mutate(trait = "Stretch height") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(N_LM_SSD_SA)$coefficients) %>%
mutate(trait = "Specific Stem Density") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(N_LM_LMF_SA)$coefficients) %>%
mutate(trait = "Leaf Mass Fraction") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(N_LM_RMF_SA)$coefficients) %>%
mutate(trait = "Root Mass Fraction") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(N_LM_Total_Biomass_SA)$coefficients) %>%
mutate(trait = "Total Biomass") %>%
slice(-c(1))
) %>%
transmute(B_SA_pooled = abs(Estimate),
SE_SA_pooled  = `Std. Error`,
Trait = trait)
)
) %>%
## calculate the difference in placticity (Pdiff) and Variance
mutate(Var_AU_pooled = SE_AU_pooled^2,
Var_SA_pooled = SE_SA_pooled^2) %>%
mutate(Pdiff_pooled = B_AU_pooled - B_SA_pooled,
Var_Pdiff_pooled = Var_SA_pooled + Var_AU_pooled)
#######################################################################
### Water
Water_meta_table <- as_tibble(summary(W_LME_Shape_AU)$coefficients) %>%
mutate(trait = "Leaf Shape") %>%
slice(-c(1)) %>%
bind_rows(.,
as_tibble(summary(W_LME_Area_AU)$coefficients) %>%
mutate(trait = "Leaf Area") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(W_LME_SLA_AU)$coefficients) %>%
mutate(trait = "Specific Leaf Area") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(W_LME_LW_AU)$coefficients) %>%
mutate(trait = "Leaf Nitrogen (%)") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(W_LME_D13c_AU)$coefficients) %>%
mutate(trait = "d13C") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(W_LME_Fv_Fm_AU)$coefficients) %>%
mutate(trait = "Fv / Fm") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(W_LME_percent_dead_leaves_AU)$coefficients) %>%
mutate(trait = "Senesced leaves (%)") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(W_LME_Internode_length_AU)$coefficients) %>%
mutate(trait = "Internode length") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(W_LME_stretch_height_AU)$coefficients) %>%
mutate(trait = "Stretch height") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(W_LME_SSD_AU)$coefficients) %>%
mutate(trait = "Specific Stem Density") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(W_LME_LMF_AU)$coefficients) %>%
mutate(trait = "Leaf Mass Fraction") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(W_LME_RMF_AU)$coefficients) %>%
mutate(trait = "Root Mass Fraction") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(W_LME_Total_Biomass_AU)$coefficients) %>%
mutate(trait = "Total Biomass") %>%
slice(-c(1))
) %>%
transmute(Trait = trait,
B_AU_pooled = abs(Estimate),
SE_AU_pooled  = `Std. Error`) %>%
left_join(.,
(
as_tibble(summary(W_LM_Shape_SA)$coefficients) %>%
mutate(trait = "Leaf Shape") %>%
slice(-c(1)) %>%
bind_rows(.,
as_tibble(summary(W_LM_Area_SA)$coefficients) %>%
mutate(trait = "Leaf Area") %>%
slice(-c(1))
) %>%
bind_rows(.,
#  as_tibble(summary(W_LM_SLA_SA)$coefficients) %>%
as_tibble(W_SLA_boot_results_table_SA) %>%
rename(Estimate = boot_B,
`Std. Error` = boot_SE) %>%
mutate(trait = "Specific Leaf Area") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(W_LM_LW_SA)$coefficients) %>%
mutate(trait = "Leaf Nitrogen (%)") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(W_LM_D13c_SA)$coefficients) %>%
mutate(trait = "d13C") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(W_LM_Fv_Fm_SA)$coefficients) %>%
mutate(trait = "Fv / Fm") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(W_LM_percent_dead_leaves_SA)$coefficients) %>%
