Month: March 2019

More data, more questions, more projects: There’s always more to learn

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

As you may have read in previous blog posts, my research focuses on the ecology of blue whales in New Zealand. Through my MS research and years of work by a dedicated team, we were able to document and describe a population of around 700 blue whales that are unique to New Zealand, present year-round, and genetically distinct from all other known populations [1]. While this is a very exciting discovery, documenting this population has also unlocked a myriad of further questions about these whales. Can we predict when and where the whales are most likely to be? How does their distribution change seasonally? How often do they overlap with anthropogenic activity? My PhD research will aim to answer these questions through models of blue whale distribution patterns relative to their environment at multiple spatial and temporal scales.

Because time at sea for vessel-based surveys is cost-limited and difficult to come by, it is in any scientist’s best interest to collect as many concurrent streams of data as possible while in the field. When Dr. Leigh Torres designed our blue whale surveys that were conducted in 2014, 2016, and 2017, she really did a miraculous job of maximizing time on the water. With more data, more questions can be asked. These complimentary datasets have led to the pursuit of many “side projects”. I am lucky enough to work on these questions in parallel with what will form the bulk of my PhD, and collaborate with a number of people in the process. In this blog post, I’ll give you some short teasers of these “side projects”!

Surface lunge feeding as a foraging strategy for New Zealand blue whales

Most of what we know about blue whale foraging behavior comes from studies conducted off the coast of Southern California[2,3] using suction cup accelerometer tags. While these studies in the California Current ecosystem have led to insights and breakthroughs in our understanding of these elusive marine predators and their prey, they have also led us to adopt the paradigm that krill patches are denser at depth, and blue whales are most likely to target these deep prey patches when they feed. We have combined our prey data with blue whale behavioral data observed via a drone to investigate blue whale foraging in New Zealand, with a particular emphasis on surface feeding as a strategy. In our recent analyses, we are finding that in New Zealand, lunge feeding at the surface may be more than just “snacking”. Rather, it may be an energetically efficient strategy that blue whales have evolved in the region with unique implications for conservation.

Figure 1. A blue whale lunges on an aggregation of krill. UAS piloted by Todd Chandler.

Combining multiple data streams for a comprehensive health assessment

In the field, we collected photographs, blubber biopsy samples, fecal samples, and conducted unmanned aerial system (UAS, a.k.a. “drone”) flights over blue whales. The blubber and fecal samples can be analyzed for stress and reproductive hormone levels; UAS imagery allows us to quantify a whale’s body condition[4]; and photographs can be used to evaluate skin condition for abnormalities. By pulling together these multiple data streams, this project aims to establish a baseline understanding of the variability in stress and reproductive hormone levels, body condition, and skin condition for the population. Because our study period spans multiple years, we also have the ability to look at temporal patterns and individual changes over time. From our preliminary results, we have evidence for multiple pregnant females from elevated pregnancy and stress hormones, as well as apparent pregnancy from the body condition analysis. Additionally, a large proportion of the population appear to be affected by blistering and cookie cutter shark bites.

Figure 2. An example aerial drone image of a blue whale that will be used to asses body condition, i.e. how healthy or malnourished the whale is. (Drone piloted by Todd Chandler).
Figure 3. Images of blue whale skin condition, affected by A) blistering and B) cookie cutter shark bites.

Comparing body shape and morphology between species

The GEMM Lab uses UAS to quantitatively study behavior[5] and health of large whales. From various projects in different parts of the world we have now assimilated UAS data on blue, gray, and humpback whales. We will measure these images to investigate differences in body shape and morphology among these species. We plan to explore how form follows function across baleen whales, based on their different  life histories, foraging strategies, and ecological roles.

Figure 4 . Aerial images of A) a blue whale in New Zealand’s South Taranaki Bight, B) a gray whale off the coast of Oregon, and C) a humpback whale off the coast of Washington. Drone piloted by Todd Chandler (A and B) and Jason Miranda (C). 

So it goes—my dissertation will contain a series of chapters that build on one another to explore blue whale distribution patterns at increasing scales, as well as a growing number of appendices for these “side projects”. Explorations and collaborations like I’ve described here allow me to broaden my perspectives and diversify my analytical skills, as well as work with many excellent teams of scientists. The more data we collect, the more questions we are able to ask. The more questions we ask, the more we seem to uncover that is yet to be understood. So stay tuned for some exciting forthcoming results from all of these analyses, as well as plenty of new questions, waiting to be posed.

