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: http://www.ebird.org
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
has been updated and thus there are a couple major changes in the way
rebird works. API requests to eBird now require 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
https://csgillespie.github.io/efficientR/r-startup.html 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.
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: 24 x 12
#> speciesCode comName sciName locId locName obsDt howMany lat lng
#> <chr> <chr> <chr> <chr> <chr> <chr> <int> <dbl> <dbl>
#> 1 amegfi Americ… Spinus… L100… Bare V… 2019… 7 41.8 -75.9
#> 2 amegfi Americ… Spinus… L447… Bingha… 2019… 6 42.1 -76.0
#> 3 amegfi Americ… Spinus… L275… "Home " 2019… 1 42.1 -76.0
#> 4 amegfi Americ… Spinus… L505… Boland… 2019… 1 42.2 -75.9
#> 5 amegfi Americ… Spinus… L351… Anson … 2019… 25 42.1 -76.1
#> 6 amegfi Americ… Spinus… L524… Victor… 2019… 3 42.1 -76.0
#> 7 amegfi Americ… Spinus… L846… 31 Pul… 2019… 2 42.2 -76.2
#> 8 amegfi Americ… Spinus… L217… Vestal 2019… 11 42.1 -76.0
#> 9 amegfi Americ… Spinus… L211… Tri-Ci… 2019… 2 42.1 -76.1
#> 10 amegfi Americ… Spinus… L166… Chugnu… 2019… NA 42.1 -76.0
#> # … with 14 more rows, and 3 more variables: obsValid <lgl>,
#> # obsReviewed <lgl>, locationPrivate <lgl>Search for bird occurrences by region and species name
ebirdregion(loc = 'US', species = 'btbwar')
#> # A tibble: 1,428 x 12
#> speciesCode comName sciName locId locName obsDt howMany lat lng
#> <chr> <chr> <chr> <chr> <chr> <chr> <int> <dbl> <dbl>
#> 1 btbwar Black-… Setoph… L100… 3907 B… 2019… 2 30.3 -81.7
#> 2 btbwar Black-… Setoph… L681… Mariti… 2019… 2 28.3 -80.6
#> 3 btbwar Black-… Setoph… L108… Jarvis… 2019… 1 32.2 -80.7
#> 4 btbwar Black-… Setoph… L100… "Parki… 2019… 2 26.1 -80.1
#> 5 btbwar Black-… Setoph… L616… Lake L… 2019… 2 35.9 -78.7
#> 6 btbwar Black-… Setoph… L127… Fort Z… 2019… 1 24.5 -81.8
#> 7 btbwar Black-… Setoph… L344… Paynes… 2019… 1 29.6 -82.3
#> 8 btbwar Black-… Setoph… L207… Wellfl… 2019… 1 41.9 -70.0
#> 9 btbwar Black-… Setoph… L643… 234 SW… 2019… 2 26.1 -80.2
#> 10 btbwar Black-… Setoph… L766… Kendal… 2019… 3 25.7 -80.4
#> # … with 1,418 more rows, and 3 more variables: obsValid <lgl>,
#> # obsReviewed <lgl>, locationPrivate <lgl>Search for bird occurrences by a given hotspot
ebirdregion(loc = 'L99381')
#> # A tibble: 67 x 12
#> speciesCode comName sciName locId locName obsDt howMany lat lng
#> <chr> <chr> <chr> <chr> <chr> <chr> <int> <dbl> <dbl>
#> 1 cangoo Canada… Branta… L993… Stewar… 2019… 6 42.5 -76.5
#> 2 mallar3 Mallard Anas p… L993… Stewar… 2019… 5 42.5 -76.5
#> 3 redhea Redhead Aythya… L993… Stewar… 2019… 1 42.5 -76.5
#> 4 commer Common… Mergus… L993… Stewar… 2019… 6 42.5 -76.5
#> 5 ribgul Ring-b… Larus … L993… Stewar… 2019… 80 42.5 -76.5
#> 6 hergul Herrin… Larus … L993… Stewar… 2019… 10 42.5 -76.5
#> 7 lbbgul Lesser… Larus … L993… Stewar… 2019… 1 42.5 -76.5
#> 8 gbbgul Great … Larus … L993… Stewar… 2019… 1 42.5 -76.5
#> 9 doccor Double… Phalac… L993… Stewar… 2019… 200 42.5 -76.5
#> 10 amecro Americ… Corvus… L993… Stewar… 2019… 1 42.5 -76.5
#> # … with 57 more rows, and 3 more variables: obsValid <lgl>,
#> # obsReviewed <lgl>, locationPrivate <lgl>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: 35 x 12
#> speciesCode comName sciName locId locName obsDt howMany lat lng
#> <chr> <chr> <chr> <chr> <chr> <chr> <int> <dbl> <dbl>
