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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: 60179988
#> A data.frame [10 x 12]
#>    occurrenceID       scientificName individualCount decimalLatitude decimalLongitude
#> 1           …21 Polytrichum juniper…              NA  60.17967        24.914629      
#> 2           …25 Polytrichum juniper…              NA  60.373472       24.993816      
#> 3           …29 Polytrichum juniper…              NA  61.612783       21.44191       
#> 4           …33 Polytrichum juniper…              NA  61.322069       23.513515      
#> 5           …37 Polytrichum juniper…              NA  61.249458       25.040691      
#> 6           …41 Polytrichum juniper…              NA  62.605448       25.925676      
#> 7           …45 Polytrichum juniper…              NA  62.22789        30.629365      
#> 8           …49 Polytrichum juniper…              NA  66.004079       28.202282      
#> 9           …53 Polytrichum juniper…              NA  69.049179       20.812003      
#> 10          …57 Polytrichum pilifer…              NA  60.373472       24.993816      
#> ...with 0 more records and 7 more variables:
#> eventDateTime, coordinateUncertaintyInMeters, hasIssues, requiresVerification,
#> requiresIdentification, occurrenceReliability, identificationVerificationStatus


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 Darwin Core style variable names by setting dwc = FALSE.

colnames(finbif_occurrence(dwc = FALSE))
#>  [1] "record_id"               "scientific_name"         "abundance"              
#>  [4] "lat_wgs84"               "lon_wgs84"               "date_time"              
#>  [7] "coordinates_uncertainty" "any_issues"              "requires_verification"  
#> [10] "requires_identification" "record_reliability"      "record_quality"

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: 139837
#> A data.frame [10 x 12]
#>    occurrenceID       scientificName individualCount decimalLatitude decimalLongitude
#> 1      …0745928 Cygnus cygnus (Linn…              NA  66              29.25          
#> 2      …0745932 Cygnus cygnus (Linn…              NA              NA               NA
#> 3      …0745937 Cygnus cygnus (Linn…              NA              NA               NA
#> 4      …0745941 Cygnus cygnus (Linn…              NA  60.17           25             
#> 5      …0745945 Cygnus cygnus (Linn…              NA  60.17           25             
#> 6      …0745949 Cygnus cygnus (Linn…              NA  60.17           25             
#> 7      …5552466 Cygnus cygnus (Linn…  1               67.773235       25.050461      
#> 8      …5552470 Cygnus cygnus (Linn…  4               69.063377       27.11982       
#> 9      …5552474 Cygnus cygnus (Linn…  1               68.713901       22.787894      
#> 10     …5559118 Cygnus cygnus (Linn…  3                           NA               NA
#> ...with 0 more records and 7 more variables:
#> eventDateTime, coordinateUncertaintyInMeters, hasIssues, requiresVerification,
#> requiresIdentification, occurrenceReliability, identificationVerificationStatus


Multiple taxa can be requested at once.

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

#> Records downloaded: 10
#> Records available: 203083
#> A data.frame [10 x 12]
#>    occurrenceID       scientificName individualCount decimalLatitude decimalLongitude
#> 1      …0745928 Cygnus cygnus (Linn…              NA  66              29.25          
#> 2      …0745932 Cygnus cygnus (Linn…              NA              NA               NA
#> 3      …0745937 Cygnus cygnus (Linn…              NA              NA               NA
#> 4      …0745941 Cygnus cygnus (Linn…              NA  60.17           25             
#> 5      …0745945 Cygnus cygnus (Linn…              NA  60.17           25             
#> 6      …0745949 Cygnus cygnus (Linn…              NA  60.17           25             
#> 7      …0745953 Cygnus olor (J.F. G…              NA  60.1741         24.9439        
#> 8      …0745957 Cygnus olor (J.F. G…              NA              NA               NA
#> 9      …0745961 Cygnus olor (J.F. G…              NA              NA               NA
#> 10     …5552466 Cygnus cygnus (Linn…  1               67.773235       25.050461      
#> ...with 0 more records and 7 more variables:
#> eventDateTime, coordinateUncertaintyInMeters, hasIssues, requiresVerification,
#> requiresIdentification, occurrenceReliability, identificationVerificationStatus


