Are predator-prey model predictions supported by empirical data? Evidence for a storm-driven shift to an alternative stable state in a crab-clam system

Abstract

A dynamic systems approach can predict steady states in predator-prey interactions, but there are very few examples of predictions from predator-prey models conforming to empirical data. Here, we examined the evidence for the low-density steady state predicted by a Lotka-Volterra model of a crab-clam predator-prey system using data from long-term monitoring, and data from a previously published field survey and field predation experiment. Changepoint analysis of time series data indicate that a shift to low density occurred for the soft-shell clam Mya arenaria in 1972, the year of Tropical Storm Agnes. A possible mechanism for the shift is that Agnes altered predator-prey dynamics between M. arenaria and the blue crab Callinectes sapidus, shifting from a system controlled from the bottom up by prey resources, to a system controlled from the top down by predation pressure on bivalves, which is supported by a correlation analysis of time series data. Predator-prey ordinary differential equation models with these 2 species were analyzed for steady states, and low-density steady states were similar to previously published clam densities and mortality rates, consistent with the idea that C. sapidus is a major driver of M. arenaria population dynamics. Relatively simple models can predict shifts to alternative stable states, as shown by agreement between model predictions (this study) and published field data in this system. The preponderance of multispecies interactions exhibiting nonlinear dynamics indicates that this may be a general phenomenon.