How to quantify the temporal storage effect using simulations instead of math.
The storage effect has become a core concept in community ecology, explaining how environmental fluctuations can promote coexistence and maintain biodiversity. However, limitations of existing theory have hindered empirical applications: the need for detailed mathematical analysis whenever the study system requires a new model, and restricted theory for structured populations. We present a new approach that overcomes both these limitations. We show how temporal storage effect can be quantified by Monte Carlo simulations in a wide range of models for competing species. We use the lottery model and a generic integral projection model (IPM) to introduce ideas, and present two empirical applications: (1) algal species in a chemostat with variable temperature, showing that the storage effect can operate without a long-lived life stage and (2) a sagebrush steppe community IPM. Our results highlight the need for careful modelling of nonlinearities so that conclusions are not driven by unrecognised model constraints.
Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY, USA. spe2@cornell.edu.
Stephen P
SP
Ellner
Department of Biology, Case Western Reserve University, Cleveland, OH, USA.
Robin E
RE
Snyder
Department of Wildland Resources and the Ecology Center, Utah State University, Logan, UT, USA.
Peter B
PB
Adler
D044822:Biodiversity; D003198:Computer Simulation; D017377:Diatoms / Q000502:physiology; D008954:Models, Biological; D010507:Periodicity; D013997:Time Factors
Coexistence; competition; environmental variability; integral projection model; storage effect; structured population model