dCov: Estimating linear and nonlinear selection differentials

In MorphoFun/psa: Phenotypic Selection Analysis tools

Description

dCov estimates the linear and nonlinear selection differentials for one or more phenotypic traits, based on descriptions in Phillips and Arnold (1989). Estimations are based on phenotypic traits that have been standardized to a mean of zero and unit variance. If one phenotypic trait is input, linear and quadratic selection differentials will be output. If more than one phenotypic trait is input, correlational selection differentials will also be output.

Usage

dCov(w, z)

Arguments

w	Relative fitness.
z	Phenotypic trait(s). Character values are not accepted.

Value

dCov returns a vector of numeric values.

Output

dCov is the selection differential calculated from the covariance between the relative fitness, w, and each phenotypic trait z, using the approach described in Table 1 of Phillips and Arnold (1989).

References

Phillips PC, Arnold SJ. 1989. Visualizing multivariate selection. Evolution 43(6): 1209-1222. http://www.jstor.org/stable/2409357

Lande R, Arnold SJ. 1983. The measurement of selection on correlated characters. Evolution 37(6): 1210-1226. http://www.jstor.org/stable/2408842

Examples

data(BumpusMales)

dCov(BumpusMales$w, BumpusMales[,3:11])

MorphoFun/psa documentation built on Nov. 10, 2021, 7:01 a.m.