How to calculate phylogenetic signal for a varying slopes model?

Short summary of the problem
I would like to know how to calculate the phylogenetic signal for models with varying slopes and intercepts. Following from

If I have a Phylogenetic Model with repeated Measurements, but also with varying slopes (below), how does it affect the formula for hypothesis() given in the original example?

model_repeat1 <- brm(
  phen ~ cofactor1*cofactor2 + (1|gr(phylo, cov = A)) + (1+cofactor1+cofactor2|species),
  data = data_repeat,
  family = gaussian(),
  data2 = list(A = A),
  prior = c(
    prior(normal(0,10), "b"),
    prior(normal(0,50), "Intercept"),
    prior(student_t(3,0,20), "sd"),
    prior(student_t(3,0,20), "sigma")
  sample_prior = TRUE, chains = 2, cores = 2,
  iter = 4000, warmup = 1000


  • Operating System: Windows 11 (64-bit operating system)
  • brms Version: 2.20.1