Occurrence records from FinBIF

William K. Morris

The core purpose of {finbif} is accessing occurrence data stored in the FinBIF database. Occurrence data can be retrieved from FinBIF with the function finbif_occurrence(). Without any arguments specified finbif_occurrence() will retrieve the latest 10 occurrence records from FinBIF.

finbif_occurrence()
Click to show/hide output.

#> Records downloaded: 10
#> Records available: 40410386
#> A data.frame [10 x 12]
#>               record_id      scientific_name abundance lat_wgs84 lon_wgs84           date_time
#> 1        …JX.1315966#18             Trametes  1         65.08865  25.45157 2021-10-05 12:00:00
#> 2         …JX.1315966#9 Trichaptum fuscovio…  1         65.08865  25.45157 2021-10-05 12:00:00
#> 3        …JX.1315966#15                Fungi  1         65.08865  25.45157 2021-10-05 12:00:00
#> 4        …JX.1315966#12                Fungi  1         65.08865  25.45157 2021-10-05 12:00:00
#> 5         …JX.1315966#3  Lycogala epidendrum  1         65.08865  25.45157 2021-10-05 12:00:00
#> 6         …JX.1315966#6 Stereum sanguinolen…  1         65.08865  25.45157 2021-10-05 12:00:00
#> 7  …KE.176/615c07e7d5d…   Acherontia atropos  1         60.11016  25.01864 2021-10-05 12:00:00
#> 8         …JX.1315969#3      Rana temporaria  1         62.48525  21.75467 2021-10-05 12:00:00
#> 9        …JX.1315960#15   Puccinia absinthii  1         62.25399  25.71361 2021-10-05 12:00:00
#> 10        …JX.1315960#7    Puccinia tanaceti  1         62.2528   25.71456 2021-10-05 12:00:00
#> ...with 0 more records and 6 more variables:
#> coordinates_uncertainty, any_issues, requires_verification, requires_identification,
#> record_reliability, record_quality


The print method for the resulting finbif_occ object will display the number of records downloaded, the total number of records available, a data summary including up to 10 rows of some core record variables (when available), the number of remaining records and variables, as well as the names of additional variables.

Darwin Core Variables

You can switch from the default variable names to Darwin Core style names by setting dwc = TRUE.

colnames(finbif_occurrence(dwc = TRUE))
#>  [1] "occurrenceID"                  "scientificName"                "individualCount"              
#>  [4] "decimalLatitude"               "decimalLongitude"              "eventDateTime"                
#>  [7] "coordinateUncertaintyInMeters" "hasIssues"                     "requiresVerification"         
#> [10] "requiresIdentification"        "occurrenceReliability"         "occurrenceQuality"

The functions to_dwc() and to_native() can be used to translate variable names to and from Darwin Core style and {finbif}’s native variable names style.

Choosing taxa

You can limit the records to certain taxa by specifying them as an argument.

finbif_occurrence("Cygnus cygnus")
Click to show/hide output.

#> Records downloaded: 10
#> Records available: 71156
#> A data.frame [10 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 0 more records and 6 more variables:
#> coordinates_uncertainty, any_issues, requires_verification, requires_identification,
#> record_reliability, record_quality


Multiple taxa can be requested at once.

finbif_occurrence("Cygnus cygnus", "Cygnus olor")
Click to show/hide output.

#> Records downloaded: 10
#> Records available: 101999
#> 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.3211/96886383-U   Cygnus cygnus  1         62.91891  28.18733 2021-10-02 12:00:00
#> 10 …HR.3211/96873463-U   Cygnus cygnus  1         61.55599  25.95057 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


You can also chose higher taxonomic groups and use common names (in English, Finnish and Swedish).

birds  <- finbif_occurrence("Birds")
linnut <- finbif_occurrence("Linnut")
faglar <- finbif_occurrence("Fåglar")

sapply(list(birds, linnut, faglar), nrow)
#> [1] 10 10 10

Request size

You can increase the number of records returned by using the n argument.

finbif_occurrence(n = 1001)
Click to show/hide output.