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")

lapply(list(birds, linnut, faglar), nrow)
#> [[1]]
#> [1] 10
#> 
#> [[2]]
#> [1] 10
#> 
#> [[3]]
#> [1] 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: 60182673
#> A data.frame [1001 x 12]
#>    occurrenceID       scientificName individualCount decimalLatitude decimalLongitude
#> 1           …21 Polytrichum juniper…              NA  60.17967        24.914629      
#> 2           …25 Polytrichum juniper…              NA  60.373472       24.993816      
#> 3           …29 Polytrichum juniper…              NA  61.612783       21.44191       
#> 4           …33 Polytrichum juniper…              NA  61.322069       23.513515      
#> 5           …37 Polytrichum juniper…              NA  61.249458       25.040691      
#> 6           …41 Polytrichum juniper…              NA  62.605448       25.925676      
#> 7           …45 Polytrichum juniper…              NA  62.22789        30.629365      
#> 8           …49 Polytrichum juniper…              NA  66.004079       28.202282      
#> 9           …53 Polytrichum juniper…              NA  69.049179       20.812003      
#> 10          …57 Polytrichum pilifer…              NA  60.373472       24.993816      
#> ...with 991 more records and 7 more variables:
#> eventDateTime, coordinateUncertaintyInMeters, hasIssues, requiresVerification,
#> requiresIdentification, occurrenceReliability, identificationVerificationStatus


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] 60182646

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: 8107
#> A data.frame [10 x 12]
#>    occurrenceID       scientificName individualCount decimalLatitude decimalLongitude
#> 1       …223360 Vulpes vulpes var. …              NA  56              160            
#> 2       …223410 Vulpes vulpes (Linn…              NA  42.87           76.72          
#> 3       …227292 Vulpes vulpes subsp…              NA              NA               NA
#> 4       …227296 Vulpes vulpes (Linn…              NA  58.7            13.83          
#> 5       …579385 Vulpes vulpes (Linn…              NA  61.13           25.77          
#> 6       …580318 Vulpes vulpes (Linn…              NA  59.931          23.706         
#> 7       …580322 Vulpes vulpes (Linn…              NA              NA               NA
#> 8       …580326 Vulpes vulpes (Linn…              NA              NA               NA
#> 9       …580330 Vulpes vulpes (Linn…              NA              NA               NA
#> 10      …580334 Vulpes vulpes (Linn…              NA  69              27.5           
#> ...with 0 more records and 7 more variables:
#> eventDateTime, coordinateUncertaintyInMeters, hasIssues, requiresVerification,
#> requiresIdentification, occurrenceReliability, identificationVerificationStatus


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: 8107
#> A data.frame [10 x 12]
#>    occurrenceID       scientificName individualCount decimalLatitude decimalLongitude
#> 1       …223360 Vulpes vulpes var. …              NA  56              160            
#> 2       …223410 Vulpes vulpes (Linn…              NA  42.87           76.72          
#> 3       …227292 Vulpes vulpes subsp…              NA              NA               NA
#> 4       …227296 Vulpes vulpes (Linn…              NA  58.7            13.83          
#> 5       …579385 Vulpes vulpes (Linn…              NA  61.13           25.77          
#> 6       …580318 Vulpes vulpes (Linn…              NA  59.931          23.706         
#> 7       …580322 Vulpes vulpes (Linn…              NA              NA               NA
#> 8       …580326 Vulpes vulpes (Linn…              NA              NA               NA
#> 9       …580330 Vulpes vulpes (Linn…              NA              NA               NA
#> 10      …580334 Vulpes vulpes (Linn…              NA  69              27.5           
#> ...with 0 more records and 7 more variables:
#> eventDateTime, coordinateUncertaintyInMeters, hasIssues, requiresVerification,
#> requiresIdentification, occurrenceReliability, identificationVerificationStatus


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 = "finnishCounty", aggregate = "species"
)
Click to show/hide output.