References

  1. Barlow DR et al. 2018 Documentation of a New Zealand blue whale population based on multiple lines of evidence. Endanger. Species Res. 36, 27–40. (doi:https://doi.org/10.3354/esr00891)
  2. Hazen EL, Friedlaender AS, Goldbogen JA. 2015 Blue whales (Balaenoptera musculus) optimize foraging efficiency by balancing oxygen use and energy gain as a function of prey density. Sci. Adv. 1, e1500469–e1500469. (doi:10.1126/sciadv.1500469)
  3. Goldbogen JA, Calambokidis J, Oleson E, Potvin J, Pyenson ND, Schorr G, Shadwick RE. 2011 Mechanics, hydrodynamics and energetics of blue whale lunge feeding: efficiency dependence on krill density. J. Exp. Biol. 214, 131–146. (doi:10.1242/jeb.048157)
  4. Burnett JD, Lemos L, Barlow DR, Wing MG, Chandler TE, Torres LG. 2018 Estimating morphometric attributes on baleen whales using small UAS photogrammetry: A case study with blue and gray whales. Mar. Mammal Sci. (doi:10.1111/mms.12527)
  5. Torres LG, Nieukirk SL, Lemos L, Chandler TE. 2018 Drone Up! Quantifying Whale Behavior From a New Perspective Improves Observational Capacity. Front. Mar. Sci. 5. (doi:10.3389/fmars.2018.00319)

Signs you’re an ecologist – you don’t spend nearly enough time geeking out about your study species…

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

This past week has been very busy for me as I gave three quite important, yet very different, presentations. The first was on Tuesday at the Pacific High School in Port Orford, near my study site. The aim of the game was recruitment – my quest for two eager local high schoolers to be my interns for this 2019 summer field season has begun (read blogs written by our 2017 HS interns Nathan Malamud and Quince Nye)! I was lucky enough to be given an entire class period to talk to the students and so I hope that the picture I painted of kayaks, gray whales and sun will be enough to entice students to apply to the internship.

The second was a short presentation in one of the classes I took this term, GEOG 561: GIScience II Analysis and Applications. The class focuses on developing and conducting geospatial analyses in R and throughout the term each student develops a small independent research project using some of their own data. For my research project, I decided to do a small cluster analysis of the zooplankton community data that we have collected from the kayak net samples.

The third and final presentation of the week happened on Thursday and marked one of the big milestones on my Master’s journey: my research review. The research review is a mandatory (and extremely helpful) process in the Department of Fisheries & Wildlife where the student (in this case me), the committee (Dr Leigh Torres, Dr Rachael Orben, Dr Kim Bernard and Dr Susanne Brander) and a department representative (Dr Brian Sidlauskas) all assemble to discuss the student’s research proposal, which lays out the intended work, chapters, analysis and timeline for the students’ thesis. My proposal (which currently bears the title: “Tonight’s specials include mysids, gammarids and more: An examination of the zooplankton prey of Oregon gray whales and its impact on individual foraging patterns”) proposes a two-chapter thesis where the first examines the quality of zooplankton prey, while the second looks at potential individual foraging specialization of gray whales along the Oregon coast. While my entire committee agreed that what I have set forth to do in the next two or so years is ambitious, they provided me with excellent feedback and confidence that I would be able to achieve what I have planned.

Now that it’s the weekend and I’ve had some time to sit back and think about the week, I realized one major commonality between all three presentations I gave. None of the Powerpoints featured more than one image of a gray whale. How could this be?! It is after all my study species and I spend so much of my summer looking at them – how could it be that so little of what I showed and talked about was the thing that I am most passionate about and is so central to my research?

In the course of doing research, it’s easy to get wound up in the nitty gritty and forget about the big picture. While the nitty gritty is also imperative to conducting the research (and ultimately getting results), I sometimes forget about why I do what I do, which is that gray whales are AWESOME. Looking into the past, it seems that some of my lab mates have had the same realizations about their study species before too: see here and here. So for this blog, I want to bring it back to basics and share some of the things that I think are most fascinating about gray whales.

  1. Gray whales are the only baleen whale that feeds benthically. This behavior is facilitated by the shorter and tougher baleen that gray whales possess in comparison to other baleen whale species (Pivorunas 1979). The majority of the Eastern North Pacific (ENP) gray whale population feeds benthically in the Bering Sea where they eat ampeliscid amphipods, which are a type of benthic invertebrates (Nerini 1984). It is estimated that gray whales must regain 11-29% of critical body mass during the feeding season (Villegas-Amtmann et al. 2015) in order to obtain the energy stores they require for the entire year. Besides the personal benefit of sea floor foraging, by using this feeding tactic gray whales create depressions in the soft sediment that benefit other species besides themselves. The highly disruptive nature of this action can increase the biodiversity of the seafloor and initiate scavenging events by lysiannassid amphipods on other infauna (Oliver & Slattery 1985). Furthermore, Grebmeier & Harrison (1992) documented that a variety of seabirds including northern fulmars, black-legged kittiwakes and thick-billed murres feed on benthic amphipods brought to the surface by this unique foraging behavior performed by gray whales.
  1. Gray whales are essentially acrobats. A preference for benthic prey goes hand in hand with a preference for shallow, coastal waters, as for example Pacific Coast Feeding Group gray whales tend to forage within the 5-15 m depth range (Weller et al. 1999). With female adults ranging between 13-15 m in length (females tend to be slightly larger than adult males) and weighing anywhere between 15-33 tons (Jones et al. 1984), I am continuously fascinated by how gracefully and slowly gray whales can navigate extremely shallow waters.

