THEORY

Introduction

The LAMARC programs estimate parameters such as effective population size, growth rate, migration rates, and recombination rate using molecular data from a random sample of individuals from one or several populations (Felsenstein et al., 1999). The relationship structure among sampled individuals, their genealogy, contains a great deal of information about the past history of the population from which those individuals were drawn. For example, in a population that has been large for a long time, most of the individuals in the sample will be distantly related; in a population that has been smaller, most of the individuals will be closely related.

The mathematical theory relating a genealogy to the structure of its underlying population, called coalescent theory, was first developed by Kingman (1982) and expanded by Hudson and Kaplan (1988) (see Chapter 17). However, use of coalescent theory to estimate parameters is hampered by the fact that the sample genealogy is almost never known with certainty and is difficult to infer accurately. Population samples are less likely to yield their correct genealogy than samples from multiple species since fewer informative mutations will be available. Additionally the possibility of recombination can make accurate genealogy reconstruction of a population almost impossibly daunting. Analysis of pairs of individuals can reveal some coalescent-based information – the genealogy connecting two individuals is relatively easy to infer.