rebird
is a package to interface with the eBird webservices.
eBird is a real-time, online bird checklist program. For more information, visit their website: https://ebird.org/home
The API for the eBird webservices can be accessed here: https://documenter.getpostman.com/view/664302/S1ENwy59?version=latest
You can install the stable version from CRAN
install.packages("rebird")
Or the development version from Github
install.packages("devtools")
devtools::install_github("ropensci/rebird")
Load the package:
library("rebird")
The eBird API
server
requires users to provide an API key, which is linked to your eBird user
account. You can pass it to the ‘key’ argument in rebird
functions,
but we highly recommend storing it as an environment variable called
EBIRD_KEY in your .Renviron file. If you don’t have a key, you can
obtain one from https://ebird.org/api/keygen.
You can keep your .Renviron file in your global R home directory
(R.home()
), your user’s home directory (Sys.getenv("HOME")
), or your
current working directory (getwd()
). Remember that .Renviron is loaded
once when you start R, so if you add your API key to the file you will
have to restart your R session. See ?Startup
for more information on
R’s startup files.
Furthermore, functions now use species codes, rather than scientific
names, for species-specific requests. We’ve made the switch easy by
providing the species_code
function, which converts a scientific name
to its species code:
species_code('sula variegata')
#> Peruvian Booby (Sula variegata): perboo1
#> [1] "perboo1"
The species_code
function can be called within other rebird
functions, or the species code can be specified directly.
The eBird taxonomy is internally stored in rebird
and can be called
using
rebird::tax
#> # A tibble: 17,415 × 15
#> sciName comName speciesCode category taxonOrder bandingCodes comNameCodes
#> <chr> <chr> <chr> <chr> <dbl> <chr> <chr>
#> 1 Struthio c… Common… ostric2 species 2 <NA> COOS
#> 2 Struthio m… Somali… ostric3 species 7 <NA> SOOS
#> 3 Struthio c… Common… y00934 slash 8 <NA> SOOS,COOS
#> 4 Casuarius … Southe… soucas1 species 10 <NA> SOCA
#> 5 Casuarius … Dwarf … dwacas1 species 11 <NA> DWCA
#> 6 Casuarius … Northe… norcas1 species 12 <NA> NOCA
#> 7 Dromaius n… Emu emu1 species 13 <NA> EMU,COEM
#> 8 Apteryx au… Southe… sobkiw1 species 19 <NA> SBKI
#> 9 Apteryx au… Southe… sobkiw2 issf 20 <NA> SBKI
#> 10 Apteryx au… Southe… sobkiw3 issf 21 <NA> SBKI
#> # ℹ 17,405 more rows
#> # ℹ 8 more variables: sciNameCodes <chr>, order <chr>, familyCode <chr>,
#> # familyComName <chr>, familySciName <chr>, reportAs <chr>, extinct <lgl>,
#> # extinctYear <int>
While the internal taxonomy is kept up to date with each package release, it could be outdated if a new taxonomy is made available before the package is updated. You can obtain the latest eBird taxonomy by
