Clara and I have just returned from ten fruitful days at sea aboard NOAA Ship Bell M. Shimada as part of the Northern California Current (NCC) ecosystem survey. We surveyed between Crescent City, California and La Push, Washington, collecting data on oceanography, phytoplankton, zooplankton, and marine mammals (Fig. 1). This year represents the third year I have participated in these NCC cruises, which I have come to cherish. I have become increasingly confident in my marine mammal observation and species identification skills, and I have become more accepting of the things out of my control – the weather, the sea state, the many sightings of “unidentified whale species”. Careful planning and preparation are critical, and yet out at sea we are ultimately at the whim of the powerful Pacific Ocean. Another aspect of the NCC cruises that I treasure is the time spent with members of the science team from other disciplines. The chatter about water column features, musings about plankton species composition, and discussions about what drives marine mammal distribution present lively learning opportunities throughout the cruise. Our concurrent data collection efforts and ongoing conversations allow us to piece together a comprehensive picture of this dynamic NCC ecosystem, and foster a collaborative research environment.
Every time I head to sea, I am reminded of the patchy distribution of resources in the vast and dynamic marine environment. On this recent cruise we documented a stark contrast between expansive stretches of warm, blue, stratified, and seemingly empty ocean and areas that were plankton-rich and supported multi-species feeding frenzies that had marine mammal observers like me scrambling to keep track of everything. This year, we were greeted by dozens of blue and humpback whales in the productive waters off Newport, Oregon. Off Crescent City, California, the water was very warm, the plankton community was dominated by gelatinous species like pyrosomes, salps, and other jellies, and the marine mammals were virtually absent except for a few groups of common dolphins. To the north, the plume of water flowing from the Columbia River created a front between water masses, where we found ourselves in the midst of pacific white-sided dolphins, northern right whale dolphins, and humpback whales. These observations highlight the strength of ecosystem-scale and multi-disciplinary data collection efforts such as the NCC surveys. By drawing together information on physical oceanography, primary productivity, zooplankton community composition and abundance, and marine predator distribution, we can gain a nearly comprehensive picture of the dynamics within the NCC over a broad spatial scale.
This year, the marine mammals delivered and kept us observers busy. We lucked out with good survey conditions and observed many different species throughout the NCC (Table 1, Fig. 2).
Table 1. Summary of all marine mammal sightings from the NCC September 2020 cruise.
This year’s NCC cruise was unique. We went to sea as a global pandemic, wildfires, and political tensions continue to strain this country and our communities. This cruise was the first NOAA Fisheries cruise to set sail since the start of the pandemic. Our team of scientists and the ship’s crew went to great lengths to make it possible, including a seven-day shelter-in-place period and COVID-19 tests prior to cruise departure. As a result of these extra challenges and preparations, I think we were all especially grateful to be on the water, collecting data. At-sea fieldwork is always challenging, but morale was up, spirits were high, and laughs were frequent despite smiles being concealed by our masks. I am grateful for the opportunity to participate in this ongoing valuable data collection effort, and to be part of this team. Thanks to all who made it such a memorable cruise.
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.
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).
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.
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.
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.
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.
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).
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.
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.
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
Whales are among the most amazing and enigmatic animals in the world. Whales are not only fascinating, they are also biologically special. Due to their key ecological role and unique biological traits (i.e., their large body size, long lifespans, and sizable home ranges), whales are extremely important in helping sustain the entire marine ecosystem.
Working towards the conservation of marine megafauna, and large charismatic animals in general, is often seen as a mere benevolent effort that conservationist groups, individuals, and governments do on behalf of the individual species. However, mounting evidence demonstrates that restoring populations of marine megafauna, including large whales, can help buffer marine ecosystems from destabilizing stresses like human driven CO2 emissions and global change due to their ability to sequester carbon in their bodies (Pershing et al. 2010). Furthermore, whales can enhance primary production in the ocean through their high consumption and defecation rates, which ultimately provides nutrients to the ecosystem and improves fishery yields (Roman-McCarthy, 2010; Morissette et al. 2012).
Relationships between humans and whales have a long history, however, these relationships have changed. For centuries, whales were valued in terms of the number of oil barrels they could yield, and the quality of their baleen and meat. In the North Atlantic, whaling started as early as 1000 AD with “shore whaling” of North Atlantic right whales by Basque whalers. This whaling was initially limited to the mother and calve pairs that were easy to target due to their coastal habits and the fact that calves are more vulnerable and slower (Reeves-Smith, 2006). Once the calving populations of near-shore waters off Europe were depleted, offshore whaling began developing. Whalers of multiple nations (including USA, British, French, Norwegian, Portuguese, and Dutch, among others), targeted whales around the world, mainly impacting the gray whale populations, and all three right whale species along with the related bowhead whale. Later, throughout the phase of modern whaling using industrialized methods, the main target species consisted of the blue, fin, humpback, minke, sei and sperm whale (Schneider- Pearce, 2004).
By the early twentieth century, many of the world´s whale populations where reduced to a small fraction of their historical numbers, and although pre-whaling abundance of whale stocks is a subject of debate, recent studies estimate that at least the 66%, and perhaps as high as 90% for some whale species and populations (Branch-Williams 2006; Christensen, 2006), where taken during this period. This systematic and serial depletion of whale papulations reduced the biomass and abundance of great whales around the world, which has likely altered the structure and function of the oceans (Balance et al. 2006; Roman et al. 2014; Croll, et al. 2006).
After centuries of unregulated whale hunting, commercial whaling was banned in the mid-twentieth century. This ban was the result of multiple factors including reduced whale stocks below the point where commercial whaling would be profitable, and a fortunate shift in public perception of whales and the emergence of conservation initiatives (Schneider- Pearce, 2004). Since this moratorium on whaling, several whale populations have recovered around the world, and some populations that were listed as endangered have been delisted (i.e., the Eastern North Pacific gray whale) and some populations are estimated to have re-bounced to their pre-whaling abundance.
