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Evolution of biological complexity seems to be a great puzzle. Although the extended evolutionary synthesis and modern technology provide a wide range of theoretical models and practical tools to study evolutionary dynamics [1][2], evolution of complexity is usually omitted. Moreover, some researchers propose that complexity can be treated as the byproduct of evolutionary adaptation [3]. For this reason it is important to develop new tools and methods to study complexity dynamics in evolution.
Inspired by the Maxwell's Demon, the Demonic Selection Principle states that the complexity of the population of organisms cannot be greater than complexity of all selective filters acting on it [4]. Although the principle itself can be questioned, the upper complexity limit is thought to be dynamic. For example, the population itself may permanently change its own environment that in consequence leads to distortions of selection pressures, creating a feedback. However, the relation between selection forces and the complexity of adapting population remains vague.
For this reason, a new method to study evolution of complexity was created, i.e., complexity flow graphs. The graphs try to track dynamics of evolving population complexity by estimation of changes in biocomplexity and complexity of selective filters that shape it. The comprehension of relative changes between these complexities may shed more light on the evolution of complexity. Complexity flow graphs were created based on a model incorporating 1D cellular automata inspired by a process of evolution with niche construction.
[1] Laland K. N. et al. (2015) The extended evolutionary synthesis: its structure, assumptions and predictions. Proc. R. Soc. B., 282(1813), https://doi.org/10.1098/rspb.2015.1019
[2] Zhang J. (2023) What Has Genomics Taught An Evolutionary Biologist? Genomics, Proteomics & Bioinformatics, 21(1), https://doi.org/10.1016/j.gpb.2023.01.005
[3] Houle D. & Rossoni M.R. (2022) Complexity, Evolvability, and the Process of Adaptation, Annual Review of Ecology, Evolution, and Systematics, 53(1), https://doi.org/10.1146/annurev-ecolsys-102320-090809
[4] Krakauer, D.C. (2011) Darwinian demons, evolutionary complexity, and information maximization. Chaos, 41, https://doi.org/10.1063/1.3643064
