Non-genetic inheritance: Evolution above the organismal level
Em: Biosystems
Editor: Elsevier
Vol: 200
DOI: https://doi.org/10.1016/j.biosystems.2020.104325
Resumo:
The article proposes to further develop the ideas of the Extended Evolutionary Synthesis by including into evolutionary research an analysis of phenomena that occur above the organismal level. We demonstrate that the current Extended Synthesis is focused more on individual traits (genetically or non-genetically inherited) and less on community system traits (synergetic/organizational traits) that characterize transgenerational biological, ecological, social, and cultural systems. In this regard, we will consider various communities that are made up of interacting populations, and for which the individual members can belong to the same or to different species. Examples of communities include biofilms, ant colonies, symbiotic associations resulting in holobiont formation, and human societies. The proposed model of evolution at the level of communities revises classic theorizing on the major transitions in evolution by analyzing the interplay between community/social traits and individual traits, and how this brings forth ideas of top-down regulations of bottom-up evolutionary processes (collaboration of downward and upward causation). The work demonstrates that such interplay also includes reticulate interactions and reticulate causation. In this regard, we exemplify how community systems provide various non-genetic ‘scaffoldings’, ‘constraints’, and ‘affordances’ for individual and sociocultural evolutionary development. Such research complements prevailing models that focus on the vertical transmission of heritable information, from parent to offspring, with research that instead focusses on horizontal, oblique and even reverse information transmission, going from offspring to parent. We call this reversed information transfer the ‘offspring effect’ to contrast it from the ‘parental effect’. We argue that the proposed approach to inheritance is effective for modelling cumulative and distributed developmental process and for explaining the biological origins and evolution of language.