Although, the recovery of some populations has motivate some communities or nations to obtain or extend their whaling quotas (see Blog Post by Lisa Hildebrand), it is important to acknowledge that the management of whale populations is arguably one of the most complicated tasks, and is distinguished from management of normal fisheries due to various biological aspects. Whales are long living mammals with slow reproduction rates, and on average a whale can only produce a calf every two or three years. Hence, the gross addition to the stock rarely would exceed 25% of the number of adults (Schneider- Pearce, 2004), which is a much lower recovery rate that any fish stock. Also, whales usually reach their age of sexual maturity at 6-10 years old, and for many species there are several uncertainties about their biology and natural history that make estimations of population abundance and growth rate even harder to estimate.
Moreover, while today´s whales are generally not killed directly by hunting, they are exposed to a variety of other increasing human stressors (e.g., entanglement in fishing gear, vessel strikes, shipping noise, and climate change). Thus, scientists must develop novel tools to overcome the challenges of studying whales and distinguish the relative importance of the different impacts to help guide conservation actions that improve the recovery and restoration of whale stocks (Hunt et al. in press). With the restoration of great whale populations, we can expect positive changes in the structure and function of the world’s oceans (Chami et al. 2019; Roman et al. 2010).
So, why it is worth keeping whales healthy?
Whales facilitate the transfer of nutrients by (1) releasing nutrient-rich fecal plumes near the surface after they have feed at depth and (2) by moving nutrients from highly productive, polar and subpolar latitude feeding areas to the low latitude calving areas (Roman et al. 2010). In this way, whales help increase the productivity of phytoplankton that in turn support zooplankton production, and thus have a bottom up effect on the productivity of many species including fish, birds, and marine mammals, including whales. These fertilization events can also facilitate mitigation of the negative impacts of climate change. The amount of iron contained in the whales’ feces can be 10 million times greater than the level of iron in the marine environment, triggering important phytoplankton blooms, which in turn sequester thousands of tons of carbon from, and release oxygen to, the atmosphere annually (Roman et al. 2016; Smith et al. 2013; Willis, 2007). Furthermore, when whales die, their massive bodies fall to the seafloor, making them the largest and most nutritious source of food waste, which is capable of sustaining a succession of macro-fauna assemblages for several decades, including some invertebrate species that are endemic to whale carcasses (Smith et al. 2015).
Despite the several environmental services that whales provide, and the positive impact on local economies that depend on whale watching tourism, which has been valued in millions of dollars per year (Hoyt E., 2001), the return of whales and other marine mammals has often been implicated in declines in fish populations, resulting in conflicts with human fisheries (Lavigne, D.M. 2003). Yet there is insufficient direct evidence for such competition (Morissette et al. 2010). Indeed, there is evidence of the contrary: In ecosystem models where whale abundances are reduced, fish stocks show significant decreases, and in some cases the presence of whales in these models result in improved fishery yields. Consistent with these findings, several models have shown that alterations in marine ecosystems resulting from the removal of whales and other marine mammals do not lead to increases in human fishery yields (Morissette et al. 2010; 2012). Although the environmental services and benefits provided by great whales, which potentially includes the enhancement of fisheries yields, and enhancement on ocean oxygen production and capturing carbon, are evident and make a strong argument for improved whale conservation, it is overwhelming how little we know about many aspects of their lives, their biology, and particularly their physiology.
This lack of knowledge is because whales are really hard to study. For many years research was limited to the observation of the brief surfacing of the whales, yet most of their lives occurs beneath the surface and were completely unknown. Fortunately, new technologies and the creativity of whale researchers are helping us to better understand many aspects of their lives that were cryptic to us even a decade ago. I am committed to filling some of these knowledge gaps. My research examines how different environmental and anthropogenic impacts affect whale health, and particularly how these impacts may relate to cases of large whale mortalities and declines in whale populations. I am applying novel methods in conservation physiology for measuring hormone levels that promise to improve our understanding of the relationship between different (extrinsic and intrinsic) stressors and the physiological response of whales. Ultimately, this research will help address important conservation questions, such as the causes of unusual whale mortality events and declines in whale populations.
Ballance LT, Pitman RL, Hewitt R, et al. 2006. The removal of large whales from the Southern Ocean: evidence for long-term ecosystem effects. In: Estes JA, DeMaster DP, Doak DF, et al. (Eds). Whales, whaling and ocean ecosystems. Berkeley, CA: University of California Press.
Branch TA and Williams TM. 2006. Legacy of industrial whaling. In: Estes JA, DeMaster DP, Doak DF, et al. (Eds). Whales, whaling and ocean ecosystems. Berkeley, CA: University of California Press.
Chami, R. Cosimano, T. Fullenkamp, C. & Oztosun, S. (2019). Nature’s solution to climate change. Finance & Development, 56(4).
Christensen LB. 2006. Marine mammal populations: reconstructing historical abundances at the global scale. Vancouver, Canada: University of British Columbia.
Croll DA, Kudela R, Tershy BR (2006) Ecosystem impact of the decline of large whales in the North Pacific. In: Estes JA, DeMaster DP, Doak DF, Williams TM, BrownellJr RL, editors. Whales, Whaling, and Ocean Ecosystems. Berkeley: University of California Press. pp. 202–214.
Hoyt, E. 2001. Whale Watching 2001: Worldwide Tourism Numbers, Expenditures and Expanding Socioeconomic Benefits
Hunt, K.E., Fernández Ajó, A. Lowe, C. Burgess, E.A. Buck, C.L. In press. A tale of two whales: putting physiological tools to work for North Atlantic and southern right whales. In: “Conservation Physiology: Integrating Physiology Into Animal Conservation And Management”, ch. 12. Eds. Madliger CL, Franklin CE, Love OP, Cooke SJ. Oxford University press: Oxford, UK.
Lavigne, D.M. 2003. Marine mammals and fisheries: the role of science in the culling debate. In: Gales N, Hindell M, and Kirkwood R (Eds). Marine mammals: fisheries, tourism, and management issues. Melbourne, Australia: CSIRO.
Morissette L, Christensen V, and Pauly D. 2012. Marine mammal impacts in exploited ecosystems: would large scale culling benefit fisheries? PLoS ONE 7: e43966.
