Visualising Speciation in Models of Cichlid Fish

An Agent-Based model of speciation in cichlid fish has been implemented. When run, this generates large amounts of trace data in which speciation is an implicit, near unobservable, processes. Fuzzy C-Means Clustering is used to identify species extant at the end of simulation, and the power set of these species is the potential set of ancestral species. Membership values for all fish in each of these theoretical ancestral species are calculated, and total set membership for each of these species is plotted against time. The resulting graph is to be a clear visualisation of the process of speciation, and the appearance and disappearance of intermediate species. Our approach allows the visualisation of speciation resulting in larger numbers of final species than was possible using previous techniques based on measuring correlations between explicit properties of modeled organisms, and is also unaffected by changes to the properties used to model fish.