IPM

Charles Fisher joined the Institute in November 2014. He had gotten his PhD from
Harvard in 2012 and did a first postdoc at Boston University. He works mostly on theoretical ecology.
The human body hosts thousands of symbiotic microbial species making up what
is called the human microbiota. Elucidating the roles of different ecological forces in
structuring the human microbiota is an important step towards understanding how
the microbiota affect human health. The Human Microbiome Project and similar
studies have taken a step towards this goal by collecting microbiota samples from
multiple body sites across a large population of different individuals. A few stylized
facts about the microbiota have emerged from these studies. First, the composition of
the microbiota of a body site in a particular person varies less over time than across
the population. Second, the variation in species composition between body sites is
much larger than the variation of a single body site across a population. These results
tell us that even though a particular body site (e.g., the human gut) shares common
features within a population of different individuals, every individual has a different
microbiota. How, then, is it possible to extract information about the ecological forces
acting on the microbiota when every sample is taken from a different environment ?
Most of Charles Fisher’s research at ENS has focused on understanding how large
ecological communities vary across different environments and how to extract infor-
mation about species interactions from these data. The hypothesis underlying this
research is based on a classical idea in theoretical ecology that species abundances
are chosen to pack species into a ‘niche space’ so as to utilize all of the resources in
the environment. Specifically, he is studying a model for relative species abundances
based on two simple principles : (1) the equilibrium relative abundances ensure that
the species fill the entire niche volume in a way (2) that maximizes the diversity of
the community. Following this idea, the relative abundances of the species can be
found by solving a specific maximum entropy problem. This simple model provides a
number of helpful insights into the ecology of the human microbiota. One of the most
important features is that it is possible to infer the parameters of the model exactly
using a technique from machine learning called Independent Component Analysis.
Currently, C. Fisher is working on applying these techniques to data obtained from
the Human Microbiome Project.
C. Fisher collaborated with Thierry Mora and Aleksandra Walzcak (ENS). Other
collaborations are with Pankaj Mehta and Daniel Segrè (Boston University) on re-
lated projects in theoretical ecology. C. Fisher published several papers while at the
Institute [28, 29, 30].