Tag: Oregon State

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Literature cited

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

A Weekend of Inspiration in Marine Science: NWSSMM and Dr. Sylvia Earle!

By Karen Lohman, Masters Student in Wildlife Science, Cetacean Conservation and Genomics Lab, Oregon State University

My name is Karen Lohman, and I’m a first-year student in Dr. Scott Baker’s Cetacean Conservation and Genomics Lab at OSU. Dr. Leigh Torres is serving on my committee and has asked me to contribute to the GEMM lab blog from time to time. For my master’s project, I’ll be applying population genetics and genomics techniques to better understand the degree of population mixing and breeding ground assignment of feeding humpback whales in the eastern North Pacific. In other words, I’ll be trying to determine where the humpback whales off the U.S. West Coast are migrating from, and at what frequency.

Earlier this month I joined the GEMM lab members in attending the Northwest Student Society of Marine Mammalogy Conference in Seattle. The GEMM lab members and I made the trip up to the University of Washington to present our work to our peers from across the Pacific Northwest. All five GEMM lab graduate students, plus GEMM lab intern Acacia Pepper, and myself gave talks presenting our research to our peers. I was able to present preliminary results on the population structure of feeding humpback whales across shared feeding habitat by multiple breeding groups in the eastern North Pacific using mitochondria DNA haplotype frequencies. In the end GEMM lab’s Dawn Barlow took home the “Best Oral Presentation” prize. Way to go Dawn!

A few of the GEMM lab members and me presenting our research at the NWSSMM conference in May 2019 at the University of Washington.

While conferences have a strong networking component, this one feels unique.  It is a chance to network with our peers, who are working through the same challenges in graduate school and will hopefully be our future research collaborators in marine mammal research when we finish our degrees. It’s also one of the few groups of people that understand the challenges of studying marine mammals. Not every day is full of dolphins and rainbows; for me, it’s mostly labwork or writing code to overcome small and/or patchy sample size problems.

All of the CCGL and GEMM Lab members excited to hear Dr. Sylvia Earle’s presentation at Portland State University in May 2019 (from L to R: Karen L., Lisa H., Alexa K., Leila L., Dawn B., and Dom K.) . Photo Source: Alexa Kownacki

On the way back from Seattle we stopped to hear the one and only Dr. Sylvia Earle, talk in Portland. With 27 honorary doctorates and over 200 publications, Dr. Sylvia Earle is a legend in marine science. Hearing a distinguished marine researcher talk about her journey in research and to present such an inspiring message of ocean advocacy was a great way to end our weekend away from normal grad school responsibilities. While the entirety of her talk was moving, one of her final comments really stood out. Near the end of her talk she called the audience to action by saying “Look at your abilities and have confidence that you can and must make a difference. Do whatever you’ve got.” As a first-year graduate student trying to figure out my path forward in research and conservation, I couldn’t think of better advice to end the weekend on.

 

Data Wrangling to Assess Data Availability: A Data Detective at Work

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

Data wrangling, in my own loose definition, is the necessary combination of both data selection and data collection. Wrangling your data requires accessing then assessing your data. Data collection is just what it sounds like: gathering all data points necessary for your project. Data selection is the process of cleaning and trimming data for final analyses; it is a whole new bag of worms that requires decision-making and critical thinking. During this process of data wrangling, I discovered there are two major avenues to obtain data: 1) you collect it, which frequently requires an exorbitant amount of time in the field, in the lab, and/or behind a computer, or 2) other people have already collected it, and through collaboration you put it to a good use (often a different use then its initial intent). The latter approach may result in the collection of so much data that you must decide which data should be included to answer your hypotheses. This process of data wrangling is the hurdle I am facing at this moment. I feel like I am a data detective.

Data wrangling illustrated by members of the R-programming community. (Image source: R-bloggers.com)

My project focuses on assessing the health conditions of the two ecotypes of bottlenose dolphins between the waters off of Ensenada, Baja California, Mexico to San Francisco, California, USA between 1981-2015. During the government shutdown, much of my data was inaccessible, seeing as it was in possession of my collaborators at federal agencies. However, now that the shutdown is over, my data is flowing in, and my questions are piling up. I can now begin to look at where these animals have been sighted over the past decades, which ecotypes have higher contaminant levels in their blubber, which animals have higher stress levels and if these are related to geospatial location, where animals are more susceptible to human disturbance, if sex plays a role in stress or contaminant load levels, which environmental variables influence stress levels and contaminant levels, and more!

Alexa, alongside collaborators, photographing transiting bottlenose dolphins along the coastline near Santa Barbara, CA in 2015 as part of the data collection process. (Image source: Nick Kellar).

Over the last two weeks, I was emailed three separate Excel spreadsheets representing three datasets, that contain partially overlapping data. If Microsoft Access is foreign to you, I would compare this dilemma to a very confusing exam question of “matching the word with the definition”, except with the words being in different languages from the definitions. If you have used Microsoft Access databases, you probably know the system of querying and matching data in different databases. Well, imagine trying to do this with Excel spreadsheets because the databases are not linked. Now you can see why I need to take a data management course and start using platforms other than Excel to manage my data.

