guide with me to choose the most sustainably-sourced seafood at restaurants. Today there is an easy-to-use application for mobile phones that replaced the paper guide. (Image Source: https://www.seafoodwatch.org/)

Preliminary and historical data on common bottlenose dolphins (Tursiops truncatus) suggest that the coastal ecotype spend more time near estuary mouths than offshore dolphins (Ballance 1992, Kownacki et al. unpublished data). Estuaries contain large concentrations of nutrients from runoff, which support zooplankton and fishes. It is for this reason that these estuaries are thought to be hotspots for bottlenose dolphin foraging. Some scientists hypothesize that these dolphins are estuarine-based prey specialists (Barros and Odell 1990), or that the dolphins simply aggregate in estuaries due to higher prey abundance (Ballance 1992).

Coastal bottlenose dolphins traveling near an estuary mouth in San Diego, CA. (Photographed under NOAA NMFS Permit # 19091).

In an effort to understand diet compositions of bottlenose dolphins, during coastal surveys seabirds were recorded in association with feeding groups of dolphins. Therefore, it is reasonable to believe that dolphins were feeding on the same fishes as Brown pelicans, blue-footed and brown boobies, double-crested cormorants, and magnificent frigatebirds, seeing as they were the most common species associated with bottlenose dolphin feeding groups (Ballance 1992). A shore-based study by Hanson and Defran (1993) found that coastal dolphins fed more often in the early morning and late afternoon, as well as during periods of high tide current. These patterns may have to do with the temporal and spatial distribution of prey fish species. From the few diet studies conducted on these bottlenose dolphins in this area, 75% of the prey were species from the families Ebiotocidae (surf perches) and Sciaendae (croakers) (Norris and Prescott 1961, Walker 1981). These studies, in addition to optimal foraging models, suggest this coastal ecotype may not be as much of a generalist as originally suggested (Defran et al. 1999).

A redtail surfperch caught by a fisherman from a beach in San Diego, CA. These fish are thought to be common prey of coastal bottlenose dolphins. (Image Source: FishwithJD)

Diet studies on the offshore ecotype of bottlenose dolphins worldwide show a preference for cephalopods, similar to other toothed cetaceans who occupy similar regions, such as Risso’s dolphin, sperm whales, and pilot whales (Clarke 1986, Cockcroft and Ross 1990, Gonzalez et al. 1994, Barros et al. 2000, Walker et al. 1999). Because these animals seldom strand on accessible beaches, stomach contents analyses are limited to few studies and isotope analysis is more widely available from biopsies. We know these dolphins are sighted in deeper waters than the habitat of coastal dolphins where there are fewer nutrient plumes, so it is reasonable to hypothesize that the offshore ecotype consumes different species and may be more specialized than the coastal ecotype.

An bottlenose dolphin forages on an octopus. (Image source: Mandurah Cruises)

For a species that is so often observed from shore and boats, and is known for its charisma, it may be surprising that the diets of both the coastal and offshore bottlenose dolphins are still largely unknown. Such is the challenge of studying animals that live and feed underwater. I wish I could simply ask a dolphin, much like I would ask staff at restaurants: what is on the menu today? But, unfortunately, that is not possible. Instead, we must make educated hypotheses about the diets of both ecotypes based on necropsies and stable isotope studies, and behavioral and spatial surveys. And, I will continue to look to new technologies and creative thinking to provide the answers we are seeking.

Literature cited:

Ballance, L. T. (1992). Habitat use patterns and ranges of the bottlenose dolphin in the Gulf of California, Mexico. Marine Mammal Science, 8(3), 262-274.

Barros, N.B., and D. K. Odell. (1990). Food habits of bottlenose dolphins in the southeastern United States. Pages 309-328 in S. Leatherwood and R. R. Reeves, eds. The bottlenose dolphin. Academic Press, San Diego, CA.

Barros, N., E. Parsons and T. Jefferson. (2000). Prey of bottlenose dolphins from the South China Sea. Aquatic Mammals 26:2–6.

