Ecology in a variable and uncertain world
Natural communities are enormously diverse and dynamic. One of the greatest challenges of modern ecology is to understand how the core processes of population dynamics – species habitat utilization, biotic interactions, and dispersal – interact across scales to determine patterns of biodiversity. Yet ecologists more often make simplifying assumptions that focus on one process while ignoring environmental variability in time and space. I ask what new insights emerge if we instead assume that environmental variability is essential to explain many natural patterns because of its significant influence on species’ population dynamics.
My work is motivated by the use of mathematical tools to disentangle the complex interplay of mechanisms generating these patterns. Even in empirical studies, a mathematical formalization of population and community processes provides a unifying conceptual foundation that can provide clear direction for tests and broaden the implications of results. Here, I summarize my research, which has often relied on data and experiments from plant communities to explore and test ideas related specifically to the role of species interactions in diversity maintenance. In particular, I seek to understand how biodiversity patterns across spatial scales emerge from competition between species’ populations for limited resources in a variable world.
New and cutting edge research
The ecology of information.
Every living organism uses information about its environment to optimize its fitness in a variable and uncertain world. Yet information is rarely seen as a fundamental feature of ecology, which hinders our understanding of information’s key role in population, community, and ecosystem dynamics. In my current work in the O’Connor lab, I am developing a new theoretical framework to understand the role of information in ecology. This is a work in progress but I’ve already produced a ton of raw code on github.
Food web ecology in a dynamic world
An extension of the ecology of information is to understand the dynamic, information-processing properties of food webs. This will help us better understand how impacts of climate change on individual species can cascade through food webs via species interactions. A primary 
goal of this theory is to unite our understanding of population dynamics and energetics into one framework to jointly consider their importance for species persistence. I draw on theoretical developments across disciplines as diverse as physics, chemistry, and computation that use statistical (information) entropy as a basis to model complex dynamical systems. This is also a work in progress but check out raw code on github. Also, some preliminary visualizations of the dynamics information processing properties of simulated food webs are available here! Check back soon for updates on this (overambitious?) project!