Species with incomplete factorial design

Models were fitted in Storyline E.

For species that did not receive both rainfall treatments and both canopy conditions, we change the covariates in the shoot growth model.

For three species with both rainfall treatments, but only in open canopy, we consider the covariates of warming, drying, and warming x drying.

df_bayes_all <- read_bayes_all(path = "alldata/intermediate/shootmodeling/uni/", design = "1c2w", derived = T, tidy_mcmc = T) %>%
  tidy_species_name()

p_bayes_summ <- plot_bayes_summary(df_bayes_all, option = "mu", derived_metric = "no")
p1 <- p_bayes_summ$p_coef_line

p_bayes_summ <- plot_bayes_summary(df_bayes_all, option = "mu", derived_metric = "only")
p2 <- p_bayes_summ$p_coef_line

p1 / (p2 + tagger::tag_facets(
  tag_suffix = "",
  tag_pool = c("D", "E", "F", "G")
))

p_bayes_summ <- plot_bayes_summary(df_bayes_all, option = "coef", derived_metric = "no")
p_bayes_summ$p_coef_line

p_bayes_summ <- plot_bayes_summary(df_bayes_all, option = "coef", derived_metric = "only")
p_bayes_summ$p_coef_line

For six species with no rainfall manipulation and only in closed canopy, we consider the covariate of warming only.

df_bayes_all <- read_bayes_all(path = "alldata/intermediate/shootmodeling/uni/", design = "1c1w", derived = T, tidy_mcmc = T) %>%
  tidy_species_name()

p_bayes_summ <- plot_bayes_summary(df_bayes_all, option = "mu", derived_metric = "no")
p1 <- p_bayes_summ$p_coef_line

p_bayes_summ <- plot_bayes_summary(df_bayes_all, option = "mu", derived_metric = "only")
p2 <- p_bayes_summ$p_coef_line

p1 / (p2 + tagger::tag_facets(
  tag_suffix = "",
  tag_pool = c("D", "E", "F", "G")
))

p_bayes_summ <- plot_bayes_summary(df_bayes_all, option = "coef", derived_metric = "no")
p_bayes_summ$p_coef_line

p_bayes_summ <- plot_bayes_summary(df_bayes_all, option = "coef", derived_metric = "only")
p_bayes_summ$p_coef_line