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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.

Click to show/hide output.

#> Records downloaded: 10
#> Records available: 47159747
#> A data.frame [10 x 12]
#>                                 record_id      scientific_name abundance lat_wgs84 lon_wgs84
#> 1  …KE.176/64895825d5de884fa20e297d#Unit1 Heracleum persicum …        NA  61.08302  22.38983
#> 2                           …JX.1594382#9 Hirundo rustica Lin…        NA  64.12716  23.99111
#> 3                          …JX.1594382#37 Pica pica (Linnaeus…        NA  64.12716  23.99111
#> 4                          …JX.1594382#49 Muscicapa striata (…        NA  64.12716  23.99111
#> 5                          …JX.1594382#39 Larus canus Linnaeu…        NA  64.12716  23.99111
#> 6                           …JX.1594382#5 Emberiza citrinella…        NA  64.12716  23.99111
#> 7                          …JX.1594382#31 Ficedula hypoleuca …        NA  64.12716  23.99111
#> 8                          …JX.1594382#41 Alauda arvensis Lin…        NA  64.12716  23.99111
#> 9                          …JX.1594382#21 Numenius arquata (L…        NA  64.12716  23.99111
#> 10                         …JX.1594382#29 Dendrocopos major (…        NA  64.12716  23.99111
#> ...with 0 more record and 7 more variables:
#> date_time, 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: 95730
#> A data.frame [10 x 12]
#>                   record_id      scientific_name abundance lat_wgs84 lon_wgs84           date_time
#> 1            …JX.1594164#13 Cygnus cygnus (Linn…        NA  64.94473  26.67958 2023-06-13 14:33:00
#> 2  …HR.4412/6489172c9ddda_U Cygnus cygnus (Linn…        NA  61.74701  23.11493 2023-06-13 12:00:00
#> 3  …HR.4412/64891730060a4_U Cygnus cygnus (Linn…        NA  61.38348  22.97288 2023-06-13 12:00:00
#> 4  …HR.4412/648917378a3b6_U Cygnus cygnus (Linn…        NA  62.76028  24.15774 2023-06-13 12:00:00
#> 5  …HR.4412/6489175adc05f_U Cygnus cygnus (Linn…        NA  60.78752  21.39263 2023-06-13 12:00:00
#> 6  …HR.4412/6489173a1db9b_U Cygnus cygnus (Linn…        NA  64.31374  26.68643 2023-06-13 12:00:00
#> 7  …HR.4412/648917456a396_U Cygnus cygnus (Linn…        NA  61.87986  25.19067 2023-06-13 12:00:00
#> 8  …HR.4412/648917454912b_U Cygnus cygnus (Linn…        NA  60.42215  24.00099 2023-06-13 12:00:00
#> 9  …HR.4412/64891750e74e7_U Cygnus cygnus (Linn…        NA  63.86383  27.70835 2023-06-13 12:00:00
#> 10 …HR.4412/64891741330f8_U Cygnus cygnus (Linn…        NA  61.74701  23.11493 2023-06-13 12:00:00
#> ...with 0 more record 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: 138681
#> A data.frame [10 x 12]
#>                   record_id      scientific_name abundance lat_wgs84 lon_wgs84           date_time
#> 1            …JX.1594164#13 Cygnus cygnus (Linn…        NA  64.94473  26.67958 2023-06-13 14:33:00
#> 2  …HR.4412/6489172c9ddda_U Cygnus cygnus (Linn…        NA  61.74701  23.11493 2023-06-13 12:00:00
#> 3  …HR.4412/64891730060a4_U Cygnus cygnus (Linn…        NA  61.38348  22.97288 2023-06-13 12:00:00
#> 4  …HR.4412/648917378a3b6_U Cygnus cygnus (Linn…        NA  62.76028  24.15774 2023-06-13 12:00:00
#> 5  …HR.4412/64891759be4c7_U Cygnus olor (J.F. G…        NA  63.40045  21.48901 2023-06-13 12:00:00
#> 6  …HR.4412/6489175adc05f_U Cygnus cygnus (Linn…        NA  60.78752  21.39263 2023-06-13 12:00:00
#> 7  …HR.4412/6489173a1db9b_U Cygnus cygnus (Linn…        NA  64.31374  26.68643 2023-06-13 12:00:00
#> 8  …HR.4412/648917456a396_U Cygnus cygnus (Linn…        NA  61.87986  25.19067 2023-06-13 12:00:00
#> 9  …HR.4412/648917454912b_U Cygnus cygnus (Linn…        NA  60.42215  24.00099 2023-06-13 12:00:00
#> 10 …HR.4412/64891750e74e7_U Cygnus cygnus (Linn…        NA  63.86383  27.70835 2023-06-13 12:00:00
#> ...with 0 more record 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.

