Differences in initial abundances reveal divergent dynamic structures in Gause's predator–prey experiments. Issue 12 (18th December 2022)

• Record Type: Journal Article
• Authors: Mühlbauer, Lina Kaya; Harpole, William Stanley; Clark, Adam Thomas
• Is Part Of: Ecology and evolution. Volume 12:Issue 12(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-12-18
• Subjects: chaos -- empirical dynamic modeling -- initial abundance -- microcosm experiments -- nonlinear dynamics -- time series analysis; Ecology -- Periodicals; Evolution -- Periodicals; 577.05
• DOI: 10.1002/ece3.9638
• Languages: English
• ISSNs: 2045-7758

Abstract

Abstract: Improved understanding of complex dynamics has revealed insights across many facets of ecology, and has enabled improved forecasts and management of future ecosystem states. However, an enduring challenge in forecasting complex dynamics remains the differentiation between complexity and stochasticity, that is, to determine whether declines in predictability are caused by stochasticity, nonlinearity, or chaos. Here, we show how to quantify the relative contributions of these factors to prediction error using Georgii Gause's iconic predator–prey microcosm experiments, which, critically, include experimental replicates that differ from one another only in initial abundances. We show that these differences in initial abundances interact with stochasticity, nonlinearity, and chaos in unique ways, allowing us to identify the impacts of these factors on prediction error. Our results suggest that jointly analyzing replicate time series across multiple, distinct starting points may be necessary for understanding and predicting the wide range of potential dynamic types in complex ecological systems. Abstract : In this manuscript, we show that differences in the initial abundances in a two‐species predator–prey microcosm experiment leads to divergence in their underlying dynamics, which impedes precise forecasting across replicates. We then access the relative contributions of nonlinearity, chaos, and stochasticity to this decrease in predictability. To do this, we analyze time‐series data of two predator–prey systems, produced by Georgii F. Gause in 1936. In these experiments, replicates only differ in their initial abundances.