20. Measuring Multivariate Selection
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Current Contents
20. Measuring Multivariate Selection
-
Selection on Multivariate Phenotypes: Differentials and Gradients
- Changes in the mean vector: the directional selection differential s
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The directional selection gradient boldbeta
- Directional gradients, fitness surface geometry and selection response
- Changes in the covariance matrix: the quadratic selection differential C
- The quadratic selection gradient boldgamma
- Quadratic gradients, fitness surface geometry and selection response
- Summary
- Multivariate Quadratic Fitness Regressions
- Estimation, hypothesis testing and confidence intervals
- Geometric aspects
- Unmeasured characters and other biological caveats
- The bias due to environmental correlations between fitness and characters
- Path Analysis and Fitness Estimation
PDF versions of a recent draft of this chapter are available. Feel free to use this for personal and/or class use until the book is available. Please note that these are copyrighted and that I would greatly appreciate feedback . Note that while the screen view can look funny in places, the printed output is fine.
Programs
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A Mathematica notebook that computes and plots the within- and between-generation changes in the phenotypic and genotypic values for a bivariate character under a Gaussian infinitesimal model.
Programs for estimating univariate fitness functions (GLMS)
and multivariate selection surfaces (PP) from data on survival,
reproductive success, or other fitness measurement have been developed
by Douglas Nychka (Department of
Statistics, North Carolina State University) and Dolph Schluter
(Zoology Department and Centre for Biodiversity Research, University of
British Columbia). Surfaces are estimated using the cubic spline, a flexible regression tool that makes no a priori assumptions about the shape of the surface. Full details can be found in Schluter (1988) Evolution 42: 849--861 and
and Schluter and Nychka (1994) Am. Nat. 143: 597--616.
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Created 13 December 2000, last updated 13 December 2000
Bruce Walsh. jbwalsh@u.arizona.edu .
Comments welcome.