#> Records downloaded: 1001
#> Records available: 40410386
#> A data.frame [1001 x 12]
#>    record_id      scientific_name abundance lat_wgs84 lon_wgs84           date_time
#> 1      …50#3 Exechiopsis fimbria…  1         65.01504  25.52607 2021-10-05 12:00:00
#> 2     …29#12 Depressaria badiella  1         62.92172  27.63335 2021-10-05 12:00:00
#> 3     …29#15 Depressaria daucella  1         62.92172  27.63335 2021-10-05 12:00:00
#> 4      …29#9   Epirrita autumnata  1         62.92172  27.63335 2021-10-05 12:00:00
#> 5      …29#6  Poecilocampa populi  1         62.92172  27.63335 2021-10-05 12:00:00
#> 6      …29#3      Xestia c-nigrum  1         62.92172  27.63335 2021-10-05 12:00:00
#> 7     …31#18 Agriopis aurantiaria  1         60.4528   22.40844 2021-10-04 12:00:00
#> 8      …31#3     Autographa gamma  1         60.4528   22.40844 2021-10-04 12:00:00
#> 9     …31#12 Chloroclysta sitera…  1         60.4528   22.40844 2021-10-04 12:00:00
#> 10    …31#15   Epirrita autumnata  1         60.4528   22.40844 2021-10-04 12:00:00
#> ...with 991 more records and 6 more variables:
#> coordinates_uncertainty, any_issues, requires_verification, requires_identification,
#> record_reliability, record_quality


You can see how many records are available for a given request, without retrieving any records, by setting count_only = TRUE.

finbif_occurrence(count_only = TRUE)
#> [1] 40410386

Checking taxa

When you request occurrence records for specific taxa, by default, the taxon names are first checked against the FinBIF database. If any of the requested taxa are not found in the database you will receive a warning but the data will still be retrieved for the remaining taxa.

finbif_occurrence("Vulpes vulpes", "Moomin")
Click to show/hide output.

#> Records downloaded: 10
#> Records available: 4238
#> A data.frame [10 x 12]
#>               record_id scientific_name abundance lat_wgs84 lon_wgs84           date_time
#> 1         …JX.1315490#3   Vulpes vulpes  1         65.05719  25.62634 2021-10-02 12:00:00
#> 2  …KE.176/6154c070d5d…   Vulpes vulpes  1         60.20882  24.90362 2021-09-29 12:00:00
#> 3         …JX.1294654#3   Vulpes vulpes  1         60.83805  21.37382 2021-09-24 05:30:00
#> 4   …HR.3211/95828765-U   Vulpes vulpes  1         60.76014  24.91448 2021-09-23 12:00:00
#> 5  …KE.176/614e5d42d5d…   Vulpes vulpes  1         60.11016  25.01864 2021-09-22 12:00:00
#> 6  …KE.176/614abfb4d5d…   Vulpes vulpes  1         60.13192  24.72079 2021-09-22 12:00:00
#> 7         …JX.1293417#7   Vulpes vulpes  1         60.82366  21.2978  2021-09-20 05:30:00
#> 8   …HR.3211/95510814-U   Vulpes vulpes  1         60.5      21.9     2021-09-19 12:00:00
#> 9       …JX.1293110#126   Vulpes vulpes  1         62.57362  28.58553 2021-09-18 12:00:00
#> 10      …JX.1272497#417   Vulpes vulpes  1         64.50244  29.98219 2021-09-17 12:00:00
#> ...with 0 more records and 6 more variables:
#> coordinates_uncertainty, any_issues, requires_verification, requires_identification,
#> record_reliability, record_quality


You can turn off taxon name pre-checking by setting the value of the check_taxa argument to FALSE.

finbif_occurrence("Vulpes vulpes", "Moomin", check_taxa = FALSE)
Click to show/hide output.

