The phylogenetic heritability, \(H^2\), is defined as the ratio of the genetic variance over the total phenotypic variance expected at a given evolutionary time t (measured from the root of the tree). Thus, the phylogenetic heritability connects the parameters alpha, sigma and sigmae of the POUMM model through a set of equations. The functions described here provide an R-implementation of these equations.

alpha(H2, sigma, sigmae, t = Inf) sigmaOU(H2, alpha, sigmae, t = Inf) sigmae(H2, alpha, sigma, t = Inf) H2e(z, sigmae, tree = NULL, tFrom = 0, tTo = Inf)

H2 | Phylogenetic heritability at time t. |
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sigmae | Numeric, environmental phenotypic deviation at the tips. |

t | Numeric value denoting evolutionary time (i.e. distance from the root of a phylogenetic tree). |

alpha, sigma | Numeric values or n-vectors, parameters of the OU process; alpha and sigma must be non-negative. A zero alpha is interpreted as the Brownian motion process in the limit alpha -> 0. |

z | Numerical vector of observed phenotypes. |

tree | A phylo object. |

tFrom, tTo | Numerical minimal and maximal root-tip distance to limit the calculation. |

All functions return numerical values or NA, in case of invalid parameters

The function sigmae uses the formula H2 = varOU(t, alpha, sigma) / (varOU(t, alpha, sigma) + sigmae^2)

`alpha`

: Calculate alpha given time t, H2, sigma and sigmae`sigmaOU`

: Calculate sigma given time t, H2 at time t, alpha and sigmae`sigmae`

: Calculate sigmae given alpha, sigma, and H2 at time t`H2e`

: "Empirical" phylogenetic heritability estimated from the empirical variance of the observed phenotypes and sigmae

This function is called sigmaOU and not simply sigma to avoid a conflict with a function sigma in the base R-package.

OU

# At POUMM stationary state (equilibrium, t=Inf) H2 <- H2(alpha = 0.75, sigma = 1, sigmae = 1, t = Inf) # 0.4 alpha <- alpha(H2 = H2, sigma = 1, sigmae = 1, t = Inf) # 0.75 sigma <- sigmaOU(H2 = H2, alpha = 0.75, sigmae = 1, t = Inf) # 1 sigmae <- sigmae(H2 = H2, alpha = 0.75, sigma = 1, t = Inf) # 1 # At finite time t = 0.2 H2 <- H2(alpha = 0.75, sigma = 1, sigmae = 1, t = 0.2) # 0.1473309 alpha <- alpha(H2 = H2, sigma = 1, sigmae = 1, t = 0.2) # 0.75 sigma <- sigmaOU(H2 = H2, alpha = 0.75, sigmae = 1, t = 0.2) # 1 sigmae <- sigmae(H2 = H2, alpha = 0.75, sigma = 1, t = 0.2) # 1