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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

Or the development version from Github

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

Direct use of rebird

Load the package:

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 ?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: 16,513 x 14
#>    sciName comName speciesCode category taxonOrder bandingCodes comNameCodes
#>    <chr>   <chr>   <chr>       <chr>         <dbl> <chr>        <chr>       
#>  1 Struth… Common… ostric2     species           1 <NA>         COOS        
#>  2 Struth… Somali… ostric3     species           6 <NA>         SOOS        
#>  3 Struth… Common… y00934      slash             7 <NA>         SOOS,COOS   
#>  4 Rhea a… Greate… grerhe1     species           8 <NA>         GRRH        
#>  5 Rhea p… Lesser… lesrhe2     species          14 <NA>         LERH        
#>  6 Rhea p… Lesser… lesrhe4     issf             15 <NA>         LERH        
#>  7 Rhea p… Lesser… lesrhe3     issf             18 <NA>         LERH        
#>  8 Nothoc… Tawny-… tabtin1     species          19 <NA>         TBTI        
#>  9 Nothoc… Highla… higtin1     species          20 HITI         <NA>        
#> 10 Nothoc… Highla… higtin2     issf             21 <NA>         HITI        
#> # … with 16,503 more rows, and 7 more variables: sciNameCodes <chr>,
#> #   order <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: 17 x 13
#>    speciesCode comName sciName locId locName obsDt howMany   lat   lng obsValid
#>    <chr>       <chr>   <chr>   <chr> <chr>   <chr>   <int> <dbl> <dbl> <lgl>   
#>  1 amegfi      Americ… Spinus… L133… "545 R… 2021…       8  42.0 -76.1 TRUE    
#>  2 amegfi      Americ… Spinus… L197… "esthe… 2021…      12  42.1 -75.9 TRUE    
#>  3 amegfi      Americ… Spinus… L275… "Home " 2021…       8  42.1 -76.0 TRUE    
#>  4 amegfi      Americ… Spinus… L109… "Hillc… 2021…       1  42.2 -75.9 TRUE    
#>  5 amegfi      Americ… Spinus… L186… "Otsin… 2021…       1  42.1 -75.9 TRUE    
#>  6 amegfi      Americ… Spinus… L895… "Nowla… 2021…       2  42.1 -75.9 TRUE    
#>  7 amegfi      Americ… Spinus… L207… "Workw… 2021…       4  42.1 -75.9 TRUE    
#>  8 amegfi      Americ… Spinus… L133… "4457 … 2021…       2  42.0 -75.9 TRUE    
#>  9 amegfi      Americ… Spinus… L870… "325 D… 2021…       1  42.2 -76.0 TRUE    
#> 10 amegfi      Americ… Spinus… L121… "1312 … 2021…       3  42.1 -76.0 TRUE    
#> 11 amegfi      Americ… Spinus… L133… "216 W… 2021…       1  42.1 -76.0 TRUE    
#> 12 amegfi      Americ… Spinus… L524… "Victo… 2021…       4  42.1 -76.0 TRUE    
#> 13 amegfi      Americ… Spinus… L505… "Bolan… 2021…       1  42.2 -75.9 TRUE    
#> 14 amegfi      Americ… Spinus… L850… "Sandy… 2021…      20  42.1 -75.9 TRUE    
#> 15 amegfi      Americ… Spinus… L351… "Anson… 2021…      16  42.1 -76.1 TRUE    
#> 16 amegfi      Americ… Spinus… L270… "Gripp… 2021…       1  42.1 -76.1 TRUE    
#> 17 amegfi      Americ… Spinus… L564… "Kinne… 2021…       1  42.1 -76.2 TRUE    
#> # … with 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: 81 x 13
#>    speciesCode comName sciName locId locName obsDt howMany   lat   lng obsValid
#>    <chr>       <chr>   <chr>   <chr> <chr>   <chr>   <int> <dbl> <dbl> <lgl>   
#>  1 btbwar      Black-… Setoph… L577… Merrit… 2021…       1  28.6 -80.7 TRUE    
#>  2 btbwar      Black-… Setoph… L863… 104 7t… 2021…       1  32.0 -80.8 TRUE    
#>  3 btbwar      Black-… Setoph… L407… Thomps… 2021…       1  38.9 -77.1 TRUE    
#>  4 btbwar      Black-… Setoph… L193… Rye     2021…       1  43.0 -70.8 TRUE    