A visual interpretation of trying to combine datasets being like matching the English definition to the Spanish translation. (Image source: Enchanted Learning)

In the first dataset, there are 6,136 sightings of Common bottlenose dolphins (Tursiops truncatus) documented in my study area. Some years have no sightings, some years have fewer than 100 sightings, and other years have over 500 sightings. In another dataset, there are 398 bottlenose dolphin biopsy samples collected between the years of 1992-2016 in a genetics database that can provide the sex of the animal. The final dataset contains records of 774 bottlenose dolphin biopsy samples collected between 1993-2018 that could be tested for hormone and/or contaminant levels. Some of these samples have identification numbers that can be matched to the other dataset. Within these cross-reference matches there are conflicting data in terms of amount of tissue remaining for analyses. Sorting these conflicts out will involve more digging from my end and additional communication with collaborators: data wrangling at its best. Circling back to what I mentioned in the beginning of this post, this data was collected by other people over decades and the collection methods were not standardized for my project. I benefit from years of data collection by other scientists and I am grateful for all of their hard work. However, now my hard work begins.

The cutest part of data wrangling: finding adorable images of bottlenose dolphins, photographed during a coastal survey. (Image source: Alexa Kownacki).

There is also a large amount of data that I downloaded from federally-maintained websites. For example, dolphin sighting data from research cruises are available for public access from the OBIS (Ocean Biogeographic Information System) Sea Map website. It boasts 5,927,551 records from 1,096 data sets containing information on 711 species with the help of 410 collaborators. This website is incredible as it allows you to search through different data criteria and then download the data in a variety of formats and contains an interactive map of the data. You can explore this at your leisure, but I want to point out the sheer amount of data. In my case, the OBIS Sea Map website is only one major platform that contains many sources of data that has already been collected, not specifically for me or my project, but will be utilized. As a follow-up to using data collected by other scientists, it is critical to give credit where credit is due. One of the benefits of using this website, is there is information about how to properly credit the collaborators when downloading data. See below for an example:

Example citation for a dataset (Dataset ID: 1201):

Lockhart, G.G., DiGiovanni Jr., R.A., DePerte, A.M. 2014. Virginia and Maryland Sea Turtle Research and Conservation Initiative Aerial Survey Sightings, May 2011 through July 2013. Downloaded from OBIS-SEAMAP (http://seamap.env.duke.edu/dataset/1201) on xxxx-xx-xx.

Citation for OBIS-SEAMAP:

Halpin, P.N., A.J. Read, E. Fujioka, B.D. Best, B. Donnelly, L.J. Hazen, C. Kot, K. Urian, E. LaBrecque, A. Dimatteo, J. Cleary, C. Good, L.B. Crowder, and K.D. Hyrenbach. 2009. OBIS-SEAMAP: The world data center for marine mammal, sea bird, and sea turtle distributions. Oceanography 22(2):104-115

Another federally-maintained data source that boasts more data than I can quantify is the well-known ERDDAP website. After a few Google searches, I finally discovered that the acronym stands for Environmental Research Division’s Data Access Program. Essentially, this the holy grail of environmental data for marine scientists. I have downloaded so much data from this website that Excel cannot open the csv files. Here is yet another reason why young scientists, like myself, need to transition out of using Excel and into data management systems that are developed to handle large-scale datasets. Everything from daily sea surface temperatures collected on every, one-degree of latitude and longitude line from 1981-2015 over my entire study site to Ekman transport levels taken every six hours on every longitudinal degree line over my study area. I will add some environmental variables in species distribution models to see which account for the largest amount of variability in my data. The next step in data selection begins with statistics. It is important to find if there are highly correlated environmental factors prior to modeling data. Learn more about fitting cetacean data to models here.

The ERDAPP website combined all of the average Sea Surface Temperatures collected daily from 1981-2018 over my study site into a graphical display of monthly composites. (Image Source: ERDDAP)

As you can imagine, this amount of data from many sources and collaborators is equal parts daunting and exhilarating. Before I even begin the process of determining the spatial and temporal spread of dolphin sightings data, I have to identify which data points have sex identified from either hormone levels or genetics, which data points have contaminants levels already quantified, which samples still have tissue available for additional testing, and so on. Once I have cleaned up the datasets, I will import the data into the R programming package. Then I can visualize my data in plots, charts, and graphs; this will help me identify outliers and potential challenges with my data, and, hopefully, start to see answers to my focal questions. Only then, can I dive into the deep and exciting waters of species distribution modeling and more advanced statistical analyses. This is data wrangling and I am the data detective.

What people may think a ‘data detective’ looks like, when, in reality, it is a person sitting at a computer. (Image source: Elder Research)

Like the well-known phrase, “With great power comes great responsibility”, I believe that with great data, comes great responsibility, because data is power. It is up to me as the scientist to decide which data is most powerful at answering my questions.

