Tag: Fieldwork

Big Data: Big possibilities with bigger challenges

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

Did you know that Excel has a maximum number of rows? I do. During Winter Term for my GIS project, I was using Excel to merge oceanographic data, from a publicly-available data source website, and Excel continuously quit. Naturally, I assumed I had caused some sort of computer error. [As an aside, I’ve concluded that most problems related to technology are human error-based.] Therefore, I tried reformatting the data, restarting my computer, the program, etc. Nothing. Then, thanks to the magic of Google, I discovered that Excel allows no more than 1,048,576 rows by 16,384 columns. ONLY 1.05 million rows?! The oceanography data was more than 3 million rows—and that’s with me eliminating data points. This is what happens when we’re dealing with big data.

According to Merriam-Webster dictionary, big data is an accumulation of data that is too large and complex for processing by traditional database management tools (www.merriam-webster.com). However, there are journal articles, like this one from Forbes, that discuss the ongoing debate of how to define “big data”. According to the article, there are 12 major definitions; so, I’ll let you decide what you qualify as “big data”. Either way, I think that when Excel reaches its maximum row capacity, I’m working with big data.

Collecting oceanography data aboard the R/V Shimada. Photo source: Alexa K.

Here’s the thing: the oceanography data that I referred to was just a snippet of my data. Technically, it’s not even MY data; it’s data I accessed from NOAA’s ERDDAP website that had been consistently observed for the time frame of my dolphin data points. You may recall my blog about maps and geospatial analysis that highlights some of the reasons these variables, such as temperature and salinity, are important. However, what I didn’t previously mention was that I spent weeks working on editing this NOAA data. My project on common bottlenose dolphins overlays environmental variables to better understand dolphin population health off of California. These variables should have similar spatiotemporal attributes as the dolphin data I’m working with, which has a time series beginning in the 1980s. Without taking out a calculator, I still know that equates to a lot of data. Great data: data that will let me answer interesting, pertinent questions. But, big data nonetheless.

This is a screenshot of what the oceanography data looked like when I downloaded it to Excel. This format repeats for nearly 3 million rows.

Excel Screen Shot. Image source: Alexa K.

I showed this Excel spreadsheet to my GIS professor, and his response was something akin to “holy smokes”, with a few more expletives and a look of horror. It was not the sheer number of rows that shocked him; it was the data format. Nowadays, nearly everyone works with big data. It’s par for the course. However, the way data are formatted is the major split between what I’ll call “easy” data and “hard” data. The oceanography data could have been “easy” data. It could have had many variables listed in columns. Instead, this data  alternated between rows with variable headings and columns with variable headings, for millions of cells. And, as described earlier, this is only one example of big data and its challenges.

Data does not always come in a form with text and numbers; sometimes it appears as media such as photographs, videos, and audio files. Big data just got a whole lot bigger. While working as a scientist at NOAA’s Southwest Fisheries Science Center, one project brought in over 80 terabytes of raw data per year. The project centered on the eastern north pacific gray whale population, and, more specifically, its migration. Scientists have observed the gray whale migration annually since 1994 from Piedras Blancas Light Station for the Northbound migration, and 2 out of every 5 years from Granite Canyon Field Station (GCFS) for the Southbound migration. One of my roles was to ground-truth software that would help transition from humans as observers to computer as observers. One avenue we assessed was to compare how well a computer “counted” whales compared to people. For this question, three infrared cameras at the GCFS recorded during the same time span that human observers were counting the migratory whales. Next, scientists, such as myself, would transfer those video files, upwards of 80 TB, from the hard drives to Synology boxes and to a different facility–miles away. Synology boxes store arrays of hard drives and that can be accessed remotely. To review, three locations with 80 TB of the same raw data. Once the data is saved in triplet, then I could run a computer program, to detect whale. In summary, three months of recorded infrared video files requires upwards of 240 TB before processing. This is big data.

Scientists on an observation shift at Granite Canyon Field Station in Northern California. Photo source: Alexa K.
Alexa and another NOAA scientist watching for gray whales at Piedras Blancas Light Station. Photo source: Alexa K.

In the GEMM Laboratory, we have so many sources of data that I did not bother trying to count. I’m entering my second year of the Ph.D. program and I already have a hard drive of data that I’ve backed up three different locations. It’s no longer a matter of “if” you work with big data, it’s “how”. How will you format the data? How will you store the data? How will you maintain back-ups of the data? How will you share this data with collaborators/funders/the public?

