Assortative mating and mutation diffusion in spatial evolutionary systems

Abstract

The influence of spatial structure on the equilibrium properties of a sexual population model defined on networks is studied numerically. Using a small-world-like topology of the networks as an investigative tool, the contributions to the fitness of assortative mating and of global mutant spread properties are considered. Simple measures of nearest-neighbor correlations and speed of spread of mutants through the system have been used to confirm that both of these dynamics are important contributory factors to the fitness. It is found that assortative mating increases the fitness of populations. Quick global spread of favorable mutations is shown to be a key factor increasing the equilibrium fitness of populations.

Analysis and perturbation of degree correlation in complex networks

“…In order to characterize and understand such preference of connections in complex networks, many statistical measures and network models have been introduced and investigated [2,3,[25][26][27][28][29][30][31][32][33][34][35][36]. For example, the average nearest neighbors' degree of nodes (ANND) [3] and the degree correlation coefficient…”

“…In biological and technological networks, high-degree nodes often preferably connect to low-degree nodes, which is referred to as -dissassortative mixing‖. The degree correlation has important influence on the topological properties of networks and may impact related problems on networks such as stability [6], the robustness of networks against attacks [7], the network controllability [8], the traffic dynamics on networks [9,10], the network synchronization [11][12][13], the spreading of information or infections and other dynamic processes [7,[13][14][15][16][17][18][19][20][21][22][23][24].In order to characterize and understand such preference of connections in complex networks, many statistical measures and network models have been introduced and investigated [2,3,[25][26][27][28][29][30][31][32][33][34][35][36]. For example, the average nearest neighbors' degree of nodes (ANND) [3] and the degree correlation coefficient…”