Morissette L, Kaschner K, and Gerber LR. 2010. “Whales eat fish”? Demystifying the myth in the Caribbean marine ecosystem. Fish Fish 11: 388–404.
Pershing AJ, Christensen LB, Record NR, Sherwood GD, Stetson PB (2010) The impact of whaling on the ocean carbon cycle: Why bigger was better. PLoS ONE 5(8): e12444.
Reeves, R. and Smith, T. (2006). A taxonomy of world whaling. In DeMaster, D. P., Doak, D. F., Williams, T. M., and Brownell Jr., R. L., eds. Whales, Whaling, and Ocean Ecosystems. University of California Press, Berkeley, CA.
Roman, J. Altman I, Dunphy-Daly MM, et al. 2013. The Marine Mammal Protection Act at 40: status, recovery, and future of US marine mammals. Ann NY Acad Sci; doi:10.1111/nyas.12040.
Roman, J. and McCarthy, J.J. 2010. The whale pump: marine mammals enhance primary productivity in a coastal basin. PLoS ONE. 5(10): e13255.
Roman, J. Estes, J.A. Morissette, L. Smith, C. Costa, D. McCarthy, J. Nation, J.B. Nicol, S. Pershing, A.and Smetacek, V. 2014. Whales as marine ecosystem engineers. Frontiers in Ecology and the Environment. 12(7). 377-385.
Roman, J. Nevins, J. Altabet, M. Koopman, H. and McCarthy, J. 2016. Endangered right whales enhance primary productivity in the Bay of Fundy. PLoS ONE. 11(6): e0156553.
Schneider, V. Pearce, D. What saved the whales? An economic analysis of 20th century whaling. Biodiversity and Conservation 13, 543–562 (2004). https://doi org.libproxy.nau.edu/10.1023/B:BIOC.0000009489.08502.1
Smith LV, McMinn A, Martin A, et al. 2013. Preliminary investigation into the stimulation of phyto- plankton photophysiology and growth by whale faeces. J Exp Mar Biol Ecol 446: 1–9.
Smith, C.R. Glover, A.G. Treude, T. Higgs, N.D. and Amon, D.J. 2015. Whale-fall ecosystems: Recent insights into ecology, paleoecology, and evolution. Annu. Rev. Marine. Sci. 7:571-596.
Willis, J. 2007. Could whales have maintained a high abundance of krill? Evol Ecol Res 9: 651–662.
Leigh Torres, Assistant Professor,PI of the GEMM Lab, Marine Mammal Institute,Department of Fisheries and Wildlife, Oregon Sea Grant, Oregon State University
Writing a blog post this week that focuses on marine mammals seems inappropriate amidst the larger social justice issues that our country – and our global community – are facing. However, I have been leaning on my scientific background recently to help me understand these events, how we got here, and where we can go. But first I want to acknowledge and thank the people on the front lines around the world who are giving a voice to this fight for equality. Equality that is deserved, inherent, and just.
There is a concept in ecology, and in particular in fisheries management, termed shifting baselines, which was developed by the brilliant scientist Dr. Daniel Pauly in 1995 (who, by the way, is a person of color but that’s not the point here). Shifting baselines has to do with how humans judge change based on their own experiences and perceptions, and not necessarily on objective data collected over a longer period than a lifetime. Over one generation, knowledge is lost about ‘how the state of the natural world used to be’, so people don’t perceive the change that is actually taking place over time.
This article has a nice description of the shifting baseline theory: …due to short life-spans and faulty memories, humans have a poor conception of how much of the natural world has been degraded by our actions, because our ‘baseline’ shifts with every generation, and sometimes even in an individual. In essence, what we see as pristine nature would be seen by our ancestors as hopelessly degraded, and what we see as degraded our children will view as ‘natural’.
The concept of shifting baselines explains so much about why convincing policy makers to protect natural resources is challenging. People with short-term goals (political election cycles) and short-term memories don’t see the long-term trends of environmental degradation.
This week I have been thinking about how the concept of shifting baselines can also be applied to the social injustice we are grappling with today and for centuries. Yet, rather than shifting baselines, its more akin to uncommon baselines.
In school, we hopefully learn about the realities of slavery, the Civil War, Abraham Lincoln and the Emancipation Proclamation, Fredrick Douglas, Jim Crow laws, the Civil Rights Movement and Martin Luther King, the Civil Rights Act of 1964, the Voting Rights Act of 1965, and more. Often, this information comes to us in an incomplete, white-washed, biased fashion. So, if we are white and privileged in this country, we may pat ourselves on the back for what we’ve been taught is progress; for example, we might be proud of seeing integration in schools, and feel good about regularly using words like diversity and inclusion. But my baseline is very different from a black American’s baseline. Where I see progress relative to an old standard, black Americans continue to suffer from a legacy of slavery, poverty, and discrimination. My baseline cannot just be progress while people of color are still experiencing the same race inequality, police bias, economic injustice and an imbalanced power structure as their grandparents and great grandparents.
Our uncommon baselines are shaped by our previous experiences, which are culturally based, and create different perceptions of where we are in the trajectory of social and economic justice. When scientists want to adjust for the influence of shifting baselines in ecology, we first need to recognize the influence of shifted baselines and then probe for ‘historical data’ (e.g., whaling records of the actual numbers of whales killed) or speak with those who know what it was like “before” (e.g., traditional ecological knowledge) to help us account for a broader scale of change. Thus, we can use a better baseline. Perhaps in this social justice context, to achieve more common baselines of race equality across cultures, we need more conversations with people of color to share past and present experiences and perceptions.
While these recent events have been heart wrenching to witness, I do feel this period is a critical reality check, forcing those of us who are privileged and powerful to acknowledge our uncommon baselines. I hope to learn by reading and talking honestly with others so we can all work toward a common baseline of equality and justice for all.
Happy World Penguin Day (officially April 25th)! I have been contemplating what to write for my tern at the GEMM lab blog. Most of my ideas were a little bit dark, but happily when I loaded my Twitter feed Saturday morning I was greeted with many beautiful photos of penguins and the hashtag #WorldPenguinDay so that inspired something more light hearted.