Clarke, M. 1986. Cephalopods in the diet of odontocetes. Pages 281–321 in M. Bryden and R. Harrison, eds. Research on dolphins. Clarendon Press, Oxford, NY.

Cockcroft, V., and G. Ross. (1990). Food and feeding of the Indian Ocean bottlenose dolphin off southern Natal, South Africa. Pages 295–308 in S. Leatherwood and R. R. Reeves, eds. The bottlenose dolphin. Academic Press, San Diego, CA.

Defran, R. H., Weller, D. W., Kelly, D. L., & Espinosa, M. A. (1999). Range characteristics of Pacific coast bottlenose dolphins (Tursiops truncatus) in the Southern California Bight. Marine Mammal Science, 15(2), 381-393.

Díaz‐Gamboa, R. E., Gendron, D., & Busquets‐Vass, G. (2018). Isotopic niche width differentiation between common bottlenose dolphin ecotypes and sperm whales in the Gulf of California. Marine Mammal Science, 34(2), 440-457.

Gonzalez, A., A. Lopez, A. Guerra and A. Barreiro. (1994). Diets of marine mammals stranded on the northwestern Spanish Atlantic coast with special reference to Cephalopoda. Fisheries Research 21:179–191.

Hanson, M. T., and Defran, R. H. (1993). The behavior and feeding ecology of the Pacific coast bottlenose dolphin, Tursiops truncatus. Aquatic Mammals, 19, 127-127.

Norris, K. S., and J. H. Prescott. (1961). Observations on Pacific cetaceans of Californian and Mexican waters. University of California Publications of Zoology 63:29, 1-402.

Shane, S. H. (1990). Comparison of bottlenose dolphin behavior in Texas and Florida, with a critique of methods for studying dolphin behavior. Pages 541-558 in S. Leatherwood and R. R. Reeves, eds. The bottlenose dolphin. Academic Press, San Diego, CA.

Shane, S., R. Wells and B. Wursig. (1986). Ecology, behavior and social organization of bottlenose dolphin: A review. Marine Mammal Science 2:34–63.

Walker, W.A. (1981). Geographical variation in morphology and biology of the bottlenose dolphins (Tursiops) in the eastern North Pacific. NMFS/SWFC Administrative Report. No, LJ-91-03C.

Walker, J., C. Potter and S. Macko. (1999). The diets of modern and historic bottlenose dolphin populations reflected through stable isotopes. Marine Mammal Science 15:335–350.

The impact of science

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

What do I mean by impact? There are different ways to measure the impact of science and I bet that the readers of this blog had different ideas pop into their heads when they read the title. My guess is that most ideas were related to the impact factor (IF) of a journal, which acts as a measure of a journal’s impact within its discipline and allows journals to be compared. Recent GEMM Lab graduate and newly minted Dr. Leila Lemos wrote a blog about this topic and I suggest reading it for more detail. In a nutshell though, the higher the IF, the more prestigious and impactful the journal. It is unsurprising that scientists found a way to measure our impact on the broader scientific community quantitatively.

However, IFs are not the impact I was referring to in my title. The impact I am talking about is arguably much harder to measure because you can’t easily put a number on it. I am talking about the impact we have on communities and individuals through outreach and engagement. The GEMM Lab’s Port Orford gray whale ecology project, which I lead, is going into its 6th consecutive year of summer field work this year. Outreach and engagement are two core components of the project that I have become very invested in since I started in 2018. And so, since we are only one week away from the field season commencing (yes, somehow it’s mid-July already…), for this week’s blog I have decided to reflect on what scientific outreach and engagement is, how we have tried to do both in Port Orford, and some of the associated highs and lows.

2018 team member Dylan presenting at the Port Orford community presentation. Source: T. Calvanese.