new_tax <- ebirdtaxonomy()
Search for bird occurrences by latitude and longitude point
ebirdgeo(species = species_code('spinus tristis'), lat = 42, lng = -76)
#> American Goldfinch (Spinus tristis): amegfi
#> # A tibble: 28 × 13
#> speciesCode comName sciName locId locName obsDt howMany lat lng obsValid
#> <chr> <chr> <chr> <chr> <chr> <chr> <int> <dbl> <dbl> <lgl>
#> 1 amegfi America… Spinus… L200… Oakrid… 2025… 1 42.1 -75.9 TRUE
#> 2 amegfi America… Spinus… L124… Happy … 2025… 13 42.1 -75.9 TRUE
#> 3 amegfi America… Spinus… L888… Nowlan… 2025… 42 42.1 -75.9 TRUE
#> 4 amegfi America… Spinus… L104… 14 Bou… 2025… 4 42.1 -75.9 TRUE
#> 5 amegfi America… Spinus… L186… Otsini… 2025… 2 42.1 -75.9 TRUE
#> 6 amegfi America… Spinus… L471… Home: … 2025… 4 42.1 -76.1 TRUE
#> 7 amegfi America… Spinus… L351… Brixiu… 2025… 14 42.1 -76.0 TRUE
#> 8 amegfi America… Spinus… L224… Highla… 2025… 2 42.1 -76.0 TRUE
#> 9 amegfi America… Spinus… L233… 1443–1… 2025… 12 42.1 -75.9 TRUE
#> 10 amegfi America… Spinus… L399… 701 Pa… 2025… 1 42.1 -76.0 TRUE
#> # ℹ 18 more rows
#> # ℹ 3 more variables: obsReviewed <lgl>, locationPrivate <lgl>, subId <chr>
Search for bird occurrences by region and species name
ebirdregion(loc = 'US', species = 'btbwar')
#> # A tibble: 46 × 13
#> speciesCode comName sciName locId locName obsDt howMany lat lng obsValid
#> <chr> <chr> <chr> <chr> <chr> <chr> <int> <dbl> <dbl> <lgl>
#> 1 btbwar Black-t… Setoph… L106… Palmet… 2025… 1 26.9 -80.1 TRUE
#> 2 btbwar Black-t… Setoph… L163… Young … 2025… 1 26.5 -80.1 TRUE
#> 3 btbwar Black-t… Setoph… L171… Three … 2025… 1 28.1 -80.7 TRUE
#> 4 btbwar Black-t… Setoph… L246… Green … 2025… 1 26.5 -80.2 TRUE
#> 5 btbwar Black-t… Setoph… L405… Frog P… 2025… 1 25.4 -80.6 TRUE
#> 6 btbwar Black-t… Setoph… L129… Lantan… 2025… 2 26.6 -80.0 TRUE
#> 7 btbwar Black-t… Setoph… L330… Orchid… 2025… 1 26.2 -80.3 TRUE
#> 8 btbwar Black-t… Setoph… L399… 715 Pa… 2025… 2 26.9 -80.1 TRUE
#> 9 btbwar Black-t… Setoph… L458… Kendal… 2025… 1 25.7 -80.4 TRUE
#> 10 btbwar Black-t… Setoph… L123… Merrit… 2025… 1 28.7 -80.7 TRUE
#> # ℹ 36 more rows
#> # ℹ 3 more variables: obsReviewed <lgl>, locationPrivate <lgl>, subId <chr>
Search for bird occurrences by a given hotspot
ebirdregion(loc = 'L99381')
#> # A tibble: 57 × 14
#> speciesCode comName sciName locId locName obsDt howMany lat lng obsValid
#> <chr> <chr> <chr> <chr> <chr> <chr> <int> <dbl> <dbl> <lgl>
#> 1 cangoo Canada … Branta… L993… Stewar… 2025… 80 42.5 -76.5 TRUE
#> 2 mallar3 Mallard Anas p… L993… Stewar… 2025… 150 42.5 -76.5 TRUE
#> 3 ambduc America… Anas r… L993… Stewar… 2025… 3 42.5 -76.5 TRUE
#> 4 canvas Canvasb… Aythya… L993… Stewar… 2025… 8 42.5 -76.5 TRUE
#> 5 redhea Redhead Aythya… L993… Stewar… 2025… 500 42.5 -76.5 TRUE
#> 6 rinduc Ring-ne… Aythya… L993… Stewar… 2025… 5 42.5 -76.5 TRUE
