The Finnish Biodiversity Information Facility (FinBIF) aggregates Finnish biodiversity data from multiple sources in a single open access portal for researchers, citizen scientists, industry and government. The finbif R package provides access to the FinBIF API directly from within R. FinBIF allows users of biodiversity information to find, access, combine and visualise data on Finnish plants, animals and microorganisms. The finbif R package makes the publicly available data in FinBIF accessible from within R. Biodiversity information is available on taxonomy and taxon occurrence. Occurrence data can be filtered by taxon, time, location and other variables. The data accessed are conveniently preformatted for subsequent analyses.

Installing the finbif package

You can install the development version of finbif from GitHub,

remotes::install_github("luomus/finbif")

Loading the finbif package

library(finbif)

Getting a FinBIF access token

To use the FinBIF API you must first request and set a personal access token. You can request an API token to be sent to your email address with the function finbif_get_token.

finbif_request_token("your@email.com")

Copy the access token that was sent to your email and set it as the environment variable FINBIF_ACCESS_TOKEN either for the current session,

Sys.setenv(
  FINBIF_ACCESS_TOKEN = "xtmSOIxjPwq0pOMB1WvcZgFLU9QBklauOlonWl8K5oaLIx8RniJLrvcJU4v9H7Et"
)
# Note: the above is not a real access token. Do not try using it.

, or by adding it to a Renviron startup file (see here for details).

Working with taxa

You can check to see if a taxon exists in the FinBIF database.

finbif_check_taxa("Ursus arctos")
#> [Ursus arctos] ID: MX.47348

If the taxon is in the FinBIF database its unique ID is returned. When a taxon is not in the FinBIF database it is reported as “not found” and for that taxa the list element is NA.

(taxa <- finbif_check_taxa(c("Ursus arctos", "Moomin")))
#> [Ursus arctos] ID: MX.47348
#> [Moomin      ] Not found
taxa[[1]]
#> Ursus arctos 
#>   "MX.47348"
taxa[[2]]
#> Moomin 
#>     NA

You can also specify the taxonomic rank when searching FinBIF and the search will be limited to the specified rank.

finbif_check_taxa(list(species = c("Ursus arctos", "Ursus"), genus = "Ursus"))
#> [species: Ursus arctos] ID: MX.47348
#> [species: Ursus       ] Not found
#> [genus:   Ursus       ] ID: MX.51311

The function finbif_taxa() can be used for a more general search for taxa in the FinBIF database. Searches can be exact, partial or likely (fuzzy matching). Information for a single taxon is returned when using exact or fuzzy matching, but multiple taxa, up to a limit, n, may be returned when using partial matching.

birch_search <- finbif_taxa("Betula pendula", 2, "partial")
str(birch_search$content, max.level = 2, list.len = 8)
#> List of 2
#>  $ :List of 11
#>   ..$ matchingName  : chr "Betula pendula var. pendula"
#>   ..$ nameType      : chr "MX.scientificName"
#>   ..$ id            : chr "MX.37994"
#>   ..$ scientificName: chr "Betula pendula var. pendula"
#>   ..$ taxonRank     : chr "MX.variety"
#>   ..$ cursiveName   : logi TRUE
#>   ..$ finnish       : logi TRUE
#>   ..$ species       : logi TRUE
#>   .. [list output truncated]
#>  $ :List of 12
#>   ..$ matchingName            : chr "Betula pendula var. carelica"
#>   ..$ nameType                : chr "MX.scientificName"
#>   ..$ id                      : chr "MX.37997"
#>   ..$ scientificName          : chr "Betula pendula var. carelica"
#>   ..$ scientificNameAuthorship: chr "(Merckl.) Hämet-Ahti"
#>   ..$ taxonRank               : chr "MX.variety"
#>   ..$ cursiveName             : logi TRUE
#>   ..$ finnish                 : logi TRUE
#>   .. [list output truncated]

Getting occurrence data

You can download occurrence data from the FinBIF database as a data.frame with the finbif_occurrence() function.

