Integrating the underlying structure of stochasticity into community ecology

Abstract

Stochasticity is a core component of ecology, as it underlies key processes that structure and create variability in nature. Despite its fundamental importance in ecological systems, the concept is often treated as synonymous with unpredictability in community ecology, and studies tend to focus on single forms of stochasticity rather than taking a more holistic view. This has led to multiple narratives for how stochasticity mediates community dynamics. Here, we present a framework that describes how different forms of stochasticity (notably demographic and environmental stochasticity) combine to provide underlying and predictable structure in diverse communities. This framework builds on the deep ecological understanding of stochastic processes acting at individual and population levels and in modules of a few interacting species. We support our framework with a mathematical model that we use to synthesize key literature, demonstrating that stochasticity is more than simple uncertainty. Rather, stochasticity has profound and predictable effects on community dynamics that are critical for understanding how diversity is maintained. We propose next steps that ecologists might use to explore the role of stochasticity for structuring communities in theoretical and empirical systems, and thereby enhance our understanding of community dynamics.

A process‐based metacommunity framework linking local and regional scale community ecology

“…Vellend 2016), we consider it to be an element of each of the three processes. This is because biological processes are probabilistic, resulting in stochasticity in demography and dispersal (Shoemaker et al 2019), which aligns with the long history of models that have included it via probabilistic draws of the underlying biological processes (e.g. Levins & Culver 1971; Hubbell 2001; Matias et al .…”

“…Third, while stochasticity is a critical feature of our framework, we do not consider it as a separate process, but instead consider stochasticity as an inherent feature in the realisation of the three fundamental processes—abiotic responses, biotic interactions and dispersal—which ultimately generates demographic stochasticity (Shoemaker et al . 2019). By distinguishing processes in this way, we can unite metacommunity theory and local coexistence within a single mathematical framework.…”

Biodiversity conservation through the lens of metacommunity ecology

“…Environmental stochasticity can also impose abundance fluctuations, but via deterministic environmental filtering. Although both types of stochasticity affect metacommunity functioning, their effects can be substantially different 55,58 …”

Trait plasticity alters the range of possible coexistence conditions in a competition–colonisation trade‐off

“…A challenge for coexistence theory has been the ability to link theoretical work, which generally focuses on relatively few species in constrained circumstances, with empirical observations of communities that display extremely high diversity (Clark et al ). Population dynamics become significantly more complex when moving from two species to three or more, often producing complex waves, limit cycles or even chaotic behaviour (Hutson & Law ; Hassell et al ; Huisman & Weissing ), and a more complex set of species interactions can arise in multispecies communities (Levine et al , Shoemaker et al ). As such, coexistence mechanisms that require a finely tuned balance of processes are difficult to evaluate in multispecies systems, and are less likely to maintain equilibrium, particularly when stochastic components are incorporated.…”