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Equilibrium in plants is for the most part a theoretical construct with little relation to reality.

We would argue that the second major development since the publication of Stebbins' work has been the application of ordered, genealogical data to the study of population-level processes. This development, which has begun to reach its potential only in the last decade, was predicated on two major advances, one technical and the other conceptual. The technical advance has been the widespread availability of ordered genetic variation at the intraspecific level, typically in the form of DNA sequence variation or mapped restriction-site data. For such data, mutational differences among genetic variants indicate the patterns of relationship among variants. These data therefore provide the raw information needed to reconstruct genealogical relationships among alleles (i.e., gene trees).

The conceptual advance has been the application of coalescent theory to the study of microevolutionary processes (for a recent review, see Fu and Li, 1999). For a population of constant size, new alleles are continually arising through mutation, and others are going extinct over successive generations (assuming neutrality). Therefore, the extant alleles of a gene in a population are all derived from (i.e., coalesce to) a single common ancestral allele that existed at some point in the past (Fig. 1). Coalescent theory provides a framework for studying the effects of population-level processes (e.g., population size fluctuations, selection, and gene flow) on the expected time to common ancestry of alleles within a gene tree. The application of gene genealogies to population genetics has allowed the study of population-level processes within a temporal, nonequilibrium framework. Thus, microevolution can be studied as a dynamic, historical process, changing over time within a species.

At the foundation of all genealogical analyses is the gene tree, which represents the inferred genealogical relationships among alleles observed in a species. Most intraspecific gene trees are unrooted, because one often cannot determine the temporal polarity of mutations, even with an outgroup (Castelloe and Templeton, 1994). A common means of representing the inferred genealogy is with a “minimum spanning tree” (e.g., Smouse, 1998), for which the number of mutational changes among alleles is minimized (Fig. 1). If homoplasy (mutational convergence or reversal) is infrequent, then a single most parsimonious minimum spanning tree often can be inferred by using maximum parsimony search algorithms (Swofford, 1993). For data showing high levels of homoplasy, more complicated tree estimation algorithms may be required (e.g., Templeton et al., 1992). Extant alleles on a gene tree are often separated by more than one mutational step, and thus, the gene tree typically contains a number of inferred intermediate alleles; these unobserved alleles may be extinct, may have been missed during population sampling, or may never have existed at all (if mutations did not accumulate in single steps).



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