Better living through physics

Journal name:
Date published:
Published online

Nowak and colleagues' explanation of the evolution of altruism (Nature 466, 10571062; 2010) in terms of individual-level selection might be reconciled with the views of their kin-selection opponents by striking an analogy with statistical mechanical and thermodynamic treatments in physics.

Statistical mechanics provides the microscopic basis for the macroscopic variables in thermodynamics, which is an equilibrium theory treating aggregate variables. As with thermodynamics, traditional multilevel selection theory is based on equilibrium solutions operating on nominal, aggregate variables. In the Hamilton kin-selection framework, variables correspond to the terms benefit, cost and relatedness. But because that treatment is not fundamentally mechanistic, it is often unclear what the units of these variables are, and how best to measure them.

Population genetics presents an evolutionary analogue of statistical mechanics that complements Hamilton's evolutionary thermodynamics. Hamilton's rule — which expresses relatedness between the helped and the helper in terms of cost and benefit to the fitness of both — and its related inequalities all express dependencies among macroscopic variables of state in structured populations.

The greater complexity of biological systems over physical ones, and their strong interdependency, make for a zoo of biological macroscopic laws with many multilevel selection principles, each with its adherents and disciples.

The great promise of evolutionary statistical mechanics is that it should allow us to enumerate the full space of possible fundamental evolutionary inequalities and the mechanistic conditions under which they apply, thence identifying those with the greatest empirical generality.

See also: Inclusive fitness is just bookkeeping, Ground truth is the test that counts, Call for a return to rigour in models

Author information


  1. Santa Fe Institute, USA

    • David C. Krakauer &
    • Jessica C. Flack

Author details

Additional data