Filtering occurrence records
William K. Morris
Source:vignettes/v05_filtering.Rmd
v05_filtering.RmdWhen getting records from FinBIF there are many options for filtering
the data before it is downloaded, saving bandwidth and local
post-processing time. For the full list of filtering options see
?filters.
Location
Records can be filtered by the name of a location.
finbif_occurrence(filter = c(country = "Finland"))
#> Records downloaded: 10
#> Records available: 57360604
#> 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, identificationVerificationStatusOr by a set of coordinates.
finbif_occurrence(
filter = list(coordinates = list(c(60, 68), c(20, 30), "wgs84"))
)
#> Records downloaded: 10
#> Records available: 48564194
#> 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 …49 Polytrichum juniper… NA 66.004079 28.202282
#> 8 …57 Polytrichum pilifer… NA 60.373472 24.993816
#> 9 …61 Polytrichum pilifer… NA 61.599004 21.434943
#> 10 …65 Polytrichum pilifer… NA 61.452593 24.099408
#> ...with 0 more records and 7 more variables:
#> eventDateTime, coordinateUncertaintyInMeters, hasIssues, requiresVerification,
#> requiresIdentification, occurrenceReliability, identificationVerificationStatusSee ?filters section “Location” for more details
Time
The event or import date of records can be used to filter occurrence data from FinBIF. The date filters can be a single year, month or date,
finbif_occurrence(filter = list(date_range_ym = "2020-12"))Click to show/hide output.
#> Records downloaded: 10
#> Records available: 30157
#> A data.frame [10 x 12]
#> occurrenceID scientificName individualCount decimalLatitude
#> 1 …herb.oulu.fi/MY.10184972 Orthotrichum anomal… NA 61.603872
#> 2 …herb.oulu.fi/MY.10185111 Schistidium submuti… NA 61.603833
#> 3 …herb.oulu.fi/MY.10313974 Skeletocutis bigutt… NA 60.234691
#> 4 …herb.oulu.fi/MY.10314039 Oxyporus populinus … NA 61.467278
#> 5 …herb.oulu.fi/MY.10314043 Stereum hirsutum (W… NA 61.467278
#> 6 …herb.oulu.fi/MY.10314116 Stereum sanguinolen… NA 60.201527
#> 7 …herb.oulu.fi/MY.10745815 Eurhynchium angusti… NA 61.467746
#> 8 …luomus.fi/MY.10204437 Dendrocopos leucoto… NA 61.6077
#> 9 …luomus.fi/MY.10221155 Allophylaria macros… NA 60.378251
#> 10 …luomus.fi/MY.10221158 Host: Chamaenerion … NA 60.378251
#> ...with 0 more records and 8 more variables:
#> decimalLongitude, eventDateTime, coordinateUncertaintyInMeters, hasIssues,
#> requiresVerification, requiresIdentification, occurrenceReliability,
#> identificationVerificationStatus
, or for record events, a range as a character vector.
finbif_occurrence(
filter = list(date_range_ymd = c("2019-06-01", "2019-12-31"))
)Click to show/hide output.
#> Records downloaded: 10
#> Records available: 1167813
#> A data.frame [10 x 12]
#> occurrenceID scientificName individualCount decimalLatitude decimalLongitude
#> 1 …244 Aneura pinguis (L.)… NA 61.86848 24.042062
#> 2 …248 Sphenolobus saxicol… NA 61.790156 24.739934
#> 3 …264 Barbilophozia hatch… NA 62.172979 23.166974
#> 4 …268 Barbilophozia hatch… NA 61.733229 23.557042
#> 5 …276 Barbilophozia hatch… NA 62.341331 23.821755
#> 6 …280 Blepharostoma trich… NA 61.817804 23.156312
#> 7 …288 Calypogeia integris… NA 61.787466 24.740131
#> 8 …296 Calypogeia muelleri… NA 61.787466 24.740131
#> 9 …317 Cephalozia bicuspid… NA 61.768742 23.877258
#> 10 …388 Lophocolea heteroph… NA 61.4436 24.119939
#> ...with 0 more records and 7 more variables:
#> eventDateTime, coordinateUncertaintyInMeters, hasIssues, requiresVerification,
#> requiresIdentification, occurrenceReliability, identificationVerificationStatusRecords for a specific season or time-span across all years can also be requested.
finbif_occurrence(
filter = list(
date_range_md = c(begin = "12-21", end = "12-31"),
date_range_md = c(begin = "01-01", end = "02-20")
)
)Click to show/hide output.
