A residence time theory for biodiversity

School of STEM, Dine College, Tsaile, Arizona, United States
Biology, Indiana University, Bloomington, Indiana, United States
DOI
10.7287/peerj.preprints.2727v3
Subject Areas
Biodiversity, Ecology, Ecosystem Science, Microbiology
Keywords
individual based modeling, ecological theory, trait diversity, growth dynamics, life history traits, chemostat theory, emergent properties, ecological constraints, dilution rate, metabolic rate
Copyright
© 2018 Locey et al.
Licence
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
Cite this article
Locey KJ, Lennon JT. 2018. A residence time theory for biodiversity. PeerJ Preprints 6:e2727v3

Abstract

From microorganisms to the largest macroorganisms, much of Earth’s biodiversity is subject to forces of physical turnover. Residence time is the ratio of an ecosystem’s size to its rate of flow and provides a means for understanding the influence of physical turnover on biological systems. Despite its use across scientific disciplines, residence time has not been integrated into the broader understanding of biodiversity, life history, and the assembly of ecological communities. Here, we propose a residence time theory for the growth, activity, abundance, and diversity of traits and taxa in complex ecological systems. Using thousands of stochastic individual-based models to simulate energetically constrained life history processes, we show that our predictions are conceptually sound, mutually compatible, and support ecological relationships that underpin much of biodiversity theory. We discuss the importance of residence time across the ecological hierarchy and propose how residence time can be integrated into theories ranging from population genetics to macroecology.

Author Comment

This most recent version is an extensive revision of the previous. All sections (Abstract, Intro, Methods, Results, and Discussion) have been greatly revised.

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