Click to show/hide output.

#> Records downloaded: 1001
#> Records available: 47159747
#> A data.frame [1001 x 12]
#>                                 record_id      scientific_name abundance lat_wgs84 lon_wgs84
#> 1  …KE.176/64895825d5de884fa20e297d#Unit1 Heracleum persicum …        NA  61.08302  22.38983
#> 2                           …JX.1594382#9 Hirundo rustica Lin…        NA  64.12716  23.99111
#> 3                          …JX.1594382#37 Pica pica (Linnaeus…        NA  64.12716  23.99111
#> 4                          …JX.1594382#49 Muscicapa striata (…        NA  64.12716  23.99111
#> 5                          …JX.1594382#39 Larus canus Linnaeu…        NA  64.12716  23.99111
#> 6                           …JX.1594382#5 Emberiza citrinella…        NA  64.12716  23.99111
#> 7                          …JX.1594382#31 Ficedula hypoleuca …        NA  64.12716  23.99111
#> 8                          …JX.1594382#41 Alauda arvensis Lin…        NA  64.12716  23.99111
#> 9                          …JX.1594382#21 Numenius arquata (L…        NA  64.12716  23.99111
#> 10                         …JX.1594382#29 Dendrocopos major (…        NA  64.12716  23.99111
#> ...with 991 more records and 7 more variables:
#> date_time, 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] 47159747

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: 5303
#> A data.frame [10 x 12]
#>                                 record_id      scientific_name abundance lat_wgs84 lon_wgs84
#> 1                    …HR.3211/167313561-U Vulpes vulpes (Linn…        NA  60.18049  25.04838
#> 2                    …HR.3211/167310567-U Vulpes vulpes (Linn…        NA  60.2241   24.89373
#> 3  …KE.176/64894ccdd5de884fa20e2972#Unit1 Vulpes vulpes (Linn…  1         60.21118  24.90744
#> 4  …KE.176/6489506dd5de884fa20e2976#Unit1 Vulpes vulpes (Linn…  1         60.11016  25.01864
#> 5  …KE.176/648802d6d5de884fa20e290d#Unit1 Vulpes vulpes (Linn…  1         60.11016  25.01864
#> 6  …KE.176/648802c7d5de884fa20e290c#Unit1 Vulpes vulpes (Linn…  1         60.11016  25.01864
#> 7                    …HR.3211/167167234-U Vulpes vulpes (Linn…        NA  60.20261  24.86879
#> 8                    …HR.3211/166968734-U Vulpes vulpes (Linn…        NA  60.5      21.9    
#> 9                    …HR.3211/166944731-U Vulpes vulpes (Linn…        NA  60.17493  24.74123
#> 10 …KE.176/64869a52d5de884fa20e28ae#Unit1 Vulpes vulpes (Linn…  1         60.23885  25.12012
#> ...with 0 more record and 7 more variables:
#> date_time, 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: 5303
#> A data.frame [10 x 12]
#>                                 record_id      scientific_name abundance lat_wgs84 lon_wgs84
#> 1                    …HR.3211/167313561-U Vulpes vulpes (Linn…        NA  60.18049  25.04838
#> 2                    …HR.3211/167310567-U Vulpes vulpes (Linn…        NA  60.2241   24.89373
#> 3  …KE.176/64894ccdd5de884fa20e2972#Unit1 Vulpes vulpes (Linn…  1         60.21118  24.90744
#> 4  …KE.176/6489506dd5de884fa20e2976#Unit1 Vulpes vulpes (Linn…  1         60.11016  25.01864
#> 5  …KE.176/648802d6d5de884fa20e290d#Unit1 Vulpes vulpes (Linn…  1         60.11016  25.01864
#> 6  …KE.176/648802c7d5de884fa20e290c#Unit1 Vulpes vulpes (Linn…  1         60.11016  25.01864
#> 7                    …HR.3211/167167234-U Vulpes vulpes (Linn…        NA  60.20261  24.86879
#> 8                    …HR.3211/166968734-U Vulpes vulpes (Linn…        NA  60.5      21.9    
#> 9                    …HR.3211/166944731-U Vulpes vulpes (Linn…        NA  60.17493  24.74123
#> 10 …KE.176/64869a52d5de884fa20e28ae#Unit1 Vulpes vulpes (Linn…  1         60.23885  25.12012
#> ...with 0 more record and 7 more variables:
#> date_time, 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 the following taxa in the FinBIF taxonomy.
#> Please check you are using accepted names and not synonyms or
#> other names for the taxa you are selecting:
#> 
#> 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: 309
#> A data.frame [10 x 2]
#>    municipality n_species
#> 1     Raasepori  2038    
#> 2     Virolahti  1978    
#> 3       Kouvola  1508    
#> 4      Rääkkylä  1367    
#> 5   Kemiönsaari  2008    
#> 6         Hanko  1945    
#> 7      Parainen  1858    
#> 8      Helsinki  1980    
#> 9        Kuopio  1345    
#> 10        Kotka  1719    