finbif_occurrence("Cygnus cygnus", n = 100)
#> Records downloaded: 100
#> Records available: 55642
#> A data.frame [100 x 30]
#>    scientific_name abundance lat_wgs84 lon_wgs84           date_time
#> 1    Cygnus cygnus         1  61.07692  21.49222 2019-10-09 05:50:00
#> 2    Cygnus cygnus         3  62.30263  24.52289 2019-10-09 04:45:00
#> 3    Cygnus cygnus         2  60.95615  21.68894 2019-10-08 06:07:00
#> 4    Cygnus cygnus         2  60.98465  21.70309 2019-10-08 05:59:00
#> 5    Cygnus cygnus         9  62.22049  24.59103 2019-10-08 04:54:00
#> 6    Cygnus cygnus         5  60.95401  26.09615 2019-09-29 21:00:00
#> 7    Cygnus cygnus         1  60.45848  22.37712 2019-09-28 21:00:00
#> 8    Cygnus cygnus         3  61.32291  28.56818 2019-09-29 00:00:00
#> 9    Cygnus cygnus         2  60.56745  21.57187 2019-09-28 21:00:00
#> 10   Cygnus cygnus         3  61.32291  28.56818 2019-09-27 07:46:00
#> ...with 90 more records and 25 more variables:
#> taxon_rank, country, province, municipality, date_start, date_end,
#> hour_start, hour_end, minute_start, minute_end, record_id,
#> individual_id, event_id, collection_id, any_issues, record_issue,
#> record_reliable, taxon_reliability, document_issue,
#> document_reliablity, coordinate_accuracy, event_issue,
#> location_issue, time_issue, duration

You can search for multiple taxa at once and filter the records with the filter argument.

finbif_occurrence(
  "Cygnus cygnus", 
  "Cygnus olor",
  filter = list(coordinates_uncertainty_max = 100)
)
#> Records downloaded: 10
#> Records available: 11297
#> A data.frame [10 x 30]
#>    scientific_name abundance lat_wgs84 lon_wgs84           date_time
#> 1    Cygnus cygnus       260  60.95257  26.48997 2019-11-04 22:00:00
#> 2    Cygnus cygnus       114  60.88855  26.12326 2019-11-04 22:00:00
#> 3    Cygnus cygnus        14  60.95321  26.09083 2019-11-03 22:00:00
#> 4    Cygnus cygnus         6  60.95231  26.09553 2019-11-03 22:00:00
#> 5    Cygnus cygnus         1  61.10238  21.54661 2019-11-02 13:30:00
#> 6    Cygnus cygnus         1  61.10237  21.54661 2019-10-31 14:20:00
#> 7    Cygnus cygnus         1  61.10965  21.53318 2019-10-27 06:25:00
#> 8    Cygnus cygnus        12  62.25014  25.74540 2019-10-26 21:00:00
#> 9      Cygnus olor         1  60.45875  22.37761 2019-10-25 21:00:00
#> 10   Cygnus cygnus         1  60.45875  22.37761 2019-10-25 21:00:00
#> ...with 0 more records and 25 more variables:
#> taxon_rank, country, province, municipality, date_start, date_end,
#> hour_start, hour_end, minute_start, minute_end, record_id,
#> individual_id, event_id, collection_id, any_issues, record_issue,
#> record_reliable, taxon_reliability, document_issue,
#> document_reliablity, coordinates_uncertainty, event_issue,
#> location_issue, time_issue, duration

See ?filters and vignette("filtering") for more details on filtering FinBIF records.

Plotting occurrence data

The finbif package has a number of inbuilt functions for plotting (see e.g., breaks_xy() and hist_xy()). There is also an inbuilt dataset that can be used to plot the border of Finland (?finland_map). Together these utilities can be used to plot occurrences after they have been downloaded from FinBIF. For example, the following can be used to plot the density of Eurasian Jay occurrences from Finland.

# Download all the occurrences of Eurasian Jay in Finland
# that have coordinates accurate to at least 100m
jays <- finbif_occurrence(
  taxa   = "Eurasian Jay",
  filter = c(
    coordinates_uncertainty_max = 100,
    country                 = "Finland"
  ),
  n      = 2e4,
  quiet  = TRUE
)
# Compute the density of occurrences in 1/4 degree cells and plot as a heatmap
with(
  data = c(jays, finland_map),
  expr = {
    par(mar = c(5, 5, 1, 1), las = 1)
    # compute a 2d histogram from the occurrences
    breaks  <- breaks_xy(bbox, .25) # breakpoints every 1/4 of a degree
    density <- hist_xy(xy = list(lon_wgs84, lat_wgs84), breaks)
    # plot the histogram as a heatmap
    image(density,
          asp    = 2.4,
          breaks = 2^seq(0, 12), # breakpoints for the gridcell colours
          col    = hcl.colors(12, rev = TRUE),
          xlab   = "Longitude",
          ylab   = "Latitude",
          panel.first = grid())
    legend("topright",
           inset  = c(0, .01),
           legend = expression(2^12, "", "", 2^6, "", "", 2^0),
           fill   = hcl.colors(7),
           border = NA,
           bty    = "n",
           adj    = c(0, 0.25), 
           x.intersp = .2,
           y.intersp = .5)
    # add the Finnish border
    polygon(x = vertices, lwd = .2)
  }
)

Caching

By default finbif uses local filesystem caching for repeated API request. This can be turned on or off on a per request or session basis. See ?caching for details.