Data is information. Information is knowledge. Knowledge is power. (Image source: thedatachick.com)

 

Looking Back: Three Years After Grad School

By Courtney Hann (NOAA Fisheries, West Coast Sustainable Fisheries Division)

Thinking back, as Leigh’s first M.Sc. student for the GEMM Lab, I wonder what poignant insight could have prepared me for my future endeavors. And having faced years of perseverance and dedication in the face of professional unknowns, perhaps the answer is none at all; fore maybe it was the many unknown challenges met that led me to where I am today.

I graduated in December of 2015, with my Masters in Marine Resource Management, and stamped completion of my research with the GEMM Lab. While my research focused on marine mammals, my broader love for the Earth’s oceans and lands guided my determination to help keep our planet’s precious ecosystem resources wild and free. So when I landed a position in terrestrial ecology after graduating, I chose to embrace the challenging decision of jumping away from theoretical research and moving back towards applied research. Consequently, I fell in love with botany, moth identification, birding, and explored the unknowns of a whole new world of conservation biology in Scotland with the Royal Society for the Protection of Birds. Not only was this work incredibly fun, interesting, and spontaneous, it offered me an opportunity to take my knowledge of developing research projects and apply it to nature reserve management. Every survey I completed and dataset I analyzed provided information required to determine the next land management steps for maximizing the conservation of rare and diverse species. From the GEMM Lab, I brought skills on: how to work through what, at times, seemed like an impassible barrier, complete tasks efficiently under a tight deadline, juggle multiple activities and obligations, and still make time to ponder the importance of seeing the bigger picture, while having fun learning new things.

Above: Botanizing and birding in Scotland with the best botanist I have ever known and my boss, Jeff Waddell, with the Royal Society for the Protection of Birds.

For me, the long game of seeing the bigger picture has always been key. And at the end of the day, I remained steadfast in answering the questioned I posed myself: Why do all of this work if not to make a truly positive impact? With that in mind, and with an expiring visa, I moved back to the West Coast of the U.S. and landed a contracting position with NOAA Fisheries. Where I met my second female mentor, Heidi Taylor, who inspired me beyond words and introduced me to the amazing world of fisheries management. All the while, I kept working my second part-time job with the West Coast Regional Planning Body (now called the West Coast Ocean Alliance, WCOA). Working two jobs allowed me to not only accelerate my learning capacity through more opportunities, but also allowed me to extend the reach of growing a positive impact.  For example, I learned about coordinating region-wide ocean management, facilitation of diverse groups, and working with tribes, states, and federal agencies while working for the WCOA. While there were moments that I struggled with overworking and fatigue, my training in graduate school to persevere really kicked in. Driven by the desire to attain a permanent position that complimented my talents and determination to provide sustained help for our Earth’s ecosystems, I worked for what sometimes felt endlessly to reach my goal. Getting there was tough, but well worth it!

One of the most challenging aspects for me was finishing my last publication for the GEMM Lab. I was no longer motivated by the research, since my career path had taken a different turn, and I was already burnt out form working overtime every week. Therefore, if it was not for Leigh’s encouraging words, the promise I made to her to complete the publication, and my other co-author’s invitation to submit a paper for a particular journal, then I likely would have thrown in the towel. I had to re-do the analysis several times, had the paper rejected once, and then ended up re-writing and re-structuring the entire paper for the final publication. In total, it took me two and half years and 100s of hours to complete this paper after graduating. Of course, there was no funding, so I felt a bit like an ongoing graduate student until the paper was finally accepted and the work complete. But the final acceptance of the paper was so sweet, and after years of uncertain challenges, a heavy weight had finally been lifted. So perhaps, if there is one piece of advice I would say to young graduate students, it is to get your work published before you graduate! I had one paper and one book chapter published before I graduated, and that made my life much easier. While I am proud for finishing the final third publication, I would have much preferred to have just taken one extra semester and finished that publication while in school. But regardless, it was completed. And in a catharsis moment, maybe the challenge of completing it taught me the determination I needed to persevere through difficult situations.

Above: Elephant seal expressing my joy of finishing that last publication! Wooohoooooo!

With that publication out of the way, I was able to focus more time on my career. While I no longer use R on a daily basis and do not miss the hours of searching for that one pesky bug, I do analyze, critique, and use scientific literature everyday. Moreover, the critical thinking, creative, and collaborative skills I honed in the GEMM Lab, have been and will be useful for the rest of my life. Those hours of working through complicated statistical analyses and results in Leigh’s office pay off everyday. Reading outside of work, volunteering and working second jobs, all of this I learned from graduate school. Carrying this motivation, hard work, determination, and perseverance on past graduate school was undeniably what led me to where I am today. I have landed my dream job, working for NOAA Fisheries Sustainable Fisheries Division on salmon management and policy, in my dream location, the Pacific Northwest.  My work now ties directly into ongoing management and policy that shapes our oceans, conservation efforts, and fisheries management. I am grateful for all the people who have supported me along the way, with this blog post focusing on the GEMM Lab and Leigh Torres as my advisor. I hope to be a mentor and guide for others along their path, as so many have helped me along mine. Good luck to any grad student reading this now! But more than luck, carry passion and determination forward because that is what will propel you onward on your own path. Thank you GEMM Lab, it is now time for me to enjoy my new job.