#> Records downloaded: 10
#> Records available: 1793259
#> A data.frame [10 x 12]
#> occurrenceID scientificName individualCount decimalLatitude decimalLongitude
#> 1 …079640 Pohlia nutans (Hedw… NA 60.321276 24.109857
#> 2 …184972 Orthotrichum anomal… NA 61.603872 24.227601
#> 3 …185111 Schistidium submuti… NA 61.603833 24.225719
#> 4 …225336 Fuscocephaloziopsis… NA 61.510093 24.343093
#> 5 …225392 Lophocolea minor Ne… NA 61.65722 24.658173
#> 6 …225400 Obtusifolium obtusu… NA 61.458209 23.658786
#> 7 …225403 Plagiomnium cuspida… NA 61.458209 23.658786
#> 8 …281093 Pseudanomodon atten… NA 61.374279 24.197437
#> 9 …281097 Pseudanomodon atten… NA 61.571317 24.305839
#> 10 …281100 Syntrichia ruralis … NA 61.571317 24.305839
#> ...with 0 more records and 7 more variables:
#> eventDateTime, coordinateUncertaintyInMeters, hasIssues, requiresVerification,
#> requiresIdentification, occurrenceReliability, identificationVerificationStatusData Quality
You can filter occurrence records by indicators of data quality. See
?filters section “Quality” for details.
strict <- c(
collection_quality = "professional", coordinates_uncertainty_max = 1,
record_quality = "expert_verified"
)
permissive <- list(
wild_status = c("wild", "non_wild", "wild_unknown"),
record_quality = c(
"expert_verified", "community_verified", "unassessed", "uncertain",
"erroneous"
),
abundance_min = 0
)
c(
strict = finbif_occurrence(filter = strict, count_only = TRUE),
permissive = finbif_occurrence(filter = permissive, count_only = TRUE)
)
#> strict permissive
#> 82631 61265240Collection
The FinBIF database consists of a number of constituent collections.
You can filter by collection with either the collection or
not_collection filters. Use
finbif_collections() to see metadata on the FinBIF
collections.
finbif_occurrence(
filter = c(collection = "iNaturalist Suomi Finland"), count_only = TRUE
)
#> [1] 1673340
finbif_occurrence(
filter = c(collection = "Notebook, general observations"), count_only = TRUE
)
#> [1] 3546019Informal taxonomic groups
You can filter occurrence records based on informal taxonomic groups
such as Birds or Mammals.
finbif_occurrence(filter = list(informal_groups = c("Birds", "Mammals")))Click to show/hide output.
#> Records downloaded: 10
#> Records available: 29626954
#> A data.frame [10 x 12]
#> occurrenceID scientificName individualCount decimalLatitude
#> 1 …herb.oulu.fi/MY.17469610 Asio flammeus (Pont… NA 67.718422
#> 2 …herb.oulu.fi/MY.17483993 Picoides tridactylu… NA 67.47766
#> 3 …luomus.fi/MY.10042206 Strix uralensis Pal… NA 63.811181
#> 4 …luomus.fi/MY.10042210 Strix uralensis Pal… NA 60.360916
#> 5 …luomus.fi/MY.10042213 Bubo bubo (Linnaeus… NA 60.930307
#> 6 …luomus.fi/MY.10042218 Bubo bubo (Linnaeus… NA 63.681831
#> 7 …luomus.fi/MY.10042223 Bubo bubo (Linnaeus… NA 60.135148
#> 8 …luomus.fi/MY.10042226 Strix uralensis Pal… NA 62.250643
#> 9 …luomus.fi/MY.10042231 Astur gentilis (Lin… NA 63.811181
#> 10 …luomus.fi/MY.10042238 Accipiter nisus (Li… NA 60.2522
#> ...with 0 more records and 8 more variables:
#> decimalLongitude, eventDateTime, coordinateUncertaintyInMeters, hasIssues,
#> requiresVerification, requiresIdentification, occurrenceReliability,
#> identificationVerificationStatusSee finbif_informal_groups() for the full list of groups
you can filter by. You can use the same function to see the subgroups
that make up the highest level informal groups:
finbif_informal_groups("Birds")
#> Birds
#> --Birds of prey and owls
#> --Owls
#> --Birds of prey
#> --WaterbirdsRegulatory
Many records in the FinBIF database include taxa that have one or
another regulatory statuses. See
finbif_metadata("regulatory_status") for a list of
regulatory statuses and short-codes.
# Search for birds on the EU invasive species list
finbif_occurrence(
filter = list(informal_groups = "Birds", regulatory_status = "EU_INVSV")
)Click to show/hide output.