    However, it is more than just simple navigation – the behaviors and moves that some gray whales display while in the shallows is phenomenal too. Last year Torres et al. (2018) documented this agility through unmanned aerial systems (UAS) footage that provided evidence for some novel foraging tactics including headstands, side-swimming, and jaw snapping and flexing.

  1. They sure are resilient. Commercial whaling of gray whales began in 1846 after two commercial whaling vessels first discovered the winter breeding grounds in Baja California, Mexico (Henderson 1984). Following this discovery, the ENP were targeted for roughly a century before receiving full protection under the International Convention for the Regulation of Whaling in 1946 (Reeves 1984). Through genetic analyses, it has been estimated that the pre-whaling abundance of the ENP population was between 76,000 – 118,000 individuals (Alter et al. 2012), which is roughly three to five times larger than current estimates (24,000 – 26,000; Scordino et al. 2018). While the gray whale populations that once existed in the Atlantic Ocean were not as fortunate as those in the Pacific (Atlantic gray whales were declared extinct in the 18thcentury due to extensive whaling; Bryant 1995), the ENP has definitely made a strong comeback. Additionally, gray whale resilience is not only evident on this long temporal scale but it can also be seen annually when gray whale mothers fight relentlessly to keep their calves alive when under attack from killer whales. A study on predation of gray whales by transient killer whales in Alaska reported that attacks were quickly abandoned if calves were aggressively defended by their mothers or if gray whales succeeded in reaching depths of 3 m or less (Barrett-Lennard et al. 2011).
  1. For some unimaginable reason, gray whales appear to feel a strong connection to us. For many, gray whales might be best known for actively seeking out human contact during their breeding season in the Mexican lagoons. I find this actuality particularly interesting because of the bloody history we share with Pacific gray whales.

Those are just some of the things about gray whales that make them so fascinating to me. I look forward to potentially discovering one or two more things that we don’t know about them yet through my research. Even if that doesn’t turn out to be the case, I feel so lucky that I at least get to spend so much time with them during their feeding season here along the Oregon coast.

 

References

Alter, E.S., et al., Pre-whaling genetic diversity and population ecology in Eastern Pacific gray whales: Insights from ancient DNA and stable isotopes.PLoS ONE, 2012. doi.org/10.1371/journal.pone.0035039.

Barrett-Lennard, L.G., et al., Predation on gray whales and prolonged feeding on submerged carcasses by transient killer whales at Unimak Island, Alaska. Marine Ecology Progress Series, 2011. 421: 229-241.

Bryant, P.J., Dating remains of gray whales from the Eastern North Atlantic. Journal of Mammalogy, 1995. 76(3): 857-861.

Grebmeier, J.M., & Harrison, N.M., Seabird feeding on benthic amphipods facilitated by gray whale feeding activity in the northern Bering Sea. Marine Ecology Progress Series, 1992. 80: 125-133.

Henderson, D.A., Nineteenth century gray whaling: Grounds, catches and kills, practices and depletion of the whale population.Pages 159-186 inJones, M.L. et al., eds. The gray whale: Eschrichtius robustus, 1984. Academic Press, Orlando.

Jones, M.L., et al., The gray whale: Eschrichtius robustus. 1984. Academic Press, Orlando.

Nerini, M., A review of the gray whale feeding ecology. Pages 423-448 inJones, M.L. et al., eds. The gray whale: Eschrichtius robustus, 1984. Academic Press, Orlando.

Oliver, J.S., & Slattery, P.N., Destruction and obstruction on the sea floor: effects of gray whale feeding.Ecology, 1985. 66: 1965-1975.

Pivorunas, A., The feeding mechanisms of baleen whales.American Scientist, 1979. 67(4): 432-440.

Reeves, R.R., Modern commercial pelagic whaling for gray whales. Pages 187-200 inJones, M.L. et al., eds. The gray whale: Eschrichtius robustus, 1984. Academic Press, Orlando.

Scordino, J., et al., Report of gray whale implementation review coordination call on 5 December 2018.

Torres, L.G., et al., Drone up! Quantifying whale behavior from a new perspective improves observational capacity.Frontiers in Marine Science, 2018. 5: doi:10.3389/fmars.2018.00319.

Villegas-Amtmann, S., et al., A bioenergetics model to evaluate demographic consequences of disturbance in marine mammals applied to gray whales. Ecosphere, 2015. 6(10): 1-19.

Weller, D.W., et al., Gray whale (Eschrichtius robustus) off Sakhalin Island, Russia: Seasonal and annual patterns of occurrence. Marine Mammal Science, 1999. 15(4): 1208-1227.

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.