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

Install

You can install the stable version from CRAN

Or the development version from Github

install.packages("devtools")
devtools::install_github("ropensci/rebird")

Direct use of 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.

Sightings at location determined by latitude/longitude

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>

Recent observations at a region

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>

Recent observations at hotspots

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>

Nearest observations of a species

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>

Frequency of observations at hotspots or regions

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 rows

Recent notable sightings

Search 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>

Historic Observations

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>

Information on a given region or hotspot

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  49.6

or 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>

rebird and other packages

How to use rebird

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.

auk vs. rebird

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.

API requests covered by rebird

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!

data/obs

product

  • [ ] Top 100
  • [ ] Checklist feed on a date
  • [ ] Recent checklists feed
  • [ ] Regional statistics on a date
  • [ ] View Checklist BETA

ref/geo

  • [ ] Adjacent Regions

ref/hotspot

  • [ ] Hotspots in a region
  • [ ] Nearby hotspots

ref/taxonomy

  • [x] eBird Taxonomy: ebirdtaxonomy()
  • [ ] Taxonomic Forms
  • [ ] Taxonomy Versions
  • [ ] Taxonomic Groups

ref/region

Meta