The wonderful aspect to big data is in the name: big and data. The scientific community can answer more, in-depth, challenging questions because of access to data and more of it. Data is often the limiting factor in what researchers can do because increased sample size allows more questions to be asked and greater confidence in results. That, and funding of course. It’s the reason why when you see GEMM Lab members in the field, we’re not only using drones to capture aerial images of whales, we’re taking fecal, biopsy, and phytoplankton samples. We’re recording the location, temperature, water conditions, wind conditions, cloud cover, date/time, water depth, and so much more. Because all of this data will help us and help other scientists answer critical questions. Thus, to my fellow scientists, I feel your pain and I applaud you, because I too know that the challenges that come with big data are worth it. And, to the non-scientists out there, hopefully this gives you some insight as to why we scientists ask for external hard drives as gifts.

Leila launching the drone to collect aerial images of gray whales to measure body condition. Photo source: Alexa K.
Using the theodolite to collect tracking data on the Pacific Coast Feeding Group in Port Orford, OR. Photo source: Alexa K.

References:

https://support.office.com/en-us/article/excel-specifications-and-limits-1672b34d-7043-467e-8e27-269d656771c3

https://www.merriam-webster.com/dictionary/big%20data

What REALLY is a Wildlife Biologist?

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

The first lecture slide. Source: Lecture1_Population Dynamics_Lou Botsford

This was the very first lecture slide in my population dynamics course at UC Davis. Population dynamics was infamous in our department for being an ultimate rite of passage due to its notoriously challenging curriculum. So, when Professor Lou Botsford pointed to his slide, all 120 of us Wildlife, Fish, and Conservation Biology majors, didn’t know how to react. Finally, he announced, “This [pointing to the slide] is all of you”. The class laughed. Lou smirked. Lou knew.

Lou knew that there is more truth to this meme than words could express. I can’t tell you how many times friends and acquaintances have asked me if I was going to be a park ranger. Incredibly, not all—or even most—wildlife biologists are park rangers. I’m sure that at one point, my parents had hoped I’d be holding a tiger cub as part of a conservation project—that has never happened. Society may think that all wildlife biologists want to walk in the footsteps of the famous Steven Irwin and say thinks like “Crikey!”—but I can’t remember the last time I uttered that exclamation with the exception of doing a Steve Irwin impression. Hollywood may think we hug trees—and, don’t get me wrong, I love a good tie-dyed shirt—but most of us believe in the principles of conservation and wise-use A.K.A. we know that some trees must be cut down to support our needs. Helicoptering into a remote location to dart and take samples from wild bear populations…HA. Good one. I tell myself this is what I do sometimes, and then the chopper crashes and I wake up from my dream. But, actually, a scientist staring at a computer with stacks of papers spread across every surface, is me and almost every wildlife biologist that I know.

The “dry lab” on the R/V Nathaniel B. Palmer en route to Antarctica. This room full of technology is where the majority of the science takes place. Drake Passage, International Waters in August 2015. Source: Alexa Kownacki

There is an illusion that wildlife biologists are constantly in the field doing all the cool, science-y, outdoors-y things while being followed by a National Geographic photojournalist. Well, let me break it to you, we’re not. Yes, we do have some incredible opportunities. For example, I happen to know that one lab member (eh-hem, Todd), has gotten up close and personal with wild polar bear cubs in the Arctic, and that all of us have taken part in some work that is worthy of a cover image on NatGeo. We love that stuff. For many of us, it’s those few, memorable moments when we are out in the field, wearing pants that we haven’t washed in days, and we finally see our study species AND gather the necessary data, that the stars align. Those are the shining lights in a dark sea of papers, grant-writing, teaching, data management, data analysis, and coding. I’m not saying that we don’t find our desk work enjoyable; we jump for joy when our R script finally runs and we do a little dance when our paper is accepted and we definitely shed a tear of relief when funding comes through (or maybe that’s just me).

A picturesque moment of being a wildlife biologist: Alexa and her coworker, Jim, surveying migrating gray whales. Piedras Blancas Light Station, San Simeon, CA in May 2017. Source: Alexa Kownacki.

What I’m trying to get at is that we accepted our fates as the “scientists in front of computers surrounded by papers” long ago and we embrace it. It’s been almost five years since I was a senior in undergrad and saw this meme for the first time. Five years ago, I wanted to be that scientist surrounded by papers, because I knew that’s where the difference is made. Most people have heard the quote by Mahatma Gandhi, “Be the change that you wish to see in the world.” In my mind, it is that scientist combing through relevant, peer-reviewed scientific papers while writing a compelling and well-researched article, that has the potential to make positive changes. For me, that scientist at the desk is being the change that he/she wish to see in the world.