#>  5 btbwar      Black-… Setoph… L195… 1 My H… 2021…       1  27.0 -80.1 TRUE    
#>  6 btbwar      Black-… Setoph… L104… Feathe… 2021…       1  25.6 -80.3 TRUE    
#>  7 btbwar      Black-… Setoph… L324… Wither… 2021…       1  31.0 -82.9 TRUE    
#>  8 btbwar      Black-… Setoph… L128… Zoo Mi… 2021…       1  25.6 -80.4 TRUE    
#>  9 btbwar      Black-… Setoph… L992… Kendal… 2021…       1  25.7 -80.4 TRUE    
#> 10 btbwar      Black-… Setoph… L133… 603 S … 2021…       1  26.2 -98.2 TRUE    
#> # … with 71 more rows, and 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: 38 x 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… L993… Stewar… 2021…     300  42.5 -76.5 TRUE    
#>  2 mallar3     Mallard Anas p… L993… Stewar… 2021…      20  42.5 -76.5 TRUE    
#>  3 commer      Common… Mergus… L993… Stewar… 2021…       2  42.5 -76.5 TRUE    
#>  4 ribgul      Ring-b… Larus … L993… Stewar… 2021…      NA  42.5 -76.5 TRUE    
#>  5 hergul      Herrin… Larus … L993… Stewar… 2021…      NA  42.5 -76.5 TRUE    
#>  6 gbbgul      Great … Larus … L993… Stewar… 2021…       3  42.5 -76.5 TRUE    
#>  7 baleag      Bald E… Haliae… L993… Stewar… 2021…       1  42.5 -76.5 TRUE    
#>  8 eursta      Europe… Sturnu… L993… Stewar… 2021…      40  42.5 -76.5 TRUE    
#>  9 doccor      Double… Phalac… L993… Stewar… 2021…       5  42.5 -76.5 TRUE    
#> 10 ambduc      Americ… Anas r… L993… Stewar… 2021…       1  42.5 -76.5 TRUE    
#> # … with 28 more rows, and 3 more variables: obsReviewed <lgl>,
#> #   locationPrivate <lgl>, subId <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: 25 x 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… 2021…      34  42.2 -75.9 TRUE    
#>  2 cangoo      Canada… Branta… L186… Otsini… 2021…     117  42.1 -75.9 TRUE    
#>  3 cangoo      Canada… Branta… L186… Cheri … 2021…       4  42.1 -75.9 TRUE    
#>  4 cangoo      Canada… Branta… L809… Port D… 2021…      74  42.1 -75.9 TRUE    
#>  5 cangoo      Canada… Branta… L527… R Tee … 2021…     100  42.2 -75.9 TRUE    
#>  6 cangoo      Canada… Branta… L133… I-81 N… 2021…      45  42.1 -75.9 TRUE    
#>  7 cangoo      Canada… Branta… L245… Water … 2021…       3  42.1 -75.9 TRUE    
#>  8 cangoo      Canada… Branta… L116… Homest… 2021…     230  42.1 -76.0 TRUE    
#>  9 cangoo      Canada… Branta… L106… IBM CC… 2021…       1  42.1 -76.0 TRUE    
#> 10 cangoo      Canada… Branta… L273… Schnur… 2021…       2  42.1 -75.8 TRUE    
#> # … with 15 more rows, and 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: 3,578 x 13
#>    speciesCode comName sciName locId locName obsDt howMany   lat   lng obsValid
#>    <chr>       <chr>   <chr>   <chr> <chr>   <chr>   <int> <dbl> <dbl> <lgl>   
#>  1 foxsp1      Fox Sp… Passer… L382… Yard    2021…       1  42.2 -71.3 FALSE   
#>  2 foxsp1      Fox Sp… Passer… L276… Standi… 2021…       1  42.3 -71.3 FALSE   
#>  3 reshaw      Red-sh… Buteo … L575… The 20… 2021…       1  44.2 -69.4 FALSE   
#>  4 gadwal      Gadwall Mareca… L143… Holyok… 2021…       2  42.2 -72.6 FALSE   
#>  5 lbbgul      Lesser… Larus … L106… Goulds… 2021…       1  42.2 -71.4 FALSE   
#>  6 pinwar      Pine W… Setoph… L919… Northb… 2021…       1  42.1 -71.7 FALSE   
#>  7 bnhcow      Brown-… Moloth… L825… Westwo… 2021…       1  42.2 -71.2 FALSE   
#>  8 comred      Common… Acanth… L358… Fort H… 2021…       2  41.8 -70.0 FALSE   
#>  9 redcro10    Red Cr… Loxia … L480… West B… 2021…       2  41.7 -70.4 FALSE   
#> 10 foxsp1      Fox Sp… Passer… L276… Standi… 2021…       1  42.3 -71.3 FALSE   
#> # … with 3,568 more rows, and 3 more variables: obsReviewed <lgl>,
#> #   locationPrivate <lgl>, subId <chr>

