Month: March 2020

Can marine mammals get coronavirus?

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

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!

Grey seal hauled out along the west coast of the U.K. Source: L. Hildebrand.

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.

Figure 1. Map of the North Sea showing Anholt island (red marker) and the Irish Sea (white circle).

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.

Bottlenose dolphins populations have been involved in several UME events related to morbillivirus along the U.S. coasts (Table 1). Source: L. Hildebrand. Image captured under NMFS permit #19116.

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.

Literature cited

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.

Empty room, full zoom!

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.

Figure 01: Tweet by the GEMMLab and retweet by the Hatfield Student Organization, showing me during my defense, and a post-defense photo with GEMMLab members (Clara Bird, Lisa Hildebrand, Leigh Torres, me, Dawn Barlow, and Alexa Kownacki – ignoring social distancing for a quick photo).
Source: Twitter (2020).

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.

Figure 02: NASA’s Earth Observatory pollution satellites show “significant decreases” in air pollution over China since the coronavirus outbreak began.
Source: NASA (2020).

 

Figure 03: Clear water is seen in Venice’s canals due to less tourists, motorboats and pollution, as the spread of the coronavirus disease (COVID-19) continues, in Venice, Italy, March 18, 2020.
Source: Newburger (2020).

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:

https://twitter.com/ikaveri/status/1239660248207589383?s=20

 

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.

 

References:

Daly, N. 2020. Fake animal news abounds on social media as coronavirus upends life. National Geographic. Accessed on 03/23/2020 at https://www.nationalgeographic.com/animals/2020/03 /coronavirus-pandemic-fake-animal-viral-social-media-posts/#close 

Guardian News. 2020. Dolphins and fish: nature moves into spaces left empty by Italian coronavirus quarantine. Accessed on 03/23/2020 at https://www.youtube.com/watch?time_ continue=89&v=jv0DLTVfwIc&feature=emb_logo

NASA. 2020. Airborne Nitrogen Dioxide Plummets Over China. Earth Observatory NASA. Accessed on 03/23/2020 at https://earthobservatory.nasa.gov/images/146362/airborne-nitrogen-dioxide-plummets-over-china

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.

Coding stories, tips, and tricks

Clara Bird1 and Karen Lohman2

1Masters Student in Wildlife Science, Geospatial Ecology of Marine Megafauna Lab

2Masters Student in Wildlife Science, Cetacean Conservation and Genomics Laboratory

In a departure from my typical science-focused blog, this week I thought I would share more about myself. This week I was inspired by International’s Woman’s Day and, with some reflection on the last eight months as a graduate student, I decided to look back on the role that coding has played in my life. We hear about how much coding can be empowering but I thought it might be cool to talk about my personal experience of feeling empowered by coding. I’ve also invited a fellow grad student in the Marine Mammal Institute, Karen Lohman, to co-author this post. We’re going to briefly talk about our experience with coding and then finish with advice for getting started with coding and coding for data analysis.

Our Stories

Clara

I’ve only been coding for a little over two and a half years. In summer 2017 I did an NSF REU (Research Experience for Undergraduates) at Bigelow Laboratory for Ocean Sciences and for my project I taught myself python (with the support of a post-doc) for a data analysis project. During those 10 weeks, I coded all day, every workday. From that experience, I not only acquired the hard skill of programming, but I gained a good amount of confidence in myself, and here’s why: For the first three years of my undergraduate career coding was a daunting skill that I knew I would eventually need but did not know where to start. So, I essentially ended up learning by jumping off the deep end. I found the immersion experience to be the most effective learning method for me. With coding, you find out if you got something right (or wrong) almost instantaneously. I’ve found that this is a double-edged sword. It means that you can easily have days where everything goes wrong. But, the feeling when it finally works is what I think of when I hear the term empowerment. I’m not quite sure how to put it into words, but it’s a combination of independence, confidence, and success. 

Aside from learning the fundamentals, I finished that summer with confidence in my ability to teach myself not just new coding skills, but other skills as well. I think that feeling confident in my ability to learn something new has been the most helpful aspect to allow me to hit the ground running in grad school and also keeping the ‘imposter syndrome’ at bay (most of the time).

