PCI Evolutionary Biology vient d’émettre une recommandation pour l’article “Selection for Function, Persistence, and Darwinian Evolution” coordonné par Frédéric Thomas (CNRS, IRD, Université de Montpellier) et Jean-Pascal Capp (TBI) : https://evolbiol.peercommunityin.org/articles/rec?id=877
Pour en savoir plus sur PCI : https://peercommunityin.org/
et son soutien par l’INRAE : https://science-ouverte.inrae.fr/fr/inrae-editeur/les-initiatives-editoriales-soutenues-par-inrae/peer-community Le CNRS soutient également PCI.
Le preprint est accessible à cette adresse : https://zenodo.org/records/20124383
Abstract
Darwinian selection (DS), based on heritable variation and differential reproductive success, is central to evolutionary theory. However, many systems in biology, including prebiotic molecular networks, microbial communities, and tumors, persist and exhibit structured dynamics despite lacking clear reproduction or lineage-based inheritance at the relevant level. Building on, but also critically refining, the concept of selection for function (SF) proposed by Wong et al. [1], we argue that SF provides a complementary descriptive framework for interpreting such systems. Rather than offering an alternative causal explanation to Darwinian processes, SF emphasizes the differential persistence of functionally coherent configurations over time. Its main value is heuristic and integrative: it makes persistence-based patterns explicit across systems in which lineage-based descriptions are incomplete, diffuse, or difficult to apply at the focal scale. Although in many biological contexts, the emergence and maintenance of traits are well explained by established Darwinian frameworks (e.g., kin selection, multilevel selection, or mutation–selection dynamics), SF highlights how system-level organization and persistence shape long-term outcomes. Through examples including seed dormancy, sexual reproduction, symbioses, biofilms, and tumor organization, we illustrate how configurations that may be costly or neutral at the individual level can nevertheless contribute to system-level stability and persistence. SF is particularly informative in systems where reproduction and inheritance are weak, diffuse, or difficult to define, but it remains compatible with Darwinian dynamics when these are present. By making persistence-based filtering explicit, SF complements existing evolutionary frameworks and provides an additional lens for interpreting complex, multilevel, and non-replicating systems. “
