In BirdStudiesCanada/rNatureCounts: Access and download data on plant and animal populations from NatureCounts

options(width = 100)
knitr::opts_chunk$set(out.width = "60%", fig.width = 6, fig.asp = 1, fig.align = "center")

In this section we'll explore Important Bird Areas (IBAs) and Bird Conservation Regions (BCRs), so you'll have a better idea of what they represent when used as data filters.

We'll be using the tidyverse packages dplyr and ggplot2 for data manipulation and plotting, respectively. We'll use the sf package for working with spatial data, and the rnaturalearth package to get example spatial data.

library(naturecounts)
library(dplyr)
library(ggplot2)
library(sf)
library(rnaturalearth)
library(mapview)

First we'll get some spatial objects for our explorations from the rnaturalearth package. A map of North America and of Canada, both transformed from CRS EPSG code 4326 (unprojected lat/lon) to 3347 (NAD83 Statistics Canada).

na <- ne_countries(continent = "north america", returnclass = "sf") %>%
  st_transform(3347)

canada <- ne_states(country = "canada", returnclass = "sf") %>%
  st_transform(3347)

Important Bird Areas

To get a visual idea of where different Important Bird Areas are, let's plot them on our map of Canada.

First we need to grab the IBA data frame and convert it to a spatial object. Because the data contains lat/lon, we assign it to CRS 4326 for GPS lat/lon data, and then convert it to match the crs of our maps.

iba <- meta_iba_codes() %>%
  st_as_sf(coords = c("longitude", "latitude"), crs = 4326) %>%
  st_transform(3347)

ggplot() +
  theme_bw() +
  geom_sf(data = canada) +
  geom_sf(data = iba)

If you want to narrow in on only one province,

a) filter the IBA data frame

iba_nwt <- filter(iba, statprov == "NT")

b) get the limits of the Northwest Territories

limits <- st_bbox(filter(canada, name == "Northwest Territories"))

Put it all together

ggplot() + 
  theme_bw() +
  geom_sf(data = canada) +
  geom_sf(data = iba_nwt) +
  geom_sf_text(data = iba_nwt, aes(label = iba_site), size = 3, vjust = -0.5) +
  coord_sf(xlim = limits[c("xmin", "xmax")], ylim = limits[c("ymin", "ymax")])

For a more detailed view of IBAs, we can also grab the shape files from Birds Canada.

iba <- st_read("https://birdmap.birdscanada.org/geoserver/atlas/ows?service=WFS&version=1.0.0&request=GetFeature&typeName=atlas:iba&outputFormat=application%2Fjson") %>%
  st_transform(3347)

iba <- filter(iba, Status == "confirmed") # Omit historical areas

ggplot() +
  theme_bw() +
  geom_sf(data = canada, colour = "grey80") +
  geom_sf(data = iba, fill = "blue", colour = NA, show.legend = FALSE, alpha = 0.5)

To really explore these areas, interactive maps can be really useful. Note that you can move the map, zoom in and out, and click on specific IBAs for more information.

mapview(iba)

Bird Conservation Regions

Bird Conservation Regions are also available from Birds Canada.

bcr <- st_read("https://birdmap.birdscanada.org/geoserver/atlas/ows?service=WFS&version=1.0.0&request=GetFeature&typeName=atlas:bcr&outputFormat=application%2Fjson") %>%
  st_transform(3347)

ggplot() +
  theme_bw() +
  geom_sf(data = na, colour = "grey80") +
  geom_sf(data = bcr, aes(fill = bcr), show.legend = FALSE, alpha = 0.5) +
  scale_fill_viridis_c()

And again, interactive maps can be really useful.

mapview(bcr)

BirdStudiesCanada/rNatureCounts documentation built on July 3, 2023, 2:06 a.m.