Clara’s Favorite Command: pd.groupby (python) – Say you have a column of measurements and a second column with the field site of each location. If you wanted the mean of the measurement per each location, you could use groupby to get this. It would look like this: dataframe.groupby(‘Location’)[‘Measurement’].mean().reset_index()

Karen

I’m quite new to coding, but once I started learning I was completely enchanted! I was first introduced to coding while working as a field assistant for a PhD student (a true R wizard who has since developed deep learning computer vision packages for automated camera trap image analysis) in the cloud forest of the Ecuadorian Andes. This remote jungle was where I first saw how useful coding can be for data management and analysis. It was a strange juxtaposition between being fully immersed in nature for remote field work and learning to think along the lines of coding syntax. It wasn’t the typical introduction to R most people have, but it was an effective hook. We were able to produce preliminary figures and analysis as we collected data, which made a tough field season more rewarding. Coding gave us instant results and motivation.

I committed to fully learning how to code during my first year of graduate school. I first learned linux/command line and python, and then I started working in R that following summer. My graduate research uses population genetics/genomics to better understand the migratory connections of humpback whales. This research means I spend a great deal of time working to develop bioinformatics and big data skills, an essential skill for this area of research and a goal for my career. For me, coding is a skill that only returns what you put in; you can learn to code quite quickly, if you devote the time. After a year of intense learning and struggle, I am writing better code every day.

In grad school research progress can be nebulous, but for me coding has become a concrete way to measure success. If my code ran, I have a win for the week. If not, then I have a clear place to start working the next day. These “tiny wins” are adding up, and coding has become a huge confidence boost.

Karen’s Favorite Command: grep (linux) – Searches for a string pattern and prints all lines containing a match to the screen. Grep has a variety of flags making this a versatile command I use every time I’m working in linux.

Advice

Getting Started

  • Be kind to yourself, think of it as a foreign language. It takes a long time and a lot of practice.
  • Once you know the fundamental concepts in any language, learning another will be easier (we promise!).
  • Ask for help! The chances that you have run into a unique error are quite small, someone out there has already solved your problem, whether it’s a lab mate or another researcher you find on Google!

Coding Tips

1. Set yourself up for success by formatting your datasheets properly

  • Instead of making your spreadsheet easy to read, try and think about how you want to use the data in the analysis.
  • Avoid formatting (merged cells, wrap text) and spaces in headers
  • Try to think ahead when formatting your spreadsheet
    • Maybe chat with someone who has experience and get their advice!

2. Start with a plan, start on paper

This low-tech solution saves countless hours of code confusion. It can be especially helpful when manipulating large data frames or in multistep analysis. Drawing out the structure of your data and checking it frequently in your code (with ‘head’ in R/linux) after manipulation can keep you on track. It is easy to code yourself into circles when you don’t have a clear understanding of what you’re trying to do in each step. Or worse, you could end up with code that runs, but doesn’t conduct the analysis you intended, or needed to do.

3. Good organization and habits will get you far

There is an excellent blog by Nice R Code on project organization and file structure. I highly recommend reading and implementing their self-contained scripting suggestions. The further you get into your data analysis the more object, directory, and function names you have to remember. Develop a naming scheme that makes sense for your project (i.e. flexible, number based, etc.) and stick with it. Temporary object names in functions or code blocks can be a good way to clarify what is the code-in-progress or the code result.

Figure 1. An example of project based workflow directory organization from Nice R Code (https://nicercode.github.io/blog/2013-04-05-projects/ )

4. Annotate. Then annotate some more.

Make comments in your code so you can remember what each section or line is for. This makes debugging much easier! Annotation is also a good way to stay on track as you code, because you’ll be describing the goal of every line (remember tip 1?). If you’re following a tutorial (or STACKoverflow answer), copy the web address into your annotation so you can find it later. At the end of a coding session, make a quick note of your thought process so it’s easier to pick up when you come back. It’s also a good habit to add some ‘metadata’ details to the top of your script describing what the script is intended for, what the input files are, the expected outputs, and any other pertinent details for that script. Your future self will thank you!

Figure 2. Example code with comments explaining the purpose of each line.

5. Get with git/github already

Github is a great way to manage version control. Remember how life-changing the advent of dropbox was? This is like that, but for code! It’s also become a great open-source repository for newly developed code and packages. In addition to backing up and storing your code, GitHub has become a ‘coding CV’ that other researchers look to when hiring.

