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Wrapper to the Global Biodiversity Information Facility API

Home Page: http://ropensci.org/tutorials/rgbif_tutorial.html

License: Other

Makefile 0.08% R 81.21% JavaScript 18.24% HTML 0.47%

rgbif's Introduction

rgbif

Build Status Build status Coverage Status rstudio mirror downloads cran version

rgbif gives you access to data from GBIF via their REST API. GBIF versions their API - we are currently using v1 of their API. You can no longer use their old API in this package - see ?rgbif-defunct.

Installation

install.packages("rgbif")

Alternatively, install development version

install.packages("devtools")
devtools::install_github("ropensci/rgbif")
library("rgbif")

Note: Windows users have to first install Rtools to use devtools

Search for occurrence data

occ_search(scientificName = "Ursus americanus", limit = 50)
#> Records found [7218] 
#> Records returned [50] 
#> No. unique hierarchies [1] 
#> No. media records [50] 
#> Args [scientificName=Ursus americanus, limit=50, offset=0, fields=all] 
#> First 10 rows of data
#> 
#>                name        key decimalLatitude decimalLongitude
#> 1  Ursus americanus 1065590124        38.36662        -79.68283
#> 2  Ursus americanus 1065588899        35.73304        -82.42028
#> 3  Ursus americanus 1065611122        43.94883        -72.77432
#> 4  Ursus americanus 1098894889        23.69470        -99.14630
#> 5  Ursus americanus 1088908315        43.86464        -72.34617
#> 6  Ursus americanus 1088923534        36.93018        -78.25027
#> 7  Ursus americanus 1088932238        32.65219       -108.53674
#> 8  Ursus americanus 1088932273        32.65237       -108.53691
#> 9  Ursus americanus 1088964797        29.27042       -103.30058
#> 10 Ursus americanus 1088961422        49.72317        -96.03215
#> ..              ...        ...             ...              ...
#> Variables not shown: issues (chr), datasetKey (chr), publishingOrgKey
#>      (chr), publishingCountry (chr), protocol (chr), lastCrawled (chr),
#>      lastParsed (chr), extensions (chr), basisOfRecord (chr), taxonKey
#>      (int), kingdomKey (int), phylumKey (int), classKey (int), orderKey
#>      (int), familyKey (int), genusKey (int), speciesKey (int),
#>      scientificName (chr), kingdom (chr), phylum (chr), order (chr),
#>      family (chr), genus (chr), species (chr), genericName (chr),
#>      specificEpithet (chr), taxonRank (chr), dateIdentified (chr), year
#>      (int), month (int), day (int), eventDate (chr), modified (chr),
#>      lastInterpreted (chr), references (chr), identifiers (chr), facts
#>      (chr), relations (chr), geodeticDatum (chr), class (chr), countryCode
#>      (chr), country (chr), verbatimEventDate (chr),
#>      http...unknown.org.occurrenceDetails (chr), rights (chr),
#>      rightsHolder (chr), occurrenceID (chr), taxonID (chr), collectionCode
#>      (chr), gbifID (chr), occurrenceRemarks (chr), institutionCode (chr),
#>      datasetName (chr), catalogNumber (chr), recordedBy (chr), eventTime
#>      (chr), identifier (chr), identificationID (chr), verbatimLocality
#>      (chr), infraspecificEpithet (chr), informationWithheld (chr)

Or you can get the taxon key first with name_backbone(). Here, we select to only return the occurrence data.

key <- name_backbone(name='Helianthus annuus', kingdom='plants')$speciesKey
occ_search(taxonKey=key, limit=20)
#> Records found [20650] 
#> Records returned [20] 
#> No. unique hierarchies [1] 
#> No. media records [18] 
#> Args [taxonKey=3119195, limit=20, offset=0, fields=all] 
#> First 10 rows of data
#> 
#>                 name        key decimalLatitude decimalLongitude
#> 1  Helianthus annuus 1095851641         0.00000          0.00000
#> 2  Helianthus annuus 1088900309        33.95239       -117.32011
#> 3  Helianthus annuus 1088933055        25.66564       -100.30348
#> 4  Helianthus annuus 1088909392        24.72449        -99.54020
#> 5  Helianthus annuus 1088937716        25.81691       -100.05940
#> 6  Helianthus annuus 1088944416        26.20518        -98.26725
#> 7  Helianthus annuus 1090389390        59.96150         17.71060
#> 8  Helianthus annuus 1092889365        32.71840       -114.75603
#> 9  Helianthus annuus 1092889645         1.27617        103.79136
#> 10 Helianthus annuus 1098903927        29.17958       -102.99551
#> ..               ...        ...             ...              ...
#> Variables not shown: issues (chr), datasetKey (chr), publishingOrgKey
#>      (chr), publishingCountry (chr), protocol (chr), lastCrawled (chr),
#>      lastParsed (chr), extensions (chr), basisOfRecord (chr), taxonKey
#>      (int), kingdomKey (int), phylumKey (int), classKey (int), orderKey
#>      (int), familyKey (int), genusKey (int), speciesKey (int),
#>      scientificName (chr), kingdom (chr), phylum (chr), order (chr),
#>      family (chr), genus (chr), species (chr), genericName (chr),
#>      specificEpithet (chr), taxonRank (chr), dateIdentified (chr),
#>      elevation (dbl), elevationAccuracy (dbl), stateProvince (chr), year
#>      (int), month (int), day (int), eventDate (chr), lastInterpreted
#>      (chr), identifiers (chr), facts (chr), relations (chr), geodeticDatum
#>      (chr), class (chr), countryCode (chr), country (chr), recordNumber
#>      (chr), rights (chr), municipality (chr), rightsHolder (chr),
#>      ownerInstitutionCode (chr), type (chr), occurrenceID (chr),
#>      collectionCode (chr), identifiedBy (chr), gbifID (chr),
#>      occurrenceRemarks (chr), institutionCode (chr), datasetName (chr),
#>      catalogNumber (chr), recordedBy (chr), locality (chr), language
#>      (chr), identifier (chr), modified (chr), references (chr),
#>      verbatimEventDate (chr), verbatimLocality (chr),
#>      http...unknown.org.occurrenceDetails (chr), taxonID (chr), eventTime
#>      (chr), identificationID (chr), coordinateAccuracy (dbl), depth (dbl),
#>      depthAccuracy (dbl), county (chr), informationWithheld (chr)