I think almost everyone in the scientific community would agree that outreach and engagement are important and that we should strive to interact frequently with the public to be transparent and build public trust, as well as to enable mutual learning. However, in my opinion, most scientists rarely put in the work needed to actually reach out to, and engage with, the community. Outreach and engagement have become buzzwords that are often thrown around, and with some hand-waving, can create the illusion that scientists are doing solid outreach and engagement work. For some, the words are probably even used interchangeably, which isn’t correct as they mean two different things.

Outreach and engagement should be thought of as occurring on two different ends of a spectrum. Outreach occurs in a one-way direction. Examples of outreach are public seminars delivered by a scientist (like Hatfield’s monthly Science on Tap) or fairs where the public is invited to come and talk to different scientific entities at their respective booths (like Hatfield’s annual Marine Science Day). Outreach is a way for scientists to disseminate their research to the public and often do not warrant the umbrella term engagement, as these “conversations” are not two-way. Engagement is collaborative and refers to intentional interactions where both sides (public and scientist) share and receive. It goes beyond a scientist telling the public about what they have been doing, but also requires the scientist to listen, absorb, and implement what the views from the ‘other side’ are.

2015 team tracking a whale on Graveyard Point above the port of Port Orford. Source: F. Sullivan.

Now that I have (hopefully) clarified the distinction between the two terms, I am going to shift the focus to specifically talk about the Port Orford project. Before I do, I would like to emphasize that I do not think our outreach and engagement is the be-all and end-all. There is definitely room for improvement and growth, but I do believe that we actively work hard to do both and to center these aspects within the project, rather than doing it as an afterthought to tick a box. 

In talking about outreach and engagement, I have been using the words ‘public’ and ‘community’. I think these words conjure an image of a big group of people, an entire town, county, state or even nation. While this can be the case, it can also refer to smaller groups of people, even individuals. The outreach we conduct for the Port Orford project certainly occurs at the town-level. At the end of every field season, we give a community presentation where the field team and Leigh present new findings and give a recount of the field season. In the past, various teams have also given talks at the Humbug Mountain Campground and at Redfish Rocks Community Team events. These events, especially the community presentation, have been packed to the brim every year, which shows the community’s interest for the gray whales and our research. In fact, Tom Calvanese, the OSU Port Orford Field Station manager, has shared with me that now in early summer, Port Orford residents ask him when the ‘whale team’ is returning. I believe that our project has perhaps shifted the perception the local community has of scientists a little bit. Although in our first year or two of the project we may have been viewed as nosy outsiders, I feel that now we are almost honorary members within the community. 

A packed room at the 2017 Port Orford community presentation. Photo: GEMM Lab.

Our outreach is not just isolated to one or two public talks per field season though. We have been close collaborators with South Coast Tours (SCT), an adventure tour company headed by Dave Lacey, since the start of the project. During the summer, SCT has almost daily kayak and fishing tours (this year, boat tours too!) out of Port Orford. The paddle routes of SCT and our kayak team will typically intersect in Tichenor’s Cove around mid-morning. When this happens, we form a little kayak fleet with the tour and research kayaks and our kayak team gives a short, informal talk about our research. We often pass around samples of zooplankton we just collected and answer questions that many of the paddlers have. These casual interactions are a highlight to the guests on SCT’s tours (Dave’s words, not mine) and they also provide an opportunity for the project’s interns to practice their science communication skills in a ‘low-stakes’ setting. 

The nature of our engagement is more at the individual-level. Since the project’s conception in 2015, the team has been composed of some combination  of 4-5 students, be it high school, undergraduate or graduate students. Aside from Florence Sullivan and myself as the GEMM Lab graduate student project leads, in total, we have had 16 students participate in the program, of which 4 were high school students (two from Port Orford’s Pacific High School and two from Astoria High School), 11 OSU and Lawrence University undergraduates, and 1 Duke University graduate student. This year we will be adding 3 more to the total tally (1 Pacific High School student, 1 OSU undergrad, and 1 graduate student from the Vrije Universiteit Brussel in Belgium). I am the first to admit that our yearly (and total) numbers of ‘impacted’ students is small. Limitations of funding and also general logistics of coordinating a large group of interns to participate in field work prevent us from having a larger cohort participate in the field season every summer. However, the impact on each of these students is huge. 

