FinBIF aggregates Finnish biodiversity data from multiple sources in a single open access portal for researchers, citizen scientists, industry and government. 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 easily accessible to programmers. 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 current stable version of finbif from CRAN,

install.packages("finbif")

You can also install the latest development version of finbif from GitHub,

remotes::install_github("luomus/finbif@dev")

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")
birch_search$content

Click to show/hide output.


[[1]]
[[1]]$matchingName
[1] "Betula pendula var. pendula"

[[1]]$nameType
[1] "MX.scientificName"

[[1]]$id
[1] "MX.37994"

[[1]]$scientificName
[1] "Betula pendula var. pendula"

[[1]]$taxonRank
[1] "MX.variety"

[[1]]$cursiveName
[1] TRUE

[[1]]$finnish
[1] TRUE

[[1]]$species
[1] TRUE

[[1]]$vernacularName
[[1]]$vernacularName$fi
[1] "vihtakoivu"

[[1]]$vernacularName$sv
[1] "vanlig vårtbjörk"


[[1]]$informalGroups
[[1]]$informalGroups[[1]]
[[1]]$informalGroups[[1]]$id
[1] "MVL.343"

[[1]]$informalGroups[[1]]$name
[[1]]$informalGroups[[1]]$name$en
[1] "Vascular plants"

[[1]]$informalGroups[[1]]$name$fi
[1] "Putkilokasvit"

[[1]]$informalGroups[[1]]$name$sv
[1] "Kärlväxter"




[[1]]$type
[1] "partialMatches"


[[2]]
[[2]]$matchingName
[1] "Betula pendula var. carelica"

[[2]]$nameType
[1] "MX.scientificName"

[[2]]$id
[1] "MX.37997"

[[2]]$scientificName
[1] "Betula pendula var. carelica"

[[2]]$scientificNameAuthorship
[1] "(Merckl.) Hämet-Ahti"

[[2]]$taxonRank
[1] "MX.variety"

[[2]]$cursiveName
[1] TRUE

[[2]]$finnish
[1] TRUE

[[2]]$species
[1] TRUE

[[2]]$vernacularName
[[2]]$vernacularName$fi
[1] "visakoivu"

[[2]]$vernacularName$sv
[1] "masurbjörk"


[[2]]$informalGroups
[[2]]$informalGroups[[1]]
[[2]]$informalGroups[[1]]$id
[1] "MVL.343"

[[2]]$informalGroups[[1]]$name
[[2]]$informalGroups[[1]]$name$en
[1] "Vascular plants"

[[2]]$informalGroups[[1]]$name$fi
[1] "Putkilokasvit"

[[2]]$informalGroups[[1]]$name$sv
[1] "Kärlväxter"




[[2]]$type
[1] "partialMatches"


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: 55923
#> A data.frame [100 x 30]
#>    scientific_name abundance lat_wgs84 lon_wgs84           date_time
#> 1    Cygnus cygnus         1  60.45824  22.37683 2019-12-03 22:00:00
#> 2    Cygnus cygnus         1  62.26510  24.69194 2019-12-04 05:20:00
#> 3    Cygnus cygnus         2  61.12486  21.54164 2019-12-03 09:50:00
#> 4    Cygnus cygnus         6  60.90052  26.31596 2019-12-02 22:00:00
#> 5    Cygnus cygnus         4  61.33203  21.65924 2019-12-01 10:20:00
#> 6    Cygnus cygnus         3  60.17308  25.10529 2019-11-30 12:00:00
#> 7    Cygnus cygnus        14  60.17308  25.10529 2019-11-30 12:00:00
#> 8    Cygnus cygnus         2  60.17308  25.10529 2019-11-30 12:00:00
#> 9    Cygnus cygnus         6  61.07310  26.46700 2019-11-24 22:00:00
#> 10   Cygnus cygnus         1  61.34301  24.23489 2019-11-16 06:30:00
#> ...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,
#> collection_reliability, coordinates_uncertainty, 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)
)

Click to show/hide output.


Records downloaded: 10
Records available: 11363
A data.frame [10 x 30]
   scientific_name abundance lat_wgs84 lon_wgs84           date_time
1    Cygnus cygnus        30  61.03529  26.13553 2020-01-07 22:00:00
2    Cygnus cygnus        26  60.93560  26.37433 2020-01-06 22:00:00
3    Cygnus cygnus         1  62.38777  26.05355 2020-01-04 22:00:00
4    Cygnus cygnus        21  60.81513  26.24554 2020-01-04 22:00:00
5    Cygnus cygnus         5  61.12549  21.53582 2020-01-05 10:45:00
6      Cygnus olor         4  61.06336  26.17340 2019-12-31 22:00:00
7    Cygnus cygnus         2  61.09991  21.50955 2019-12-17 10:20:00
8    Cygnus cygnus        40  60.91752  26.32643 2019-12-15 22:00:00
9    Cygnus cygnus         6  60.90052  26.31596 2019-12-02 22:00:00
10   Cygnus cygnus         4  61.33203  21.65924 2019-12-01 10:20:00
...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,
collection_reliability, coordinates_uncertainty, event_issue,
location_issue, time_issue, duration


See ?filters and vignette("v0_filtering") for more details on filtering FinBIF records.

Random sampling

It is possible to request a random sample of records instead of the last n records (or records ordered by some other variable).

finbif_occurrence("Birds", sample = TRUE)

Click to show/hide output.


Records downloaded: 10
Records available: 17751448
A data.frame [10 x 30]
        scientific_name abundance lat_wgs84 lon_wgs84           date_time
1    Erithacus rubecula         1  60.47356  27.44691 2007-09-01 04:00:00
2      Numenius arquata         1  59.81111  22.89545 2008-09-01 21:00:00
3     Falco tinnunculus         1  60.61667  22.93333 2012-06-29 13:00:00
4  Corvus corone cornix         1  62.70686  22.02384 1985-06-10 01:20:00
5    Ficedula hypoleuca         1  69.01667  20.86667 1973-06-29 23:00:00
6      Acanthis flammea         1  60.82859  24.25148 1999-12-31 22:00:00
7  Phylloscopus trochi…         1  64.80000  24.63333 1993-06-01 21:00:00
8         Turdus merula         1  60.63333  22.41667 2001-02-18 06:00:00
9  Phylloscopus trochi…         1  60.19879  24.81963 2004-09-11 03:00:00
10  Aegithalos caudatus         1  59.88393  22.54163 1999-12-31 22:00:00
...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,
collection_reliability, coordinates_uncertainty, event_issue,
location_issue, time_issue, duration


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.

Click to show/hide code.

# 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.