Traveling is quite disruptive, especially when you have a family at home, and a lab to run. However, having to travel to incredibly beautiful destinations to meet old friends makes the whole ordeal much more pleasant.
I have just returned to Chicago after a week in Monterey, CA, where I taught a short course on computing at the Hopkins Marine Station of Stanford University. The class was great, and the organizer was my friend Giulio De Leo. I got to spend some time with Giulio and Fiorenza, as well as to interact with an incredibly motivated group of students. I also gave a talk at Hopkins and one at the main campus in Palo Alto. This is what I would see when I went for a run:
Just before heading to Stanford, I have been in Venezia, Italy, for a school on complex systems, organized by Antonio Trovato, Samir Suweis and our very own Jacopo Grilli. Again, the school was great, and the location—in San Servolo island—unbeatable:
These trips energized me a lot, but I am really happy to be home for a good stretch of time!
Just came back from the very first BSD QBio Boot Camp @ MBL. A fantastic week — it’s been so great to see all the incoming graduate students, from all branches of Biology working and learning together!
Here come old flat top He come groovin’ up slowly He got joo joo eyeball Come together
Lennon & Mccartney
We have been working on the applications of random matrix theory to ecology for four years. By now, it is quite clear that the most important challenge ahead is to extend the theory to the case of structured networks (as described here). A new study we just published is a first step in this direction:
In this work, we studied community matrices produced according to the cascade model, in which “big fish eat little fish”. These matrices look like this:
where the red squares represent negative coefficients (effects of predators on prey), and the blue ones positive coefficients (effects of prey on predators). These matrices produce a peculiar spectrum, suggestive of an “eyeball”:
In the paper, we derive simple, analytical results that allow us to approximate the spectrum (and hence the stability) of the eyeball.
I wrote an R package that performs the analysis described in the paper, and published it on github.
A bit on the backstory: in December 2014, I gave a talk at UC Davis, and, at dinner, Sebastian Schreiber mentioned that if I liked problems involving eigenvalues I should have looked at the classic Hanski & Ovaskainen model. Back in Chicago, Gyuri (who had just started his postdoc) and Jacopo (who was visiting from Italy) thought it would be a good project to jumpstart our collaboration…