To be fair, it really should be Alcidae vs. Spheniscidae (scientific family names for auks and penguins). However, I have spent many months in the field studying murres (an alcid), and I find them fascinating. Soon it will be time for them to lay their eggs at colonies along the Oregon coast, including Yaquina Head. Murres have some amazing life history characteristics.
Some of the flamboyant alcid species found in the North Pacific. These species are all crevice or burrow nesters like some penguins including Magellanic, African, and little blue penguins.
So how do murres stack up against penguins?
At first glance, murres and penguins are fairly similar. They are deep diving seabirds that forage on crustaceans and forage fish. Like murres, penguins have countershading, with black feathers on their backs and white feathers on their front. This coloring is thought to help provide camouflage when they are foraging (Cairns 1986).
There are two species of murres: common murres and thick-billed murres. Both species have a circumpolar distribution in the northern hemisphere with thick-billed murres nesting a colonies in the Arctic and common murres nesting in more temperate latitudes as far south as the central California coast. Their distributions overlap in the subarctic where they often share colonies (Irons et al. 2008).
I am under the impression that one of the reasons people love penguins so much is because they waddle. Murres aren’t so graceful either, but they spend much less of their time walking around since they commute between the sea and their colonies by flying. However, murres have to work harder to fly than they do to dive (Elliott et al. 2013). This is because they have high wing-loading. Essentially, they have big bodies and relatively small wings that they use for flying through air and water. Bigger wings would be better for air, but smaller wings are better for moving through water.
It really gets interesting when we start comparing the diving ability of alcids and penguins. Murres are the largest alcid species, and as dive depth scales with body size, they can dive the deepest. If we control for body size, alcids dive deeper then penguins (Burger 1991)! For instance, the deepest depth recorded from a thick-billed murres is 210 meters and the deepest dive of the smallest penguin (just a few hundred grams larger then the typical murre at ~1.5 kg), the little blue penguin, is a mere 69 meters (Penguiness.net).
Colonies & Nests
Murres typically nest in colonies on cliffs, off-shore sea stacks, and occasionally low lying predator free islands. Common murres use wider ledges and nest in very close proximity to each other while thick-billed murres prefer narrow ledges. Murres don’t build nests and simply lay their eggs on the rock ledge.
Penguin nesting colonies can take a variety of forms. Colonies of the “brush-tailed” penguins (chinstrap, Adélie and gentoo penguins) are found in places that are snow free for most of the summer. These colonies tend to form as a meandering collection of sub-colonies. These species build nests out of small rocks that they diligently collect. The rocks help keep their eggs out of snow meltwater. Emperor and king penguins stand together in a group. Burrow nesting penguins like Magellanic penguins can spread their colonies out across large areas where there is suitable habitat for burrowing.
Murres lay one large pyriform (pear-shaped) speckled egg that ranges in color from pale cream to brilliant turquoise. This variation allows them to recognize their own eggs (Gaston et al 1993)! The purpose of the shape of murre eggs is something that has been continually puzzled over, but the shape appears to help the blunt end stay cleaner, is stronger, and is more stable on sloping surfaces (Birkhead et al. 2017, 2018).
In comparison, penguin eggs don’t look that remarkable. Many penguin species lay two eggs (e.g. Adélie, chinstrap, rockhopper, gentoo), but king penguins and emperor penguins will just lay one, incubating it on top of their feet. The first egg that macaroni penguins lay is 55-75% smaller than their second egg, potentially due to constraints imposed by migration (Crossin et al. 2010).
Seabirds are not generally known for their melodious songs, but they are still an important part of their social lives. For this comparison I recommend an exploration of the Cornell Lab of Ornithology’s Macaulay Library. Start with the murres and then explore some penguin species. Recently it was discovered that penguins make short noises underwater (Thiebault 2019). Perhaps murres do as well.
If you are interesting a hearing a seabird that can sing, search for Light Mantled Sooty Albatross.
Murres bring whole fish back to the colony to feed their chick. One fish for each trip. Murre chicks fledge before their flight feathers are fully grown. They jump from the cliffs and glide down to the ocean (hopefully) where they are joined by their male parent. Then the pair paddle out to find good foraging grounds. The male parent needs to feed the growing chick frequently and by bringing the chick to the food is able to meet these demands.
In contrast, penguins regurgitate their stomach contents to feed their offspring. They are able to carry large amounts of food this way. For instance a chinstrap penguin might bring back ~610 grams of food, almost 15% of its body weight (Miller et al. 2010). Adult penguins still have to balance their needs and the demands of their growing chicks. So the adults will leave their chicks alone once they are large enough. The chicks stand in groups known as créches to help protect them against predators like skuas.
Feather molt is an important part of all birds’ life histories. Feathers don’t last forever and need to be replaced. Both murres and penguins have unique strategies for replacing their feathers. For any flighted bird, replacing primary feathers is especially important. Murres become flightless during molt, which happens in the fall (Birkhead & Taylor 1977). This is actually thought to help their diving as with smaller wings they should be able to fly underwater more easily (Thompson et al. 1998). They replace their body feathers gradually to maintain waterproofing and warmth.
Penguins have solved this problem in another way. Instead of gradually replacing their feathers they undergo a “catastrophic molt” and replace all their feathers at once. Penguins need to be out of the water during this time and will fast, so it is advantageous to quickly grow a new coat of feathers. They too molt after their chicks are fledged.
I will let you decide which seabirds you find most fascinating, because really I find them all amazing and in need of our continued protection. Thanks for reading!
Birkhead TR, Taylor AM (1977) Moult of the Guillemot Uria aalge. Ibis 119:80–85
Birkhead TR, Thompson JE, Jackson D, Biggins JD (2017) The point of a Guillemot’s egg. Ibis 159:255–265
Burger, A. E. (1991). Maximum diving depths and underwater foraging in alcids and penguins. In Studies of High-Latitude Seabirds. 1. Behavioural, Energetic and Oceanographic Aspects of Seabird Feeding Ecology (ed. W. A. Montevecchi and A. J. Gaston), pp. 9-15. Canada: Canadian Wildlife Service Occasional Paper.
