Effects of correlated interactions in a biological coevolution model with individual-based dynamics

Abstract

Models of coevolution have recently been studied, in which a species is defined by a genome in the form of a bitstring, and the interactions between species i and j are given by a fixed matrix with independent, randomly distributed elements M_{ij}. A consequence of the stochastic independence is that species whose genotypes differ even by a single bit may have completely different phenotypes. This is clearly unrealistic, as closely related species should be similar in their interactions with the rest of the ecosystem. Here we therefore study a model, in which the M_{ij} are correlated to a controllable degree. We calculate, both analytically and numerically, the correlation function for matrix elements M_{ij} and M_{kl} versus the Hamming distance between the bitstrings representing the species. We compare Monte Carlo simulations of coevolution models with uncorrelated and correlated interactions. In particular, we consider the lifetimes of individual species. The species-lifetime distribution is close to a power law with an exponent near -2 in both uncorrelated and correlated cases. The durations of quasi-steady states and power spectral densities for the diversity indices display noticeable differences. However, some qualitative features, like 1/f behaviour in power spectral densities for the diversity indices, are not affected by the correlations in the interaction matrix.