or a region

ebirdnotable(locID = 'US-NY-109')
#> # A tibble: 81 x 13
#>    speciesCode comName sciName locId locName obsDt howMany   lat   lng obsValid
#>    <chr>       <chr>   <chr>   <chr> <chr>   <chr>   <int> <dbl> <dbl> <lgl>   
#>  1 blkvul      Black … Coragy… L212… Steven… 2021…       1  42.4 -76.4 FALSE   
#>  2 redcro      Red Cr… Loxia … L550… Cornel… 2021…       1  42.5 -76.5 FALSE   
#>  3 yerwar      Yellow… Setoph… L351… Fuerte… 2021…       1  42.5 -76.5 FALSE   
#>  4 redcro      Red Cr… Loxia … L123… Boyer … 2021…       5  42.3 -76.3 FALSE   
#>  5 whwcro      White-… Loxia … L550… Cornel… 2021…       2  42.5 -76.5 FALSE   
#>  6 x00684      Canvas… Aythya… L140… East S… 2021…       1  42.5 -76.5 FALSE   
#>  7 x00684      Canvas… Aythya… L140… East S… 2021…       1  42.5 -76.5 FALSE   
#>  8 blksco2     Black … Melani… L353… Salt P… 2021…       1  42.5 -76.5 FALSE   
#>  9 evegro      Evenin… Coccot… L133… 571 So… 2021…      17  42.3 -76.4 FALSE   
#> 10 hoared2     Hoary … Acanth… L686… George… 2021…       1  42.5 -76.3 FALSE   
#> # … with 71 more rows, and 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 x 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-… Anas c… L139… Lickin… 2019…       8  38.1 -78.7 TRUE    
#>  4 killde      Killde… Charad… L139… Lickin… 2019…       1  38.1 -78.7 TRUE    
#>  5 baleag      Bald E… 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      Caroli… Thryot… L139… Lickin… 2019…       1  38.1 -78.7 TRUE    
#>  8 whtspa      White-… Zonotr… L139… Lickin… 2019…       2  38.1 -78.7 TRUE    
#>  9 norcar      Northe… Cardin… L139… Lickin… 2019…       1  38.1 -78.7 TRUE    
#> 10 canvas      Canvas… Aythya… L331… Montic… 2019…      19  38.0 -78.5 TRUE    
#> # … with 3 more variables: obsReviewed <lgl>, locationPrivate <lgl>,
#> #   subId <chr>

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 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-b… Larus … L196… Vancou… 2019…       4  49.3 -123. TRUE    
#>  3 glwgul      Glauco… Larus … L196… Vancou… 2019…      29  49.3 -123. TRUE    
#>  4 norcro      Northw… Corvus… L196… Vancou… 2019…     100  49.3 -123. TRUE    
#>  5 bkcchi      Black-… Poecil… L196… Vancou… 2019…      16  49.3 -123. TRUE    
#>  6 bushti      Bushtit Psaltr… L196… Vancou… 2019…      20  49.3 -123. TRUE    
#>  7 pacwre1     Pacifi… Troglo… L196… Vancou… 2019…       1  49.3 -123. TRUE    
#>  8 houfin      House … Haemor… L196… Vancou… 2019…       2  49.3 -123. TRUE    
#>  9 purfin      Purple… Haemor… L196… Vancou… 2019…       3  49.3 -123. TRUE    
#> 10 amegfi      Americ… Spinus… L196… Vancou… 2019…      15  49.3 -123. TRUE    
#> 11 daejun      Dark-e… Junco … L196… Vancou… 2019…      37  49.3 -123. TRUE    
#> 12 sonspa      Song S… Melosp… L196… Vancou… 2019…      12  49.3 -123. TRUE    
#> 13 spotow      Spotte… Pipilo… L196… Vancou… 2019…       1  49.3 -123. TRUE    
#> 14 rewbla      Red-wi… Agelai… L196… Vancou… 2019…       6  49.3 -123. TRUE    
#> # … with 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 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>, locID <chr>, locName <chr>,
#> #   lat <dbl>, lng <dbl>, hierarchicalName <chr>

