Use of recurrence analysis to measure the dynamical stability of a multi-species community model

Abstract

Quantifying the effects of species richness and environmental disturbance on the stability of communities is a long-standing challenge in ecology. In this study, multivariate recurrence analysis was used to assess the dynamical stability of modelled ecological communities subject to random, correlated environmental noise. Based on an analysis of biomass time series for each species, we show that two measures computed from the joint recurrence matrix, the Kolmogorov entropy and percent determinism, capture aspects of community stability that are not detected using the coefficient of variation for the whole community. In particular, when population fluctuations are correlated in time, recurrence analysis is a superior method for detecting the stabilizing effect of species richness on a community. We conclude that recurrence analysis is an appropriate tool for the analysis of ecological data, and that it may be particularly useful for detecting the relative importance of exogenous and endogenous drivers on the dynamics of ecological communities.