Crossin GT, Trathan PN, Phillips RA, Dawson A, Le Bouard F, Williams TD (2010) A Carryover Effect of Migration Underlies Individual Variation in Reproductive Readiness and Extreme Egg Size Dimorphism in Macaroni Penguins. Am Nat 176:357–366
Elliott KH, Ricklefs RE, Gaston AJ, Hatch SA, John R Speakmane F, Davoren GK (2013) High flight costs, but low dive costs, in auks support the biomechanical hypothesis for flightlessness in penguins. PNAS:9380–9384
Irons DB, Anker-Nilssen T, Gaston AJ, Byrd GV, Falk K, Gilchrist G, Hario M, Hjernquist M, Krasnov YV, Mosbech A, Olsen B, Petersen A, Reid JB, Robertson GJ, Strøm H, Wohl KD (2008) Fluctuations in circumpolar seabird populations linked to climate oscillations. Global Change Biology 14:1455–1463
Miller AK, Kappes MA, Trivelpiece SG, Trivelpiece WZ (2010) Foraging-Niche Separation of Breeding Gentoo and Chinstrap Penguins, South Shetland Islands, Antarctica. The Condor 112:683–695
Thiebault A (2019) First evidence of underwater vocalizations in hunting penguins. PeerJ:1–16
Thompson CW, Wilson ML, Melvin EF, Pierce DJ (1998) An unusual sequence of flight-feather molt in Common Murres and its evolutionary implications. The Auk 115:653–669
Clara Bird, Masters Student, OSU Department of Fisheries and Wildlife, Geospatial Ecology of Marine Megafauna Lab
Whale blow, the puff of air mixed with moisture that a whale releases when it comes to the surface, is a famously thrilling indicator of the presence of a whale. From shore, spotting whale blow brings the excitement of knowing that there are whales nearby. During boat-based field work, seeing or hearing blow brings the rush of adrenaline meaning that it’s game time. Whale blow can also be used to identify different species of whales, for example gray whale blow is heart shaped (Figure 1). However, whale blow can be used for more than just spotting and identifying whales. We can use the time between blows to study energetics.
A blow interval is the time between consecutive blows when a whale is at the surface (Stelle, Megill, and Kinzel 2008). These are also known as short breath holds, whereas long breath holds are times between surfacings (Sumich 1983). Sumich (1983) hypothesized that short breath holds lead to efficient rates of oxygen use. The body uses oxygen to create energy, so “efficient rate of oxygen use” means that longer breath holds do not use much more oxygen and subsequently do not produce more energy. Surfacings, during which short blow intervals occur, are often thought of as recovery periods for whales. Think of it this way, when you sprint, immediately afterwards you typically need to take a break to just breathe and recover.
We hypothesize that we can use blow intervals as a measure of how strenuous an activity is; shorter blow intervals may indicate that an activity is more energetically demanding (Wursig, Wells, and Croll 1986). Let’s go back to the sprinting analogy and compare the energetic demands of walking and running. Imagine I asked you to walk for five minutes, stop and measure the time between each breath, and then run for five minutes and do the same; after running, you would likely breathe more heavily and take more breaths with less time between them. This result indicates that running is more demanding, which we already know because we can do other experiments with humans to study metabolic rate and related metrics. In the case of gray whales, we cannot do experiments in the same way, but we can use the same analogy. Several studies have examined how blow intervals differ between travelling and foraging.
Wursig, Wells, and Croll (1986) measured blow interval, surfacing time, and estimated dive depth and duration of gray whales in Alaska from a boat during the foraging season. They found that blow intervals were shorter during feeding. They also found that the number of blows per surfacing increased with increasing depth. Overall these findings suggest that during the foraging season, feeding is more strenuous than other behaviors and that deeper dives may be more physiologically stressful.
Stelle, Megill, and Kinzel (2008) studied gray whales foraging off of British Columbia, Canada. They found shorter blow intervals during foraging, intermediate blow intervals during searching, and longer blow intervals during travelling. Interestingly, within feeding behaviors, they found a difference between whales feeding on mysids (krill-like animals that swim in the water column) and whales feeding benthically on amphipods. They found that whales feeding on mysids made more frequent but shorter dives with short blow intervals at surface, while whales feeding benthically had longer dives with longer blow intervals. They hypothesized that this difference in surfacing pattern is because mysids might scatter when disturbed, so gray whales surface more often to allow the mysids swarm to reform. These studies inspired me to start investigating these same questions with my drone video data.
As I review the drone footage and code the behaviors I also mark the time of each blow. I’ve done some initial video coding and using this data I have started to look into differences in blow intervals. As it turns out, we see a similar difference in blow interval relative to behavior state in our data: whales that are foraging have shorter blow intervals than when traveling (Figure 2). It is encouraging to see that our data shows similar patterns.
Next, I would like to examine how blow intervals differ between foraging tactics. A significant part of my thesis is dedicated to studying specific foraging tactics. The perspective from the drone allows us to identify behaviors in greater detail than studies from shore or boat (Torres et al. 2018), allowing us to dig into the differences between the different foraging behaviors. The purpose of foraging is to gain energy. However, this gain is a net gain. To understand the different energetic “values” of each tactic we need to understand the cost of each behavior, i.e. how much energy is required to perform the behavior. Given previous studies, maybe blow intervals could help us measure this cost or at least compare the energetic demands of the behaviors relative to each other. Furthermore, because different behaviors are likely associated with different prey types (Dunham and Duffus 2001), we also need to understand the different energetic gains of each prey type (this is something that Lisa is studying right now, check out the COZI project to learn more). By understanding both of these components – the gains and costs – we can understand the energetic tradeoffs of the different foraging tactics.
Another interesting component to this energetic balance is a whale’s health and body condition. If a whale is in poor health, can it afford the energetic costs of certain behaviors? If whales in poor body condition engage in different behavior patterns than whales in good body condition, are these patterns explained by the energetic costs of the different foraging behaviors? All together this line of investigation is leading to an understanding of why a whale may choose to use different foraging behaviors in different situations. We may never get the full picture; however, I find it really exciting that something as simple and non-invasive as measuring the time between breaths can contribute such a valuable data stream to this project.