#> 1 cangoo Canada… Branta… L207… Workwa… 2019… 1 42.1 -75.9
#> 2 cangoo Canada… Branta… L465… "Bingh… 2019… 120 42.1 -75.9
#> 3 cangoo Canada… Branta… L274… River … 2019… 20 42.1 -76.0
#> 4 cangoo Canada… Branta… L255… Wall S… 2019… 1 42.1 -75.9
#> 5 cangoo Canada… Branta… L147… Quaker… 2019… 2 42.0 -75.9
#> 6 cangoo Canada… Branta… L978… Murphy… 2019… NA 42.1 -76.0
#> 7 cangoo Canada… Branta… L245… Water … 2019… 20 42.1 -75.9
#> 8 cangoo Canada… Branta… L446… PA-SQ-… 2019… 25 41.8 -75.9
#> 9 cangoo Canada… Branta… L179… Joyce … 2019… 6 41.8 -75.9
#> 10 cangoo Canada… Branta… L186… Cheri … 2019… 30 42.1 -75.9
#> # … with 25 more rows, and 3 more variables: obsValid <lgl>,
#> # obsReviewed <lgl>, locationPrivate <lgl>Obtain historical frequencies of bird occurrences by hotspot or region
ebirdfreq(loctype = 'hotspots', loc = 'L196159')
#> # A tibble: 9,408 x 4
#> comName monthQt frequency sampleSize
#> <chr> <chr> <dbl> <dbl>
#> 1 Snow Goose January-1 0 33
#> 2 Greater White-fronted Goose January-1 0 33
#> 3 Cackling Goose January-1 0 33
#> 4 Canada Goose January-1 0 33
#> 5 Cackling/Canada Goose January-1 0 33
#> 6 Trumpeter Swan January-1 0 33
#> 7 Wood Duck January-1 0.152 33
#> 8 Blue-winged Teal January-1 0 33
#> 9 Cinnamon Teal January-1 0 33
#> 10 Blue-winged/Cinnamon Teal January-1 0 33
#> # … with 9,398 more rowsSearch for notable sightings at a given latitude and longitude
ebirdnotable(lat = 42, lng = -70)
#> # A tibble: 1,747 x 12
#> speciesCode comName sciName locId locName obsDt howMany lat lng
#> <chr> <chr> <chr> <chr> <chr> <chr> <int> <dbl> <dbl>
#> 1 chiswi Chimne… Chaetu… L392… North … 2019… 11 41.3 -70.1
#> 2 leasan Least … Calidr… L707… Hell's… 2019… 2 42.7 -72.5
#> 3 semsan Semipa… Calidr… L707… Hell's… 2019… 1 42.7 -72.5
#> 4 pinwar Pine W… Setoph… L280… Herman… 2019… 1 42.3 -72.3
#> 5 trokin Tropic… Tyrann… L593… Rock M… 2019… 1 42.4 -71.2
#> 6 trokin Tropic… Tyrann… L593… Rock M… 2019… 1 42.4 -71.2
#> 7 trokin Tropic… Tyrann… L593… Rock M… 2019… 1 42.4 -71.2
#> 8 rehwoo Red-he… Melane… L633… Burley… 2019… 1 43.1 -71.0
#> 9 trokin Tropic… Tyrann… L593… Rock M… 2019… 1 42.4 -71.2
#> 10 reevir1 Red-ey… Vireo … L207… Manome… 2019… 1 41.9 -70.5
#> # … with 1,737 more rows, and 3 more variables: obsValid <lgl>,
#> # obsReviewed <lgl>, locationPrivate <lgl>or a region
ebirdnotable(locID = 'US-NY-109')
#> # A tibble: 55 x 12
#> speciesCode comName sciName locId locName obsDt howMany lat lng
#> <chr> <chr> <chr> <chr> <chr> <chr> <int> <dbl> <dbl>
#> 1 woothr Wood T… Hyloci… L281… Cornel… 2019… 1 42.5 -76.5
#> 2 whevir White-… Vireo … L100… 210 Fi… 2019… 1 42.4 -76.5
#> 3 whevir White-… Vireo … L100… 204 Fi… 2019… 1 42.4 -76.5
#> 4 norpar Northe… Setoph… L100… stakeo… 2019… 1 42.4 -76.5
#> 5 whevir White-… Vireo … L100… stakeo… 2019… 1 42.4 -76.5
#> 6 whevir White-… Vireo … L100… stakeo… 2019… 1 42.4 -76.5
#> 7 norpar Northe… Setoph… L100… 118 Fi… 2019… 1 42.4 -76.5
#> 8 whevir White-… Vireo … L100… 118 Fi… 2019… 1 42.4 -76.5
#> 9 whevir White-… Vireo … L100… 201–29… 2019… 1 42.4 -76.5
#> 10 whevir White-… Vireo … L100… 201–29… 2019… 1 42.4 -76.5
#> # … with 45 more rows, and 3 more variables: obsValid <lgl>,
#> # obsReviewed <lgl>, locationPrivate <lgl>Search for historic observations on a date at a region
ebirdhistorical(loc = 'US-VA-003', date = '2019-02-14',max = 10)
#> # A tibble: 10 x 12
#> speciesCode comName sciName locId locName obsDt howMany lat lng