The 2019 team with Dave Lacey who instructed our kayak paddle & safety course. Photo: L. Hildebrand.

If I had to pick one word to describe the 6-week Port Orford field season, it would be ‘intense’. The word is perfect because it can simultaneously describe something positive and negative, and the Port Orford field season definitely has elements of both. Both as a team and as individuals we experience incredible high points (an example being last year when we saw Port Orford’s favorite whale ‘Buttons’ breach multiple times on several different days), but we also have pretty low points (I’m thinking of a day in 2018 when two of my interns tried incredibly hard to get our GoPro stick dislodged from a rocky crevice for over 1-hour before radioing me to tell me they couldn’t retrieve it). These highs and lows occur on top of the team’s slowly depleting levels of energy as the field season goes on; with every day we get up at 5:30 am and we get a little more exhausted. The work requires a lot of brain power, a lot of muscle, and a lot of teamwork. Like I said, it’s intense and that’s coming from someone who had several years of marine mammal field work experience before running this project for the first time in 2018. The majority of the interns who have participated in our project have had no marine mammal field experience, some have had no field experience at all. It’s double, if not triple, intense for the interns!

I ask a lot of my interns. I am aware of that. It has been a steep learning curve for me since I took on the project in 2018. I’ve had to adjust my expectations and remember not to measure the performance of my interns against my own. I can always give 110% during the field season, even when I’m exhausted, because the stakes are high for me. After all, the data that is being collected feeds straight into my thesis. However, it took me a while to realize that the stakes, and therefore the motivation, aren’t the same for my interns as they are for me. And so, expecting them to perform at the same level I am, is unfair. I believe I have grown a lot since running that first field season. I have taken the feedback from interns to heart and tried to make adjustments accordingly. While those adjustments were hard because it ultimately meant making compromises that affected the amount of data collected, I recognize and respect the need to make those adjustments. I am incredibly grateful to all of the interns, including the ones that participated before my leadership of the project,  who really gave it their all to collect the data that I now get to dig into and draw conclusions from.

2016 interns Kelli and Catherine paddling to a kayak sampling station. Photo: F. Sullivan.

But, as I said before, engagement is not one-sided, and I am not the only one who benefits from having interns participate in the project. The interns themselves learn a wealth of skills that are valuable for the future. Some of these skills are very STEM (Science, Technology, Engineering & Mathematics) specific (e.g. identifying zooplankton with a microscope, tracking whales with a theodolite), but a lot of them are transferrable to non-STEM futures (e.g. attention to detail and concentration required for identifying zooplankton, team work, effective communication). Our reach may be small with this project but the impact that participating in our internship has on each intern is a big one. Three of our four high school interns have gone on to start college. One plans to major in Marine Studies (in part a result of participating in this internship) while another decided to go to college to study Biology because of this internship. Several of the undergraduate students that participated in the 2015, 2016, 2017 & 2018 field seasons have gone on to start Master’s degrees at graduate schools around the country (3 of which have already graduated from their programs). A 2015 intern now teaches middle school in Washington and a 2016 intern is working with Oceans Initiative on their southern resident killer whale project this summer. Leigh, Florence and I have written many letters of recommendations for our interns, and these letters were not written out of duty, but out of conviction.

I love working closely with students and watching them grow. For the last two years, my proudest moment has always been watching my interns present our research at the annual community presentation we give at the end of the field season in Port Orford. No matter the amount of lows and struggles I experienced throughout the season, I watch my interns and my face almost hurts because of the huge smile on my face. The interns truly undergo a transformation where at the start of the season they are shy or feel inadequate and awkward when talking to the public about gray whales and the methods we employ to study them. But on that final day, there is so much confidence and eloquence with which the interns talk about their internship, that they are oftentimes even comfortable enough to crack jokes and share personal stories with the audience. As I said before, engagement of this nature is hard to measure and put a number on. Our statistic (engaging with 16 students) makes it sound like a small impact, but when you dig into what these engagements have meant for each student, the impact is enormous.

