rebird: wrapper to the eBird API

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

Install

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")

Direct use of `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.

eBird Taxonomy

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()

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: 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>

Recent observations at a region

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>

Recent observations at hotspots

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>

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: 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>

Recent notable sightings

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>

Historic Observations

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>

Information on a given region or hotspot

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

Checklist Feed

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…

View Checklist

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>

Hotspots in a region or nearby coordinates

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>

`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

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()

product

Top 100
Checklist feed on a date: ebirdchecklistfeed()
Regional statistics on a date
Species list for a region: ebirdregionspecies()
View Checklist: ebirdchecklist()

ref/geo

Adjacent Regions

ref/hotspot

Hotspots in a region: ebirdhotspotlist()
Nearby hotspots: ebirdhotspotlist()
Hotspot Info: ebirdregioninfo()

ref/taxonomy

eBird Taxonomy: ebirdtaxonomy()
Taxonomic Forms
Taxonomy Versions: ebirdtaxonomyversion()
Taxonomic Groups

ref/region

Region Info: ebirdregioninfo()
Sub Region List: ebirdsubregionlist()