Above: Enjoying in my new home in the Pacific Northwest.

 

 

 

Over the Ocean and Under the Bridges: STEM Cruise on the R/V Oceanus

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

From September 22nd through 30th, the GEMM Lab participated in a STEM research cruise aboard the R/V Oceanus, Oregon State University’s (OSU) largest research vessel, which served as a fully-functioning, floating, research laboratory and field station. The STEM cruise focused on integrating science, technology, engineering and mathematics (STEM) into hands-on teaching experiences alongside professionals in the marine sciences. The official science crew consisted of high school teachers and students, community college students, and Oregon State University graduate students and professors. As with a usual research cruise, there was ample set-up, data collection, data entry, experimentation, successes, and failures. And because everyone in the science party actively participated in the research process, everyone also experienced these successes, failures, and moments of inspiration.

The science party enjoying the sunset from the aft deck with the Astoria-Megler bridge in the background. (Image source: Alexa Kownacki)

Dr. Leigh Torres, Dr. Rachael Orben, and I were all primarily stationed on flybridge—one deck above the bridge—fully exposed to the elements, at the highest possible location on the ship for best viewing. We scanned the seas in hopes of spotting a blow, a splash, or any sign of a marine mammal or seabird. Beside us, students and teachers donned binoculars and positioned themselves around the mast, with Leigh and I taking a 90-degree swath from the mast—either to starboard or to port. For those who had not been part of marine mammal observations previously, it was a crash course into the peaks and troughs—of both the waves and of the sightings. We emphasized the importance of absence data: knowledge of what is not “there” is equally as important as what is. Fortunately, Leigh chose a course that proved to have surprisingly excellent environmental conditions and amazing sightings. Therefore, we collected a large amount of presence data: data collected when marine mammals or seabirds are present.

High school student, Chris Quashnick Holloway, records a seabird sighting for observer, Dr. Rachael Orben. (Image source: Alexa Kownacki).

When someone sighted a whale that surfaced regularly, we assessed the conditions: the sea state, the animal’s behavior, the wind conditions, etc. If we deemed them as “good to fly”, our licensed drone pilot and Orange Coast Community College student, Jason, prepared his Phantom 4 drone. While he and Leigh set up drone operations, I and the other science team members maintained a visual on the whale and stayed in constant communication with the bridge via radio. When the drone was ready, and the bridge gave the “all clear”, Jason launched his drone from the aft deck. Then, someone tossed an unassuming, meter-long, wood plank overboard—keeping it attached to the ship with a line. This wood board serves as a calibration tool; the drone flies over it at varying heights as determined by its built-in altimeter. Later, we analyze how many pixels one meter occupied at different heights and can thereby determine the body length of the whale from still images by converting pixel length to a metric unit.

High school student, Alishia Keller, uses binoculars to observe a whale, while PhD student, Alexa Kownacki, radios updates on the whale’s location to the bridge and the aft deck. (Image source: Tracy Crews)

Finally, when the drone is calibrated, I radio the most recent location of our animal. For example, “Blow at 9 o’clock, 250 meters away”. Then, the bridge and I constantly adjust the ship’s speed and location. If the whale “flukes” (dives and exposes the ventral side of its tail), and later resurfaced 500 meters away at our 10 o’clock, I might radio to the bridge to, “turn 60 degrees to port and increase speed to 5 knots”. (See the Hidden Math Lesson below). Jason then positions the drone over the whale, adjusting the camera angle as necessary, and recording high-quality video footage for later analysis. The aerial viewpoint provides major advantages. Whales usually expose about 10 percent of their body above the water’s surface. However, with an aerial vantage point, we can see more of the whale and its surroundings. From here, we can observe behaviors that are otherwise obscured (Torres et al. 2018), and record footage that to help quantify body condition (i.e. lengths and girths). Prior to the batteries running low, Jason returns the drone back to the aft deck, the vessel comes to an idle, and Leigh catches the drone. Throughout these operations, those of us on the flybridge photograph flukes for identification and document any behaviors we observe. Later, we match the whale we sighted to the whale that the drone flew over, and then to prior sightings of this same individual—adding information like body condition or the presence of a calf. I like to think of it as whale detective work. Moreover, it is a team effort; everyone has a critical role in the mission. When it’s all said and done, this noninvasive approach provides life history context to the health and behaviors of the animal.