Search for many species

Get the keys first with name_backbone(), then pass to occ_search()

splist <- c('Accipiter erythronemius', 'Junco hyemalis', 'Aix sponsa')
keys <- sapply(splist, function(x) name_backbone(name=x)$speciesKey, USE.NAMES=FALSE)
occ_search(taxonKey=keys, limit=5, hasCoordinate=TRUE)
#> Occ. found [2480598 (20), 2492010 (1925675), 2498387 (589944)] 
#> Occ. returned [2480598 (5), 2492010 (5), 2498387 (5)] 
#> No. unique hierarchies [2480598 (1), 2492010 (1), 2498387 (1)] 
#> No. media records [2480598 (1), 2492010 (5), 2498387 (5)] 
#> Args [taxonKey=2480598,2492010,2498387, hasCoordinate=TRUE, limit=5,
#>      offset=0, fields=all] 
#> First 10 rows of data from 2480598
#> 
#>                      name        key decimalLatitude decimalLongitude
#> 1 Accipiter erythronemius  920169861       -20.55244        -56.64104
#> 2 Accipiter erythronemius  920184036       -20.76029        -56.71314
#> 3 Accipiter erythronemius 1001096527       -27.58000        -58.66000
#> 4 Accipiter erythronemius 1001096518       -27.92000        -59.14000
#> 5 Accipiter erythronemius  699417490         5.26667        -60.73333
#> Variables not shown: issues (chr), datasetKey (chr), publishingOrgKey
#>      (chr), publishingCountry (chr), protocol (chr), lastCrawled (chr),
#>      lastParsed (chr), extensions (chr), basisOfRecord (chr), taxonKey
#>      (int), kingdomKey (int), phylumKey (int), classKey (int), orderKey
#>      (int), familyKey (int), genusKey (int), speciesKey (int),
#>      scientificName (chr), kingdom (chr), phylum (chr), order (chr),
#>      family (chr), genus (chr), species (chr), genericName (chr),
#>      specificEpithet (chr), taxonRank (chr), year (int), month (int), day
#>      (int), eventDate (chr), lastInterpreted (chr), identifiers (chr),
#>      facts (chr), relations (chr), geodeticDatum (chr), class (chr),
#>      countryCode (chr), country (chr), gbifID (chr), institutionCode
#>      (chr), catalogNumber (chr), recordedBy (chr), locality (chr),
#>      collectionCode (chr), modified (chr), created (chr),
#>      higherClassification (chr), associatedSequences (chr), occurrenceID
#>      (chr), identifier (chr), taxonID (chr), sex (chr), elevation (dbl),
#>      elevationAccuracy (dbl), recordNumber (chr), institutionID (chr),
#>      rights (chr), higherGeography (chr), type (chr), georeferenceSources
#>      (chr), otherCatalogNumbers (chr), bibliographicCitation (chr),
#>      verbatimEventDate (chr), preparations (chr),
#>      georeferenceVerificationStatus (chr), occurrenceRemarks (chr),
#>      accessRights (chr), datasetName (chr), verbatimElevation (chr),
#>      language (chr)

Maps

Make a simple map of species occurrences.

splist <- c('Cyanocitta stelleri', 'Junco hyemalis', 'Aix sponsa')
keys <- sapply(splist, function(x) name_backbone(name=x)$speciesKey, USE.NAMES=FALSE)
dat <- occ_search(taxonKey=keys, limit=100, return='data', hasCoordinate=TRUE)
library('plyr')
datdf <- ldply(dat)
gbifmap(datdf)

plot of chunk unnamed-chunk-8

Meta


This package is part of a richer suite called SPOCC Species Occurrence Data, along with several other packages, that provide access to occurrence records from multiple databases.


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