Biology Reference
In-Depth Information
DEVELOPMENTAL STABILITY: QUANTIFYING
DEVELOPMENTAL NOISE
“Developmental stability” refers to the ability of a genotype to produce the same pheno-
type under the same environmental conditions by buffering developmental noise ( Reeve,
1960a; Zakharov, 1992; Clarke, 1998; Van Dongen and Lens, 2000 ). Developmental stability,
or rather its converse, developmental instability, is usually measured by fluctuating asym-
metry (FA), the random deviations from bilateral symmetry. An advantage of measuring
developmental stability by FA is that we actually know the expected value for the trait
barring developmental perturbation: both sides of a bilaterally symmetric individual have
the same genotype and develop within the same environment so they should be identical,
barring developmental perturbations ( Reeve, 1960b; Palmer and Strobeck, 1986 ).
Developmental stability has been intensively studied recently for at least three major rea-
sons. First, decreased developmental stability may provide a sensitive indicator of environ-
mentally or genetically stressed populations ( Clarke, 1993; Graham et al., 1993; Estes et al.,
2006 ). If that is generally the case, elevated FA could serve as a useful biomarker for
stressed populations and aid conservation efforts. However, the causal connection
between stress (environmental or genetic) and FA remains a contentious issue because
many studies fail to find elevated FA in stressed populations (see Hoffmann and Woods,
2001; Hoffmann et al., 2005; Leamy and Klingenberg, 2005 ).
A second stimulus for studies of FA comes from theoretical models for the evolution of
variability. One interesting hypothesis is that selection for one variational property indi-
rectly selects for others; for example, selection for environmental canalization might indi-
rectly select for genetic canalization (e.g. Wagner et al., 1997 ). This has been termed
“plastogenetic congruence” by Ancel and Fontana (2000) . Congruence between the classes
of canalization (genetic, and macro- and microenvironmental) and developmental stability
has thus become an important issue in evolutionary theory, stimulating several empirical
investigations of the correspondence between them (e.g. Debat et al., 2000; Hallgr ´ msson
et al., 2002; Dworkin, 2005b; Santos et al., 2005; Willmore et al., 2005; Breuker et al., 2006;
Breno et al., 2011; Klingenberg et al., 2012 ). This is likely to remain an area of active inves-
tigation given the disparity and complexity of the results.
The Statistical Analysis of FA
FA is now usually studied by a two-way mixed model Analysis of Variance (ANOVA),
whose two main factors are Individuals (a random factor) and Sides (a fixed factor); FA is
quantified by the interaction term Individuals
Sides ( Leamy, 1984; Palmer and Strobeck,
1986 ). This approach was extended to shape data by Klingenberg and colleagues
( Klingenberg and McIntyre, 1998; Klingenberg et al., 2002 ) and has now been extended to
symmetries more complex than bilateral ( Savriama and Klingenberg, 2011 ). Here we
restrict the discussion to bilateral symmetry and follow Klingenberg's exposition of the
method.
In the case of bilateral symmetry, two kinds of symmetry can be distinguished ( Mardia
et al., 2000 ). One is “matching symmetry”, which refers to the case in which there are two
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