Drone pilot, Jason Miranda, flying his drone using his handheld ground station on the aft deck. (Photo source: Tracy Crews)

Hidden Math Lesson: The location of 10 o’clock and 60 degrees to port refer to the exact same direction. The bow of the ship is our 12 o’clock with the stern at our 6 o’clock; you always orient yourself in this manner when giving directions. The same goes for a compass measurement in degrees when relating the direction to the boat: the bow is 360/0. An angle measure between two consecutive numbers on a clock is: 360 degrees divided by 12-“hour” markers = 30 degrees. Therefore, 10 o’clock was 0 degrees – (2 “hours”)= 0 degrees- (2*30 degrees)= -60 degrees. A negative degree less than 180 refers to the port side (left).

Killer whale traveling northbound.

Our trip was chalked full of science and graced with cooperative weather conditions. There were more highlights than I could list in a single sitting. We towed zooplankton nets under the night sky while eating ice cream bars; we sang together at sunset and watched the atmospheric phenomena: the green flash; we witnessed a humpback lunge-feeding beside the ship’s bow; and we saw a sperm whale traveling across calm seas.

Sperm whale surfacing before a long dive.

On this cruise, our lab focused on the marine mammal observations—which proved excellent during the cruise. In only four days of surveying, we had 43 marine mammal sightings containing 362 individuals representing 9 species (See figure 1). As you can see from figure 2, we traveled over shallow, coastal and deep waters, in both Washington and Oregon before inland to Portland, OR. Because we ventured to areas with different bathymetric and oceanographic conditions, we increased our likelihood of seeing a higher diversity of species than we would if we stayed in a single depth or area.

Humpback whale lunge feeding off the bow.

Number of sightings Total number of individuals
Humpback whale 22 40
Pacific white-sided dolphin 3 249
Northern right whale dolphin 1 9
Killer whale 1 3
Dall’s porpoise 5 49
Sperm whale 1 1
Gray whale 1 1
Harbor seal 1 1
California sea lion 8 9
Total 43 362

Figure 1. Summary table of all species sightings during cruise while the science team observed from the flybridge.

Pacific white-sided dolphins swimming towards the vessel.

Figure 2. Map with inset displaying study area and sightings observed by species during the cruise, made in ArcMap. (Image source: Alexa Kownacki).

Even after two days of STEM outreach events in Portland, we were excited to incorporate more science. For the transit from Portland, OR to Newport, OR, the entire science team consisted two people: me and Jason. But even with poor weather conditions, we still used science to answer questions and help us along our journey—only with different goals than on our main leg. With the help of the marine technician, we set up a camera on the bow of the ship, facing aft to watch the vessel maneuver through the famous Portland bridges.

Video 1. Time-lapse footage of the R/V Oceanus maneuvering the Portland Bridges from a GoPro. Compiled by Alexa Kownacki, assisted by Jason Miranda and Kristin Beem.

Prior to the crossing the Columbia River bar and re-entering the Pacific Ocean, the R/V Oceanus maneuvered up the picturesque Columbia River. We used our geospatial skills to locate our fellow science team member and high school student, Chris, who was located on land. We tracked each other using GPS technology in our cell phones, until the ship got close enough to use natural landmarks as reference points, and finally we could use our binoculars to see Chris shining a light from shore. As the ship powered forward and passed under the famous Astoria-Megler bridge that connects Oregon to Washington, Chris drove over it; he directed us “100 degrees to port”. And, thanks to clear directions, bright visual aids, and spatiotemporal analysis, we managed to find our team member waving from shore. This is only one of many examples that show how in a few days at sea, students utilized new skills, such as marine mammal observational techniques, and honed them for additional applications.

On the bow, Alexa and Jason use binoculars to find Chris–over 4 miles–on the Washington side of the Columbia River. (Image source: Kristin Beem)

Great science is the result of teamwork, passion, and ingenuity. Working alongside students, teachers, and other, more-experienced scientists, provided everyone with opportunities to learn from each other. We created great science because we asked questions, we passed on our knowledge to the next person, and we did so with enthusiasm.

High school students, Jason and Chris, alongside Dr. Leigh Torres, all try to get a glimpse at the zooplankton under Dr. Kim Bernard’s microscope. (Image source: Tracy Crews).

Check out other blog posts written by the science team about the trip here.

The Recipe for a “Perfect” Marine Mammal and Seabird Cruise

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

Science—and fieldwork in particular—is known for its failures. There are websites, blogs, and Twitter pages dedicated to them. This is why, when things go according to plan, I rejoice. When they go even better than expected, I practically tear up from amazement. There is no perfect recipe for a great marine mammal and seabird research cruise, but I would suggest that one would look like this:

 A Great Marine Mammal and Seabird Research Cruise Recipe:

  • A heavy pour of fantastic weather
    • Light on the wind and seas
    • Light on the glare
  • Equal parts amazing crew and good communication
  • A splash of positivity
  • A dash of luck
  • A pinch of delicious food
  • Heaps of marine mammal and seabird sightings
  • Heat to approximately 55-80 degrees F and transit for 10 days along transects at 10-12 knots

The end of another beautiful day at sea on the R/V Shimada. Image source: Alexa K.

