Biology Reference
In-Depth Information
2001
). Most studies concentrate on a single developmental stage, but a few have examined
the ontogenetic dynamics of variance (e.g.
Foote, 1986; Zelditch, 1988; Zelditch and
Carmichael, 1989; Zelditch et al., 1993
).
The concept of variation is also central to systematic studies, both because systematists
study evolutionary processes and also because the systematic value of a character is partly
a function of its variability. In the systematics literature, the term “variation” is sometimes
used very broadly, such as when talking about “ontogenetic variation”. In that context, the
“variation” results from the mixture of ages in the sample; because individuals differ in
age, they differ in everything that changes with age. Ontogeny is thus the factor explaining
the variation within the sample, but that is not the variance on which selection acts (unless
we seriously entertain the idea that selection favors adults over juveniles, which is unlikely
in the first place and would not have any evolutionary consequences in the second).
To study the variance on which selection could act, we would first need to remove the
variation resulting from the heterogeneity of the sample. Should removing that variation
strike you as an improper manipulation of the data, ask yourself whether it is reasonable
to imagine that selection acts on it.
A classic hypothesis linking variance to disparity is often called the “Kluge
Kerfoot”
phenomenon: traits that vary the most (within populations) are also the ones that most
differentiate populations (
Kluge and Kerfoot, 1973
). The original empirical support for the
hypothesis was harshly criticized on methodological grounds (e.g.
Sokal, 1976; Rohlf et al.,
1983
), but the hypothesis has re-emerged in the recent literature with more impressive
empirical support; the dimension of greatest (genetic) variance is sometimes regarded as
the evolutionary line of least resistance (e.g.
Schluter, 1996
).
Metrics for Disparity and Variance
As mentioned above, there is no universally accepted metric for disparity (there is for
variation, so we will focus on disparity throughout this section). One major distinction
among the available metrics is whether they measure the variety of forms in a sample or
the diversification along branches of a cladogram. The first could be viewed as a static
measure of disparity, the second as a dynamic measure of diversification. We will
focus on the first approach for two reasons: the first is that we define disparity in terms of
variety rather than in terms of magnitudes or rates of diversification; the second is that
ancestral morphologies are rarely observed and known to be ancestral. Without direct
observations of known ancestors, ancestral morphologies must be inferred, and the meth-
ods for inferring ancestral morphologies are still a matter of dispute.
Metrics for the variety of observed forms can be subdivided into two broad classes: (1)
those applied to continuously valued variables (such as size and shape) and (2) those
applied to ordinal or categorical data. The distinction (which is based on the type of data)
is important, because continuously valued variables are measured on an unambiguous
scale, which is not the case for ordinal or categorical data. For example, if we want to
know how different two organisms are, and one is 10 mm while the other is 12 mm, we
can say that their difference is 2 mm. Given a third, which is 14 mm, we would say that
the difference between the first and third is 4 mm, and the difference between the second
