# The History of the Panmictic Population Concept and Its Legacy in Contemporary Population Genetics

## TL;DR

This paper explores the history and ongoing influence of the panmictic population concept in genetics, showing how it shaped early evolutionary theories and still affects modern research.

## Contribution

The paper reveals the early embedding of panmixia in evolutionary thought and its lingering impact on contemporary genetic assumptions.

## Key findings

- The panmictic concept became influential early on to reconcile essentialism with Darwinian evolution.
- Modern genomic data may reduce the usefulness of panmixia assumptions in favor of continuous space models.
- Legacy assumptions from panmixia affect how populations are studied in human evolution, conservation, and medicine.

## Abstract

The panmictic population concept is at the heart of population, evolutionary and conservation genetics. However, in nature, true panmictic populations are vanishingly rare. As an idea conceived for modelling evolutionary dynamics, it has been thought that the assumption of panmixia was formalised during the development of the Modern Synthesis. Here, we show that while the idea's longevity is almost certainly due to its mathematical convenience, it became embedded in evolutionary thought much earlier, initially as a way to reconcile long‐standing essentialist ideas with the advent of Darwin's theories. Though the principles of essentialism and reversion have been largely rejected, these ideas persist in shaping assumptions made about populations in contemporary genetics research, including how they are conceptualised and sampled. This legacy has important implications for the interpretation of genomic findings in human evolution, conservation and medicine. From an evaluation of this history and its legacy, we contend that while the panmictic population concept has been, and continues to be useful, with the generation of terabytes of genomic data in the 21st century, its utility is likely to diminish as the need for continuous space models grows.