The Northern California Current Ecosystem (NCCE) is a highly productive area that is home to a wide variety of cetacean species. Many cetaceans are indicator species of ecosystem health as they consume large quantities of prey from different levels in trophic webs and inhabit diverse areas—from deep-diving beaked whales to gray whales traveling thousands of miles along the eastern north Pacific Ocean. Because cetacean surveys are a predominant survey method in large bodies of water, they can be extremely costly. One alternative to dedicated cetacean surveys is using other research vessels as research platforms and effort becomes transect-based and opportunistic—with less flexibility to deviate from predetermined transects. This decreases expenses, creates collaborative research opportunities, and reduces interference in animal behavior as they are never pursued. Observing animals from large, motorized, research vessels (>100ft) at a steady, significant speed (>10kts/hour), provides a baseline for future, joint research efforts. The NCCE is regularly surveyed by government agencies and institutions on transects that have been repeated nearly every season for decades. This historical data provides critical context for environmental and oceanographic dynamics that impact large ecosystems with commercial and recreational implications.

My research cruise took place aboard the 208.5-foot R/V Bell M. Shimada in the first two weeks of May. The cruise was designated for monitoring the NCCE with the additional position of a marine mammal observer. The established guidelines did not allow for deviation from the predetermined transects. Therefore, mammals were surveyed along preset transects. The ship left port in San Francisco, CA and traveled as far north as Cape Meares, OR. The transects ranged from one nautical mile from shore and two hundred miles offshore. Observations occurred during “on effort” which was defined as when the ship was in transit and moving at a speed above 8 knots per hour dependent upon sea state and visibility. All observations took place on the flybridge during conducive weather conditions and in the bridge (one deck below the flybridge) when excessive precipitation was present. The starboard forward quarter: zero to ninety degrees was surveyed—based on the ship’s direction (with the bow at zero degrees). Both naked eye and 7×50 binoculars were used with at least 30 percent of time binoculars in use. To decrease observer fatigue, which could result in fewer detected sightings, the observer (me) rotated on a 40 minutes “on effort”, 20 minutes “off effort” cycle during long transits (>90 minutes).

Alexa on-effort using binoculars to estimate the distance and bearing of a marine mammal sighted off the starboard bow. Image source: Alexa K.

Data was collected using modifications to the SEEbird Wincruz computer program on a ruggedized laptop and a GPS unit was attached. At the beginning of each day and upon changes in conditions, the ship’s heading, weather conditions, visibility, cloud cover, swell height, swell direction, and Beaufort sea state (BSS) were recorded. Once the BSS or visibility was worse than a “5” (1 is “perfect” and 5 is “very poor”) observations ceased until there was improvement in weather. When a marine mammal was sighted the latitude and longitude were recorded with the exact time stamp. Then, I noted how the animal was sighted—either with binoculars or naked eye—and what action was originally noticed—blow, splash, bird, etc. The bearing and distance were noted using binoculars. The animal was given three generalized behavior categories: traveling, feeding, or milling. A sighting was defined as any marine mammal or group of animals. Therefore, a single sighting would have the species and the best, high, and low estimates for group size.

By my definitions, I had the research cruise of my dreams. There were moments when I imagined people joining this trip as a vacation. I *almost* felt guilty. Then, I remember that after watching water for almost 14 hours (thanks to the amazing weather conditions), I worked on data and reports and class work until midnight. That’s the part that no one talks about: the data. Fieldwork is about collecting data. It’s both what I live for and what makes me nervous. The amount of time, effort, and money that is poured into fieldwork is enormous. The acquisition of the data is not as simple as it seems. When I briefly described my position on this research cruise to friends, they interpret it to be something akin to whale-watching. To some extent, this is true. But largely, it’s grueling hours that leave you fatigued. The differences between fieldwork and what I’ll refer to as “everything else” AKA data analysis, proposal writing, manuscript writing, literature reviewing, lab work, and classwork, are the unbroken smile, the vaguely tanned skin, the hours of laughter, the sea spray, and the magical moments that reassure me that I’ve chosen the correct career path.

Alexa photographing a gray whale at sunset near Newport, OR. Image source: Alexa K.

This cruise was the second leg of the Northern California Current Ecosystem (NCCE) survey, I was the sole Marine Mammal and Seabird Observer—a coveted position. Every morning, I would wake up at 0530hrs, grab some breakfast, and climb to the highest deck: the fly-bridge. Akin to being on the top of the world, the fly-bridge has the best views for the widest span. From 0600hrs to 2000hrs I sat, stood, or danced in a one-meter by one-meter corner of the fly-bridge and surveyed. This visual is why people think I’m whale watching. In reality, I am constantly busy. Nonetheless, I had weather and seas that scientists dream about—and for 10 days! To contrast my luck, you can read Florence’s blog about her cruise. On these same transects, in February, Florence experienced 20-foot seas with heavy rain with very few marine mammal sightings—and of those, the only cetaceans she observed were gray whales close to shore. That starkly contrasts my 10 cetacean species with upwards of 45 sightings and my 20-minute hammock power naps on the fly-bridge under the warm sun.

