In LiamDBailey/Baileyetal_2019_JAE:

In this code, we determine the median maximum territory movement for males over their lifetime.

Load packages

devtools::load_all()
devtools::install_github("LiamDBailey/MyFuncs", upgrade = "never")

#Load libraries
library(raster)
library(rgdal)
library(deldir)
library(rgeos)
library(ggplot2)
library(dplyr)
library(purrr)
library(extrafont)
library(MyFuncs)

Load territory polygons

#Load territory data
data("Territories")

#Estimate max distance for each individual male over its recorded lifetime.
males <- subset(Territories, !is.na(MaleCode))

#Rework the data to be a spatial points datafame (i.e. territory centre points)
males <- SpatialPointsDataFrame(coords = males[, c("X", "Y")], data = males@data,
                               proj4string = crs(males))
males$Year <- as.numeric(males$Year)

#Map through all male IDs and determine their max territory range
all_dist <- pmap_df(.l = list(name = unique(males$MaleCode)),
                    .f = function(name, input_data){

                      #Subset to just be one male
                      one_male <- input_data[input_data$MaleCode == name, ]

                      #If there's only one territory then return NA
                      if(nrow(one_male) == 1){

                        return(tibble(name = name, dist = NA, sex = "M", time = NA))

                      } else {

                        #determine distance of all territories
                        male_dist <- gDistance(one_male, byid = TRUE)

                        return(tibble(name = name, dist = max(male_dist), sex = "M", time = max(one_male$Year) - min(one_male$Year)))

                      }

                    }, input_data = males)

#Determine median max movement
#Need to remove NAs for individuals only sighted once.
(pop_med <- median(all_dist$dist, na.rm = T))

(move_hist <- ggplot()+
  geom_histogram(data = filter(all_dist, !is.na(dist)),
                 aes(x = dist), fill = "dark grey", bins = 25, colour = "black") +
  geom_vline(xintercept = pop_med, lty = 2, size = 1, colour = "black")+
  scale_x_continuous(breaks = seq(0, 3000, 250))+
  labs(x = "Maximum lifetime territory movement (m)", y = "Number of individuals")+
  theme_ubuntu()+
  theme(text = element_text(family = "sans"))+
  theme(legend.position = "None",
  plot.margin = margin(0, 0.5, 0, 0, "cm")))

#Save as pdf
ggsave("../plots/Figure_S4.pdf", width = 17, height = 15, units = "cm", dpi = 600)

#Number of males used
filter(all_dist, !is.na(dist)) %>% 
  nrow()

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