#> Records downloaded: 10
#> Records available: 507
#> A data.frame [10 x 12]
#> occurrenceID scientificName individualCount decimalLatitude decimalLongitude
#> 1 …7350700 Pycnonotus cafer su… 3 NA NA
#> 2 …7351780 Corvus splendens su… 2 NA NA
#> 3 …7351784 Corvus splendens su… 2 NA NA
#> 4 …7351788 Corvus splendens su… 2 NA NA
#> 5 …7351792 Corvus splendens su… 1 NA NA
#> 6 …7352178 Oxyura jamaicensis … 7 NA NA
#> 7 …7352182 Oxyura jamaicensis … 8 NA NA
#> 8 …7355894 Oxyura jamaicensis … 8 NA NA
#> 9 …7430682 Corvus splendens su… 3 NA NA
#> 10 …8449767 Alopochen aegyptiac… NA NA NA
#> ...with 0 more records and 7 more variables:
#> eventDateTime, coordinateUncertaintyInMeters, hasIssues, requiresVerification,
#> requiresIdentification, occurrenceReliability, identificationVerificationStatusIUCN red list
Filtering can be done by IUCN red list category. See
finbif_metadata("red_list") for the IUCN red list
categories and their short-codes.
# Search for near threatened mammals
finbif_occurrence(
filter = list(informal_groups = "Mammals", red_list_status = "NT")
)Click to show/hide output.
#> Records downloaded: 10
#> Records available: 82019
#> A data.frame [10 x 12]
#> occurrenceID scientificName individualCount decimalLatitude decimalLongitude
#> 1 …223201 Microtus arvalis (P… NA NA NA
#> 2 …223245 Microtus arvalis (P… NA NA NA
#> 3 …223249 Microtus arvalis (P… NA NA NA
#> 4 …223253 Microtus arvalis (P… NA NA NA
#> 5 …223565 Microtus arvalis (P… NA NA NA
#> 6 …223659 Castor fiber Linnae… NA NA NA
#> 7 …223878 Castor fiber Linnae… NA NA NA
#> 8 …580236 Castor fiber Linnae… NA NA NA
#> 9 …580240 Castor fiber Linnae… NA NA NA
#> 10 …580398 Ursus arctos Linnae… NA 67.05 29.25
#> ...with 0 more records and 7 more variables:
#> eventDateTime, coordinateUncertaintyInMeters, hasIssues, requiresVerification,
#> requiresIdentification, occurrenceReliability, identificationVerificationStatusHabitat type
Many taxa are associated with one or more primary or secondary
habitat types (e.g., forest) or subtypes (e.g., herb-rich alpine birch
forests). Use finbif_metadata("habitat_type") to see the
habitat types in FinBIF. You can filter occurrence records based on
primary (or primary/secondary) habitat type or subtype codes. Note that
filtering based on habitat is on taxa not on the location (i.e.,
filtering records with primary_habitat = "M" will only
return records of taxa considered to primarily inhabit forests, yet the
locations of those records may encompass habitats other than
forests).
head(finbif_metadata("habitat_type"))
#> code name
#> MKV.habitatMt Mt alpine birch forests
#> MKV.habitatTlk Tlk alpine calcareous rock outcrops and boulder …
#> MKV.habitatTlr Tlr alpine gorges and canyons
#> MKV.habitatT T Alpine habitats
#> MKV.habitatTp Tp alpine heath scrubs
#> MKV.habitatTk Tk alpine heaths
# Search records of taxa for which forests are their primary or secondary
# habitat type
finbif_occurrence(filter = c(primary_secondary_habitat = "M"))Click to show/hide output.
#> Records downloaded: 10
#> Records available: 34008277
#> 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, identificationVerificationStatusYou may further refine habitat based searching using a specific
habitat type qualifier such as “sun-exposed” or “shady”. Use
finbif_metadata("habitat_qualifier") to see the qualifiers
available. To specify qualifiers use a named list of character vectors
where the names are habitat types or subtypes and the elements of the
character vectors are the qualifier codes.
finbif_metadata("habitat_qualifier")[4:6, ]
#> code name
#> MKV.habitatSpecificTypeCA CA calcareous effect
#> MKV.habitatSpecificTypeH H esker forests, also semi-open forests
#> MKV.habitatSpecificTypeLK LK fishless ponds
# Search records of taxa for which forests with sun-exposure and broadleaved
# deciduous trees are their primary habitat type
finbif_occurrence(filter = list(primary_habitat = list(M = c("PAK", "J"))))Click to show/hide output.