mutate(trait = "Senesced leaves (%)") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(W_LM_Internode_length_SA)$coefficients) %>%
mutate(trait = "Internode length") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(W_LM_stretch_height_SA)$coefficients) %>%
mutate(trait = "Stretch height") %>%
slice(-c(1))
) %>%
bind_rows(.,
#    as_tibble(summary(W_LM_SSD_SA)$coefficients) %>%
as_tibble(W_SSD_boot_results_table_SA) %>%
rename(Estimate = boot_B,
`Std. Error` = boot_SE) %>%
mutate(trait = "Specific Stem Density") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(W_LM_LMF_SA)$coefficients) %>%
mutate(trait = "Leaf Mass Fraction") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(W_LM_RMF_SA)$coefficients) %>%
mutate(trait = "Root Mass Fraction") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(W_LM_Total_Biomass_SA)$coefficients) %>%
mutate(trait = "Total Biomass") %>%
slice(-c(1))
) %>%
transmute(B_SA_pooled = abs(Estimate),
SE_SA_pooled  = `Std. Error`,
Trait = trait)
)
) %>%
## calculate the difference in placticity (Pdiff) and Variance
mutate(Var_AU_pooled = SE_AU_pooled^2,
Var_SA_pooled = SE_SA_pooled^2) %>%
mutate(Pdiff_pooled = B_AU_pooled - B_SA_pooled,
Var_Pdiff_pooled = Var_SA_pooled + Var_AU_pooled)
Water_meta_table
?write_xlsx
?write_xl
??write_xlsx
library(writexl)
## write meta analysis tables to excel
write_xlsx(list(Water_meta_table = Water_meta_table),
path = 'meta_analysis_tables.xlsx')
### 5.3  write meta analysis tables to excel
write_xlsx(list(Nutrient_meta_table = Nutrient_meta_table,
Water_meta_table = Water_meta_table),
path = 'meta_analysis_tables.xlsx')
write_xlsx(list(Nutrient_meta_table = Nutrient_meta_table,
Water_meta_table = Water_meta_table),
path = 'Datasets/meta_analysis_tables.xlsx')
# 5. Create table for input into meta analysis
###  table of beta coefficients, standard error and variance
###  for the effect of treatment in each raange
source('4_1_Calculate_reaction_norms_Nutrients.R')
source('4_2_Calculate_reaction_norms_Water.R')
### 5.1  nutrient treatment
Nutrient_meta_table <- as_tibble(summary(N_LME_Shape_AU)$coefficients) %>%
mutate(trait = "Leaf Shape") %>%
slice(-c(1)) %>%
bind_rows(.,
as_tibble(summary(N_LME_Area_AU)$coefficients) %>%
mutate(trait = "Leaf Area") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(N_LME_SLA_AU)$coefficients) %>%
mutate(trait = "Specific Leaf Area") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(N_LME_LN_AU)$coefficients) %>%
mutate(trait = "Leaf Nitrogen (%)") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(N_LME_D13c_AU)$coefficients) %>%
mutate(trait = "d13C") %>%
slice(-c(1))
) %>%
bind_rows(.,
# as_tibble(summary(N_LME_Fv_Fm_AU)$coefficients) %>%
# use bootstrap results
as_tibble(N_FV_FM_boot_results_table_AU) %>%
rename(Estimate = boot_B,
`Std. Error` = boot_SE) %>%
mutate(trait = "Fv / Fm") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(N_LME_percent_dead_leaves_AU)$coefficients) %>%
mutate(trait = "Senesced leaves (%)") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(N_LME_Internode_length_AU)$coefficients) %>%
mutate(trait = "Internode length") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(N_LME_stretch_height_AU)$coefficients) %>%
mutate(trait = "Stretch height") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(N_LME_SSD_AU)$coefficients) %>%
mutate(trait = "Specific Stem Density") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(N_LME_LMF_AU)$coefficients) %>%