Dunham, Jason S., and David A. Duffus. 2001. “Foraging Patterns of Gray Whales in Central Clayoquot Sound, British Columbia, Canada.” Marine Ecology Progress Series 223 (November): 299–310. https://doi.org/10.3354/meps223299.
Stelle, Lei Lani, William M. Megill, and Michelle R. Kinzel. 2008. “Activity Budget and Diving Behavior of Gray Whales (Eschrichtius Robustus) in Feeding Grounds off Coastal British Columbia.” Marine Mammal Science 24 (3): 462–78. https://doi.org/10.1111/j.1748-7692.2008.00205.x.
Sumich, James L. 1983. “Swimming Velocities, Breathing Patterns, and Estimated Costs of Locomotion in Migrating Gray Whales, Eschrichtius Robustus.” Canadian Journal of Zoology 61 (3): 647–52. https://doi.org/10.1139/z83-086.
Torres, Leigh G., Sharon L. Nieukirk, Leila Lemos, and Todd E. Chandler. 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.
Wursig, B., R. S. Wells, and D. A. Croll. 1986. “Behavior of Gray Whales Summering near St. Lawrence Island, Bering Sea.” Canadian Journal of Zoology 64 (3): 611–21. https://doi.org/10.1139/z86-091.
By: Alexa Kownacki, Ph.D. Student, OSU Department of Fisheries and Wildlife,
Geospatial Ecology of Marine Megafauna Lab
We live in an interesting time. Many of us academic
scientists sit in the confines of our homes, reading scientific papers,
analyzing years-worth of data, working through a years-worth of house projects,
or simply watching Netflix. While we are confined to a much smaller area,
wildlife is not.
During this challenging situation we have unique
opportunities to study what happens when people are not outside for recreation.
All of us who feel trapped inside our homes are not only saving human lives, we
are changing ecosystems. Humans are constantly molding our ecosystems on fine
and grand scales, from xeriscaping our lawns with native, drought-resistant
plants to developing large plots of land for new homes. We manipulate nature,
for better or for worse.
So, what happens when we change our behavior? Rather than
driving, we’re gardening, instead of playing at parks, we’re playing board
games at our kitchen tables; we as a society are completely changing our
habitat-use patterns. When any top predator changes its habitat-use, switches
niches, or drastically changes its behaviors, there are top-down ecosystem
effects. When one species changes its behavior, there are major downstream
impacts on predation, foraging, diet, and habitat use. For example, when
bluegill sunfish underwent large shifts in both diet and habitat, major
predator-mediated habitat use changes in other species occurred (Mittelbach
1986). There are multiple studies describing the impacts of human-mediated
drivers on ecosystems worldwide. In coastal environments, anthropogenic
activities, specifically shipping, industry, and urban development, dramatically
change both the coastal and marine ecosystems (Mead et al. 2013).
By far the most pronounced example of how an international halt on travel can alter ecosystems comes from the tragic terrorist attacks on September 11, 2001. Prior to this current, viral pandemic, the events following 9/11 were the first time that nearly all major transit stopped in the USA—including airplanes and major shipping traffic. This halt created a unique opportunity to study some of the secondary impacts, such as a reduction in shipping traffic noise, on cetaceans. Following 9/11, there was a six decibel decrease in underwater noise that co-occurred with a decrease in stress hormones of endangered North Atlantic right whales (Rolland et al. 2012). When I first read about this study, my first thought was “leave it to scientists to make the best out of a terrible situation.” Truly, learning from nature, even in the darkest of days, is an incredible skillset. Research like this inspires me to ask questions about what changes are happening in ecosystems now because of recent events. For example, the entire port of San Diego, its beaches and bays, are closed for all recreational activity and I wonder how this reduction in traffic is similar to the post-9/11 study but on bottlenose dolphins, gray whales, and pinnipeds that are coast-associated. Are urban and suburban neighborhoods slowly becoming more rural and making space for wildlife again?
Mead, A., Griffiths, C.L., Branch, G.M.,
McQuaid, C.D., Blamey, L.K., Bolton, J.J., Anderson, R.J., Dufois, F., Rouault,
M., Froneman, P.W. and Whitfield, A.K., 2013. Human-mediated drivers of
change—impacts on coastal ecosystems and marine biota of South Africa. African
Journal of Marine Science, 35(3), pp.403-425.
Mittelbach, Gary. 1986. Predator-mediated
habitat use: some consequences for species interactions. Environ Biol
Fish16, 159–169. https://doi.org/10.1007/BF00005168
Rolland, R.M., Parks, S.E., Hunt, K.E.,
Castellote, M., Corkeron, P.J., Nowacek, D.P., Wasser, S.K. and Kraus, S.D.,
2012. Evidence that ship noise increases stress in right whales. Proceedings
of the Royal Society B: Biological Sciences, 279(1737),
I want to start my post this week with a disclaimer – I am not a virologist or an epidemiologist. My knowledge and understanding on what a virus is, how it changes and spreads, and predicting its trajectory, is very limited (though it has definitely improved in recent weeks). Nevertheless, I did not want that to stop me from shifting my focus and time currently spent reading about a certain virus in humans, to thinking about viruses in marine mammals. So, after several hours of reading papers and reports, I believe I have a good enough grasp on viruses in marine mammals to write a blog post on this topic.
To answer the question in my title – yes, marine mammals can get coronavirus! Coronaviruses have been detected in several marine mammals – mostly in captive ones (harbor seal, beluga whale, Indo-Pacific bottlenose dolphin), but it was also detected in a wild harbor seal1. It is at this point where I am going to step back from marine mammals for a moment and give a very short ‘lesson’ on viruses.
