EMODnet Biology robis demo

Install the robis package

robis is not available on CRAN. It needs to be installed from GitHub. In the devtools package, you will find the function install_github() which does the installation for you. If devtools is not yet installed on your machine, do that first.

Download occurence data from OBIS

By scientific name

data2 <- occurrence(scientificname = c("Cetartiodactyla"), geometry = st_as_text(pol_ext))

Retrieved 2000 records of 3453 (57%)
Retrieved 3453 records of 3453 (100%)

leaflet(data) %>%
  addTiles(group = "OSM (default)") %>%
  addProviderTiles("Hydda.Base", group = "Hydda.Base") %>%
  addProviderTiles("Esri.WorldImagery", group = "Esri.WorldImagery") %>%
  addWMSTiles("http://ows.emodnet-bathymetry.eu/wms",
              layers = "emodnet:mean_multicolour",
              options = WMSTileOptions(version = "1.3.0", format="image/png", transparent = T),
              group = "EMODnet bathymetry") %>%
  addWMSTiles("http://geodata.nationaalgeoregister.nl/natura2000/ows",
              layers = "natura2000",
              options = WMSTileOptions(version = "1.3.0", format="image/png", transparent = T, EPSG = "28992"), group = "Natura2000") %>%
  addProviderTiles("OpenSeaMap", group = "OpenSeaMap") %>%
  addCircleMarkers(lat = ~decimalLatitude, lng = ~decimalLongitude, radius = ~log10(individualCount/100), group = "species") %>%
  addLayersControl(
    baseGroups = c("OSM (default)", "Hydda.Base", "Esri.WorldImagery"),
    overlayGroups =  c("EMODnet bathymetry", "OpenSeaMap", "observations", "Natura2000")
  ) %>%
  hideGroup(c("EMODnet bathymetry", "OpenSeaMap", "Natura2000"))

Or plot using ggplot

data("countriesHigh")
world <- fortify(countriesHigh)
ggplot(data = data, aes(decimalLongitude, decimalLatitude)) +
  geom_polygon(data = world, aes(x = long, y = lat, group = group), fill = "darkgrey") +
  geom_point(aes(size = individualCount, color = scientificName)) +
  coord_quickmap(xlim = range(data$decimalLongitude), ylim = range(data$decimalLatitude))

data %>% 
  ggplot (aes(x = yearcollected, y = individualCount)) + 
  geom_boxplot(aes(group = yearcollected)) + 
  scale_y_log10()

data %>% group_by(yearcollected) %>% 
  summarize(average = mean(individualCount, na.rm = T)) %>%
  ggplot (aes(x = yearcollected, y = average)) + 
  geom_point(aes()) + 
  scale_y_log10()