Journal article

Integrating the underlying structure of stochasticity into community ecology

LG Shoemaker, LL Sullivan, I Donohue, JS Cabral, RJ Williams, MM Mayfield, JM Chase, C Chu, WS Harpole, A Huth, J HilleRisLambers, ARM James, NJB Kraft, F May, R Muthukrishnan, S Satterlee, F Taubert, X Wang, T Wiegand, Q Yang Show all

Ecology | Published : 2020

Open access

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..

View full abstract

University of Melbourne Researchers

Grants

Awarded by National Science Foundation


Funding Acknowledgements

LGS and LLS contributed equally to this manuscript, and authorship was determined by a single draw from a Bernoulli distribution. This work is a joint effort of the working group sNiche (Expanding neo-Chessonian coexistence theory towards a stochastic theory for species rich communities) supported by sDiv, the Synthesis Centre of iDiv (DFG FZT 118). We thank editor Dr. Tom Miller, two anonymous reviewers, and the Snyder and Abbott lab groups for comments that greatly improved the quality of this manuscript. During the completion of this work, LLS was supported by the Legislative-Citizen Commission on Minnesota Resources (LCCMR) Environmental and Natural Resources Trust Fund (ENRTF) grant (M.L. 2016, Ch. 186, Sec. 2, Subd. 08b), and startup funds from the University of Minnesota provided to Allison K. Shaw; LGS was supported by the James S. McDonnell Foundation grant 220020513; KCA was supported by a Complex Systems Scholar Award from the James S. McDonnell Foundation; MMM was supported by an ARC Future Fellowship (FT140100498); NJBK was supported by the National Science Foundation (DEB 1644641); XW was supported by the National Natural Science Foundation of China (31722010) and the Strategic Priority Research Program of the Chinese Academy of Sciences (XDB31030000); CC was supported by the National Natural Science Foundation of China (31570426 and 31622014); QY was supported by a postgraduate scholarship from the Irish Research Council (GOIPG/2013/1474). LLS, LGS, and KCA led the manuscript, LLS, LGS, ID, JSC, RJW, and MMM contributed substantially to writing, modeling, and/or word association analyses. All authors contributed to idea development and provided comments on earlier drafts.