mutate(trait = "Leaf Mass Fraction") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(N_LME_RMF_AU)$coefficients) %>%
mutate(trait = "Root Mass Fraction") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(N_LME_Total_Biomass_AU)$coefficients) %>%
mutate(trait = "Total Biomass") %>%
slice(-c(1))
) %>%
transmute(Trait = trait,
B_AU_pooled = abs(Estimate),
SE_AU_pooled  = `Std. Error`) %>%
left_join(.,
(
as_tibble(summary(N_LM_Shape_SA)$coefficients) %>%
mutate(trait = "Leaf Shape") %>%
slice(-c(1)) %>%
bind_rows(.,
as_tibble(summary(N_LM_Area_SA)$coefficients) %>%
mutate(trait = "Leaf Area") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(N_LM_SLA_SA)$coefficients) %>%
mutate(trait = "Specific Leaf Area") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(N_LM_LN_SA)$coefficients) %>%
mutate(trait = "Leaf Nitrogen (%)") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(N_LM_D13c_SA)$coefficients) %>%
mutate(trait = "d13C") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(N_LM_Fv_Fm_SA)$coefficients) %>%
mutate(trait = "Fv / Fm") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(N_LM_percent_dead_leaves_SA)$coefficients) %>%
mutate(trait = "Senesced leaves (%)") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(N_LM_Internode_length_SA)$coefficients) %>%
mutate(trait = "Internode length") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(N_LM_stretch_height_SA)$coefficients) %>%
mutate(trait = "Stretch height") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(N_LM_SSD_SA)$coefficients) %>%
mutate(trait = "Specific Stem Density") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(N_LM_LMF_SA)$coefficients) %>%
mutate(trait = "Leaf Mass Fraction") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(N_LM_RMF_SA)$coefficients) %>%
mutate(trait = "Root Mass Fraction") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(N_LM_Total_Biomass_SA)$coefficients) %>%
mutate(trait = "Total Biomass") %>%
slice(-c(1))
) %>%
transmute(B_SA_pooled = abs(Estimate),
SE_SA_pooled  = `Std. Error`,
Trait = trait)
)
) %>%
## calculate the difference in placticity (Pdiff) and Variance
mutate(Var_AU_pooled = SE_AU_pooled^2,
Var_SA_pooled = SE_SA_pooled^2) %>%
mutate(Pdiff_pooled = B_AU_pooled - B_SA_pooled,
Var_Pdiff_pooled = Var_SA_pooled + Var_AU_pooled)
#######################################################################
### 5.2 Water
Water_meta_table <- as_tibble(summary(W_LME_Shape_AU)$coefficients) %>%
mutate(trait = "Leaf Shape") %>%
slice(-c(1)) %>%
bind_rows(.,
as_tibble(summary(W_LME_Area_AU)$coefficients) %>%
mutate(trait = "Leaf Area") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(W_LME_SLA_AU)$coefficients) %>%
mutate(trait = "Specific Leaf Area") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(W_LME_LW_AU)$coefficients) %>%
mutate(trait = "Leaf Nitrogen (%)") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(W_LME_D13c_AU)$coefficients) %>%
mutate(trait = "d13C") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(W_LME_Fv_Fm_AU)$coefficients) %>%
mutate(trait = "Fv / Fm") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(W_LME_percent_dead_leaves_AU)$coefficients) %>%
mutate(trait = "Senesced leaves (%)") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(W_LME_Internode_length_AU)$coefficients) %>%
mutate(trait = "Internode length") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(W_LME_stretch_height_AU)$coefficients) %>%
mutate(trait = "Stretch height") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(W_LME_SSD_AU)$coefficients) %>%