Viruses are microscopic infectious agents that replicate inside living cells of organisms. They have the ability to infect all forms of life – anything from bacteria to plants to animals to humans. Nothing is excluded. Viruses are classified similarly to how living organisms are classified. Try to think back to middle school science when your teacher used mnemonic devices like, “Kids prefer candy over fancy green salad” or “Kings play chess on fine glass surfaces”, to get you to remember the Kingdom-Phylum-Class-Order-Family-Genus-Species classification. Well, viruses have almost the same classification tree. The only difference is that instead of Kingdom at the top, viruses have a Realm. As of 2019, the International Committee on Taxonomy of Viruses (ICTV) has defined 5,560 species of viruses in over 1,000 genera and 150 families. Different species of virus are classified based on their genomic material and key elements of structure and replication. That is as far as I am going to go with virus background – back to marine mammals!
So, yes, coronaviruses have been detected in marine mammals before. But, no, they were not the same species of coronavirus that is currently spreading across the globe in humans. Coronavirus, or Coronaviridae, is a family of viruses that contains around 40 species. However, coronavirus is not the family that has plagued marine mammals the most since research on marine mammal diseases began. The infectious disease that I have found to be the most common and recurring in marine mammals is morbillivirus and I will therefore focus on that virus for the rest of this post.
Morbillivirus is a genus of viruses in the family Paramyxoviridae and hosts of this genus include humans, dogs, cats, cattle, seals, and cetaceans. There are seven described species of morbillivirus, three of which have been detected in marine mammals, namely canine distemper virus (CDV), cetacean morbillivirus (CeMV), and phocine distemper virus (PDV). The earliest, traceable case of morbillivirus in a marine mammal occurred in 1982 in bottlenose dolphins in the Indian and Banana Rivers in Florida2. This case was followed by hundreds of others in subsequent years all along the Atlantic U.S. coast and resulted in the first Unusual Mortality Event (UME; 1987-1988) that was concluded to have been caused by morbillivirus (Table 1).
Table 1. Unusual Mortality Events (UMEs) of marine mammals in the U.S. where the cause was determined to be or is suspected to be morbillivirus. Data obtained from NOAA Fisheries.
Interestingly, at the same time as this 1980s morbillivirus in the US, the first documented marine mammal morbillivirus epidemic occurred in Europe in the North Sea. This outbreak led to the death of more than 23,000 harbor seals, which accounted for roughly 60% of all North Sea harbor seals at the time3. The virus that was isolated from the stranded seals in the North Sea was similar to CDV but not exactly the same. Resultantly, it was described as a new species of morbillivirus and it was therefore the first outbreak of PDV. Another interesting thing about this case in Europe is that while the infection originated at the Danish island of Anholt, new centers of infection appeared quite far from this first epicenter within a relatively short amount of time (~3-4 weeks) from the initial outbreak, some as far as the Irish Sea (~2,000 km away; Figure 1). Harbor seals typically have a limited home range and do not travel such distances, leading scientists to speculate that grey seals may have been a carrier of the virus and transported it from Anholt to haul-out sites in the Irish Sea. Mixed species haul-out sites of harbor and grey seals are very common across the North Sea and is the most logical explanation for the rapid spread of the virus across such distances.
Harbor seals seem to be the most susceptible to PDV based on all documented cases of PDV outbreaks, however the reason for this pattern remains unknown1. While CDV has only been detected in Baikal and Caspian seals, CeMV has occurred in a larger number of cetaceans including harbor porpoises, striped, bottlenose, Guiana and Fraser’s dolphins, pilot whales, and a minke whale. This list is not extensive as morbillivirus has been found in 23 of the 90 cetacean species. In fact, it has been suggested that CeMV should be divided into more than one species as the morbilliviruses detected in the Northern Hemisphere show significant divergence from those found in the Southern Hemisphere.
Transmission is believed to mostly occur horizontally, meaning that the morbillivirus is passed from one individual to another. This transfer happens when one individual inhales the aerosolized virus breathed out by an infected individual. This is likely the reason why odontocete and pinniped groups are most affected due to their social group behavior and/or high density of individuals within groups4. However, vertical transmission has also been suggested as a possible transmission route as morbillivirus antigens have been detected in the mammary glands of bottlenose dolphins along the U.S. Atlantic Coast5 and striped dolphins in the Mediterranean Sea affected by CeMV6. Thus, it has been postulated that CeMV infected females could transmit the infection to their fetuses and neonates in utero, as well as to their calves during lactation.
Morbilliviruses mostly affect the respiratory and neurologic systems in marine mammals, wherein affected individuals may display ocular and naval discharge, erratic swimming, respiratory distress, raised body temperature, and/or cachexia (weakness and wasting away of the body due to severe illness). However, most diagnoses occur post-mortem. Some individuals may survive the initial acute infection of morbillivirus, yet the general weakening of the immune system will make individuals more susceptible to other infections, diseases, and disturbance events7.
It is impossible to know whether marine mammals take precautions when a virus has taken grip of a group or population, or if marine mammals even have an awareness of such things occurring. There obviously is no such thing as an emergency room or a doctor in the lives of marine mammals, but do individuals perhaps demonstrate social distancing by increasing the space between each other when traveling in groups? Do groups decrease their traveling distances or foraging ranges to isolate themselves in a smaller area? Are sick individuals ‘quarantined’ by being forced out of a group? These are just some of the questions I have been asking myself while working from home (day 16 for me now). I hope you are all staying safe and healthy and have enjoyed distracting yourselves from thinking about one virus to learn about another in a different kind of mammal.
1 Bossart, G. D., and P. J. Duignan. 2018. Emerging viruses in marine mammals. CAB Reviews 13(52): doi:10.1079/PAVSNNR201913052.
2 Duignan, P. J., C. House, D. K. Odell, R. S. Wells, L. J. Hansen, M. T. Walsh, D. J. St. Aubin, B. K. Rima, and J. R. Geraci. 1996. Morbillivirus infection in bottlenose dolphins: evidence for recurrent epizootics in the western Atlantic and Gulf of Mexico. Marine Mammal Science 12(4):499-515.