#> 7 comgol Common … Buceph… L993… Stewar… 2025… 4 42.5 -76.5 TRUE
#> 8 hoomer Hooded … Lophod… L993… Stewar… 2025… 10 42.5 -76.5 TRUE
#> 9 commer Common … Mergus… L993… Stewar… 2025… 300 42.5 -76.5 TRUE
#> 10 rebmer Red-bre… Mergus… L993… Stewar… 2025… 10 42.5 -76.5 TRUE
#> # ℹ 47 more rows
#> # ℹ 4 more variables: obsReviewed <lgl>, locationPrivate <lgl>, subId <chr>,
#> # exoticCategory <chr>
Search for a species’ occurrences near a given latitude and longitude
nearestobs(species_code('branta canadensis'), 42, -76)
#> Canada Goose (Branta canadensis): cangoo
#> # A tibble: 14 × 13
#> speciesCode comName sciName locId locName obsDt howMany lat lng obsValid
#> <chr> <chr> <chr> <chr> <chr> <chr> <int> <dbl> <dbl> <lgl>
#> 1 cangoo Canada … Branta… L109… Hillcr… 2025… 8 42.2 -75.9 TRUE
#> 2 cangoo Canada … Branta… L247… Conflu… 2025… 14 42.1 -75.9 TRUE
#> 3 cangoo Canada … Branta… L189… Conflu… 2025… 5 42.1 -75.9 TRUE
#> 4 cangoo Canada … Branta… L505… Boland… 2025… 9 42.2 -75.9 TRUE
#> 5 cangoo Canada … Branta… L186… Otsini… 2025… 60 42.1 -75.9 TRUE
#> 6 cangoo Canada … Branta… L201… Conflu… 2025… 150 42.1 -76.3 TRUE
#> 7 cangoo Canada … Branta… L351… Anson … 2025… 34 42.1 -76.1 TRUE
#> 8 cangoo Canada … Branta… L714… Draper… 2025… 4 42.1 -76.3 TRUE
#> 9 cangoo Canada … Branta… L367… River … 2025… 120 42.1 -76.3 TRUE
#> 10 cangoo Canada … Branta… L154… IBM Gl… 2025… 13 42.1 -76.0 TRUE
#> 11 cangoo Canada … Branta… L278… Harold… 2025… 85 42.1 -76.0 TRUE
#> 12 cangoo Canada … Branta… L137… Apalac… 2025… 80 42.1 -76.1 TRUE
#> 13 cangoo Canada … Branta… L166… Chugnu… 2025… 80 42.1 -76.0 TRUE
#> 14 cangoo Canada … Branta… L501… Willia… 2025… 80 42.1 -76.0 TRUE
#> # ℹ 3 more variables: obsReviewed <lgl>, locationPrivate <lgl>, subId <chr>
Search for notable sightings at a given latitude and longitude
ebirdnotable(lat = 42, lng = -70)
#> # A tibble: 3,942 × 14
#> speciesCode comName sciName locId locName obsDt howMany lat lng obsValid
#> <chr> <chr> <chr> <chr> <chr> <chr> <int> <dbl> <dbl> <lgl>
#> 1 norsho Norther… Spatul… L152… Lagoon… 2025… 1 41.4 -70.6 FALSE
#> 2 kineid King Ei… Somate… L464… BHI--N… 2025… 1 42.3 -71.0 FALSE
#> 3 grycat Gray Ca… Dumete… L376… 35 Cox… 2025… 1 43.8 -69.8 FALSE
#> 4 amepip America… Anthus… L754… Plaice… 2025… 6 42.9 -70.8 FALSE
#> 5 fiscro Fish Cr… Corvus… L164… Highla… 2025… 10 42.8 -71.2 FALSE
#> 6 kineid King Ei… Somate… L464… BHI--N… 2025… 1 42.3 -71.0 FALSE
#> 7 merlin Merlin Falco … L123… Fitchb… 2025… 1 42.6 -71.8 FALSE
#> 8 amewig America… Mareca… L483… Spurwi… 2025… 1 43.6 -70.3 FALSE
#> 9 rusbla Rusty B… Euphag… L483… Spurwi… 2025… 1 43.6 -70.3 FALSE
#> 10 rehwoo Red-hea… Melane… L538… Elys F… 2025… 2 41.4 -72.4 TRUE
#> # ℹ 3,932 more rows
#> # ℹ 4 more variables: obsReviewed <lgl>, locationPrivate <lgl>, subId <chr>,
