### Figure4.R
### Visualizing root dry mass over time for cuttings grown in different soils and environments.

### Script for:
# "Restoring South African subtropical succulent thicket using 
# Portulacaria afra: rooting variation across three soil types"
# Authors: AJ Potts, D Liddell, C Clarke, N Galuszynski

# --- Setup Libraries and Environment ---
library(groundhog) # Ensures reproducible package versions
set.groundhog.folder("C:\\Groundhog_R\\R4.4.1_2024-05-14") # Sets folder for storing library versions
GroundhogDay <- '2024-05-14' # Snapshot date for reproducibility
groundhog.library("tidyverse", GroundhogDay) # Load Tidyverse for data handling

# --- Define Working Directory ---
# Replace this path with the location of your data
setwd("D:\\Google Drive\\0_SpekboomResearchGroup2.0\\3_Experiments\\NMU22(07)SoilRootingExperiment\\DataForSubmission/") 

# --- Load and Prepare Data ---
# Load the experimental data
dat <- read_csv("NMU22(07)SoilRootingExperiment_data.csv") 

# Modify the Harvest column and create labels for plotting
dat <- dat %>%
  mutate(
    Harvest = Harvest * 7 + 7, # Convert weeks to days after planting
    HarvestLabel = factor(Harvest, 
                          levels = 1:7 * 7 + 7, 
                          labels = paste0(1:7 * 7 + 7, " days after planting"))
  )

# --- Calculate Summary Statistics ---
# Filter, group, and calculate mean, SE, and error bars for Root Dry Mass
summary_data <- dat %>%
  filter(RootDryMass_g < 0.5) %>% # Exclude outliers above 0.5g
  group_by(SiteCode, Harvest, Environment) %>%
  summarise(
    uRootDryMass = mean(RootDryMass_g), # Mean root dry mass
    n = n(), # Sample size
    se = sd(RootDryMass_g) / sqrt(n - 1), # Standard error
    ymin = uRootDryMass - se, # Lower error bar
    ymax = uRootDryMass + se  # Upper error bar
  ) %>%
  ungroup() %>%
  mutate(
    Harvest = ifelse(Environment == "Glasshouse", Harvest - 0.1, Harvest + 0.1) # Adjust Harvest for clarity
  )

# --- Generate Plot ---
plot <- ggplot(summary_data, aes(Harvest, uRootDryMass, colour = Environment, linetype = Environment)) +
  geom_line(size = 1.5) + # Add lines
  geom_errorbar(aes(ymin = ymin, ymax = ymax), size = 0.8, width = 2) + # Add error bars
  geom_point(size = 2) + # Add points
  scale_colour_manual(values = c("darkgrey", "black"), name = "Experiment") +
  scale_linetype_manual(values = c(1, 2), name = "Experiment") +
  facet_wrap(~SiteCode) + # Separate plots by SiteCode
  scale_x_continuous(breaks = seq(14, 14 * 7, by = 7)) + # Custom x-axis ticks
  ylab("Root Dry Mass (g)") +
  xlab("Days after planting") +
  theme_bw() + # Set theme
  theme(
    legend.position = c(0.9, 0.99),
    legend.justification = c("right", "top"),
    legend.box.just = "right",
    legend.margin = margin(6, 6, 6, 6),
    legend.box.background = element_rect(colour = "black")
  )
plot
# Save the plot as a high-quality image
ggsave("Figure4.jpg", plot = plot, units = "cm", width = 18, height = 11)