Characterizing spatiotemporal patterns in three-state lattice models

TL;DR

This paper investigates the coexistence patterns in a two-species spatial model, distinguishing between homogeneous and spatiotemporal oscillatory states, and introduces metrics and corrections to better understand these dynamics.

Contribution

It introduces new metrics for characterizing spatiotemporal patterns and develops correction methods to improve mean-field models based on simulation data.

Findings

Identification of noise-sustained oscillations in spatiotemporal patterns

Development of metrics to characterize pattern onset

Enhanced mean-field models with correction sequences

Abstract

A two-species spatially extended system of hosts and parasitoids is studied. There are two distinct kinds of coexistence; one with populations distributed homogeneously in space and another one with spatiotemporal patterns. In the latter case, there are noise-sustained oscillations in the population densities, whereas in the former one the densities are essentially constants in time with small fluctuations. We introduce several metrics to characterize the patterns and onset thereof. We also build a consistent sequence of corrections to the mean-field equations using a posteriori knowledge from simulations. These corrections both lead to better description of the dynamics and connect the patterns to it. The analysis is readily applicable to realistic systems, which we demonstrate by an example using an empirical metapopulation landscape.