Introduction to the finbif package

William K. Morris

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$sv
#> [1] "vanlig vårtbjörk"
#> 
#> [[1]]$vernacularName$fi
#> [1] "vihtakoivu"
#> 
#> 
#> [[1]]$informalGroups
#> [[1]]$informalGroups[[1]]
#> [[1]]$informalGroups[[1]]$id
#> [1] "MVL.343"
#> 
#> [[1]]$informalGroups[[1]]$name
#> [[1]]$informalGroups[[1]]$name$fi
#> [1] "Putkilokasvit"
#> 
#> [[1]]$informalGroups[[1]]$name$sv
#> [1] "Kärlväxter"
#> 
#> [[1]]$informalGroups[[1]]$name$en
#> [1] "Vascular plants"
#> 
#> 
#> 
#> 
#> [[1]]$type
#> [1] "partialMatches"
#> 
#> 
#> [[2]]
#> [[2]]$matchingName
#> [1] "Betula nana × pendula"
#> 
#> [[2]]$nameType
#> [1] "MX.scientificName"
#> 
#> [[2]]$id
#> [1] "MX.38005"
#> 
#> [[2]]$scientificName
#> [1] "Betula nana × pendula"
#> 
#> [[2]]$taxonRank
#> [1] "MX.infragenericHybrid"
#> 
#> [[2]]$cursiveName
#> [1] TRUE
#> 
#> [[2]]$finnish
#> [1] TRUE
#> 
#> [[2]]$species
#> [1] TRUE
#> 
#> [[2]]$vernacularName
#> named list()
#> 
#> [[2]]$informalGroups
#> [[2]]$informalGroups[[1]]
#> [[2]]$informalGroups[[1]]$id
#> [1] "MVL.343"
#> 
#> [[2]]$informalGroups[[1]]$name
#> [[2]]$informalGroups[[1]]$name$fi
#> [1] "Putkilokasvit"
#> 
#> [[2]]$informalGroups[[1]]$name$sv
#> [1] "Kärlväxter"
#> 
#> [[2]]$informalGroups[[1]]$name$en
#> [1] "Vascular plants"
#> 
#> 
#> 
#> 
#> [[2]]$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: 71156
#> A data.frame [100 x 12]
#>              record_id scientific_name abundance lat_wgs84 lon_wgs84           date_time
#> 1       …JX.1315699#12   Cygnus cygnus  3         60.56739  21.57188 2021-10-03 12:00:00
#> 2        …JX.1315624#7   Cygnus cygnus  2         63.77814  23.07286 2021-10-03 12:00:00
#> 3       …JX.1315190#24   Cygnus cygnus  2         60.42794  22.20052 2021-10-02 12:00:00
#> 4  …HR.3211/96901650-U   Cygnus cygnus  1         60.20356  25.18139 2021-10-02 12:00:00
#> 5  …HR.3211/96886383-U   Cygnus cygnus  1         62.91891  28.18733 2021-10-02 12:00:00
#> 6  …HR.3211/96873463-U   Cygnus cygnus  1         61.55599  25.95057 2021-10-02 12:00:00
#> 7       …JX.1315449#15   Cygnus cygnus  6         61.32296  28.56814 2021-10-02 10:40:00
#> 8       …JX.1315165#30   Cygnus cygnus  2         61.10535  21.55759 2021-10-02 08:25:00
#> 9        …JX.1296318#3   Cygnus cygnus  26        60.83174  26.44824 2021-09-30 12:00:00
#> 10 …HR.3211/96581760-U   Cygnus cygnus  1         61.46442  23.65117 2021-09-29 12:00:00
#> ...with 90 more records and 6 more variables:
#> coordinates_uncertainty, any_issues, requires_verification, requires_identification,
#> record_reliability, record_quality

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: 26352
#> A data.frame [10 x 12]
#>              record_id scientific_name abundance lat_wgs84 lon_wgs84           date_time
#> 1        …JX.1315856#9     Cygnus olor  8         60.42794  22.20052 2021-10-04 12:00:00
#> 2       …JX.1315724#21     Cygnus olor  6         60.44906  22.76845 2021-10-03 12:00:00
#> 3       …JX.1315701#36     Cygnus olor  8         60.42794  22.20052 2021-10-03 12:00:00
#> 4       …JX.1315699#24     Cygnus olor  8         60.56739  21.57188 2021-10-03 12:00:00
#> 5       …JX.1315699#12   Cygnus cygnus  3         60.56739  21.57188 2021-10-03 12:00:00
#> 6        …JX.1315624#7   Cygnus cygnus  2         63.77814  23.07286 2021-10-03 12:00:00
#> 7       …JX.1315190#24   Cygnus cygnus  2         60.42794  22.20052 2021-10-02 12:00:00
#> 8  …HR.3211/96901650-U   Cygnus cygnus  1         60.20356  25.18139 2021-10-02 12:00:00
#> 9  …HR.3211/96873463-U   Cygnus cygnus  1         61.55599  25.95057 2021-10-02 12:00:00
#> 10 …HR.3211/96867853-U     Cygnus olor  1         60.12642  24.73924 2021-10-02 12:00:00
#> ...with 0 more records and 6 more variables:
#> coordinates_uncertainty, any_issues, requires_verification, requires_identification,
#> record_reliability, record_quality


See ?filters and vignette("v05_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: 19686186
#> A data.frame [10 x 12]
#>               record_id      scientific_name abundance lat_wgs84 lon_wgs84           date_time
#> 1         …MHU.29129341     Sturnus vulgaris  1         60.52698  21.62055 2010-05-01 12:00:00
#> 2           …JX.93743#5 Corvus corone cornix  46        62.14011  24.59989 1969-12-26 09:00:00
#> 3   …KE.67/3168115#Unit     Numenius arquata  1         63.15     27.83333 2008-06-06 13:00:00
#> 4  …KE.67/11186470#Unit  Emberiza citrinella  1         62.75622  26.6937  2017-01-17 14:00:00
#> 5       …JX.1029925#296    Turdus philomelos  1         61.43368  28.6004  1998-06-05 05:02:00
#> 6   …KE.67/3446629#Unit          Parus major  1         60.33031  25.20922 2011-03-27 17:00:00
#> 7   …KE.67/7662953#Unit   Sylvia atricapilla  1         59.83333  19.93333 1976-09-07 12:00:00
#> 8   …KE.67/7531888#Unit   Prunella modularis  1         59.83333  19.93333 1993-04-26 07:00:00
#> 9   …KE.383/1607#UNIT76 Lophophanes cristat…  3         59.9815   24.39953 1996-12-16 12:00:00
#> 10      …JX.1025345#261    Fringilla coelebs  1         62.29238  24.35626 2009-06-08 03:30:00
#> ...with 0 more records and 6 more variables:
#> coordinates_uncertainty, any_issues, requires_verification, requires_identification,
#> record_reliability, record_quality


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 caching for repeated API requests. This can be turned on or off on a per request or session basis. See ?caching for details.