Combining Math and Jellyfish

July 1st, 2015


Hello! My name is Anna Kronauer, and I’m working as an REU intern this summer at Bigelow Labs under the guidance of Dr. Nick Record. As a rising senior at Colby College, I’m surprisingly not majoring in anything related to Biology or Chemistry – I’m actually a Math/Statistics major with a minor in Computer Science. I’ve become particularly interested in mathematical modeling and machine learning and know that this is an area I’d like to pursue post-graduation (specifically, epidemiology and biostatistics programs). Together with my prior coding experience in Python, Java, and R, my internship this summer has been a wonderful fit for me.

The purpose of my research is to develop an empirical model for predicting the abundance of gelatinous zooplankton in the Gulf of Maine, a region that has received remarkably little attention, despite its accelerated rates of climate change. I’m also interested in answering several other questions:

  • Has there been a true increase in baseline levels of jelly abundance, or can the recent surges be attributed to approximately decadal oscillations?
  • How do jellyfish blooms affect other, non-gelatinous marine species, and should this be cause for concern?
  • Under the umbrella of “gelatinous zooplankton,” do the different taxa tend to vary together? If not, what are the population trends that uniquely define each taxa?

Jellyfish blooms, which have have been well documented in the Bering Sea, the Black Sea, the Sea of Japan, and the Casco Bay, have countless effects on human enterprises: beach closures and other tourism impacts due to jellyfish stings, clogged intakes in coastal power and desalination plants, and interference with fishing (clogged and split nets, spoiled catch, damaged gear) and aquaculture (fish deaths, pens fouled by polyps). These localized increases are thought to coincide with climate change: warming temperatures, which enhance production, feeding, and growth rates of jellyfish, and the spread of hypoxia, to which jellyfish exhibit greater tolerance than most other metazoans.

Chlorophyll and sea surface temperature will be the primary drivers for the model, and I will be using two classifiers to improve its prediction accuracy: Naïve Bayes, which focuses on conditional probabilities, and K-nearest neighbors, which focuses on the Euclidean distances between exemplars. By the end of the summer, my goal is to develop a GUI (a graphical user interface) in Python, so the user would be able to visualize the model’s predictions overlaid spatially onto the Gulf of Maine. I hope that this project would be useful in the development of preventative measure and reliable warning indicators of phase shifts, especially since Maine’s economy is heavily dependent upon the commercial fishing industry.

Outside of my research project, I’ve had the opportunity to further explore the wonders of Maine. Last weekend, I hiked Cadillac Mountain, the highest point along the North Atlantic seaboard. I’ve also visited the coastal botanical gardens, viewed the fireworks in the Harbor as part of Boothbay’s Windjammer days, and kayaked several miles along the coast – not to mention my cooking skills have improved immensely (homemade chicken quesadillas, anyone?). My housemates are amazing, and I look forward to the adventures that are to come!

Combining Math and Jellyfish