The probability of improvement in Fisher's geometric model: a probabilistic approach

TL;DR

This paper introduces a probabilistic method to analyze Fisher's geometric model, offering new insights into the likelihood of beneficial mutations and their role in adaptive evolution.

Contribution

It presents an alternative probabilistic solution to Fisher's geometric model, enhancing understanding of mutation benefits in evolutionary processes.

Findings

Derived a probabilistic solution to Fisher's model

Provided new interpretation of mutation benefits

Enhanced understanding of adaptive evolution mechanisms

Abstract

Fisher developed his geometric model to support the micro-mutationalism hypothesis which claims that small mutations are more likely to be beneficial and therefore to contribute to evolution and adaptation. While others have provided a general solution to the model using geometric approaches, we derive an equivalent general solution using a probabilistic approach. Our approach to Fisher's geometric model provides alternative intuition and interpretation of the solution in terms of the model's parameters: for mutation to improve a phenotype, its relative beneficial effect must be larger than the ratio of its total effect and twice the difference between the current phenotype and the optimal one. Our approach provides new insight into this classical model of adaptive evolution.