3 Härkönen, T., R. Dietz, P. Reijnders, J. Teilmann, K. Harding, A. Hall, S. Brasseur, U. Siebert, S. J. Goodman, P. D. Jepson, T. D. Rasmussen, and P. Thompson. 2006. A review of the 1988 and 2002 phocine distemper virus epidemics in European harbor seals. Diseases of Aquatic Organisms 68:115-130.
4 Van Bressem, M-F., P. J. Duignan, A. Banyard, M. Barbieri, K. M. Colegrove, S. De Guise, G. Di Guardo, A. Dobson, M. Domingo, D. Fauquier, A. Fernandez, T. Goldstein, B. Grenfell, K. R. Groch, F. Gulland, B. A. Jensen, P. D. Jepson, A. Hall, T. Kuiken, S. Mazzariol, S. E. Morris, O. Nielsen, J. A. Raga, T. K. Rowles, J. Saliki, E. Sierra, N. Stephens, B. Stone, I. Tomo, J. Wang, T. Waltzek, and J. F. X. Wellehan. 2014. Cetacean morbillivirus: current knowledge and future directions. Viruses 6(12):5145-5181.
5 Schulman, F. Y., T. P. Lipscomb, D. Moffett, A. E. Krafft, J. H. Lichy, M. M. Tsai, J. K. Taubenberger, and S. Kennedy. 1997. Histologic, immunohistochemical, and polymerase chain reaction studies of bottlenose dolphins from the 1987-1988 United States Atlantic coast epizootic. Veterinary Pathology 34(4):288-295.
6 Domingo, M., J. Visa, M. Pumarola, A. J. Marco, L. Ferrer, R. Rabanal, and S. Kennedy. 1992. Pathologic and immunocytochemical studies of morbillivirus infection in striped dolphins (Stenella coeruleoalba). Veterinary Pathology 29(1):1-10.
7 Wellehan, J., and G. Cortes-Hinojosa. 2019. Marine Mammal Viruses. Fowler’s Zoo and Wild Animal Medicine Current Therapy 9:597-602.
By Leila Lemos, PhD (no more PhD candidate!), OSU Department of Fisheries and Wildlife, Geospatial Ecology of Marine Megafauna Lab
Did you read the byline above? Yes! I finally became a PhD last week and I will not be signing as a PhD candidate anymore. The past few months have been really challenging as I wrapped up my PhD, sent my written dissertation to my committee and synthesized all of the results of my four different chapters into a single presentation. On top of that I had family members visiting me for my defense in the middle of this whole coronavirus chaos.
For my PhD defense, everybody was encouraged to watch it online to help contain the virus spread. There were around 10 people in the room seated with at least two empty chairs between each other. I usually get a bit nervous with full rooms and public speaking, so that was a plus for me. However, I was delighted to hear that there were 61 people watching my defense online (Fig. 01), and I was thrilled to share the results of almost five years of research on this amazing project about gray whale body condition, hormones, and associations with ambient noise.
One of the questions I got from one of my committee members, Dr. Kathleen Hunt, in the closed-door session of my defense that actually motivated me to write this blog was: “what do I expect would happen to the whales during this coronavirus situation”. That made me think of the Rolland et al. (2012) article immediately, which looked into North Atlantic Right Whale (NARWs) cortisol responses to decreased ship traffic and ambient noise after the 9/11 event. Those authors found that NARWs decreased their overall cortisol (i.e., stress-related hormone) concentrations, supporting the theory that noise caused by ship traffic affects the physiology of these animals. Thus, I would expect the same to occur with gray whales in the Pacific northwest. If vessel activities in general are reduced, we can expect a quieter and cleaner environment, which would allow the animals and overall nature to “breath”.
In fact, multiple news stories over the last days have pointed out declines in air pollution (Fig. 02) and cleaner waters with no boat traffic (Fig. 03), which demonstrate how poorly we treat the environment during “normal” times.
It is impressive to see how fast nature can take back what we, humans, have been taking from it. In addition, there were lots of photos that went viral on Twitter of animals returning to urban areas, including fish swarms, swans, dolphins, and wild boars. Even though there are reports saying that the apparition of some of these animals is fake (Daly 2020), it definitely can make us all reflect on how dense tourism, boat traffic, and overall anthropogenic activities impacts and changes the environment. Perhaps once this coronavirus scare is over people may act in ways that better balance these activities with also allowing our planet to keep breathing.
Here you can see some of these tweets:
Here's an unexpected side effect of the pandemic – the water's flowing through the canals of Venice is clear for the first time in forever. The fish are visible, the swans returned. pic.twitter.com/2egMGhJs7f
The Guardian also added a video showing some of these cases:
Source: Guardian News (2020).
In a near future, it will also be a great moment for researchers to evaluate potential shifts in ecosystem pollution, flora, and evaluate physiological responses in bioindicator species to inform management and conservation efforts, setting up potential thresholds for these activities. As I mentioned before, I worked with gray whale body condition, hormone quantification, and associations with ambient noise in my PhD project. I explored an association between cortisol levels and ambient noise, and now, with a reduction in overall vessel traffic, would be an ideal moment to see if cortisol levels would decrease in this population. The problem is that we are not able to leave our houses for now to do research. But maybe other variables can be evaluated once this chaos passes. Maybe it will be reflected in individual body condition and reproductive rates, maybe we will see fewer signs of fisheries interactions, or maybe we just need to be creative and think of other possible ways.
Efforts to identify these potential changes and setting up thresholds for these activities may aid in building a planet that will be in equilibrium, and maybe declines in air pollution, and clearer waters will be more common and the apparition of species in urban areas will not be fake news.
Newburger, E. 2020. Air pollution falls as coronavirus slows travel, but scientists warn of longer-term threat to climate change progress. CNBC. Accessed on 03/23/2020 at https://www.cnbc. com/2020/03/21/air-pollution-falls-as-coronavirus-slows-travel-but-it-forms-a-new-threat.html
Rolland, R. M., S. E. Parks, K. E. Hunt, M. Castellote, P. J. Corkeron, D. P. Nowacek, S. K. Wasser, and S. D. Kraus. 2012. Evidence that ship noise increases stress in right whales Proceedings of the Royal Society B 279:2363–2368.