Jacob Moran


Date of Award

Spring 5-15-2023

Author's School

Graduate School of Arts and Sciences

Author's Department


Degree Name

Doctor of Philosophy (PhD)

Degree Type



The interface between statistical physics and theoretical ecology has a long history, employing powerful concepts such as ensemble approaches and typicality to study emergent properties of ecosystems. This of course raises the question of what ensembles are useful to describe the typical behaviors of evolution and ecology, but so far, the traditional context of high-diversity ecology has considered ensembles of random, unstructured ecosystems. Although much insight has been gained in this regime, one naturally wonders how representative are random ensembles of real, natural ecosystems that are arguably atypical and highly structured by evolution. Moreover, the question of coarse-graining ecosystems has yet to be addressed because the very ingredient responsible for predictive coarse-grained descriptions – ecosystem structure – is explicitly absent from the current theoretical framework. This dissertation investigates the coarse-grainability of ecosystems within minimal models that intend to capture the atypicality generated by evolution, aiming to establish a conceptual language from which a general theoretical framework can be built.

In the first two chapters, I review the applications of statistical physics in classical models of ecology, moving on to then explore the evolutionary consequences of the atypicality that arises from evolution. In Chapter 3, I present a model for investigating random, structured ecosystems, enabling me to begin studying the emergent coarse-grainability of microbial ecosystems. In particular, I develop the hypothesis that a high strain diversity, despite being nominally more complex, may in fact facilitate coarse-grainability, which is maximized when an ecosystem is assembled in its native environment. Building on this framework in Chapter 4, I provide a more principled approach for defining coarse-grainability by systematically mapping the prediction power versus information content of coarse-grained descriptions of ecosystem composition. Applying this framework to experimental data, I confirm the diversity-enhanced coarse-grainability hypothesis and discuss how this effect cannot be reproduced in standard ecological models parameterized using random ensembles. Finally, I link these results to the theoretical concept of functional attractors of diverse ecosystems.


English (en)

Chair and Committee

Mikhail Tikhonov

Committee Members

Anders Carlsson, Shankar Mukherji, Alexander Seidel, Ralf Wessel,