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.

💡 Research Summary

The paper asks whether the laws of modern physics are sufficient to describe the extraordinary organizational complexity that biological systems achieve. It begins by drawing a formal analogy between statistical thermodynamics and population‑genetic theory. In thermodynamics, a system evolves toward a minimum of free energy; in evolutionary biology, the average fitness of a population changes under mutation, selection, and drift. To bridge the two, the authors introduce a “biological potential” ϕ, a scalar function that depends on mutation rate (μ), selection strength (s), effective population size (N_e) and other evolutionary parameters. Just as free energy drives physical systems toward equilibrium, the decrease of ϕ drives a population toward states with higher “innovation propensity.” In this view, evolution can be recast as a process of minimizing a thermodynamic‑like potential.

Next, the authors import the concept of frustration from condensed‑matter physics, especially the behavior of spin glasses, into evolutionary theory. In a glass, competing interactions prevent the system from reaching a single global minimum, producing a rugged energy landscape with many metastable minima. Analogously, biological evolution is subject to conflicts among multiple levels of selection—genes, cells, organisms, and groups. These conflicts generate a “frustrated” evolutionary landscape where populations wander among numerous quasi‑stable configurations. The paper argues that such frustration underlies both periods of rapid innovation (e.g., post‑mass‑extinction radiations) and prolonged stasis (e.g., morphological conservatism). High frustration increases the density of local fitness peaks, making the response to mutation and selection highly non‑linear and creating opportunities for sudden, large‑scale phenotypic shifts.

The third major contribution is an application of percolation theory to multidimensional fitness landscapes. The authors model the fitness space as a high‑dimensional graph: each genotype is a node, and mutational or recombinational steps create edges with a certain probability. Evolution proceeds by traversing this graph. When the probability of forming edges exceeds a critical percolation threshold p_c, a giant connected component emerges, allowing the whole population to explore a vast “fitness sea.” Below p_c the graph fragments into isolated islands, limiting evolutionary exploration. The authors propose that the tree‑like phylogenies characteristic of complex multicellular organisms arise only when the evolutionary dynamics operate above this percolation threshold, ensuring a single, expansive lineage that can branch repeatedly. Below the threshold, lineages become disconnected, leading to either evolutionary dead‑ends or abrupt jumps when a new percolating path opens.

Finally, the paper emphasizes that these physical analogies are not merely metaphorical. The biological potential ϕ can be estimated from genomic data, frustration can be quantified by measuring the degree of conflict among selection pressures at different hierarchical levels, and percolation thresholds can be inferred from empirical mutation‑recombination networks. By integrating concepts from thermodynamics, glass physics, and percolation, the authors outline a coherent, quantitative framework that could complement classical evolutionary theory. This “physics of evolution” aims to explain how complexity emerges, how innovation is regulated, and why certain large‑scale evolutionary transitions display universal patterns, suggesting that a meaningful physical theory of biological evolution is indeed within reach.