Understanding community changes in ecological systems: a probabilistic and geometric perspective

Abstract

Regulating and predicting community changes in ecological systems represent fundamental challenges in science and engineering, particularly in systems subject to constant environmental perturbations (e.g., natural, in vivo, and in situ environments). Consequently, a central goal of ecological research has been to understand the processes of coexistence, invasion, and assembly in open systems that underlie changes in the composition of ecological communities. These changes can be induced by either natural events (e.g., viruses infecting humans) or human actions (e.g., fecal microbiota transplantation). Although previous studies have theoretically explored criteria for successful coexistence, invasion, and assembly under specific or fixed environmental conditions, the variable and often unknown environmental conditions in nature have left these criteria largely untested.

The overarching goal of my PhD thesis is to provide a testable theoretical framework for the dynamics of coexistence, invasion, and assembly under environmental uncertainty (i.e., in nature or open systems). This framework, rooted in the generalized Lotka-Volterra model, adopts a probabilistic and geometric perspective to understand these dynamics. In particular, my thesis comprises three core projects. The first project develops probabilistic system-level measures to quantify the effects of third-party species on the coexistence of a pair (or subset) of species by integrating population dynamics models (i.e., the Lotka-Volterra model) with in vivo experimental data from fruit fly gut microbiota. Additionally, I test general heuristic rules based on the proposed probabilistic measures using in vitro soil and in vivo gut microbial communities. The aim is to predict how non-resident species (invaders) can alter resident communities and to assess the applicability of our probabilistic measures. The second project seeks to unify coexistence and invasion theories within a geometric and probabilistic framework that is testable. This unification enables us to predict and test the impact of interspecific interactions on invasion and exclusion probabilities without requiring detailed model parameterization or extensive datasets. The third project identifies the general principle governing the development of ecological systems under environmental uncertainty, which could assist in regulating or even predicting changes in ecological community compositions. This principle is validated across a broad spectrum of ecological scales, from large mammals to gut microbes, through publicly available data. I believe this thesis will bring us closer to understanding the processes that influence community compositions and their changes, knowledge that holds great potential for advancing bio-conservation, bio-technologies, and bio-medicine.