Wondering how to get started with GitHub? Check out this guide: https://guides.github.com/activities/hello-world/

Looking for a good text/code editor? Check out atom (https://atom.io/), you can push your edits straight to git from here.

6. You don’t have to learn everything, but you should probably learn the R Tidyverse ASAP

Tidyverse is a collection of data manipulation packages that make data wrangling a breeze. It also includes ggplot, an incredibly versatile data visualization package. For python users hesitant to start working in R, Tidyverse is a great place to start. The syntax will feel more familiar to python, and it has wonderful documentation online. It’s also similar to the awk/sed tools from linux, as dplyr removes any need to write loops. Loops in any language are awful, learn how to do them, and then how to avoid them.

7. Functions!

Break your code out into blocks that can be run as functions! This allows easier repetition of data analysis, in a more readable format. If you need to call your functions across multiple scripts, put them all into one ‘function.R’ script and source them in your working scripts. This approach ensures that all the scripts can access the same function, without copy and pasting it into multiple scripts. Then if you edit the function, it is changed in one place and passed to all dependent scripts.

8. Don’t take error messages personally

  • Repeat after me: Everyone googles for every other line of code, everyone forgets the command some (….er every) time.
  • Debugging is a lifestyle, not a task item.
  • One way to make it less painful is to keep a list of fixes that you find yourself needing multiple times. And ask for help when you’re stuck!

9. Troubleshooting

  • Know that you’re supposed to google but not sure what?
    • start by copying and pasting the error message
  • When I started it was hard to know how to phrase what I wanted, these might be some common terms
    • A dataframe is the coding equivalent of a spreadsheet/table
    • Do you want to combine two dataframes side by side? That’s a merge
    • Do you want to stack one dataframe on top of another? That’s concatenating
    • Do you want to get the average (or some other statistic) of values in a column that are all from one group or category? Check out group by or aggregate
    • A loop is when you loop through every value in a column or list and do something with it (use it in an equation, use it in an if/else statement, etc).

Favorite Coding Resource (other than github….)

  • Learnxinyminutes.com
    • This is great ‘one stop googling’ for coding in almost any language! I frequently switch between coding languages, and as a result almost always have this open to check syntax.
  • https://swirlstats.com/
    • This is a really good resource for getting an introduction to R

Parting Thoughts

We hope that our stories and advice have been helpful! Like many skills, you tend to only see people once they have made it over the learning curve. But as you’ve read Karen and I both started recently and felt intimidated at the beginning. So, be patient, be kind to yourself, believe in yourself, and good luck!

Marine heatwaves and their impact on marine mammals

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

In recent years, anomalously warm ocean temperatures known as “marine heatwaves” have sparked considerable attention and concern around the world. Marine heatwaves (MHW) occur when seawater temperatures rise above a seasonal threshold (greater than the 90th percentile) for five consecutive days or longer (Hobday et al. 2016; Fig. 1). With global ocean temperatures continuing to rise, we are likely to see more frequent and more intense MHW conditions in the future. Indeed, the global prevalence of MHWs is increasing, with a 34% rise in frequency, a 17%  increase in duration, and a 54% increase in annual MHW days globally since 1925 (Oliver et al. 2018). With sustained anomalously warm water temperatures come a range of ecological, sociological, and economic consequences. These impacts include changes in water column structure, primary production, species composition, marine life distribution and health, and fisheries management including closures and quota changes (Oliver et al. 2018).

Figure 1. Illustration of how marine heatwaves are defined. Source: marineheatwaves.org

The notorious “warm blob” was an MHW event that plagued the northeast Pacific Ocean from 2014-2016. Some of the most notable consequences of this MHW were extremely high levels of domoic acid, extreme changes in the biodiversity of pelagic species, and an unprecedented delay in the opening of the Dungeness crab fishery, which is an important and lucrative fishery for the West Coast of the United States (Santora et al. 2020). The “warm blob” directly impacted the California Current ecosystem, which is typically a highly productive coastal area driven by seasonal upwelling. Yet, as a consequence of the 2014-2016 MHW, upwelling habitat was compressed and constricted to the coastal boundary, resulting in a contraction in available habitat for humpback whales and a shift in their prey (Santora et al. 2020; Fig. 2).

