In RS-eco/traitdata: Easy access to various ecological trait data

knitr::opts_chunk$set(collapse = TRUE, comment = "#>", eval=F)

Calculate bird species richness (SR) for each island large than 1 ha

Load island data

# Load islands data
data(largeislands, package="ggmap2")

Load bird species richness data

# Read bird data
data(ter_birds_dist, package="rasterSp")

# Add presence column
ter_birds_dist$presence <- 1

# Calulate bird SR
library(dplyr)
sr_birds <- ter_birds_dist %>% group_by(x, y) %>% 
  summarise(sum = sum(presence))
library(ggmap2)
ggmap2(data=sr_birds, name="SR")

# Convert bird data to a spatial object
sp::coordinates(sr_birds) <- ~x+y

# Make sure both files have the same projection
library(sp)
proj4string(sr_birds) <- sf::st_crs(largeislands)$proj4string

Extract bird SR for each island

sr_birds <- raster::rasterFromXYZ(sr_birds)
sr_islands <- raster::extract(sr_birds, largeislands, fun=sum, na.rm=FALSE, sp=TRUE)
sr_islands <- sr_islands@data

Save data to file

write.csv(sr_islands, "sr_islands.csv", row.names=F)

Now, we can identify the 10 islands with the highest bird SR

library(dplyr)
arrange(sr_islands, sum) %>% head(10) %>% select(NAME_ENGLI, Island) %>% unique()

Identify bird species occuring on islands

# Convert bird data to a spatial object
sp::coordinates(ter_birds_dist) <- ~x+y

# Make sure both files have the same projection
proj4string(ter_birds_dist) <- sf::st_crs(largeislands)$proj4string

# SF approach

# Turn ter_birds into sf object
library(sf)
ter_birds_dist <- st_as_sf(ter_birds_dist)
island_birds <- ter_birds_dist[sf::st_within(ter_birds_dist, largeislands),]

# Spatial approach

# Turn large islands into an sp object
#largeislands <- as(largeislands, "Spatial")

# Extract bird names occuring on islands
#island_birds <- sp::over(ter_birds_dist, largeislands)
#island_birds_all <- cbind(ter_birds_dist@data, island_birds)
#island_birds <- tidyr::drop_na(island_birds_all)

# Only want to have unique names
island_birds <- unique(island_birds$species)
head(island_birds)

Save species names of birds that occur on islands to file

write.csv(island_birds, "island_birds.csv", row.names=F)

Find island birds for which we have traits

Load traitdata of birds

library(traitdata)
data(globTherm)

Standardise species names of island_birds

# Read island birds
island_birds <- read.csv("island_birds.csv")

# Load standardised taxonomy
load("data/taxonomyStd.rda")

# Change species column of island birds
colnames(island_birds) <- "scientificName"

# Check which species have already a standardised taxonomy
island_birds %>% left_join(taxonomyStd)

# Add standardised taxonomy of remaining species
#island_species <- traitdata::standardize_taxonomy(island_species, 
#                                                      return="scientificNameStd")

Merge island birds with globTherm

#Merge data
island_birds_traits <- dplyr::full_join(island_species, globTherm, by="scientificNameStd")

Identify species that have certain traits

# number of unique species
species_num <- length(unique(island_birds_traits$taxonomyStd))

# island species with maximum thermal tolerance
species_tmax <- length(unique(island_birds_traits$taxonomyStd[which(!is.na(island_birds_traits$Tmax))]))