#> # exoticCategory <chr>
or a region
ebirdnotable(locID = 'US-NY-109')
#> # A tibble: 16 × 13
#> speciesCode comName sciName locId locName obsDt howMany lat lng obsValid
#> <chr> <chr> <chr> <chr> <chr> <chr> <int> <dbl> <dbl> <lgl>
#> 1 cacgoo1 Cacklin… Branta… L286… Ladoga… 2025… 2 42.5 -76.5 FALSE
#> 2 blksco2 Black S… Melani… L241… Stewar… 2025… 3 42.5 -76.5 FALSE
#> 3 blksco2 Black S… Melani… L993… Stewar… 2025… 3 42.5 -76.5 FALSE
#> 4 killde Killdeer Charad… L353… Salt P… 2025… 1 42.5 -76.5 FALSE
#> 5 x00681 Redhead… Aythya… L140… East S… 2025… 1 42.5 -76.5 TRUE
#> 6 evegro Evening… Coccot… L144… Shinda… 2025… 3 42.3 -76.3 TRUE
#> 7 evegro Evening… Coccot… L143… Shinda… 2025… 4 42.3 -76.3 TRUE
#> 8 comgra2 Common … Quisca… L784… Monkey… 2025… 1 42.5 -76.4 TRUE
#> 9 comgra2 Common … Quisca… L784… Monkey… 2025… 1 42.5 -76.4 TRUE
#> 10 killde Killdeer Charad… L996… Myers … 2025… 1 42.5 -76.6 TRUE
#> 11 fiespa Field S… Spizel… L351… Fuerte… 2025… 1 42.5 -76.5 TRUE
#> 12 fiespa Field S… Spizel… L215… Newman… 2025… 1 42.5 -76.5 TRUE
#> 13 evegro Evening… Coccot… L397… 89 Shi… 2025… 1 42.3 -76.3 TRUE
#> 14 evegro Evening… Coccot… L396… 89 Shi… 2025… 2 42.3 -76.3 TRUE
#> 15 evegro Evening… Coccot… L396… 89 Shi… 2025… 2 42.3 -76.3 TRUE
#> 16 evegro Evening… Coccot… L396… 89 Shi… 2025… 3 42.3 -76.3 TRUE
#> # ℹ 3 more variables: obsReviewed <lgl>, locationPrivate <lgl>, subId <chr>
Obtain a list of species reported on a specific date in a given region
ebirdhistorical(loc = 'US-VA-003', date = '2019-02-14',max = 10)
#> # A tibble: 10 × 13
#> speciesCode comName sciName locId locName obsDt howMany lat lng obsValid
#> <chr> <chr> <chr> <chr> <chr> <chr> <int> <dbl> <dbl> <lgl>
#> 1 cangoo Canada … Branta… L139… Lickin… 2019… 30 38.1 -78.7 TRUE
#> 2 mallar3 Mallard Anas p… L139… Lickin… 2019… 5 38.1 -78.7 TRUE
#> 3 gnwtea Green-w… Anas c… L139… Lickin… 2019… 8 38.1 -78.7 TRUE
#> 4 killde Killdeer Charad… L139… Lickin… 2019… 1 38.1 -78.7 TRUE
#> 5 baleag Bald Ea… Haliae… L139… Lickin… 2019… 1 38.1 -78.7 TRUE
#> 6 belkin1 Belted … Megace… L139… Lickin… 2019… 1 38.1 -78.7 TRUE
#> 7 carwre Carolin… Thryot… L139… Lickin… 2019… 1 38.1 -78.7 TRUE
#> 8 whtspa White-t… Zonotr… L139… Lickin… 2019… 2 38.1 -78.7 TRUE
#> 9 norcar Norther… Cardin… L139… Lickin… 2019… 1 38.1 -78.7 TRUE
#> 10 canvas Canvasb… Aythya… L331… Montic… 2019… 19 38.0 -78.5 TRUE
#> # ℹ 3 more variables: obsReviewed <lgl>, locationPrivate <lgl>, subId <chr>
or a hotspot
ebirdhistorical(loc = 'L196159', date = '2019-02-14', fieldSet = 'full')
#> # A tibble: 14 × 27
#> speciesCode comName sciName locId locName obsDt howMany lat lng obsValid
#> <chr> <chr> <chr> <chr> <chr> <chr> <int> <dbl> <dbl> <lgl>
#> 1 annhum Anna's … Calypt… L196… Vancou… 2019… 4 49.3 -123. TRUE
