TY - JOUR

T1 - Integrating the underlying structure of stochasticity into community ecology

AU - Shoemaker, Lauren G.

AU - Sullivan, Lauren L.

AU - Donohue, Ian

AU - Cabral, Juliano S.

AU - Williams, Ryan J.

AU - Mayfield, Margaret M.

AU - Chase, Jonathan M.

AU - Chu, Chengjin

AU - Harpole, W. Stanley

AU - Huth, Andreas

AU - HilleRisLambers, Janneke

AU - James, Aubrie R.M.

AU - Kraft, Nathan J.B.

AU - May, Felix

AU - Muthukrishnan, Ranjan

AU - Satterlee, Sean

AU - Taubert, Franziska

AU - Wang, Xugao

AU - Wiegand, Thorsten

AU - Yang, Qiang

AU - Abbott, Karen C.

PY - 2020/2/1

Y1 - 2020/2/1

N2 - 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.

AB - 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.

KW - autocorrelation

KW - demographic stochasticity

KW - distribution

KW - diversity

KW - environmental stochasticity

KW - population dynamics

KW - scale

KW - uncertainty

KW - Ecosystems Research

KW - Environmental Governance

UR - http://www.scopus.com/inward/record.url?scp=85077182019&partnerID=8YFLogxK

U2 - 10.1002/ecy.2922

DO - 10.1002/ecy.2922

M3 - Journal articles

C2 - 31652337

AN - SCOPUS:85077182019

VL - 101

JO - Ecology

JF - Ecology

SN - 0012-9658

IS - 2

M1 - e02922

ER -