Scientists aboard the R/V Nathaniel B. Palmer using the time in between net tows to draft papers and analyze data…note the facial expressions. Antarctic Peninsula in August 2015. Source: Alexa Kownacki.

One of my favorite people to colloquially reference in the wildlife biology field is Milton Love, a research biologist at the University of California Santa Barbara, because he tells it how it is. In his oh-so-true-it-hurts website, he has a page titled, “So You Want To Be A Marine Biologist?” that highlights what he refers to as, “Three really, really bad reasons to want to be a marine biologist” and “Two really, really good reasons to want to be a marine biologist”. I HIGHLY suggest you read them verbatim on his site, whether you think you want to be a marine biologist or not because they’re downright hilarious. However, I will paraphrase if you just can’t be bothered to open up a new tab and go down a laugh-filled wormhole.

Really, Really Bad Reasons to Want to be a Marine Biologist:

  1. To talk to dolphins. Hint: They don’t want to talk to you…and you probably like your face.
  2. You like Jacques Cousteau. Hint: I like cheese…doesn’t mean I want to be cheese.
  3. Hint: Lack thereof.

Really, Really Good Reasons to Want to be a Marine Biologist:

  1. Work attire/attitude. Hint: Dress for the job you want finally translates to board shorts and tank tops.
  2. You like it. *BINGO*
Alexa with colleagues showing the “cool” part of the job is working the zooplankton net tows. This DOES have required attire: steel-toed boots, hard hat, and float coat. R/V Nathaniel B. Palmer, Antarctic Peninsula in August 2015. Source: Alexa Kownacki.

In summary, as wildlife or marine biologists we’ve taken a vow of poverty, and in doing so, we’ve committed ourselves to fulfilling lives with incredible experiences and being the change we wish to see in the world. To those of you who want to pursue a career in wildlife or marine biology—even after reading this—then do it. And to those who don’t, hopefully you have a better understanding of why wearing jeans is our version of “business formal”.

A fieldwork version of a lab meeting with Leigh Torres, Tom Calvanese (Field Station Manager), Florence Sullivan, and Leila Lemos. Port Orford, OR in August 2017. Source: Alexa Kownacki.

The five senses of fieldwork

By Leila Lemos, PhD student

 

This summer was full of emotions for me: I finally started my first fieldwork season after almost a year of classes and saw my first gray whale (love at first sight!).

During the fieldwork we use a small research vessel (we call it “Red Rocket”) along the Oregon coast to collect data for my PhD project. We are collecting gray whale fecal samples to analyze hormone variations; acoustic data to assess ambient noise changes at different locations and also variations before, during and after events like the “Halibut opener”; GoPro recordings to evaluate prey availability; photographs in order to identify each individual whale and assess body and skin condition; and video recordings through UAS (aka “drone”) flights, so we can measure the whales and classify them as skinny/fat, calf/juvenile/adult and pregnant/non-pregnant.

However, in order to collect all of these data, we need to first find the whales. This is when we use our first sense: vision. We are always looking at the horizon searching for a blow to come up and once we see it, we safely approach the animal and start watching the individual’s behavior and taking photographs.

If the animal is surfacing regularly to allow a successful drone overflight, we stay with the whale and launch the UAS in order to collect photogrammetry and behavior data.

Each team member performs different functions on the boat, as seen in the figure below.

Figure 1: UAS image showing each team members’ functions in the boat at the moment just after the UAS launch.
Figure 1: UAS image showing each team members’ functions in the boat at the moment just after the UAS launch.

 

While one member pilots the boat, another operates the UAS. Another team member is responsible for taking photos of the whales so we can match individuals with the UAS videos. And the last team member puts the calibration board of known length in the water, so that we can later calculate the exact size of each pixel at various UAS altitudes, which allows us to accurately measure whale lengths. Team members also alternate between these and other functions.

Sometimes we put the UAS in the air and no whales are at the surface, or we can’t find any. These animals only stay at the surface for a short period of time, so working with whales can be really challenging. UAS batteries only last for 15-20 minutes and we need to make the most of that time as we can. All of the members need to help the UAS pilot in finding whales, and that is when, besides vision, we need to use hearing too. The sound of the whale’s respiration (blow) can be very loud, especially when whales are closer. Once we find the whale, we give the location to the UAS pilot: “whale at 2 o’clock at 30 meters from the boat!” and the pilot finds the whale for an overflight.

