Ecological stability is complex and multifaceted, fueling vigorous research into ecosystem attributes that contribute to stability. However, the integration and synthesis of stability research is difficult because relationships between different definitions of stability are not always understood or easily compared, and theoretical and empirical studies tend to focus on different aspects.
In this study we compare two definitions of stability measured from the same experimental aquatic mesocosm communities. Temporal variability, expressed as the coefficient of variation (CV), measures ongoing variability and is used frequently in empirical studies. Asymptotic stability, estimated by the dominant eigenvalue of the community matrix, measures the asymptotic rate of return to equilibrium after a perturbation and is typically the focus of theoretical work.
Using time series data, we calculated the CV of plankton populations and communities. Through multivariate-autoregressive models (MARs), we also generated community matrices from which we calculated asymptotic resilience. We use these various stability measures to explore how different definitions of stability are related, and how ecosystem attributes such as species richness and interaction strength affect different aspects of stability.
Our results indicate that temporal stability of populations and communities is not clearly associated with increased stability as measured by asymptotic resilience. We also find that different attributes of ecosystems (species richness and interaction strength) do not affect different definitions of stability in the same way. For instance, species richness tends to enhance the temporal stability of populations and communities, but does not clearly enhance asymptotic stability. And, while interaction strength has been proposed to be an important attribute of ecosystems whereby more weak interactions promote stability, our results do not consistently agree with this hypothesis.
In summary, we show that different measures of stability may not always be correlated, and mechanisms that work to promote one type of stability may not work for all definitions of stability. Therefore we must proceed carefully as we try to integrate and synthesize the results of different studies that use quite different measures of stability.