Obtain a list of eBird species codes for all species recorded in a region

ebirdregionspecies("GB-ENG-LND")
#> # A tibble: 304 x 1
#>    speciesCode
#>    <chr>      
#>  1 bahgoo     
#>  2 snogoo     
#>  3 gragoo     
#>  4 gwfgoo     
#>  5 tunbeg1    
#>  6 pifgoo     
#>  7 brant      
#>  8 bargoo     
#>  9 cangoo     
#> 10 rebgoo1    
#> # … with 294 more rows

or a hotspot

ebirdregionspecies("L5803024")
#> # A tibble: 156 x 1
#>    speciesCode
#>    <chr>      
#>  1 gragoo     
#>  2 gwfgoo     
#>  3 bargoo     
#>  4 cangoo     
#>  5 mutswa     
#>  6 egygoo     
#>  7 comshe     
#>  8 manduc     
#>  9 gargan     
#> 10 norsho     
#> # … with 146 more rows

Obtain a list of all subregions within an eBird region

ebirdsubregionlist("subnational1","US")
#> # A tibble: 51 x 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             
#> # … with 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 x 8
#>   locId  subId  userDisplayName  numSpecies obsDt obsTime subID loc             
#>   <chr>  <chr>  <chr>                 <int> <chr> <chr>   <chr> <chr>           
#> 1 L2073… S6617… David Wood               10 24 M… 14:47   S661… L207391,Mt. Aub…
#> 2 L2073… S6617… Sofia Prado-Irw…         15 24 M… 14:31   S661… L207391,Mt. Aub…
#> 3 L2073… S6619… Jeffrey Gantz            19 24 M… 13:30   S661… L207391,Mt. Aub…
#> 4 L2073… S6617… Ann Gurka                21 24 M… 13:00   S661… L207391,Mt. Aub…
#> 5 L2073… S7098… Barbara Olson            20 24 M… 10:30   S709… L207391,Mt. Aub…

Hotspots in a region or nearby coordinates

Obtain a list of hotspots within a region

ebirdhotspotlist("CA-NS-HL")
#> # A tibble: 220 x 9
#>    locId locName countryCode subnational1Code subnational2Code   lat   lng
#>    <chr> <chr>   <chr>       <chr>            <chr>            <dbl> <dbl>
#>  1 L233… Abraha… CA          CA-NS            CA-NS-HL          45.2 -62.6
#>  2 L700… Admira… CA          CA-NS            CA-NS-HL          44.7 -63.7
#>  3 L176… Admira… CA          CA-NS            CA-NS-HL          44.8 -63.1
#>  4 L584… Albro … CA          CA-NS            CA-NS-HL          44.7 -63.6
#>  5 L437… Aldern… CA          CA-NS            CA-NS-HL          44.7 -63.6
#>  6 L122… Armdal… CA          CA-NS            CA-NS-HL          44.6 -63.6
#>  7 L624… Atlant… CA          CA-NS            CA-NS-HL          44.7 -63.3
#>  8 L239… Bald R… CA          CA-NS            CA-NS-HL          44.5 -63.6
#>  9 L759… Bayers… CA          CA-NS            CA-NS-HL          44.6 -63.7
#> 10 L642… Beaufo… CA          CA-NS            CA-NS-HL          44.7 -63.5
#> # … with 210 more rows, and 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: 52 x 9
#>    locId locName countryCode subnational1Code subnational2Code   lat   lng
#>    <chr> <chr>   <chr>       <chr>            <chr>            <dbl> <dbl>
#>  1 L602… Algier… US          US-LA            US-LA-071         30.0 -90.1
#>  2 L388… Armstr… US          US-LA            US-LA-071         30.0 -90.1
#>  3 L727… Audubo… US          US-LA            US-LA-071         30.0 -90.0
#>  4 L666… BAEA N… US          US-LA            US-LA-087         30.0 -90.0
#>  5 L666… BAEA N… US          US-LA            US-LA-071         29.9 -90.0
#>  6 L242… Bayou … US          US-LA            US-LA-071         30.0 -90.0
#>  7 L725… Bayou … US          US-LA            US-LA-071         30.1 -89.9
#>  8 L727… Chalme… US          US-LA            US-LA-087         29.9 -90.0
#>  9 L453… City P… US          US-LA            US-LA-071         30.0 -90.1
#> 10 L522… City P… US          US-LA            US-LA-071         30.0 -90.1
#> # … with 42 more rows, and 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

product

ref/geo

  • [ ] Adjacent Regions

ref/hotspot

ref/taxonomy

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

ref/region

Meta