The opposite – too many whales around – can also happen. While we are observing one individual or searching for it in one direction, we may hear a blow from another whale right behind us, and that’s the signal for us to look for other individuals too.

But now you might be asking yourself: “ok, I agree with vision and hearing, but what about the other three senses? Smell? Taste? Touch?” Believe it or not, this happens. Sometimes whales surface pretty close to the boat and blow. If the wind is in our direction – ARGHHHH – we smell it and even taste it (after the first time you learn to close your mouth!). Not a smell I recommend.

Fecal samples are responsible for the 5th sense: touch!

Once we identify that the whale pooped, we approach the fecal plume in order to collect as much fecal matter as possible (Fig.2).

Figure 2: A: the poop is identified; B: the boat approaches the feces that are floating at the surface (~30 seconds); C: one of the team members remains at the bow of the boat to indicate where the feces are; D: another team member collects it with a fine-mesh net. Filmed under NOAA/NMFS permit #16111 to John Calambokidis).
Figure 2: A: the poop is identified; B: the boat approaches the feces that are floating at the surface (~30 seconds); C: one of the team members remains at the bow of the boat to indicate where the feces are; D: another team member collects it with a fine-mesh net. Filmed under NOAA/NMFS permit #16111 to John Calambokidis).

 

After collecting the poop we transfer all of it from the net to a small jar that we then keep cool in an ice chest until we arrive back at the lab and put it in the freezer. So, how do we transfer the poop to the jar? By touching it! We put the jar inside the net and transfer each poop spot to the jar with the help of water pressure from a squeeze bottle full of ambient salt water.

Figure 3: Two gray whale individuals swimming around kelp forests. Filmed under NOAA/NMFS permit #16111 to John Calambokidis).
Figure 3: Two gray whale individuals swimming around kelp forests. Filmed under NOAA/NMFS permit #16111 to John Calambokidis).

 

That’s how we use our senses to study the whales, and we also use an underwater sensory system (a GoPro) to see what the whales were feeding on.

GoPro video of mysid swarms that we recorded near feeding gray whales in Port Orford in August 2016:

Our fieldwork is wrapping up this week, and I can already say that it has been a success. The challenging Oregon weather allowed us to work on 25 days: 6 days in Port Orford and 19 days in the Newport and Depoe Bay region, totaling 141 hours and 50 minutes of effort. We saw 195 whales during 97 different sightings and collected 49 fecal samples. We also performed 67 UAS flights, 34 drifter deployments (to collect acoustic data), and 34 GoPro deployments.

It is incredible to see how much data we obtained! Now starts the second part of the challenge: how to put all of this data together and find the results. My next steps are:

– photo-identification analysis;

– body and skin condition scoring of individuals;

– photogrammetry analysis;

– analysis of the GoPro videos to characterize prey;

– hormone analysis laboratory training in November at the Seattle Aquarium

 

For now, enjoy some pictures and a video we collected during the fieldwork this summer. It was hard to choose my favorite pictures from 11,061 photos and a video from 13 hours and 29 minutes of recording, but I finally did! Enjoy!

Figure 4: Gray whale breaching in Port Orford on August 27th. (Photo by Leila Lemos; Taken under NOAA/NMFS permit #16111 to John Calambokidis).
Figure 4: Gray whale breaching in Port Orford on August 27th. (Photo by Leila Lemos; Taken under NOAA/NMFS permit #16111 to John Calambokidis).

 

Figure 5: Rainbow formation through sunlight refraction on the water droplets of a gray whale individual's blow in Newport on September 15th. (Photo by Leila Lemos; Taken under NOAA/NMFS permit #16111 to John Calambokidis).
Figure 5: Rainbow formation through sunlight refraction on the water droplets of a gray whale individual’s blow in Newport on September 15th. (Photo by Leila Lemos; Taken under NOAA/NMFS permit #16111 to John Calambokidis).

 

Likely gray whale nursing behavior (Taken under NOAA/NMFS permit #16111 to John Calambokidis):

Southern Sunshine Meets Oregon Wind: Interning with the GEMM Lab!