mutate(trait = "Specific Stem Density") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(W_LME_LMF_AU)$coefficients) %>%
mutate(trait = "Leaf Mass Fraction") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(W_LME_RMF_AU)$coefficients) %>%
mutate(trait = "Root Mass Fraction") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(W_LME_Total_Biomass_AU)$coefficients) %>%
mutate(trait = "Total Biomass") %>%
slice(-c(1))
) %>%
transmute(Trait = trait,
B_AU_pooled = abs(Estimate),
SE_AU_pooled  = `Std. Error`) %>%
left_join(.,
(
as_tibble(summary(W_LM_Shape_SA)$coefficients) %>%
mutate(trait = "Leaf Shape") %>%
slice(-c(1)) %>%
bind_rows(.,
as_tibble(summary(W_LM_Area_SA)$coefficients) %>%
mutate(trait = "Leaf Area") %>%
slice(-c(1))
) %>%
bind_rows(.,
#  as_tibble(summary(W_LM_SLA_SA)$coefficients) %>%
as_tibble(W_SLA_boot_results_table_SA) %>%
rename(Estimate = boot_B,
`Std. Error` = boot_SE) %>%
mutate(trait = "Specific Leaf Area") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(W_LM_LW_SA)$coefficients) %>%
mutate(trait = "Leaf Nitrogen (%)") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(W_LM_D13c_SA)$coefficients) %>%
mutate(trait = "d13C") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(W_LM_Fv_Fm_SA)$coefficients) %>%
mutate(trait = "Fv / Fm") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(W_LM_percent_dead_leaves_SA)$coefficients) %>%
mutate(trait = "Senesced leaves (%)") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(W_LM_Internode_length_SA)$coefficients) %>%
mutate(trait = "Internode length") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(W_LM_stretch_height_SA)$coefficients) %>%
mutate(trait = "Stretch height") %>%
slice(-c(1))
) %>%
bind_rows(.,
#    as_tibble(summary(W_LM_SSD_SA)$coefficients) %>%
as_tibble(W_SSD_boot_results_table_SA) %>%
rename(Estimate = boot_B,
`Std. Error` = boot_SE) %>%
mutate(trait = "Specific Stem Density") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(W_LM_LMF_SA)$coefficients) %>%
mutate(trait = "Leaf Mass Fraction") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(W_LM_RMF_SA)$coefficients) %>%
mutate(trait = "Root Mass Fraction") %>%
slice(-c(1))
) %>%
bind_rows(.,
as_tibble(summary(W_LM_Total_Biomass_SA)$coefficients) %>%
mutate(trait = "Total Biomass") %>%
slice(-c(1))
) %>%
transmute(B_SA_pooled = abs(Estimate),
SE_SA_pooled  = `Std. Error`,
Trait = trait)
)
) %>%
## calculate the difference in placticity (Pdiff) and Variance
mutate(Var_AU_pooled = SE_AU_pooled^2,
Var_SA_pooled = SE_SA_pooled^2) %>%
mutate(Pdiff_pooled = B_AU_pooled - B_SA_pooled,
Var_Pdiff_pooled = Var_SA_pooled + Var_AU_pooled)
### 5.3  write meta analysis tables to excel
write_xlsx(list(Nutrient_meta_table = Nutrient_meta_table,
Water_meta_table = Water_meta_table),
path = 'Datasets/meta_analysis_tables.xlsx')
Water_meta_table
Nutrient_meta_table
source('5_Create_meta_analysis_table.R')
metafor_N_pooled<- rma(yi= Pdiff_pooled, vi= Var_Pdiff_pooled,
data=Nutrient_meta_table, slab=Trait, method="REML", measure="GEN")
forest_plot_nutrient <- forest(metafor_N_pooled, xlim=c(-13.5,11.5), alim=c(-4,4), mlab="Random Effects Model", xlab="Plasticity Difference")
forest_plot_nutrient
### Final forest plot for water
metafor_W_pooled<- rma(yi= Pdiff_pooled, vi= Var_Pdiff_pooled, data=Water_meta_table, slab=Trait, method="REML", measure="GEN")
forest_plot_water <- forest(metafor_W_pooled, xlim=c(-13.5,11.5), alim=c(-4,4), mlab="Random Effects Model", xlab="Plasticity Difference")
forest_plot_water