Figure 2. A figure from Santora et al. 2020 illustrating the compression in available upwelling habitat, defined by areas with SST<12°C (delineated by the black line), during the 2014-2016 marine heatwave in the California Current ecosystem.

Shifting to an example from another part of the world, the austral summer of 2015-2016 coincided with a strong regional MHW in the Tasman Sea between Australia and New Zealand, which lasted for 251 days and had a maximum intensity of 2.9°C above the climatological average (Oliver et al. 2017). Subsequently, the conditions were linked to a significant shift in zooplankton species composition and abundance in Australia (Evans et al. 2020). Ocean warming, including MHWs, also appears to decrease primary production in the Tasman Sea and large portions of New Zealand’s marine ecosystem (Chiswell & Sutton 2020). In New Zealand’s South Taranaki Bight region, where we study the ecology of blue whales, we observed a shift in blue whale distribution in the MWH conditions of February 2016 relative to more typical ocean conditions in 2014 and 2017 (Fig. 3). The first chapter of my dissertation includes a detailed analysis of the impacts of the 2016 MHW on New Zealand oceanography, krill, and blue whales, documenting how the warm, stratified water column of 2016 led to consequences across multiple trophic levels, from phytoplankton, to zooplankton, to whales.

Figure 3. Maps showing monthly sea surface temperature (SST) in the South Taranaki Bight region of New Zealand during our three years of survey effort to document blue whale distribution (February 2014, 2016, and 2017). Vessel tracklines are shown in black, with blue whale sighting locations shown in dark red. Red circles are scaled by the number of blue whales observed at each sighting. The color ramp of SST values is consistent across the three maps, making the dramatically warmer ocean conditions of 2016 evident.

The response of marine mammals is tightly linked to shifts in their environment and prey (Silber et al. 2017). With MHWs and changing ocean conditions, there will likely be “winners” and “losers” among marine predators including large whales. Blue whales are highly selective krill specialists (Nickels et al. 2019), whereas other species of whales, such as humpback whales, have evolved flexible feeding tactics that allow them to switch target prey species when needed (Cade et al. 2020). In California, humpback whales have been shown to switch their primary prey from krill to fish during warm years (Fossette et al. 2017, Santora et al. 2020). By contrast, blue whales shift their distribution in response to changing krill availability during warm years (Fossette et al. 2017), however this strategy comes with increased risk and energetic cost associated with searching for prey in new areas. Furthermore, in instances when a prey resource such as krill becomes increasingly scarce for a multi-year period (Santora et al. 2020), krill specialist predators such as blue whales are at a considerable disadvantage. It is also important to acknowledge that although the humpbacks in California may at first seem to have a winning strategy for adaptation by switching their food source, this tactic may come with unforeseen consequences. Their distribution overlapped substantially with Dungeness crab fishing gear during MHW conditions in the warm blob years, resulting in record numbers of entanglements that may have population-level repercussions (Santora et al. 2020).

While this is certainly not the most light-hearted blog topic, I believe it is an important one. As warming ocean temperatures contribute to the increase in frequency, intensity, and duration of extreme conditions such as MHW events, it is paramount that we understand their impacts and take informed management actions to mitigate consequences, such as lethal entanglements as a result of compressed whale habitat. But perhaps more importantly, even as we do our best to manage consequences, it is critical that we as individuals realize the role we have to play in reducing the root cause of warming oceans, by being conscious consumers and being mindful of the impact our actions have on the climate. 

References

Cade DE, Carey N, Domenici P, Potvin J, Goldbogen JA (2020) Predator-informed looming stimulus experiments reveal how large filter feeding whales capture highly maneuverable forage fish. Proc Natl Acad Sci USA.

Chiswell SM, Sutton PJH (2020) Relationships between long-term ocean warming, marine heat waves and primary production in the New Zealand region. New Zeal J Mar Freshw Res.

Evans R, Lea MA, Hindell MA, Swadling KM (2020) Significant shifts in coastal zooplankton populations through the 2015/16 Tasman Sea marine heatwave. Estuar Coast Shelf Sci.

