“Simplicity is the greatest form of sophistication”
Variation and diversity in microbial communities
How coexistence of many species is maintained is a fundamental and unanswered question in ecology. Coexistence is a puzzle because we lack a quantitative understanding of the variation in species presence and abundance. Whether variation in ecological communities is driven by deterministic or random processes is one of the most controversial issues in ecology. We studied the variation of species presence and abundance in microbial communities from a macroecological standpoint, identifying three novel, universal, and foundamental macroecological laws [NC2020].
Stability of large ecological systems and ecological networks
Mainly with: S. Allesina, G. Barabás, A. Maritan, S. Suweis
Ecosystems are typically composed by a large number of interacting individuals and species. What do determine their stability respect to perturbation and their persistence in time? The first lesson of statistical physics is that we cannot use the same methods that we use to study the motion of two bodies to describe a tank of gas. Following a long tradition in theoretical ecology, we study stability and persistence of ecosystems using random matrices. This approach allows to identify what are the relevant quantities that determine the fate of those systems. In particular we were able to find a stability condition for empirical food-webs [NC2015a], to characterize how perturbations spread across species [NC2015b], and to link modularity and stability [NC2016]. We also studied the probability to observe a randomly interacting set of species coexist [NC2017] and what is the typical number of species coexisting [NatE&E2018]. We showed that higher-order interactions have a strong effect on stability of ecological communties [Nature2017].
Mainly with: M. Cosentino Lagomarsino, G. Micali, M. Osella
The dream of every cell is to become two cells. Without a coupling between cell size and division, cells would not have the experimentally observed stationary distribution of sizes. How this control is coordinated has not been yet understood. We showed that the statistical properties of size and time of division can be explained using scaling arguments, without the need of invoking specific mechanisms [PRE2016]. Scaling allows, in fact, to connect apparently unrelated measurable quantities in a parameter-free setting. On the other hand, we characterized the class of models compatible with scaling, isolating few parameters that describe cell-size control across species and conditions [PRE2017] and we study their dependence on cell-growth fluctuations [frontMB2018]. We studied the empirical correlation patterns of DNA replication and cell division showing that no master control is needed to achieve the observed coordination [SciAdv2018,CellRep2018].
Statistical laws in genomes evolution
Mainly with: M. Cosentino Lagomarsino, S. Maslov
Life populates almost every corner of this planet, with striking differences of forms and shapes, that reflect the adaptation to a particular environment and unique evolutionary histories. Despite the contingency of the processes shaping genomes, remarkable regularities and patterns can be found across organisms. We studied how different patterns involving genes with the same functions were connected to patterns of evolutionary closely related genes [NAR2012,NAR2017]. We also studied the role of HGT in shaping the genomes of prokaryotes and the relation between genes occurrence and HGT [NAR2014].
Neutral theory and spatial ecology
Mainly with: S. Azaele, J.R. Banavar, A. Maritan
Macroscopic phenomena are intrinsically stochastic and noise strongly affects the species composition and diversity of ecosystems. Statistical mechanics offers many tools that can be applied to study these systems [RMP2016]. We showed how spatial dispersal of species makes ecosystems inevitably out of equilibrium [EPL2012]. While this fact makes simple models analytically untractable, there is still room for analytical solutions in spatially explicit systems. Using a phenomenological model we were able to connect different spatial and non-spatial ecological patterns [JTB2012].