All of the past PO gray whale ecology teams, from left to right: 2015 (Sarah, Florence, Cricket, Justin), 2016 (Florence, Kelli, Catherine, Cathryn), 2017 (Nathan, Quince, Florence, Morgan), 2018 (Haley, Robyn, Hayleigh, Dylan, Lisa), and 2019 (Anthony, Donovan, Lisa, Mia). Bottom left: Florence and Leigh; bottom right: Lisa and Leigh.

I treasure my 6 weeks in Port Orford. Even though they are intense and there are new challenges every year, they bring me a lot of happiness. And it’s only in part because I get to see gray whales and kayak on an (almost) daily basis. A large part is because of the bonds I have formed and continue to cultivate with Port Orford locals, the leaps and bounds I know the interns will make, and the fact that the gray whales, completely unknowingly, bring together a small group of students and a community every year. 

If you feel like taking a trip down memory lane, below are the links of the blogs written by previous PO interns:

2015: Cricket, Justin, Sarah

2016: Catherine, Kelli, Cathryn

2017: Morgan, Nathan, Quince

2018: Haley, Dylan, Hayleigh, Robyn

2019: Mia, Donovan, Anthony

Inference, and the intersection of ecology and statistics

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

Recently, I had the opportunity to attend the International Statistical Ecology Conference (ISEC), a biennial meeting of researchers at the interface of ecology and statistics. I am a marine ecologist, fascinated by the interactions between animals and the dynamic ocean environment they inhabit. If you had asked me five years ago whether I thought I would ever consider myself a statistician or a computer programmer, my answer would certainly have been “no”. Now, I find myself studying the ecology of blue whales in New Zealand using a variety of data streams and methodologies, but a central theme for my dissertation is species distribution modeling. Species distribution models (SDMs) are mathematical algorithms that correlate observations of a species with environmental conditions at their observed locations to gain ecological insight and predict spatial distributions of the species (Fig. 1; Elith and Leathwick 2009). I still can’t say I would identify as a statistician, but I have a growing appreciation for the role of statistics to gain inference in ecology.

Figure 1. A schematic of a species distribution model (SDM) illustrating how the relationship between mapped species and environmental data (left) is compared to describe “environmental space” (center), and then map predictions from a model using only environmental predictors (right). Note that inter-site distances in geographic space might be quite different from those in environmental space—a and c are close geographically, but not environmentally. The patterning in the predictions reflects the spatial autocorrelation of the environmental predictors. Figure reproduced from Elith and Leathwick (2009).

Before I continue, let’s take a look at just a few definitions from Merriam-Webster’s dictionary:

Statistics: a branch of mathematics dealing with the collection, analysis, interpretation, and presentation of masses of numerical data

Ecology: a branch of science concerned with the interrelationship of organisms and their environments

Inference: a conclusion or opinion that is formed because of known facts or evidence

Ecological data are notoriously noisy, messy, and complex. Statistical tests are meant to help us understand whether a pattern in the data is different from what we would expect through random chance. When we study how organisms interact with one another and their environment, it is impossible to completely capture all elements of the ecosystem. Therefore, ecology is a field ripe with challenges for statisticians. How do we quantify a meaningful biological signal amidst all the noise? How can we gain inference from ecological data to enhance knowledge, and how can we use that knowledge to make informed predictions? Marine mammals are notoriously difficult to study. They inhabit an environment that is relatively inaccessible and inhospitable to humans, they occur in low numbers, they are highly mobile, and they are rarely visible. All ecological data are difficult and noisy and riddled with small sample sizes, but counting trees presents fewer logistical challenges than counting moving whales in an ever-changing open-ocean setting. Therefore, new methodologies in areas like species distribution modeling are often developed using large, terrestrial datasets and eventually migrate to applications in the marine environment (Robinson et al. 2011).