#> Records downloaded: 10
#> Records available: 218
#> A data.frame [10 x 12]
#> occurrenceID scientificName individualCount decimalLatitude
#> 1 …id.luomus.fi/MY.19077695 Pammene fasciana (L… 1 60.188362
#> 2 …tun.fi/HR.3211/53817755-U Pammene fasciana (L… NA 59.90452
#> 3 …tun.fi/JX.1011605#97 Pammene fasciana (L… 1 60.50396
#> 4 …tun.fi/JX.1011998#37 Pammene fasciana (L… 1 59.960224
#> 5 …tun.fi/JX.1012832#367 Pammene fasciana (L… 1 60.002166
#> 6 …tun.fi/JX.1038248#475 Pammene fasciana (L… NA 59.934164
#> 7 …tun.fi/JX.1098381#487 Pammene fasciana (L… NA 60.045579
#> 8 …tun.fi/JX.1103286#13 Pammene fasciana (L… 1 59.90522
#> 9 …tun.fi/JX.1134471#4 Pammene fasciana (L… 2 61.549842
#> 10 …tun.fi/JX.1143718#265 Pammene fasciana (L… NA 60.37543
#> ...with 0 more records and 8 more variables:
#> decimalLongitude, eventDateTime, coordinateUncertaintyInMeters, hasIssues,
#> requiresVerification, requiresIdentification, occurrenceReliability,
#> identificationVerificationStatusStatus of taxa in Finland
You can restrict the occurrence records by the status of the taxa in Finland. For example you can request records for only rare species.
finbif_occurrence(filter = c(finnish_occurrence_status = "rare"))Click to show/hide output.
#> Records downloaded: 10
#> Records available: 499022
#> A data.frame [10 x 12]
#> occurrenceID scientificName individualCount decimalLatitude decimalLongitude
#> 1 …3990009 Amanita coryli Nevi… NA 68.058832 24.058368
#> 2 …3990121 Amanita flavescens … NA 64.756355 26.197092
#> 3 …3993454 Amanita flavescens … 2 66.65863 27.482198
#> 4 …3993458 Amanita coryli Nevi… 3 66.371875 27.409632
#> 5 …4018238 Hydnum jussii Niska… NA 64.368844 28.004874
#> 6 …4018310 Lamelloclavaria pet… NA 64.421905 27.677572
#> 7 …4018314 Lamelloclavaria pet… NA 64.323694 28.044601
#> 8 …8016027 Amanita coryli Nevi… 5 66.168299 25.765382
#> 9 …8016087 Amanita coryli Nevi… 3 69.007453 20.930394
#> 10 …8016091 Amanita coryli Nevi… 2 68.185593 23.992918
#> ...with 0 more records and 7 more variables:
#> eventDateTime, coordinateUncertaintyInMeters, hasIssues, requiresVerification,
#> requiresIdentification, occurrenceReliability, identificationVerificationStatus
Or, by using the negation of occurrence status, you can request
records of birds excluding those considered vagrants.
finbif_occurrence(
filter = list(
informal_groups = "birds",
finnish_occurrence_status_neg = sprintf("vagrant_%sregular", c("", "ir"))
)
)Click to show/hide output.
#> Records downloaded: 10
#> Records available: 29048611
#> A data.frame [10 x 12]
#> occurrenceID scientificName individualCount decimalLatitude
#> 1 …herb.oulu.fi/MY.17469610 Asio flammeus (Pont… NA 67.718422
#> 2 …herb.oulu.fi/MY.17483993 Picoides tridactylu… NA 67.47766
#> 3 …luomus.fi/MY.10042206 Strix uralensis Pal… NA 63.811181
#> 4 …luomus.fi/MY.10042210 Strix uralensis Pal… NA 60.360916
#> 5 …luomus.fi/MY.10042213 Bubo bubo (Linnaeus… NA 60.930307
#> 6 …luomus.fi/MY.10042218 Bubo bubo (Linnaeus… NA 63.681831
#> 7 …luomus.fi/MY.10042223 Bubo bubo (Linnaeus… NA 60.135148
#> 8 …luomus.fi/MY.10042226 Strix uralensis Pal… NA 62.250643
#> 9 …luomus.fi/MY.10042231 Astur gentilis (Lin… NA 63.811181
#> 10 …luomus.fi/MY.10042238 Accipiter nisus (Li… NA 60.2522
#> ...with 0 more records and 8 more variables:
#> decimalLongitude, eventDateTime, coordinateUncertaintyInMeters, hasIssues,
#> requiresVerification, requiresIdentification, occurrenceReliability,
#> identificationVerificationStatusSee finbif_metadata("finnish_occurrence_status") for a
full list of statuses and their descriptions.