Fisher's Geometric Model as a Tool to Study Speciation

Abstract

Interactions between alleles and across environments play an important role in the fitness of hybrids, and are at the heart of the speciation process. Fitness landscapes capture these interactions and can be used to model hybrid fitness, helping us to interpret empirical observations and clarify verbal models. Here, we review recent progress in understanding hybridization outcomes through Fisher's geometric model, an intuitive and analytically tractable fitness landscape that captures many fitness patterns observed across taxa. We use case studies to illustrate how the model parameters can be estimated from different types of data, and discuss how these estimates can be used to make inferences about the divergence history and genetic architecture. We also highlight some areas where the model's predictions differ from alternative incompatibility-based models, such as the snowball effect and outlier patterns in genome scans.Given eqs. 1 and 2, and the complete set of the a ij and d ij , we can assign a fitness value to all possible genotypes. Moreover, from knowledge of the distributions of the a ij and d ij , we can make predictions about the typical fitnesses of different classes of genotype (see §2.2 below). Note also that the description above encompasses important models of speciation, such as that of Mani and Clarke (1990), even though those authors did not use the term "Fisher's geometric model".A phenotypic model or a fitness landscape?The model described above is often treated primarily as a phenotypic model, and used to study the evolution of quantitative traits -i.e. the evolution of the z i (e.g.