Many presentations I attended at the conference were geared toward moving beyond correlative SDMs. SDMs were developed to correlate species occurrence patterns with features of the environment they inhabit (e.g. temperature, precipitation, terrain, etc.). However, those relationships do not actually explain the underlying mechanism of why a species is more likely to occur in one environment compared to another. Therefore, ecological statisticians are now using additional information and modeling approaches within SDMs to incorporate information such as species co-occurrence patterns, population demographic information, and physiological constraints. Building SDMs to include such process-explicit information allows us to make steps toward understanding not just when and where a species occurs, but why.

Machine learning is an area that continues to advance and open doors to new applications in ecology. Machine learning approaches differ fundamentally from classical statistics. In statistics, we formulate a hypothesis, select the appropriate model to test that hypothesis (for example, linear regression), then test how well the data fit the model (“Is the relationship linear?”), and test the strength of that inference (“Is the linear pattern different from what we would expect due to random chance?”). Machine learning, on the other hand, does not use a predetermined notion of relationships between variables. Rather, it tries to create an algorithm that fits the patterns in the data. Statistics asks how well the data fit a model, and machine learning asks how well a model fits the data.

Machine learning approaches allow for very complex relationships to be included in models and can be excellent for making predictions. However, sometimes the relationships fitted by a machine learning algorithm are so complex that it is not possible to infer any ecological meaning from them. As one ISEC presenter put it, in machine learning “the computer learns but the scientist does not”. The most important thing when selecting your methodology is to remember your question and your goal. Do you want to understand the mechanism of why an animal is where it is? Or do you not need to understand the driver, but rather want to make the best predictions of where an animal will be? In my case, the answer to that question differs from one of my PhD chapters to the next. We want to understand the functional relationships between oceanography, krill availability, and blue whale distribution (Barlow et al. 2020), and subsequently we want to develop forecasting models that can reliably predict blue whale distribution to inform conservation efforts (Fig. 2).

Figure 2. An example predictive map of where we expect blue whales to be distributed based on environmental conditions. Warmer colors represent areas with a higher probability of blue whale occurrence, and the blue crosses represent locations where blue whales were observed.

ISEC was an excellent opportunity for me to break out of my usual marine mammal-centered bubble and get a taste of what is happening on the leading edge of statistical ecology. I learned about the latest approaches and innovations in species distribution modeling, and in the process I also learned about trees, koalas, birds, and many other organisms from around the world. A fun bonus of attending a methods-focused conference is learning about completely new study species and systems. There are many ways of approaching an ecological question, gaining inference, and making predictions. I look forward to incorporating the knowledge I gained through ISEC into my own research, both in my doctoral work and in applications of new methods to future research projects.

Figure 3. The virtual conference photo of all who attended the biennial International Statistical Ecology Conference. Thank you to the organizers, who made it a truly excellent and engaging conference experience!

References

Barlow, D.R., Bernard, K.S., Escobar-Flores, P., Palacios, D.M., and Torres, L.G. 2020. Links in the trophic chain: Modeling functional relationships between in situ oceanography, krill, and blue whale distribution under different oceanographic regimes. Mar. Ecol. Prog. Ser. doi:https://doi.org/10.3354/meps13339.

Elith, J., and Leathwick, J.R. 2009. Species Distribution Models: Ecological Explanation and Prediction Across Space and Time. Annu. Rev. Ecol. Evol. Syst. 40(1): 677–697. doi:10.1146/annurev.ecolsys.110308.120159.

Robinson, L.M., Elith, J., Hobday, A.J., Pearson, R.G., Kendall, B.E., Possingham, H.P., and Richardson, A.J. 2011. Pushing the limits in marine species distribution modelling: Lessons from the land present challenges and opportunities. doi:10.1111/j.1466-8238.2010.00636.x.