An environment-dependent framework of ecological networks
Species interactions are central for the persistence of almost every form of life on Earth. Ecological networks provide an integrated representation of how species interactions are organized within ecological communities. Importantly, ecological networks are highly structured, which has motivated generations of ecologists to elucidate how these structures affect species coexistence. Unfortunately, we still do not have a clear and consistent answer about the link between network structure and species coexistence. Yet, solving this puzzle can provide key insights regarding the maintenance of biodiversity and ecosystem services.
Interestingly, despite the extensive empirical evidence supporting that the environment affects both network structure and species coexistence, most of the studies do not take into account the conditional effects of the environment on these two variables. Indeed, due to the multidimensional and changing nature of environmental factors, it has not been easy to develop a general framework that can link the structure of ecological networks, species coexistence, and the environment. The majority of the theoretical studies have addressed this topic by looking at environmental perturbations on the state space (species abundance) but not on the parameter space (such as intrinsic growth rates and species interactions) of ecological dynamics. However, the vast empirical evidence suggests that system parameters are also perturbed under changing environments. My work has established a rigorous framework to understand how ecological networks affect species coexistence within an environmental context, which has uncovered and explained patterns in a broad range of data from different ecological systems.
Overarching theoretical framework
I argue that this problem can be naturally framed under the notion of structural stability, which can be conceptualized as the range of tolerance to environmental perturbations on system parameters before losing species coexistence (Biodiv. Sci., 2020; Eco. Evo., 2018). Structural stability provides a probabilistic measure of species coexistence with unpredictable environmental perturbations: the larger the structural stability, the more likely the species can coexist under random environmental perturbations. To formalize this concept, I have developed a quantitative estimation of structural stability for arbitrary ecological network structures with any interaction type and trophic constraints for a large class of nonlinear population dynamics (J. Theo. Bio., 2018; Ecology, 2018).
Novel computational methods
Under the umbrella of the overarching theoretical framework, I have developed computational methods to study a wide range of ecological questions beyond the study of local coexistence.
- To study network properties, I developed a new metric to fairly compare nestedness—an important network property—across different ecological communities (J. Anim. Ecol., 2017; J. Anim. Ecol., 2019).
- To study the nature of environmental perturbations, I developed a new method to disentangle different types of environmental perturbations acting on ecological communities (J. Ecol., 2020).
- To study competitive exclusion, I developed a new metric to differentiate contingent and deterministic exclusions (Ecol. Lett., in revision).
- To study priority effects, I developed a new shuffling method to detect the underlying mechanisms (Ecol. Lett., 2018).
Uncovering and explaining patterns in empirical data
The theoretical framework and associated computational methods have opened a new door to understand the context-dependency of local ecological dynamics caused by environmental changes. The figure outlines the breadth of empirical evidence emerging from the framework.
- Focusing on the environmental gradient, I found that ecological systems located in more variable environments have more nested structures (J. Anim. Ecol., 2017; J. Anim. Ecol., 2019).
- Focusing on the environmental stress, I identified that intrinsic growth rates are under stronger environmental perturbations than species interactions (J. Ecol., 2020).
- Focusing on the population dynamics, I found that the network structures of systems governed by mutualistic and antagonistic dynamics can be differentiated if and only if we control for the local environmental variability (PLoS Comp. Bio, 2020).
- Focusing on the interaction modification, I reconciled the observations that mutualisms have tended to persist in nature despite being the most likely to switch in experiments (Trend Eco. Evo., 2020).
- Focusing on the structural transformations, I explained the observed patterns of phenological events (Proc. R. Soc. B., 2018) and competitive exclusions (Ecol. Lett., in revision).