#> Records downloaded: 10
#> Records available: 4238
#> A data.frame [10 x 12]
#>               record_id scientific_name abundance lat_wgs84 lon_wgs84           date_time
#> 1         …JX.1315490#3   Vulpes vulpes  1         65.05719  25.62634 2021-10-02 12:00:00
#> 2  …KE.176/6154c070d5d…   Vulpes vulpes  1         60.20882  24.90362 2021-09-29 12:00:00
#> 3         …JX.1294654#3   Vulpes vulpes  1         60.83805  21.37382 2021-09-24 05:30:00
#> 4   …HR.3211/95828765-U   Vulpes vulpes  1         60.76014  24.91448 2021-09-23 12:00:00
#> 5  …KE.176/614e5d42d5d…   Vulpes vulpes  1         60.11016  25.01864 2021-09-22 12:00:00
#> 6  …KE.176/614abfb4d5d…   Vulpes vulpes  1         60.13192  24.72079 2021-09-22 12:00:00
#> 7         …JX.1293417#7   Vulpes vulpes  1         60.82366  21.2978  2021-09-20 05:30:00
#> 8   …HR.3211/95510814-U   Vulpes vulpes  1         60.5      21.9     2021-09-19 12:00:00
#> 9       …JX.1293110#126   Vulpes vulpes  1         62.57362  28.58553 2021-09-18 12:00:00
#> 10      …JX.1272497#417   Vulpes vulpes  1         64.50244  29.98219 2021-09-17 12:00:00
#> ...with 0 more records and 6 more variables:
#> coordinates_uncertainty, any_issues, requires_verification, requires_identification,
#> record_reliability, record_quality


By setting the argument, on_check_fail to "error" (the default is "warn"), you can elevate the warnings to errors and the request will fail if any of the taxa are not found in the FinBIF database.

finbif_occurrence("Vulpes vulpes", "Moomin", on_check_fail = "error")
#> Error: Cannot find taxa: Moomin

This can be a useful strategy if you are using {finbif} non-interactively (in a script), and you do not want to proceed if any of your taxon names are wrong or misspelled.

Aggregating records

You can request records in aggregate using the aggregate argument to finbif_occurrence. Aggregated requests will return counts for the combination of the variables you specify with the select argument. You can request counts of "records", "species" or "taxa" by using the corresponding string as the value for the aggregate argument. Aggregating by "species" will count the number of unique species identifiers for a set of records grouped by the combination of selected variables. Note that this count will not include records of taxa that do not have species identifiers, including records of higher taxa (e.g., genus only records), records of the non-species children of aggregate or complex taxa, and hybrid taxa. Therefore, in some contexts the results returned will be an underestimate of species richness. Likewise, aggregating by "taxa", which returns a count the number of unique taxon identifiers, could represent an overestimate of the number of taxa as records of higher taxa will contribute to the count while their true identify may be a duplicate of other records.

To illustrate, you can count the number of moths and butterflies by municipality with the following:

finbif_occurrence("Lepidoptera", select = "municipality", aggregate = "species")
Click to show/hide output.

#> Records downloaded: 10
#> Records available: 317
#> A data.frame [10 x 2]
#>    municipality n_species
#> 1       Kouvola      1328
#> 2     Virolahti      1932
#> 3      Rääkkylä      1346
#> 4   Kemiönsaari      1963
#> 5      Parainen      1765
#> 6         Hanko      1895
#> 7      Helsinki      1937
#> 8     Raasepori      1860
#> 9         Kotka      1635
#> 10       Kuopio      1319


Time & duration

The default behaviour of finbif_occurrence is to consolidate date and time data for occurrence recording events into a date_time variable. This can be turned off (which can speed up data processing time) by deselecting the date_time variable.

finbif_occurrence(select = "-date_time")
Click to show/hide output.

#> Records downloaded: 10
#> Records available: 40410386
#> A data.frame [10 x 11]
#>               record_id      scientific_name abundance lat_wgs84 lon_wgs84 coordinates_uncertainty
#> 1        …JX.1315966#18             Trametes  1         65.08865  25.45157  1                     
#> 2         …JX.1315966#9 Trichaptum fuscovio…  1         65.08865  25.45157  1                     
#> 3        …JX.1315966#15                Fungi  1         65.08865  25.45157  1                     
#> 4        …JX.1315966#12                Fungi  1         65.08865  25.45157  1                     
#> 5         …JX.1315966#3  Lycogala epidendrum  1         65.08865  25.45157  1                     
#> 6         …JX.1315966#6 Stereum sanguinolen…  1         65.08865  25.45157  1                     
#> 7  …KE.176/615c07e7d5d…   Acherontia atropos  1         60.11016  25.01864  50000                 
#> 8         …JX.1315969#3      Rana temporaria  1         62.48525  21.75467  1                     
#> 9        …JX.1315960#15   Puccinia absinthii  1         62.25399  25.71361  1                     
#> 10        …JX.1315960#7    Puccinia tanaceti  1         62.2528   25.71456  1                     
#> ...with 0 more records and 5 more variables:
#> any_issues, requires_verification, requires_identification, record_reliability, record_quality


