Philosophy and Evolution: Minding the Gap Between Evolutionary Patterns and Tree-Like Patterns

Ever since Darwin, the familiar genealogical pattern known as the Tree of Life (TOL) has been prominent in evolutionary thinking and has dominated not only systematics, but also the analysis of the units of evolution. However, recent findings indicate that the evolution of DNA, especially in prokaryotes and such DNA vehicles as viruses and plasmids, does not follow a unique tree-like pattern. Because evolutionary patterns track a greater range of processes than those captured in genealogies, genealogical patterns are in fact only a subset of a broader set of evolutionary patterns. This fact suggests that evolutionists who focus exclusively on genealogical patterns are blocked from providing a significant range of genuine evolutionary explanations. Consequently, we highlight challenges to tree-based approaches, and point the way toward more appropriate methods to study evolution (although we do not present them in technical detail). We argue that there is significant benefit in adopting wider range of models, evolutionary representations, and evolutionary explanations, based on an analysis of the full range of evolutionary processes. We introduce an ecosystem orientation into evolutionary thinking that highlights the importance of “type 1 coalitions” (functionally related units with genetic exchanges, aka “friends with genetic benefits”), “type 2 coalitions” (functionally related units without genetic exchanges), “communal interactions,” and “emergent evolutionary properties.” On this basis, we seek to promote the study of (especially prokaryotic) evolution with dynamic evolutionary networks, which are less constrained than the TOL, and to provide new ways to analyze an expanded range of evolutionary units (genetic modules, recombined genes, plasmids, phages and prokaryotic genomes, pangenomes, microbial communities) and evolutionary processes. Finally, we discuss some of the conceptual and practical questions raised by such network-based representation.