#> 2 ribgul Ring-bi… Larus … L196… Vancou… 2019… 4 49.3 -123. TRUE
#> 3 glwgul Glaucou… Larus … L196… Vancou… 2019… 29 49.3 -123. TRUE
#> 4 amecro America… Corvus… L196… Vancou… 2019… 100 49.3 -123. TRUE
#> 5 bkcchi Black-c… Poecil… L196… Vancou… 2019… 16 49.3 -123. TRUE
#> 6 bushti Bushtit Psaltr… L196… Vancou… 2019… 20 49.3 -123. TRUE
#> 7 pacwre1 Pacific… Troglo… L196… Vancou… 2019… 1 49.3 -123. TRUE
#> 8 houfin House F… Haemor… L196… Vancou… 2019… 2 49.3 -123. TRUE
#> 9 purfin Purple … Haemor… L196… Vancou… 2019… 3 49.3 -123. TRUE
#> 10 amegfi America… Spinus… L196… Vancou… 2019… 15 49.3 -123. TRUE
#> 11 daejun Dark-ey… Junco … L196… Vancou… 2019… 37 49.3 -123. TRUE
#> 12 sonspa Song Sp… Melosp… L196… Vancou… 2019… 12 49.3 -123. TRUE
#> 13 spotow Spotted… Pipilo… L196… Vancou… 2019… 1 49.3 -123. TRUE
#> 14 rewbla Red-win… Agelai… L196… Vancou… 2019… 6 49.3 -123. TRUE
#> # ℹ 17 more variables: obsReviewed <lgl>, locationPrivate <lgl>, subId <chr>,
#> # subnational2Code <chr>, subnational2Name <chr>, subnational1Code <chr>,
#> # subnational1Name <chr>, countryCode <chr>, countryName <chr>,
#> # userDisplayName <chr>, obsId <chr>, checklistId <chr>, presenceNoted <lgl>,
#> # hasComments <lgl>, firstName <chr>, lastName <chr>, hasRichMedia <lgl>
Obtain detailed information on any valid eBird region
ebirdregioninfo("CA-BC-GV")
#> # A tibble: 1 × 5
#> region minX maxX minY maxY
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 Metro Vancouver, British Columbia, Canada -123. -122. 49.0 49.6
or hotspot
ebirdregioninfo("L196159")
#> # A tibble: 1 × 16
#> locId name latitude longitude countryCode countryName subnational1Name
#> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr>
#> 1 L196159 Vancouver… 49.3 -123. CA Canada British Columbia
#> # ℹ 9 more variables: subnational1Code <chr>, subnational2Code <chr>,
#> # subnational2Name <chr>, isHotspot <lgl>, locName <chr>, lat <dbl>,
#> # lng <dbl>, hierarchicalName <chr>, locID <chr>
Obtain a list of eBird species codes for all species recorded in a region
ebirdregionspecies("GB-ENG-LND")
#> # A tibble: 384 × 1
#> speciesCode
#> <chr>
#> 1 wfwduc1
#> 2 fuwduc
#> 3 bahgoo
#> 4 empgoo
#> 5 snogoo
#> 6 rosgoo
#> 7 gragoo
#> 8 swagoo1
#> 9 gwfgoo
#> 10 lwfgoo
#> # ℹ 374 more rows
or a hotspot
ebirdregionspecies("L5803024")
#> # A tibble: 188 × 1
#> speciesCode
#> <chr>
#> 1 gragoo
#> 2 gwfgoo
#> 3 tunbeg1
#> 4 pifgoo
#> 5 bargoo
#> 6 cangoo
#> 7 x00758
#> 8 mutswa
#> 9 whoswa
#> 10 egygoo
#> # ℹ 178 more rows
Obtain a list of all subregions within an eBird region
ebirdsubregionlist("subnational1","US")
#> # A tibble: 51 × 2
#> code name
#> <chr> <chr>
#> 1 US-AL Alabama
#> 2 US-AK Alaska
#> 3 US-AZ Arizona
#> 4 US-AR Arkansas
#> 5 US-CA California
#> 6 US-CO Colorado
#> 7 US-CT Connecticut
#> 8 US-DE Delaware
#> 9 US-DC District of Columbia
