Current Contents

19. Individual Fitness and the Measurement of Univariate Selection

• Episodes of selection
  • Fitness components
  • Assigning fitness components
• Variance in Individual Fitness
  • Partitioning I across episodes of selection
  • Some caveats in using opportunity of selection
• Descriptions of Phenotypic Selection: Introductory Remarks
  • Fitness surfaces
• Descriptions of Phenotypic Selection: Changes in Phenotypic Moments
  • Partitioning changes in means and variances into episodes of selection
  • Standard errors for estimates of differentials and gradients
• Descriptions of Phenotypic Selection: Individual Fitness Surfaces
  • Linear and quadratic approximations of W(z)
  • Hypothesis testing and approximate confidence intervals
  • Schluter's cublic-spline estimate
  • The importance of experimental manipulation

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.

• Chapter 19 PDF file ( v. 16 March 1998 ): (29 typeset pages, 646K)

Programs

• 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.
  • Web page

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Bruce Walsh. jbwalsh@u.arizona.edu . Comments welcome.