Digital evolution is a computer-based instantiation of Darwinian evolution in which short self-replicating computer programs compete, mutate, and evolve. It is an excellent platform for addressing topics in long-term evolution and paleobiology, such as mass extinction and recovery, with experimental evolutionary approaches. We evolved model communities with ecological interdependence among community members, which were subjected to two principal types of mass extinction: a pulse extinction that killed randomly, and a selective press extinction involving an alteration of the abiotic environment to which the communities had to adapt. These treatments were applied at two different strengths, along with unperturbed control experiments. We examined how stability in the digital communities was affected from the perspectives of division of labor, relative shift in rank abundance, and genealogical connectedness of the community's component ecotypes. Mass extinction that was due to a Strong Press treatment was most effective in producing reshaped communities that differed from the pre-treatment ones in all of the measured perspectives; weaker versions of the treatments did not generally produce significant departures from a Control treatment; and results for the Strong Pulse treatment generally fell between those extremes. The Strong Pulse treatment differed from others in that it produced a slight but detectable shift towards more generalized communities. Compared to Press treatments, Pulse treatments also showed a greater contribution from re-evolved ecological doppelgangers rather than new ecotypes. However, relatively few Control communities showed stability in any of these metrics over the whole course of the experiment, and most did not represent stable states (by some measure of stability) that were disrupted by the extinction treatments. Our results have interesting, broad qualitative parallels with findings from the paleontological record, and show the potential of digital evolution studies to illuminate many aspects of mass extinction and recovery by addressing them in a truly experimental manner.

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Among the major unresolved questions in ecosystem evolution are whether coevolving multispecies communities are dominated more by biotic or by abiotic factors, and whether evolutionary stasis affects performance as well as ecological profile; these issues remain difficult to address experimentally. Digital evolution, a computer-based instantiation of Darwinian evolution in which short self-replicating computer programs compete, mutate, and evolve, is an excellent platform for investigating such topics in a rigorous experimental manner. We evolved model communities with ecological interdependence among community members, which were subjected to two principal types of mass extinction: a pulse extinction that killed randomly, and a selective press extinction involving an alteration of the abiotic environment to which the communities had to adapt. These treatments were applied at two different strengths (Strong and Weak), along with unperturbed Control experiments. We performed several kinds of competition experiments using simplified versions of these communities to see whether long-term stability that was implied previously by ecological and phylogenetic metrics was also reflected in performance, namely, whether fitness was static over long periods of time. Results from Control and Weak treatment communities revealed almost completely transitive evolution, while Strong treatment communities showed higher incidences of temporal intransitivity, with pre-treatment ecotypes often able to displace some of their post-recovery successors. However, pre-treatment carryovers more often had lower fitness in mixed communities than in their own fully native conditions. Replacement and invasion experiments pitting single ecotypes against pre-treatment reference communities showed that many of the invading ecotypes could measurably alter the fitnesses of one or more residents, usually with depressive effects, and that the strength of these effects increased over time even in the most stable communities. However, invaders taken from Strong treatment communities often had little or no effect on resident performance. While we detected periods of time when the fitness of a particular evolving ecotype remained static, this stasis was not permanent and never affected an entire community at once. Our results lend support to the fitness-deterioration interpretation of the Red Queen hypothesis, and highlight community context dependence in determining fitness, the shaping of communities by both biotic factors and abiotic forcing, and the illusory nature of evolutionary stasis. Our results also demonstrate the potential of digital evolution studies to illuminate many aspects of evolution in interacting multispecies communities.