#> 10 US-FL Florida
#> # ℹ 41 more rows
Obtain a list of checklists submitted on a given date at a region or hotspot
ebirdchecklistfeed(loc = "L207391", date = "2020-03-24", max = 5)
#> # A tibble: 5 × 9
#> locId subId userDisplayName numSpecies obsDt obsTime isoObsDate subID loc
#> <chr> <chr> <chr> <int> <chr> <chr> <chr> <chr> <chr>
#> 1 L207391 S6617… David Wood 10 24 M… 14:47 2020-03-2… S661… L207…
#> 2 L207391 S6617… Sofia Prado-Ir… 15 24 M… 14:31 2020-03-2… S661… L207…
#> 3 L207391 S6619… Jeffrey Gantz 19 24 M… 13:30 2020-03-2… S661… L207…
#> 4 L207391 S6617… Ann Gurka 21 24 M… 13:00 2020-03-2… S661… L207…
#> 5 L207391 S7098… Barbara Olson 20 24 M… 10:30 2020-03-2… S709… L207…
Obtain all information on a specific checklist
ebirdchecklist("S139153079")
#> # A tibble: 99 × 25
#> subId protocolId locId groupId durationHrs allObsReported subComments
#> <chr> <chr> <chr> <chr> <dbl> <lgl> <chr>
#> 1 S139153079 P22 L17 G10310841 11.2 TRUE "There are …
#> 2 S139153079 P22 L17 G10310841 11.2 TRUE "There are …
#> 3 S139153079 P22 L17 G10310841 11.2 TRUE "There are …
#> 4 S139153079 P22 L17 G10310841 11.2 TRUE "There are …
#> 5 S139153079 P22 L17 G10310841 11.2 TRUE "There are …
#> 6 S139153079 P22 L17 G10310841 11.2 TRUE "There are …
#> 7 S139153079 P22 L17 G10310841 11.2 TRUE "There are …
#> 8 S139153079 P22 L17 G10310841 11.2 TRUE "There are …
#> 9 S139153079 P22 L17 G10310841 11.2 TRUE "There are …
#> 10 S139153079 P22 L17 G10310841 11.2 TRUE "There are …
#> # ℹ 89 more rows
#> # ℹ 18 more variables: creationDt <chr>, lastEditedDt <chr>, obsDt <chr>,
#> # obsTimeValid <lgl>, checklistId <chr>, numObservers <int>,
#> # effortDistanceKm <dbl>, effortDistanceEnteredUnit <chr>,
#> # subnational1Code <chr>, deleteTrack <lgl>, userDisplayName <chr>,
#> # numSpecies <int>, speciesCode <chr>, obsId <chr>, howManyStr <chr>,
#> # obsComments <chr>, photoCounts <int>, videoCounts <int>
Obtain a list of hotspots within a region
ebirdhotspotlist("CA-NS-HL")
#> # A tibble: 298 × 9
#> locId locName countryCode subnational1Code subnational2Code lat lng
#> <chr> <chr> <chr> <chr> <chr> <dbl> <dbl>
#> 1 L2334369 Abraham … CA CA-NS CA-NS-HL 45.2 -62.6
#> 2 L7003818 Admiral … CA CA-NS CA-NS-HL 44.7 -63.7
#> 3 L1765807 Admiral … CA CA-NS CA-NS-HL 44.8 -63.1
#> 4 L12227034 Armdale-… CA CA-NS CA-NS-HL 44.6 -63.6
#> 5 L12690538 Armdale-… CA CA-NS CA-NS-HL 44.6 -63.6
#> 6 L2390509 Bald Roc… CA CA-NS CA-NS-HL 44.5 -63.6
#> 7 L7598385 Bayers L… CA CA-NS CA-NS-HL 44.6 -63.7
#> 8 L11019120 Beaver B… CA CA-NS CA-NS-HL 44.8 -63.7
#> 9 L1872934 Bedford … CA CA-NS CA-NS-HL 44.7 -63.7
#> 10 L12134597 Bedford-… CA CA-NS CA-NS-HL 44.7 -63.7
#> # ℹ 288 more rows
#> # ℹ 2 more variables: latestObsDt <chr>, numSpeciesAllTime <int>
or within a radius of up to 50 kilometers, from a given set of coordinates.
