Species distribution with R.Rmd

---
title: "Species distribution with R"
author: "Rosario Iacono"
date: "13/11/2019"
output: html_document
---

```{r}
#installing the packages required for the tutorial

install.packages("dismo")#installing dismo package
install.packages("readr")#installing readr package to read csv files
install.packages("maptools")#installing maptools
install.packages("dplyr")
install.packages("ggplot2")
install.packages("ggmap")
install.packages("sf", dependencies = TRUE)
install.packages("rnaturalearthdata", dependencies = TRUE)
```
# Loading the data
For this tutorial we are going to use a set of data downloaded from Global Biodiversity Information Facility (GBIF)

```{r}
library(readr)
miscanthus <- read_csv("./miscanthus distribution.csv")#import the data from the file downloaded from https://www.gbif.org/
head(miscanthus)
```
# Mapping with maptools
```{r}
library(maptools)
data(wrld_simpl)
plot(wrld_simpl, xlim=c(60,155), ylim=c(-20,60), axes=TRUE, col="light yellow")
# restore the box around the map
box()

# add the points
plot(wrld_simpl, xlim=c(60,155), ylim=c(-20,60), axes=TRUE, col="light yellow")
points(miscanthus$decimalLongitude, miscanthus$decimalLatitude, col=as.factor(miscanthus$species), pch=20, cex=0.75)
# plot points again to add a border, for better visibility 
points(miscanthus$decimalLongitude, miscanthus$decimalLatitude, col=as.factor(miscanthus$species), cex=0.75)
```

# Mapping with sf
```{r}
library(sf)
library(rnaturalearth)
library(rnaturalearthdata)
# Create data frame of only longitude and latitude values
coords <- select(miscanthus_dens, decimalLongitude, decimalLatitude)

# Create SpatialPoints object with coords and CRS
points_sf <- st_as_sf(miscanthus_dens, coords = c("decimalLongitude", "decimalLatitude"), crs = 4326)

coast_sf <- ne_coastline(scale = "medium", returnclass = "sf")
countries_sf <- ne_countries(scale = "medium", returnclass = "sf")
```

```{r}


ggplot()+
  geom_sf(data = coast_sf) + 
  geom_sf(data = points_sf,
          aes(color = species, size = n),
          alpha = 0.7,
          show.legend = "point") +
    labs(title= "A map showing our distribution")+
    xlab("Longitude (decimal degrees)")+
    ylab("Latitude (decimal degrees)")+
  coord_sf(xlim=c(60,155), ylim=c(-20,60))
```

# Mapping with ggmap
```{r}
library(dplyr)
miscanthus_dens<-miscanthus%>%
  count(species, decimalLatitude, decimalLongitude)
head(miscanthus_dens)

library("ggmap")
map <- c(left = 60, bottom = -20, right = 155, top = 60)
map1<-get_stamenmap(map, zoom = 3, maptype = "toner-lite")
ggmap(map1)+
    #geom_point(data = miscanthus_dens, 
               #mapping = aes(x = decimalLongitude, 
                             #y = decimalLatitude))+
    stat_density_2d(data = miscanthus_dens,aes(x = decimalLongitude,
                                               y = decimalLatitude, 
                                               fill = species), 
                    geom = "polygon", 
                    alpha = .3, 
                    color = NA)
```