Biology Reference
In-Depth Information
two parts we wish to examine further and conducting a within-configuration PLS analysis.
Alternatively, or additionally, we could construct a model that allows spatially disjunct
regions to belong to the same module, and also allows for partial overlap between
modules.
The analysis of modularity does pose real challenges, but it is not because we lack
methods for analyzing modularity of shape data. Rather, it is because of the complexity of
patterns of covariance. As should be evident from this example, testing only one model is
not sufficient
had we tested only the Front/Back model, it would have been apparently
confirmed by all the methods. Each model yielded the lowest
RV
or
RV
M
of all the models
to which it was compared and each deviated less from the data than expected by chance.
With the sole exception of the
Satb2
model, which was rejected by one test statistic (the
correlation between the observed and expected correlation matrices), any of these models
would be confirmed by all three methods. Yet, the models do not fit equally well, and the
exploratory analysis raises the possibility that no modular structure fits the data as well as
a non-modular one. Thus, an important part of the hypothesis-testing strategy is to
consider multiple hypotheses, and to consider the possibility of
integration without
modularity.
References
Adams, D. C., & Collyer, M. L. (2009). A general framework for the analysis of phenotypic trajectories in evolu-
tionary studies.
Evolution
,
63
, 1143
1154.
Adams, D. C., Rohlf, F. J., & Slice, D. E. (2004). Geometric morphometrics: ten years of progress following the
'revolution'.
Italian Journal of Zoology
,
71
,5
16.
Akaike, H. (1974). A new look at the statistical model identification.
IEEE Transactions on Automatic Control
,
19
,
716
723.
Ancel, L. W., & Fontana, W. (2000). Plasticity, evolvability, and modularity in RNA.
Journal of Experimental
Zoology
,
288
, 242
283.
Atchley, W. R., & Hall, B. K. (1991). A model for development and evolution of complex morphological struc-
tures.
Biological Reviews of the Cambridge Philosophical Society
,
66
, 101
157.
Box, G. E. P. (1949). A general distribution theory for a class of likelihood criteria.
Biometrika
,
36
, 317
346.
Breno, M., Leirs, H., & Van Dongen, S. (2011). No relationship between canalization and developmental stability
of the skull in a natural population of
Mastomys natalensis
(Rodentia: Muridae).
Biological Journal of the Linnean
Society
,
104
, 207
216.
Breuker, C. J., Patterson, J. S, & Klingenberg, C. P. (2006). A single basis for developmental buffering of
Drosophila
wing shape.
Plos One
,
1
.
Cheverud, J. M. (1982). Phenotypic, genetic, and environmental morphological
integration in the cranium.
516.
Cheverud, J. M. (1995). Morphological
Evolution
,
36
, 499
integration in the saddle-back tamarin (
Saguinus fuscicollis
) cranium.
89.
Cheverud, J. M. (2004). Modular pleiotropic effects of quantitative trait loci on morphological traits.
Modularity in
Development and Evolution,
132
American Naturalist
,
145
,63
153.
Cheverud, J. M., Ehrich, T. H., Vaughn, T. T., Koreishi, S. F., Linsey, R. B., & Pletscher, L. S. (2004). Pleiotropic
effects on mandibular morphology II: Differential epistasis and genetic variation in morphological integration.
Journal of Experimental Zoology Part B-Molecular and Developmental Evolution
,
302B
, 424
435.
Cheverud, J. M., Routman, E. J., & Irschick, D. J. (1997). Pleiotropic effects of individual gene loci on mandibular
morphology.
Evolution
,
51
, 2006
2016.
Clarke, G. M. (1993). Fluctuating asymmetry of invertebrate populations as a biological indicator of environmental
quality.
Environmental Pollution
,
82
, 207
211.
