Towards physical principles of biological evolution

Biological systems reach organizational complexity that far exceeds the complexity of any known inanimate objects. Biological entities undoubtedly obey the laws of quantum physics and statistical mechanics. However, is modern physics sufficient to adequately describe, model and explain the evolution of biological complexity? Detailed parallels have been drawn between statistical thermodynamics and the population-genetic theory of biological evolution. Based on these parallels, we outline new perspectives on biological innovation and major transitions in evolution, and introduce a biological equivalent of thermodynamic potential that reflects the innovation propensity of an evolving population. Deep analogies have been suggested to also exist between the properties of biological entities and processes, and those of frustrated states in physics, such as glasses. We extend such analogies by examining frustration-type phenomena, such as conflicts between different levels of selection, in biological evolution. We further address evolution in multidimensional fitness landscapes from the point of view of percolation theory and suggest that percolation at level above the critical threshold dictates the tree-like evolution of complex organisms. Taken together, these multiple connections between fundamental processes in physics and biology imply that construction of a meaningful physical theory of biological evolution might not be a futile effort.Comment: Invited article, Focus Issue on 21th Century Frontiers, final versio

Rank Statistics in Biological Evolution

We present a statistical analysis of biological evolution processes. Specifically, we study the stochastic replication-mutation-death model where the population of a species may grow or shrink by birth or death, respectively, and additionally, mutations lead to the creation of new species. We rank the various species by the chronological order by which they originate. The average population N_k of the kth species decays algebraically with rank, N_k ~ M^{mu} k^{-mu}, where M is the average total population. The characteristic exponent mu=(alpha-gamma)/(alpha+beta-gamma)$ depends on alpha, beta, and gamma, the replication, mutation, and death rates. Furthermore, the average population P_k of all descendants of the kth species has a universal algebraic behavior, P_k ~ M/k.Comment: 4 pages, 3 figure

Evolution of Biological Complexity

In order to make a case for or against a trend in the evolution of complexity in biological evolution, complexity needs to be both rigorously defined and measurable. A recent information-theoretic (but intuitively evident) definition identifies genomic complexity with the amount of information a sequence stores about its environment. We investigate the evolution of genomic complexity in populations of digital organisms and monitor in detail the evolutionary transitions that increase complexity. We show that because natural selection forces genomes to behave as a natural ``Maxwell Demon'', within a fixed environment genomic complexity is forced to increase.Comment: LaTeX 19 pages, incl. 4 fig

Nonlinear deterministic equations in biological evolution

We review models of biological evolution in which the population frequency changes deterministically with time. If the population is self-replicating, although the equations for simple prototypes can be linearised, nonlinear equations arise in many complex situations. For sexual populations, even in the simplest setting, the equations are necessarily nonlinear due to the mixing of the parental genetic material. The solutions of such nonlinear equations display interesting features such as multiple equilibria and phase transitions. We mainly discuss those models for which an analytical understanding of such nonlinear equations is available.Comment: Invited review for J. Nonlin. Math. Phy

Does Meaning Evolove?

A common method of improving how well understood a theory is, is by comparing it to another theory which has been better developed. Radical interpretation is a theory which attempts to explain how communication has meaning. Radical interpretation is treated as another time dependent theory and compared to the time dependent theory of biological evolution. Several similarities and differences are uncovered. Biological evolution can be gradual or punctuated. Whether radical interpretation is gradual or punctuated depends on how the question is framed: on the coarse-grained time scale it proceeds gradually, but on the fine-grained time scale it proceeds by punctuated equilibria. Biological evolution proceeds by natural selection, the counterpart to this is the increase in both correspondence and coherence. Exaption, mutations, and spandrels have counterparts metaphor, speech errors, and puns respectively. Homologous and analogs have direct counterparts in specific words. The most important differences originate from the existence of a unit of inheritance (the traditional gene) occurring in biological evolution - there is no such unit in language

Self-organized Critical Model Of Biological Evolution

A punctuated equilibrium model of biological evolution with relative fitness between different species being the fundamental driving force of evolution is introduced. Mutation is modeled as a fitness updating cellular automaton process where the change in fitness after mutation follows a Gaussian distribution with mean $x>0$ and standard deviation $\sigma$. Scaling behaviors are observed in our numerical simulation, indicating that the model is self-organized critical. Besides, the numerical experiment suggests that models with different $x$ and $\sigma$ belong to the same universality class. PACS numbers: 87.10.+e, 05.40.+jComment: 8 pages in REVTEX 3.0 with 4 figures (Figures available on request by sending e-mail to [email protected]

Cultural replication and microbial evolution

The aim of this paper is to argue that cultural evolution is in many ways much more similar to microbial than to macrobial biological evolution. As a result, we are better off using microbial evolution as the model of cultural evolution. And this shift from macrobial to microbial entails adjusting the theoretical models we can use for explaining cultural evolution