#> Records downloaded: 10
#> Records available: 309
#> A data.frame [10 x 2]
#>    finnishCounty n_species
#> 1      Raasepori  2078    
#> 2      Virolahti  2037    
#> 3       Rääkkylä  1396    
#> 4        Kouvola  1578    
#> 5    Kemiönsaari  2042    
#> 6          Hanko  1994    
#> 7       Parainen  1922    
#> 8       Helsinki  2069    
#> 9         Kuopio  1445    
#> 10         Turku  1827    


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 = "-eventDateTime")
Click to show/hide output.

#> Records downloaded: 10
#> Records available: 60179991
#> A data.frame [10 x 11]
#>    occurrenceID       scientificName individualCount decimalLatitude decimalLongitude
#> 1           …21 Polytrichum juniper…              NA  60.17967        24.914629      
#> 2           …25 Polytrichum juniper…              NA  60.373472       24.993816      
#> 3           …29 Polytrichum juniper…              NA  61.612783       21.44191       
#> 4           …33 Polytrichum juniper…              NA  61.322069       23.513515      
#> 5           …37 Polytrichum juniper…              NA  61.249458       25.040691      
#> 6           …41 Polytrichum juniper…              NA  62.605448       25.925676      
#> 7           …45 Polytrichum juniper…              NA  62.22789        30.629365      
#> 8           …49 Polytrichum juniper…              NA  66.004079       28.202282      
#> 9           …53 Polytrichum juniper…              NA  69.049179       20.812003      
#> 10          …57 Polytrichum pilifer…              NA  60.373472       24.993816      
#> ...with 0 more records and 6 more variables:
#> coordinateUncertaintyInMeters, hasIssues, requiresVerification, requiresIdentification,
#> occurrenceReliability, identificationVerificationStatus


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: 60179988
#> A data.frame [10 x 12]
#>    occurrenceID       scientificName individualCount decimalLatitude decimalLongitude
#> 1           …21 Polytrichum juniper…              NA  60.17967        24.914629      
#> 2           …25 Polytrichum juniper…              NA  60.373472       24.993816      
#> 3           …29 Polytrichum juniper…              NA  61.612783       21.44191       
#> 4           …33 Polytrichum juniper…              NA  61.322069       23.513515      
#> 5           …37 Polytrichum juniper…              NA  61.249458       25.040691      
#> 6           …41 Polytrichum juniper…              NA  62.605448       25.925676      
#> 7           …45 Polytrichum juniper…              NA  62.22789        30.629365      
#> 8           …49 Polytrichum juniper…              NA  66.004079       28.202282      
#> 9           …53 Polytrichum juniper…              NA  69.049179       20.812003      
#> 10          …57 Polytrichum pilifer…              NA  60.373472       24.993816      
#> ...with 0 more records and 7 more variables:
#> eventDateTime, coordinateUncertaintyInMeters, hasIssues, requiresVerification,
#> requiresIdentification, occurrenceReliability, identificationVerificationStatus


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: 60179988
#> A data.frame [10 x 12]
#>    occurrenceID       scientificName individualCount decimalLatitude decimalLongitude
#> 1           …21 Polytrichum juniper…              NA  60.17967        24.914629      
#> 2           …25 Polytrichum juniper…              NA  60.373472       24.993816      
#> 3           …29 Polytrichum juniper…              NA  61.612783       21.44191       
#> 4           …33 Polytrichum juniper…              NA  61.322069       23.513515      
#> 5           …37 Polytrichum juniper…              NA  61.249458       25.040691      
#> 6           …41 Polytrichum juniper…              NA  62.605448       25.925676      
#> 7           …45 Polytrichum juniper…              NA  62.22789        30.629365      
#> 8           …49 Polytrichum juniper…              NA  66.004079       28.202282      
#> 9           …53 Polytrichum juniper…              NA  69.049179       20.812003      
#> 10          …57 Polytrichum pilifer…              NA  60.373472       24.993816      
#> ...with 0 more records and 7 more variables:
#> eventDateTime, coordinateUncertaintyInMeters, hasIssues, requiresVerification,
#> requiresIdentification, occurrenceReliability, identificationVerificationStatus


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.