Timezone

Timezone input

The FinBIF database doesn’t currently store timezone information, so {finbif} makes assumptions about the appropriate timezone based on the time and location of the occurrence recording events to calculate date_time and duration. By default, a fast heuristic is used to determine the timezones. If you require greater accuracy (e.g., you are using data on the Finnish/Swedish border and daytime/nighttime hours are important), you can switch to more accurate, though slower, timezone calculation method.

finbif_occurrence(date_time_method = "accurate")
Click to show/hide output.

#> Records downloaded: 10
#> Records available: 40410386
#> A data.frame [10 x 12]
#>               record_id      scientific_name abundance lat_wgs84 lon_wgs84           date_time
#> 1        …JX.1315966#18             Trametes  1         65.08865  25.45157 2021-10-05 12:00:00
#> 2         …JX.1315966#9 Trichaptum fuscovio…  1         65.08865  25.45157 2021-10-05 12:00:00
#> 3        …JX.1315966#15                Fungi  1         65.08865  25.45157 2021-10-05 12:00:00
#> 4        …JX.1315966#12                Fungi  1         65.08865  25.45157 2021-10-05 12:00:00
#> 5         …JX.1315966#3  Lycogala epidendrum  1         65.08865  25.45157 2021-10-05 12:00:00
#> 6         …JX.1315966#6 Stereum sanguinolen…  1         65.08865  25.45157 2021-10-05 12:00:00
#> 7  …KE.176/615c07e7d5d…   Acherontia atropos  1         60.11016  25.01864 2021-10-05 12:00:00
#> 8         …JX.1315969#3      Rana temporaria  1         62.48525  21.75467 2021-10-05 12:00:00
#> 9        …JX.1315960#15   Puccinia absinthii  1         62.25399  25.71361 2021-10-05 12:00:00
#> 10        …JX.1315960#7    Puccinia tanaceti  1         62.2528   25.71456 2021-10-05 12:00:00
#> ...with 0 more records and 6 more variables:
#> coordinates_uncertainty, any_issues, requires_verification, requires_identification,
#> record_reliability, record_quality


Timezone output

The timezone of the calculated date_time variable is determined by the timezone of your operating system.

Sys.timezone()

You can override this by setting the tzone argument to a different value.

finbif_occurrence(tzone = "Etc/UTC")
Click to show/hide output.

#> Records downloaded: 10
#> Records available: 40410386
#> A data.frame [10 x 12]
#>               record_id      scientific_name abundance lat_wgs84 lon_wgs84           date_time
#> 1        …JX.1315966#18             Trametes  1         65.08865  25.45157 2021-10-05 09:00:00
#> 2         …JX.1315966#9 Trichaptum fuscovio…  1         65.08865  25.45157 2021-10-05 09:00:00
#> 3        …JX.1315966#15                Fungi  1         65.08865  25.45157 2021-10-05 09:00:00
#> 4        …JX.1315966#12                Fungi  1         65.08865  25.45157 2021-10-05 09:00:00
#> 5         …JX.1315966#3  Lycogala epidendrum  1         65.08865  25.45157 2021-10-05 09:00:00
#> 6         …JX.1315966#6 Stereum sanguinolen…  1         65.08865  25.45157 2021-10-05 09:00:00
#> 7  …KE.176/615c07e7d5d…   Acherontia atropos  1         60.11016  25.01864 2021-10-05 09:00:00
#> 8         …JX.1315969#3      Rana temporaria  1         62.48525  21.75467 2021-10-05 09:00:00
#> 9        …JX.1315960#15   Puccinia absinthii  1         62.25399  25.71361 2021-10-05 09:00:00
#> 10        …JX.1315960#7    Puccinia tanaceti  1         62.2528   25.71456 2021-10-05 09:00:00
#> ...with 0 more records and 6 more variables:
#> coordinates_uncertainty, any_issues, requires_verification, requires_identification,
#> record_reliability, record_quality


Or set the global timezone option to set the timezone for the current session.

options(finbif_tz = "Etc/UTC")

This may be advisable for reproducibility or when working with multiple systems.