Examining Community Stability in the Face of Mass Extinction in Communities of Digital Organisms

Symbiosis in Digital Evolution: Past, Present, and Future

Symbiosis, the living together of unlike organisms as symbionts, is ubiquitous in the natural world. Symbioses occur within and across all scales of life, from microbial to macro-faunal systems. Further, the interactions between symbionts are multimodal in both strength and type, can span from parasitic to mutualistic within one partnership, and persist over generations. Studying the ecological and evolutionary dynamics of symbiosis in natural or laboratory systems poses a wide range of challenges, including the long time scales at which symbioses evolve de novo, the limited capacity to experimentally control symbiotic interactions, the weak resolution at which we can quantify interactions, and the idiosyncrasies of current model systems. These issues are especially challenging when seeking to understand the ecological effects and evolutionary pressures on and of a symbiosis, such as how a symbiosis may shift between parasitic and mutualistic modes and how that shift impacts the dynamics of the partner population. In digital evolution, populations of computational organisms compete, mutate, and evolve in a virtual environment. Digital evolution features perfect data tracking and allows for experimental manipulations that are impractical or impossible in natural systems. Furthermore, modern computational power allows experimenters to observe thousands of generations of evolution in minutes (as opposed to several months or years), which greatly expands the range of possible studies. As such, digital evolution is poised to become a keystone technique in our methodological repertoire for studying the ecological and evolutionary dynamics of symbioses. Here, we review how digital evolution has been used to study symbiosis, and we propose a series of open questions that digital evolution is well-positioned to answer.

Alteration of (Frequency-Dependent) Fitness in Time-Shift Experiments Reveals Cryptic Coevolution and Uncoordinated Stasis in a Virtual Jurassic Park

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.