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5_DiversityMaps.R
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5_DiversityMaps.R
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#===================================#
# Maps of global diversity patterns #
#===================================#
library(tidyverse)
library(sf)
library(colorspace)
library(rnaturalearth)
library(rnaturalearthdata)
sf_use_s2(FALSE)
# Set color palette
colorspace::sequential_hcl(n = 12, h = 0, c = c(8, 80, NA),
l = c(5, 95), power = 1,
register = "Biogeography")
cells <- st_read("Data/global_cells.shp")
world <- ne_coastline(scale = "medium", returnclass = "sf") %>%
st_crop(c(xmin=-180, xmax=180, ymin=-60, ymax=85))
# ----- BIRDS ----------
# ---------- Species richness (Supplementary Fig. 3a) ----------
# Load data
data <- cells %>%
right_join(read.csv("Data/bird_SR_cells.csv"), "cell_id")
# Save figure
svg("Results/SR_map_bird.svg",
width = 2.5, height = 1.5)
ggplot() +
geom_sf(data = world, colour="grey85", lwd=.1, linewidth=.1) +
geom_sf(data=data, aes(color = SR, fill = SR),
lwd=.1, linewidth=.1) +
scale_color_continuous_sequential("Biogeography") +
scale_fill_continuous_sequential("Biogeography") +
theme_void() +
theme(legend.title = element_blank(),
legend.text = element_text(size=7),
legend.position = "bottom") +
theme(legend.key.height = unit(.17, "cm"),
legend.key.width = unit(1.1,"cm"))
dev.off()
# ---------- Phylogenetic diversity (Supplementary Fig. 3b) ----------
# Load data
data <- cells %>%
right_join(read.csv("Data/bird_PD_cells.csv"), "cell_id")
# Save figure
svg("Results/PD_map_bird.svg",
width = 2.5, height = 1.5)
ggplot() +
geom_sf(data = world, colour="grey85", lwd=.1, linewidth=.1) +
geom_sf(data=data, aes(color = PD, fill = PD),
lwd=.1, linewidth=.1) +
scale_color_continuous_sequential("Biogeography") +
scale_fill_continuous_sequential("Biogeography") +
theme_void() +
theme(legend.title = element_blank(),
legend.text = element_text(size=7),
legend.position = "bottom") +
theme(legend.key.height = unit(.17, "cm"),
legend.key.width = unit(1.1,"cm"))
dev.off()
# ---------- Functional richness (Supplementary Fig. 3c) ----------
# Load data
data <- cells %>%
right_join(read.csv("Data/bird_FR_cells.csv"), "cell_id")
# Save figure
svg("Results/FR_map_bird.svg",
width = 2.5, height = 1.5)
ggplot() +
geom_sf(data = world, colour="grey85", lwd=.1, linewidth=.1) +
geom_sf(data=data, aes(color = FR, fill = FR),
lwd=.1, linewidth=.1) +
scale_color_continuous_sequential("Biogeography") +
scale_fill_continuous_sequential("Biogeography") +
theme_void() +
theme(legend.title = element_blank(),
legend.text = element_text(size=7),
legend.position = "bottom") +
theme(legend.key.height = unit(.17, "cm"),
legend.key.width = unit(1.1,"cm"))
dev.off()
# ---------- Mean func beta turnover (Fig. 4a) ----------
# Load data
data <- cells %>%
right_join(read.csv("Data/bird_mean_fb.csv"), "cell_id")
# Save figure
svg("Results/FB_map_bird.svg",
width = 3, height = 1.8)
ggplot() +
geom_sf(data = world, colour="grey85", lwd=.1, linewidth=.1) +
geom_sf(data=data, aes(color = mean_fb, fill = mean_fb),
lwd=.1, linewidth=.1) +
scale_color_continuous_sequential("Biogeography", limits=c(0,.51)) +
scale_fill_continuous_sequential("Biogeography", limits=c(0,.51)) +
theme_void() +
theme(legend.title = element_blank(),
legend.text = element_text(size=7),
legend.position = "bottom") +
theme(legend.key.height = unit(.2, "cm"),
legend.key.width = unit(1.3,"cm"))
dev.off()
# ----- MAMMALS ----------
# ---------- Species richness (Supplementary Fig. 3d) ----------
# Load data
data <- cells %>%
right_join(read.csv("Data/mamm_SR_cells.csv"), "cell_id")
# Save figure
svg("Results/SR_map_mamm.svg",
width = 2.5, height = 1.5)
ggplot() +
geom_sf(data = world, colour="grey85", lwd=.1, linewidth=.1) +
geom_sf(data=data, aes(color = SR, fill = SR),
lwd=.1, linewidth=.1) +
scale_color_continuous_sequential("Biogeography") +
scale_fill_continuous_sequential("Biogeography") +
theme_void() +
theme(legend.title = element_blank(),
legend.text = element_text(size=7),
legend.position = "bottom") +
theme(legend.key.height = unit(.17, "cm"),
legend.key.width = unit(1.1,"cm"))
dev.off()
# ---------- Phylogenetic diversity (Supplementary Fig. 3e) ----------
# Load data
data <- cells %>%
right_join(read.csv("Data/mamm_PD_cells.csv"), "cell_id")
# Save figure
svg("Results/PD_map_mamm.svg",
width = 2.5, height = 1.5)
ggplot() +
geom_sf(data = world, colour="grey85", lwd=.1, linewidth=.1) +