Pacific white-sided dolphins traveling nearby. Image source: Alexa K.

Marine mammal sightings from this cruise included 10 cetacean species: Pacific white-sided dolphin, Dall’s porpoise, unidentified beaked whale, Cuvier’s beaked whale, gray whale, Minke whale, fin whale, Northern right whale dolphin, blue whale, humpback whale, and transient killer whale and one pinniped species: northern fur seal. What better way to illustrate these sightings than with a map? We are a geospatial lab after all.

Cetacean Sightings on the NCCE Cruise in May 2018. Image source: Alexa K.

This map is the result of data collection. However, it does not capture everything that was observed: sea state, weather, ocean conditions, bathymetry, nutrient levels, etc. There are many variables that can be added to maps–like this one (thanks to my GIS classes I can start adding layers!)–that can provide a better understanding of the ecosystem, predator-prey dynamics, animal behavior, and population health.

The catch from a bottom trawl at a station with some fish and a lot of pyrosomes (pink tube-like creatures). Image source: Alexa K.

Being a Ph.D. student can be physically and mentally demanding. So, when I was offered the opportunity to hone my data collection skills, I leapt for it. I’m happiest in the field: the wind in my face, the sunshine on my back, surrounded by cetaceans, and filled with the knowledge that I’m following my passion—and that this data is contributing to the greater scientific community.

Humpback whale photographed traveling southbound. Image source: Alexa K.

Managing Oceans: the inner-workings of marine policy

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

When we hear “marine policy” we broadly lump it together with environmental policy. However, marine ecosystems differ greatly from their terrestrial counterparts. We wouldn’t manage a forest like an ocean, nor would we manage an ocean like a forest. Why not? The answer to this question is complex and involves everything from ecology to politics.

Oceans do not have borders; they are fluid and dynamic. Interestingly, by defining marine ecosystems we are applying some kind of borders. But water (and all its natural and unnatural content) flows between these ‘ecosystems’. Marine ecosystems are home to a variety of anthropogenic activities such as transportation and recreation, in addition to an abundance of species that represent the three major domains of biology: Archaea, Bacteria, and Eukarya. Humans are the only creatures who “recognize” the borders that policymakers and policy actors have instilled. A migrating gray whale does not have a passport stamped as it travels from its breeding grounds in Mexican waters to its feeding grounds in the Gulf of Alaska. In contrast, a large cargo ship—or even a small sailing vessel—that crosses those boundaries is subjected to a series of immigration checkpoints. Combining these human and the non-human facets makes marine policy complex and variable.

The eastern Pacific gray whale migration route includes waters off of Mexico, Canada, and the United States. Source: https://www.learner.org/jnorth/tm/gwhale/annual/map.html

Environmental policy of any kind can be challenging. Marine environmental policy adds many more convoluted layers in terms of unknowns; marine ecosystems are understudied relative to terrestrial ecosystems and therefore have less research conducted on how to best manage them. Additionally, there are more hands in the cookie jar, so to speak; more governments and more stakeholders with more opinions (Leslie and McLeod 2007). So, with fewer examples of successful ecosystem-based management in coastal and marine environments and more institutions with varied goals, marine ecosystems become challenging to manage and monitor.

A visual representation of what can happen when there are many groups with different goals: no one can easily get what they want. Image Source: The Brew Monks

With this in mind, it is understandable that there is no official manual on policy development.  There is, however, a broadly standardized process of how to develop, implement, and evaluate environmental policies: 1) recognize a problem 2) propose a solution 3) choose a solution 4) put the solution into effect and 4) monitor the results (Zacharias pp. 16-21). For a policy to be deemed successful, specific criteria must be met, which means that a common policy is necessary for implementation and enforcement. Within the United States, there are a multiple governing bodies that protect the ocean, including the National Oceanic and Atmospheric Administration (NOAA), Environmental Protection Agency (EPA), Fish and Wildlife Service (USFWS), and the Department of Defense (DoD)—all of which have different mission statements, budgets, and proposals. To create effective environmental policies, collaboration between various groups is imperative. Nevertheless, bringing these groups together, even those within the same nation, requires time, money, and flexibility.

This is not to say that environmental policy for terrestrial systems, but there are fewer moving parts to manage. For example, a forest in the United States would likely not be an international jurisdiction case because the borders are permanent lines and national management does not overlap. However, at a state level, jurisdiction may overlap with potentially conflicting agendas. A critical difference in management strategies is preservation versus conservation. Preservation focuses on protecting nature from use and discourages altering the environment. Conservation, centers on wise-use practices that allow for proper human use of environments such as resource use for economic groups. One environmental group may believe in preservation, while one government agency may believe in conservation, creating friction amongst how the land should be used: timber harvest, public use, private purchasing, etc.