**GUEST POST**written by Cheyenne Coleman of Savannah State University

My first journey to the west coast, was spent on a six hour flight to Portland, Oregon in anticipation of my upcoming summer internship with the Geospatial Ecology and Marine Megafuana lab (GEMM Lab) at the Hatfield Marine Science Center (HMSC). I had never before been to the west coast, but luckily for me I did not have to make this long journey alone; my friend, Kamiliya Daniels, was also doing an internship at HMSC. After a long bus ride to Corvallis, Kamiliya and I, were warmly greeted by one of my GEMM lab members, Amanda Holdman. With her, was honorary GEMM lab member and Amanda’s dog, Boiler, who spent the greater part of the drive to Newport sleeping on my lap while I spent the drive asking Amanda several series of questions,

“Are there bears in these woods?”

“What do the dorms look like? How do I get around town? I hear it’s a small town, is there at least a Walmart?”

But without any answer to my curiosity, all of these questions were left with one reply:

“I’ll let you see for yourself.”

And then just as Amanda proposed, I did exactly that.

My name is Cheyenne and I am from Savannah State University in Georgia interning with LMRCSC (Living Marine Resources Cooperative Science Center) in Newport, Oregon. My expectations of the Oregon coast and the reality was vastly different than what I had pictured. I imagined the entire West Coast would match a California summer; Sunny and hot.

But on the contrary, upon arrival to Newport, I learned, it doesn’t. It is windy and chilly and hardly ever above 70 degrees. Thinking an Oregon summer would match a California summer, in my suitcase I possessed only three small sweaters and an abundant supply of shorts and tank tops. Needless, to say I was quickly off to buy an Oregon Coast sweatshirt that would double as warmth and a souvenir. Upon first entering Newport, I was mostly shocked at how small the town felt, and I noticed every structure was made of wood, and coming from Georgia this was strange to me. In Georgia, everything is made of bricks and cement. The dorms on first glance reminded me of summer camp for adults: slightly dated with bunk bed sleeping arrangements. Yikes!

However, my worries that come along with moving to a new place, were quickly diminished when I was welcomed to the GEMM lab; Florence greeted with a warm cup of tea, I was introduced to everyone who worked at HMSC, and even given my very own desk in the GEMM lab. After a day of transitions, and a much needed good night’s rest, I was introduced to my project on California Sea Lions (Zalophus californianus).

If you’ve been following along with all of the latest posts from GEMM lab students, you might think the lives of spatial ecologists revolve around glamorous fieldwork. We’ve got Amanda eavesdropping on porpoises, Florence surveying for foraging gray whales, and Leigh playing hide and seek with seabirds down in Yachats. I, however, am admittedly not spending my summer in the field this year and am learning that there is more to being a scientist than picturesque moments with charismatic study species in beautiful locations.

Prior to entering the GEMM lab, I had limited experience in computing and data analysis and spent my prior summer’s doing fieldwork on invertebrates, usually bagging sediment and collecting water samples. This internship was a new and unique opportunity for me to learn the next step of the scientific process. While I had always wondered, “What happens after data collection?” I was not given the experience to find out.  I quickly learned, that this includes a lot of sorting, categorizing, and modeling, all of which are very time consuming.

By using satellite tracking information of California sea lions collected by the Oregon Department of Fish and Wildlife (ODFW) from 2005 and 2007, I am able to measure movements and habitat use of California sea lions. By analyzing their routes between their initial and final locations, we can study their distributions patterns.

To some people, sitting at a computer doing analysis may not seem as glamorous as working in the field. Some people might question why someone would chose to spend their career in front of a computer screen. But my internship this summer, really showed me the value of having experience working at all stages of the scientific process. Seeing all of my efforts in processing, sorting, and categorizing come together to create an end result really enhanced my love for science. By connecting the questions to the answers, and making contributions to the scientific community, I feel rewarded for my hard work.

My internship has come to an end, and given my initial hesitations, I’ve grown accustomed to Newport and the GEMM lab. I enjoy sitting at my desk running through a wild assortment of data and hearing the wonderful ding of the teapot. In the last days of my internship, I was able to escape my computer screen to assist Florence in data collection on beautiful gray whale surveys. Last Thursday, a lab meeting was held and my lab mates and I were able to update each other on our research. We shared ideas on how to enhance everyone’s project, and who might be able to answer questions we were struggling with in our own data sets. As my internship comes to a close, I have gained more knowledge and real life skill then I would ever hope to gain just through courses at Savannah State. I learned new software programs like R Statistical Package and sharpened my own skills in ArcGIS. I gained the experience of collaborating with a lab, and understanding how powerful working with your peers and colleagues can be. Gaining this much experience has, without a doubt, given me an edge in the competitive field I will enter after graduation. I have made connections, hopefully life long, with the nicest people; I know that in the future, which ever path I may choose, I’ll always be a part of the GEMM lab.