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: 47159747
#> A data.frame [10 x 11]
#>                                 record_id      scientific_name abundance lat_wgs84 lon_wgs84
#> 1  …KE.176/64895825d5de884fa20e297d#Unit1 Heracleum persicum …        NA  61.08302  22.38983
#> 2                           …JX.1594382#9 Hirundo rustica Lin…        NA  64.12716  23.99111
#> 3                          …JX.1594382#37 Pica pica (Linnaeus…        NA  64.12716  23.99111
#> 4                          …JX.1594382#49 Muscicapa striata (…        NA  64.12716  23.99111
#> 5                          …JX.1594382#39 Larus canus Linnaeu…        NA  64.12716  23.99111
#> 6                           …JX.1594382#5 Emberiza citrinella…        NA  64.12716  23.99111
#> 7                          …JX.1594382#31 Ficedula hypoleuca …        NA  64.12716  23.99111
#> 8                          …JX.1594382#41 Alauda arvensis Lin…        NA  64.12716  23.99111
#> 9                          …JX.1594382#21 Numenius arquata (L…        NA  64.12716  23.99111
#> 10                         …JX.1594382#29 Dendrocopos major (…        NA  64.12716  23.99111
#> ...with 0 more record and 6 more variables:
#> coordinates_uncertainty, 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: 47159747
#> A data.frame [10 x 12]
#>                                 record_id      scientific_name abundance lat_wgs84 lon_wgs84
#> 1  …KE.176/64895825d5de884fa20e297d#Unit1 Heracleum persicum …        NA  61.08302  22.38983
#> 2                           …JX.1594382#9 Hirundo rustica Lin…        NA  64.12716  23.99111
#> 3                          …JX.1594382#37 Pica pica (Linnaeus…        NA  64.12716  23.99111
#> 4                          …JX.1594382#49 Muscicapa striata (…        NA  64.12716  23.99111
#> 5                          …JX.1594382#39 Larus canus Linnaeu…        NA  64.12716  23.99111
#> 6                           …JX.1594382#5 Emberiza citrinella…        NA  64.12716  23.99111
#> 7                          …JX.1594382#31 Ficedula hypoleuca …        NA  64.12716  23.99111
#> 8                          …JX.1594382#41 Alauda arvensis Lin…        NA  64.12716  23.99111
#> 9                          …JX.1594382#21 Numenius arquata (L…        NA  64.12716  23.99111
#> 10                         …JX.1594382#29 Dendrocopos major (…        NA  64.12716  23.99111
#> ...with 0 more record and 7 more variables:
#> date_time, 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.

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: 47159747
#> A data.frame [10 x 12]
#>                                 record_id      scientific_name abundance lat_wgs84 lon_wgs84
#> 1  …KE.176/64895825d5de884fa20e297d#Unit1 Heracleum persicum …        NA  61.08302  22.38983
#> 2                           …JX.1594382#9 Hirundo rustica Lin…        NA  64.12716  23.99111
#> 3                          …JX.1594382#37 Pica pica (Linnaeus…        NA  64.12716  23.99111
#> 4                          …JX.1594382#49 Muscicapa striata (…        NA  64.12716  23.99111
#> 5                          …JX.1594382#39 Larus canus Linnaeu…        NA  64.12716  23.99111
#> 6                           …JX.1594382#5 Emberiza citrinella…        NA  64.12716  23.99111
#> 7                          …JX.1594382#31 Ficedula hypoleuca …        NA  64.12716  23.99111
#> 8                          …JX.1594382#41 Alauda arvensis Lin…        NA  64.12716  23.99111
#> 9                          …JX.1594382#21 Numenius arquata (L…        NA  64.12716  23.99111
#> 10                         …JX.1594382#29 Dendrocopos major (…        NA  64.12716  23.99111
#> ...with 0 more record and 7 more variables:
#> date_time, 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.