%0 Journal Article
%T Integrating the underlying structure of stochasticity into community ecology
%A Andreas Huth
%A Aubrie R. M. James
%A Chengjin Chu
%A Felix May
%A Franziska Taubert
%A Ian Donohue
%A Janneke HilleRisLambers
%A Jonathan M. Chase
%A Juliano S. Cabral
%A Karen C. Abbott
%A Lauren G. Shoemaker
%A Lauren L. Sullivan
%A Margaret M. Mayfield
%A Nathan J. B. Kraft
%A Qiang Yang
%A Ranjan Muthukrishnan
%A Ryan J. Williams
%A Sean Satterlee
%A Thorsten Wieg
%A W. Stanley Harpole
%A Xugao Wang
%J Ecology - Wiley Online Library
%D 2019
%R https://doi.org/10.1002/ecy.2922
%X 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. Variability plays a central role in structuring ecological communities (Chesson 2000, Ives and Carpenter 2007, Leibold and Chase 2018). This variability comes from multiple sources, such as heterogeneity across space and time (Tilman 1994, Mouquet and Loreau 2003, Questad and Foster 2008, Hart et al. 2017), variation among individuals (Clark 2010, Bolnick et al. 2011, Clark et al. 2011), and stochasticity (Lande 1993, Vellend et al. 2014, Vellend 2016). Although stochasticity is well known to be one of the key sources of variability in ecological communities, it is not considered as a driver of community dynamics as frequently as other forms of variability (Hart et al. 2017). For example, in diverse communities stochasticity is often equated with neutrality (Vellend et al. 2014) or is simply treated as an impediment to our ability to understand dynamics (Boettiger 2018). In fact, stochasticity arises from the probabilistic nature of core biological processes, including births, deaths, species interactions, and movement (May 1973, Cohen 1976, Clark 2005, Black and McKane 2012), each of which can be described by an underlying distribution of possible events. Communities are the outcome of interactions among these
%U https://esajournals.onlinelibrary.wiley.com/doi/full/10.1002/ecy.2922