ebirdhotspotlist(lat = 30, lng = -90, dist = 10)
#> No region code provided, locating hotspots using lat/lng
#> # A tibble: 54 × 9
#> locId locName countryCode subnational1Code subnational2Code lat lng
#> <chr> <chr> <chr> <chr> <chr> <dbl> <dbl>
#> 1 L6025517 Algiers … US US-LA US-LA-071 30.0 -90.1
#> 2 L3886471 Armstron… US US-LA US-LA-071 30.0 -90.1
#> 3 L727179 Audubon … US US-LA US-LA-071 30.0 -90.0
#> 4 L6665071 BAEA Nes… US US-LA US-LA-087 30.0 -90.0
#> 5 L6666949 BAEA Nes… US US-LA US-LA-071 29.9 -90.0
#> 6 L2423926 Bayou Bi… US US-LA US-LA-071 30.0 -90.0
#> 7 L725034 Bayou Sa… US US-LA US-LA-071 30.1 -89.9
#> 8 L37730406 Bayou Sa… US US-LA US-LA-071 30.1 -89.9
#> 9 L727232 Chalmett… US US-LA US-LA-087 29.9 -90.0
#> 10 L453412 City Par… US US-LA US-LA-071 30.0 -90.1
#> # ℹ 44 more rows
#> # ℹ 2 more variables: latestObsDt <chr>, numSpeciesAllTime <int>
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. We recommend using spocc
as the primary R interface to
rebird
unless your needs are limited to this single source.
Those interested in eBird data may also want to consider
auk
, an R package
that helps extracting and processing the whole eBird dataset. The
functions in rebird
are faster but mostly limited to accessing recent
(i.e. within the last 30 days) observations, although ebirdfreq()
does
provide historical frequency of observation data. In contrast, auk
gives access to the full set of ~ 500 million eBird observations. For
most ecological applications, users will require auk
; however, for
some use cases, e.g. building tools for birders, rebird
provides a
quicker and easier way to access data. rebird
and auk
are both part
of the rOpenSci project.
The 2.0 APIs have considerably been expanded from the previous version,
and rebird
only covers some of them. The webservices covered are
listed below; if you’d like to contribute wrappers to APIs not yet
covered by this package, feel free to submit a pull request!
- Recent observations in a region:
ebirdregion()
- Recent notable observations in a region:
ebirdnotable()
- Recent observations of a species in a region:
ebirdregion()
- Recent nearby observations:
ebirdgeo()
- Recent nearby observations of a species:
ebirdgeo()
- Nearest observations of a species:
nearestobs()
- Recent nearby notable observations:
ebirdnotable()
- Recent checklists feed
- Historic observations on a date:
ebirdhistorical()
- Top 100
- Checklist feed on a date:
ebirdchecklistfeed()
- Regional statistics on a date
- Species list for a region:
ebirdregionspecies()
- View Checklist:
ebirdchecklist()
- Adjacent Regions
- Hotspots in a region:
ebirdhotspotlist()
- Nearby hotspots:
ebirdhotspotlist()
- Hotspot Info:
ebirdregioninfo()
- eBird Taxonomy:
ebirdtaxonomy()
- Taxonomic Forms
- Taxonomy Versions:
ebirdtaxonomyversion()
- Taxonomic Groups
- Region Info:
ebirdregioninfo()
- Sub Region List:
ebirdsubregionlist()
- Please report any issues or bugs.
- License: MIT
- Get citation information for
rebird
in R doingcitation(package = 'rebird')
- Please note that the ‘rebird’ project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.