The view of a data scientist - BONUS BIO-C3 & BONUS INSPIRE
I share here my lessons while working in BONUS BIO-C3 and INSPIRE as a "data scientist". I call myself a “marine biologist”, but my career was decided in the first day of my PhD studies, when I opened “R” instead of the lab door. I can never be thankful enough for my supervisor for showing me that door. This path of data scientist placed me on the rollercoaster of co-operations with many research groups. And on the way, I hope, I learned something of the plankton and the sea too.
Most of the Baltic zooplankton is specialized on small food
This entire post is about one figure my colleague (and boss) Henn Ojaveer showed at the annual meeting of one of the Bonus projects (called BIOC3).
In short, this figure tells us that most of the tiny animals floating around in the Baltic Sea are specialised on consuming rather small food that they can filter from the water.
How did I make this figure?
For many many years, people have taken the ships or boats, and went out on the Baltic Sea, to collect water samples. One type of these samples (zooplankton samples) is designed to capture all these animals that are usually between 0.5-3 mm in size. These animals (collectively called zooplankton) are quite important link in marine ecosystems, because they channel the primary production to the higher levels of food web (e.g. herring) (because most fish won't eat plants - e.g. the phytoplankton).
Because of this sampling, we know which species where and when were was how abundant.
With some more work, we equipped each species with most important information - called functional traits - telling us how big and complicated each species is, and how it eats its food.
The figure below uses only data of three main groups of zooplankton - these are copepods, cladocerans and rotifers. Copepods are most complicated, rotifers are the simplest. But all these animals have learned two types of feeding - filtering the water to catch whatever is in there, or actively capturing their prey. Knowing how big and complicated each species is, as well as how it eats, is enough to draw a map, where the different types of organisms make up the locations.
And if we now look, how many of these organisms we actually see in each sample, then we can place each sampled community on this map, so that the point representing each sample is closest to the kind of animals that were most abundant in that sample. Which results in the figure below (of about 16000 zooplankton samples from Baltic Sea). Put simply, this figure tells us that most abundant in each sample are the animals that filter their food (instead of capturing it). On of the names is not easy to see (because covered with data points) - but on the north-east side, we have "filtering rotifers", "filtering cladocerans", and "filtering copepods". And the points - that represent samples - are all aligned close to the line connecting the filtering animals.
This is one way to use the monitoring data to gain valuable insights to the type of food webs our sea hosts. And it feels quite revealing.