In LiamDBailey/Baileyetal_2019_JAE:

Load ggplot themes

devtools::load_all()
devtools::install_github("LiamDBailey/MyFuncs")

library(ggplot2)
library(dplyr)
library(MyFuncs)
library(extrafont)

Load data

data("VacatedTerritories")

Create summary of number of abandonments

plot_dat <- VacatedTerritories %>% 
  #Change name of status to be more understandable
  rowwise() %>% 
  mutate(Status = ifelse(Status == "leapfrog", "Inland", "Coastal")) %>% 
  ungroup() %>% 
  group_by(Year, Status) %>% 
  summarise(Perc_vacated = (sum(Vacated)/n()) * 100)

Generate plot

ggplot(data = plot_dat)+
  geom_line(aes(x = Year, y = Perc_vacated), lty = 2)+
  geom_point(aes(x = Year, y = Perc_vacated, fill = Status), shape = 21, size = 3, stroke = 1)+
  facet_wrap(facets = ~Status)+
  scale_fill_manual(values = c("black", "dark grey"))+
  theme_ubuntu()+
  theme(text = element_text(family = "sans"))+
  xlab("")+
  ylab("Percentage of territories vacated")+
  scale_y_continuous(limits = c(0, 100))+
  scale_x_continuous(breaks = seq(1985, 2015, 5))+
  theme(strip.background = element_rect(fill = "white", colour = "black"),
        strip.text = element_text(size = rel(0.8), colour = "black", face = "bold"),
        panel.border = element_rect(fill = NA, colour = "black"))

ggsave("../plots/Figure_S6.pdf", width = 20, height = 12, units = "cm", dpi = 600)

LiamDBailey/Baileyetal_2019_JAE documentation built on May 20, 2019, 12:58 a.m.