#> <chr> <chr> <chr> <chr> <chr> <chr> <int> <dbl> <dbl>
#> 1 cangoo Canada… Branta… L139… Lickin… 2019… 30 38.1 -78.7
#> 2 mallar3 Mallard Anas p… L139… Lickin… 2019… 5 38.1 -78.7
#> 3 gnwtea Green-… Anas c… L139… Lickin… 2019… 8 38.1 -78.7
#> 4 killde Killde… Charad… L139… Lickin… 2019… 1 38.1 -78.7
#> 5 baleag Bald E… Haliae… L139… Lickin… 2019… 1 38.1 -78.7
#> 6 belkin1 Belted… Megace… L139… Lickin… 2019… 1 38.1 -78.7
#> 7 carwre Caroli… Thryot… L139… Lickin… 2019… 1 38.1 -78.7
#> 8 whtspa White-… Zonotr… L139… Lickin… 2019… 2 38.1 -78.7
#> 9 norcar Northe… Cardin… L139… Lickin… 2019… 1 38.1 -78.7
#> 10 canvas Canvas… Aythya… L331… Montic… 2019… 19 38.0 -78.5
#> # … with 3 more variables: obsValid <lgl>, obsReviewed <lgl>,
#> # locationPrivate <lgl>or a hotspot
ebirdhistorical(loc = 'L196159', date = '2019-02-14', fieldSet = 'full')
#> # A tibble: 14 x 27
#> speciesCode comName sciName locId locName obsDt howMany lat lng
#> <chr> <chr> <chr> <chr> <chr> <chr> <int> <dbl> <dbl>
#> 1 annhum Anna's… Calypt… L196… Vancou… 2019… 4 49.3 -123.
#> 2 ribgul Ring-b… Larus … L196… Vancou… 2019… 4 49.3 -123.
#> 3 glwgul Glauco… Larus … L196… Vancou… 2019… 29 49.3 -123.
#> 4 norcro Northw… Corvus… L196… Vancou… 2019… 100 49.3 -123.
#> 5 bkcchi Black-… Poecil… L196… Vancou… 2019… 16 49.3 -123.
#> 6 bushti Bushtit Psaltr… L196… Vancou… 2019… 20 49.3 -123.
#> 7 pacwre1 Pacifi… Troglo… L196… Vancou… 2019… 1 49.3 -123.
#> 8 houfin House … Haemor… L196… Vancou… 2019… 2 49.3 -123.
#> 9 purfin Purple… Haemor… L196… Vancou… 2019… 3 49.3 -123.
#> 10 amegfi Americ… Spinus… L196… Vancou… 2019… 15 49.3 -123.
#> 11 daejun Dark-e… Junco … L196… Vancou… 2019… 37 49.3 -123.
#> 12 sonspa Song S… Melosp… L196… Vancou… 2019… 12 49.3 -123.
#> 13 spotow Spotte… Pipilo… L196… Vancou… 2019… 1 49.3 -123.
#> 14 rewbla Red-wi… Agelai… L196… Vancou… 2019… 6 49.3 -123.
#> # … with 18 more variables: obsValid <lgl>, obsReviewed <lgl>,
#> # locationPrivate <lgl>, subnational2Code <chr>, subnational2Name <chr>,
#> # subnational1Code <chr>, subnational1Name <chr>, countryCode <chr>,
#> # countryName <chr>, userDisplayName <chr>, subId <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 x 5
#> region minX maxX minY maxY
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 Metro Vancouver, British Columbia, Canada -123. -122. 49.0 49.6or hotspot
ebirdregioninfo("L196159")
#> # A tibble: 1 x 16
#> locId name latitude longitude countryCode countryName subnational1Name
#> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr>
#> 1 L196… Vanc… 49.3 -123. CA Canada British Columbia
#> # … with 9 more variables: subnational1Code <chr>, subnational2Code <chr>,
#> # subnational2Name <chr>, isHotspot <lgl>, locName <chr>, lat <dbl>,
#> # lng <dbl>, hierarchicalName <chr>, locID <chr>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() - Historic observations on a date:
ebirdhistorical()
- Top 100
- Checklist feed on a date
- Recent checklists feed
- Regional statistics on a date
- View Checklist BETA
- Adjacent Regions
- Hotspots in a region
- Nearby hotspots
- eBird Taxonomy:
ebirdtaxonomy() - Taxonomic Forms
- Taxonomy Versions
- Taxonomic Groups
- Hotspot Info:
ebirdregioninfo() - Region Info:
ebirdregioninfo() - Sub Region List
- Please report any issues or bugs.
- License: MIT
- Get citation information for
rebirdin 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.
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