geom_sf(data=data, aes(color = PD, fill = PD),
lwd=.1, linewidth=.1) +
scale_color_continuous_sequential("Biogeography") +
scale_fill_continuous_sequential("Biogeography") +
theme_void() +
theme(legend.title = element_blank(),
legend.text = element_text(size=7),
legend.position = "bottom") +
theme(legend.key.height = unit(.17, "cm"),
legend.key.width = unit(1.1,"cm"))
dev.off()
# ---------- Functional richness (Supplementary Fig. 3f) ----------
# Load data
data <- cells %>%
right_join(read.csv("Data/mamm_FR_cells.csv"), "cell_id")
# Save figure
svg("Results/FR_map_mamm.svg",
width = 2.5, height = 1.5)
ggplot() +
geom_sf(data = world, colour="grey85", lwd=.1, linewidth=.1) +
geom_sf(data=data, aes(color = FR, fill = FR),
lwd=.1, linewidth=.1) +
scale_color_continuous_sequential("Biogeography") +
scale_fill_continuous_sequential("Biogeography") +
theme_void() +
theme(legend.title = element_blank(),
legend.text = element_text(size=7),
legend.position = "bottom") +
theme(legend.key.height = unit(.17, "cm"),
legend.key.width = unit(1.1,"cm"))
dev.off()
# ---------- Mean func beta turnover (Fig. 4b) ----------
# Load data
data <- cells %>%
right_join(read.csv("Data/mamm_mean_fb.csv"), "cell_id")
# Save figure
svg("Results/FB_map_mamm.svg",
width = 3, height = 1.8)
ggplot() +
geom_sf(data = world, colour="grey85", lwd=.1, linewidth=.1) +
geom_sf(data=data, aes(color = mean_fb, fill = mean_fb),
lwd=.1, linewidth=.1) +
scale_color_continuous_sequential("Biogeography", limits=c(0,.51)) +
scale_fill_continuous_sequential("Biogeography", limits=c(0,.51)) +
theme_void() +
theme(legend.title = element_blank(),
legend.text = element_text(size=7),
legend.position = "bottom") +
theme(legend.key.height = unit(.2, "cm"),
legend.key.width = unit(1.3,"cm"))
dev.off()
# ----- BATS ----------
# ---------- Species richness (Supplementary Fig. 3g) ----------
# Load data
data <- cells %>%
right_join(read.csv("Data/bat_SR_cells.csv"), "cell_id")
# Save figure
svg("Results/SR_map_bat.svg",
width = 2.5, height = 1.5)
ggplot() +
geom_sf(data = world, colour="grey85", lwd=.1, linewidth=.1) +
geom_sf(data=data, aes(color = SR, fill = SR),
lwd=.1, linewidth=.1) +
scale_color_continuous_sequential("Biogeography") +
scale_fill_continuous_sequential("Biogeography") +
theme_void() +
theme(legend.title = element_blank(),
legend.text = element_text(size=7),
legend.position = "bottom") +
theme(legend.key.height = unit(.17, "cm"),
legend.key.width = unit(1.1,"cm"))
dev.off()
# ---------- Phylogenetic diversity (Supplementary Fig. 3h) ----------
# Load data
data <- cells %>%
right_join(read.csv("Data/bat_PD_cells.csv"), "cell_id")
# Save figure
svg("Results/PD_map_bat.svg",
width = 2.5, height = 1.5)
ggplot() +
geom_sf(data = world, colour="grey85", lwd=.1, linewidth=.1) +
geom_sf(data=data, aes(color = PD, fill = PD),
lwd=.1, linewidth=.1) +
scale_color_continuous_sequential("Biogeography") +
scale_fill_continuous_sequential("Biogeography") +
theme_void() +
theme(legend.title = element_blank(),
legend.text = element_text(size=7),
legend.position = "bottom") +
theme(legend.key.height = unit(.17, "cm"),
legend.key.width = unit(1.1,"cm"))
dev.off()
# ---------- Functional richness (Fig. 6b) ----------
# Load data
data <- cells %>%
right_join(read.csv("Data/bat_FR_cells.csv"), "cell_id") %>%
na.omit()
# Save figure
svg("Results/FR_map_bat.svg",
width = 3, height = 1.8)
ggplot() +
geom_sf(data = world, colour="grey85", lwd=.1, linewidth=.1) +
geom_sf(data=data, aes(color = FR, fill = FR),
lwd=.1, linewidth=.1) +
scale_color_continuous_sequential("Biogeography") +
scale_fill_continuous_sequential("Biogeography") +
theme_void() +
theme(legend.title = element_blank(),
legend.text = element_text(size=7),
legend.position = "bottom") +
theme(legend.key.height = unit(.2, "cm"),
legend.key.width = unit(1.3,"cm"))
dev.off()
# ---------- Mean func beta turnover (Supplementary Fig. 3i) ----------
# Load data
data <- cells %>%
right_join(read.csv("Data/bat_mean_fb.csv"), "cell_id") %>%
na.omit()
# Save figure
svg("Results/FB_map_bat.svg",
width = 2.5, height = 1.5)
ggplot() +
geom_sf(data = world, colour="grey85", lwd=.1, linewidth=.1) +
geom_sf(data=data, aes(color = mean_fb, fill = mean_fb),
lwd=.1, linewidth=.1) +
scale_color_continuous_sequential("Biogeography") +
scale_fill_continuous_sequential("Biogeography") +
theme_void() +
theme(legend.title = element_blank(),
legend.text = element_text(size=7),
legend.position = "bottom") +
theme(legend.key.height = unit(.17, "cm"),
legend.key.width = unit(1.1,"cm"))
dev.off()