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Cooperative Fishing: Symbiotic Relationships between People and Dolphins

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

Human-wildlife interactions have occurred since people first inhabited the Earth. However, today, when describing human-wildlife interactions specifically in relation to dolphins, frequently we hear about ‘conflicts’. Interactions between fisheries and dolphins that lead to bycatch or depredation (stealing bait/catching from gear) are particularly common. But, symbiotic relationships with dolphin species and certain human groups can also be mutualistic, with both groups benefitting. These symbiotic relationships have been around for hundreds, if not thousands of years.

A depiction of Aboriginal Australians using nets to catch fish in a small inlet with the assistance of coastal dolphins. (Image source: Our Pacific Ocean)

In eastern Australia, cooperative fishing interactions occur between Aboriginal Australians and dolphins—both bottlenose dolphins and orcas. In Burleigh Heads National Park, Queensland, AUS, the dolphins are thought to help the local indigenous Kombemerri (saltwater) people hunt for fish. Indigenous stories recall men wading into the water with their spears and nets. Then, many of the men would hit the surface waters to make noises with the splashes. Underwater, this sound was amplified and then the dolphins would begin chasing the fish toward the men and their nets (Neil 2002). Aboriginal Australians, especially those in eastern Australia have an emotional and spiritual connection to both dolphins and orcas. There are widespread accounts of cooperation between indigenous people and small cetaceans on the eastern Australian coastline, which create both context and precedent for the economic and emotional objectives to contemporary human-dolphin interactions such as dolphin provisioning (Neil 2002).

Dolphins and fishermen work together in Laguna, Brazil, to catch mullet. (Image Source: Fábio Daura-Jorge)

In the coasts off of Laguna, Brazil, bottlenose dolphins and local fishermen cooperatively fish while tourists gather to watch. Previously, PhD candidate Leila Lemos wrote about these interactions in a blog post. Like many groups of socializing dolphins, these dolphins have a unique whistle to recognize each other. The waters surrounding Laguna, Brazil are murky, turbid and dark green to the point where the fisherman cannot see any of the fish in the water. As the fishermen wade into the murky waters, bottlenose dolphins chase shoals of mullet toward the shore. Then the dolphins tail slap or abruptly dive, “signaling” the fishermen to cast their nets. Research has shown that when the fishermen “work with” the dolphins, both the dolphins and the people catch more, larger fish (Roman 2013). One fisherman claims it is not worth fishing unless the dolphins are around (Roman 2013). Here, the fishermen know the dolphins based on their markings. They know which dolphins participate in the different parts of hunting as well—which dolphin initiates the tail slap, which dolphin usually circles the fish, and which drive the fish towards the coastline. After the dolphins round up and chase the fish for the fishermen and themselves, there is no “reward” from the fishermen for the dolphins—no fish tossed their way. Scientists also found there is a difference in whistle structure between cooperative and non-cooperative dolphin groups (Preston 2017).

A fisherman in Brazil throws a net after dolphins chase mullet into the shore. (Image Source: Leo Francini:Alamy Stock Photo)

Along most coastlines worldwide, humans and dolphins are competitors. Dolphins are seen as thieves who steal fish out of nets, or get caught in their gear and ruin fishing opportunities. Thus, dolphins are often unwelcome near fishing communities. Such negative interactions sometimes lead to human-caused fatalities of dolphin from gunshots or stabbings, thought to be from angry fishermen.  Yet, in this same world, fishermen thank the dolphins for bringing their catch to them. Clearly, both humans and dolphins share high intelligence levels and skills in fishing. If it is a matter of two minds are better than one, then I think indigenous communities figured this equation out first: working with the dolphins, and not against, can better feed their people.

Citations:

Neil, David. (2002). Cooperative fishing interactions between Aboriginal Australians and dolphins in eastern Australia. Anthrozoos: A Multidisciplinary Journal of The Interactions of People & Animals. 15. 10.2752/089279302786992694.

Preston, Elizabeth. “Dolphins That Work with Humans to Catch Fish Have Unique Accent.” New Scientist, 2 Oct. 2017, www.newscientist.com/article/2149139-dolphins-that-work-with-humans-to-catch-fish-have-unique-accent/.

Roman, Joe. “Fishing with Dolphins: An astonishing cooperative venture in which every species wins but the fish.” Slate Magazine, 31 Jan. 2013, slate.com/technology/2013/01/fishing-with-dolphins-symbiosis-between-humans-and-marine-mammals-to-catch-more-fish.html.