Linear representation of preservation versus conservation versus exploitation. Image Source: Raoof Mostafazadeh

Furthermore, a terrestrial forest has distinct edges with measurable and observable qualities; it possesses intrinsic and extrinsic values that are broadly recognized because humans have been utilizing them for centuries. Intrinsic values are things that people can monetize, such as commercial fisheries or timber harvests whereas extrinsic values are things that are challenging to put an actual price on in terms of biological diversity, such as the enjoyment of nature or the role of species in pest management; extrinsic values generally have a high level of human subjectivity because the context of that “resource” in question varies upon circumstances (White 2013). Humans are more likely to align positively with conservation policies if there are extrinsic benefits to them; therefore, anthropocentric values associated with the resources are protected (Rode et al. 2015). Hence, when creating marine policy, monetary values are often placed on the resources, but marine environments are less well-studied due to lack of accessibility and funding, making any valuation very challenging.

The differences between direct (intrinsic) versus indirect (extrinsic) values to biodiversity that factor into environmental policy. Image Source: Conservationscienceblog.wordpress.com

Assigning a cost or benefit to environmental services is subjective (Dearborn and Kark 2010). What is the benefit to a child seeing an endangered killer whale for the first time? One could argue priceless. In order for conservation measures to be implemented, values—intrinsic and extrinsic—are assigned to the goods and services that the marine environment provides—such as seafood and how the ocean functions as a carbon sink. Based off of the four main criteria used to evaluate policy, the true issue becomes assessing the merit and worth. There is an often-overlooked flaw with policy models: it assumes rational behavior (Zacharias 126). Policy involves relationships and opinions, not only the scientific facts that inform them; this is true in terrestrial and marine environments. People have their own agendas that influence, not only the policies themselves, but the speed at which they are proposed and implemented.

Tourists aboard a whale-watching vessel off of the San Juan Islands, enjoying orca in the wild. Image Source: Seattle Orca Whale Watching

One example of how marine policy evolves is through groups, such as the International Whaling Commission, that gather to discuss such policies while representing many different stakeholders. Some cultures value the whale for food, others for its contributions to the surrounding ecosystems—such as supporting healthy seafood populations. Valuing one over the other goes beyond a monetary value and delves deeper into the cultures, politics, economics, and ethics. Subjectivity is the name of the game in environmental policy, and, in marine environmental policy, there are many factors unaccounted for, that decision-making is incredibly challenging.

Efficacy in terms of the public policy for marine systems presents a challenge because policy happens slowly, as does research. There is no equation that fits all problems because the variables are different and dynamic; they change based on the situation and can be unpredictable. When comparing institutional versus impact effectiveness, they both are hard to measure without concrete goals (Leslie and McLeod 2007). Marine ecosystems are open environments which add an additional hurdle: setting measurable and achievable goals. Terrestrial environments contain resources that more people utilize, more frequently, and therefore have more set goals. Without a problem and potential solution there is no policy. Terrestrial systems have problems that humans recognize. Marine systems have problems that are not as visible to people on a daily basis. Therefore, terrestrial systems have more solutions presented to mitigate problems and more policies enacted.

As marine scientists, we don’t always immediately consider how marine policy impacts our research. In the case of my project, marine policy is something I constantly have to consider. Common bottlenose dolphins are protected under the Marine Mammal Protection Act (MMPA) and inhabit coastal of both the United States and Mexico, including within some Marine Protected Areas (MPA). In addition, some funding for the project comes from NOAA and the DoD. Even on the surface-level it is clear that policy is something we must consider as marine scientists—whether we want to or not. We may do our best to inform policymakers with results and education based on our research, but marine policy requires value-based judgements based on politics, economics, and human objectivity—all of which are challenging to harmonize into a succinct problem with a clear solution.

Two common bottlenose dolphins (coastal ecotype) traveling along the Santa Barbara, CA shoreline. Image Source: Alexa Kownacki

References:

Dearborn, D. C. and Kark, S. 2010. Motivations for Conserving Urban Biodiversity. Conservation Biology, 24: 432-440. doi:10.1111/j.1523-1739.2009.01328.x

Leslie, H. M. and McLeod, K. L. (2007), Confronting the challenges of implementing marine ecosystem‐based management. Frontiers in Ecology and the Environment, 5: 540-548. doi:10.1890/060093

Munguia, P., and A. F. Ojanguren. 2015. Bridging the gap in marine and terrestrial studies. Ecosphere 6(2):25. http://dx.doi.org/10.1890/ES14-00231.1

Rode, J., Gomez-Baggethun, E., Krause, M., 2015. Motivation crowding by economic payments in conservation policy: a review of the empirical evidence. Ecol. Econ. 117, 270–282 (in this issue).

White, P. S. (2013), Derivation of the Extrinsic Values of Biological Diversity from Its Intrinsic Value and of Both from the First Principles of Evolution. Conservation Biology, 27: 1279-1285. doi:10.1111/cobi.12125

Zacharias, M. 2014. Marine Policy. London: Routledge.