Soil features of the sampling sites

• This figure corresponds to figure S8 in the manuscript.
• An high-resolution version of this figure is available here.

library(tidyverse)
library(ggtern)
library(patchwork)
library(gridExtra)
library(lemon)
source("../scripts/aux.R")


### Physico-Chemical features  
#### Texture 
soil_fq <- read_csv("../data/soil_data.csv") |> 
  mutate(species = paste0("P. ", sp_code)) |>
  mutate(elev_code = case_when(
    elev_code == "low2" ~ "low-Dec", 
    TRUE ~ elev_code
  )) |> 
  mutate(elev_code = fct_relevel(elev_code, "low-Dec", "low", "medium", "high")) |> 
  mutate(sp_code = fct_relevel(sp_code, "halepensis","pinaster", "nigra", "sylvestris")) 

# Plots parameters 
custom_theme <- list(
  labs(yarrow = "Clay (%)",
       zarrow = "Silt (%)", 
       xarrow = "Sand (%)"),
  theme_bw(),
  ggplot2::xlab(""),
  ggplot2::ylab(""), 
  ggtern::zlab(""),
  theme_showarrows(),
  theme_showgrid(),
  scale_shape_manual(values = shape_elev, name = "Elevation"),
  scale_colour_manual(values = colours_Specie, labels = expression(italic("P. halepensis"), italic("P. pinaster"), italic("P. nigra"), italic("P. sylvestris")), name = "Species"),
  scale_fill_manual(values = colours_Specie, labels = expression(italic("P. halepensis"), italic("P. pinaster"), italic("P. nigra"), italic("P. sylvestris")),
                    name = "Species"),
  # tern_limits(T=0.4, L = 0.8, R=0.5) 
  tern_limits(T=1, L = 1, R=1),
  theme(
    tern.axis.arrow.text = element_text(size = 14, face = "bold"), 
    tern.axis.arrow.text.T = element_text(vjust = -1), # clay
    tern.axis.arrow.text.L = element_text(vjust = -1), # sand
    tern.axis.arrow.text.R = element_text(vjust = 1), # silt
    tern.axis.text = element_text(size = 14),
    plot.title = element_text(face = "bold")
  )
)


gsup <- soil_fq |> 
  filter(type == "Textura Superficial") |> 
  dplyr::select(-res, -layer, -type) |> 
  pivot_wider(values_from = value, 
              names_from = soil_var)

plot_sup <- ggtern(data = gsup, 
                   aes(x = arena_sup, y = arcilla_sup, z = limo_sup, 
                       color = species, fill = species)) +
  geom_point(size = 5, aes(shape = elev_code), alpha = 0.8) +
  ggtitle("A", subtitle = "Soil texture surface (25-30 cm)") +
  custom_theme 


gsub <- soil_fq |> 
  filter(type == "Textura Subsuperficial") |> 
  dplyr::select(-res, -layer, -type) |> 
  pivot_wider(values_from = value, 
              names_from = soil_var)

plot_sub <- ggtern(data = gsub, 
                   aes(x = arena_sub, y = arcilla_sub, z = limo_sub, 
                       color = species, fill = species)) +
  geom_point(size = 5, aes(shape = elev_code), alpha = 0.8) +
  ggtitle("B", subtitle = "Soil texture subsurface (>30 cm)") +
  custom_theme




common_legend <- lemon::g_legend(plot_sub + theme(legend.position = "bottom",
                                                  legend.background = element_blank()))

combined_ggtern <- ggtern::grid.arrange(plot_sup + 
                                          theme(legend.position = "hidden",
                                                plot.margin = unit(c(t=0.4, r=-5, b=-.6, l=0), "cm")),
                                        plot_sub + 
                                          theme(legend.position = "hidden",
                                                plot.margin = unit(c(t=0.4, r=0, b=-.6, l=-5), "cm")),
                                        common_legend,
                                        # nrow = 1, 
                                        # widths = c(2,2,0.5),
                                        layout_matrix = matrix(c(1, 3, 2, 3), nrow = 2), 
                                        heights = c(5,1))

Ternary soil maps showing percent composition of sand, clay and silt of the studied sites, for surface (up to 25-30 cm depth) (a) and subsurface (> 30 cm depth) soils (b).