Intro to the rebird package

¶ Intro to the rebird package A programmatic interface to the eBird database. Find out more about eBird at their website. Installation
¶ 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")`
¶ Then load the package into the R sesssion	`library("rebird")`
¶ Usage 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: 45 x 12 ## speciesCode comName sciName locId locName obsDt howMany lat lng ## <chr> <chr> <chr> <chr> <chr> <chr> <int> <dbl> <dbl> ## 1 amegfi America… Spinus … L447… Binghamt… 2018… 2 42.1 -76.0 ## 2 amegfi America… Spinus … L207… Workwalk 2018… 1 42.1 -75.9 ## 3 amegfi America… Spinus … L495… Binghamt… 2018… 1 42.1 -76.0 ## 4 amegfi America… Spinus … L527… R Tee Go… 2018… 1 42.2 -75.9 ## 5 amegfi America… Spinus … L795… US-New Y… 2018… 7 42.1 -76.0 ## 6 amegfi America… Spinus … L978… Murphys … 2018… 5 42.1 -76.0 ## 7 amegfi America… Spinus … L209… Aquaterr… 2018… 9 42.0 -75.9 ## 8 amegfi America… Spinus … L320… Hillcres… 2018… 1 42.2 -75.9 ## 9 amegfi America… Spinus … L285… Camp Sus… 2018… 1 42.0 -75.9 ## 10 amegfi America… Spinus … L519… IBM Glen… 2018… 3 42.1 -76.0 ## # ... with 35 more rows, and 3 more variables: obsValid <lgl>, ## # obsReviewed <lgl>, locationPrivate <lgl>
¶ Same, but with additional parameter settings, returning only 10 records, including provisional records, and hotspot records.	`ebirdgeo(lat = 42, lng = -76, max = 10, includeProvisional = TRUE, hotspot = TRUE)` ## # 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 … L1869… Cheri A… 2018… 4 42.1 -75.9 ## 2 mallar3 Mallard Anas pl… L1869… Cheri A… 2018… 20 42.1 -75.9 ## 3 rocpig Rock Pi… Columba… L1869… Cheri A… 2018… 3 42.1 -75.9 ## 4 doccor Double-… Phalacr… L1869… Cheri A… 2018… 5 42.1 -75.9 ## 5 grbher3 Great B… Ardea h… L1869… Cheri A… 2018… 1 42.1 -75.9 ## 6 greegr Great E… Ardea a… L1869… Cheri A… 2018… 5 42.1 -75.9 ## 7 blujay Blue Jay Cyanoci… L1869… Cheri A… 2018… 1 42.1 -75.9 ## 8 amecro America… Corvus … L1869… Cheri A… 2018… 1 42.1 -75.9 ## 9 grycat Gray Ca… Dumetel… L1869… Cheri A… 2018… 1 42.1 -75.9 ## 10 normoc Norther… Mimus p… L1869… Cheri A… 2018… 2 42.1 -75.9 ## # ... with 3 more variables: obsValid <lgl>, obsReviewed <lgl>, ## # locationPrivate <lgl>
¶ Recent sightings from location IDs
¶ Search for bird occurrences for in a hotspot using its ID	`ebirdregion(loc = 'L99381')` ## # A tibble: 64 x 12 ## speciesCode comName sciName locId locName obsDt howMany lat lng ## <chr> <chr> <chr> <chr> <chr> <chr> <int> <dbl> <dbl> ## 1 wooduc Wood Duck Aix spon… L993… Stewar… 2018… 4 42.5 -76.5 ## 2 mallar3 Mallard Anas pla… L993… Stewar… 2018… 16 42.5 -76.5 ## 3 ambduc American… Anas rub… L993… Stewar… 2018… 1 42.5 -76.5 ## 4 rocpig Rock Pig… Columba … L993… Stewar… 2018… 4 42.5 -76.5 ## 5 ribgul Ring-bil… Larus de… L993… Stewar… 2018… 110 42.5 -76.5 ## 6 hergul Herring … Larus ar… L993… Stewar… 2018… 1 42.5 -76.5 ## 7 lbbgul Lesser B… Larus fu… L993… Stewar… 2018… 1 42.5 -76.5 ## 8 gbbgul Great Bl… Larus ma… L993… Stewar… 2018… 5 42.5 -76.5 ## 9 doccor Double-c… Phalacro… L993… Stewar… 2018… 118 42.5 -76.5 ## 10 grnher Green He… Butoride… L993… Stewar… 2018… 1 42.5 -76.5 ## # ... with 54 more rows, and 3 more variables: obsValid <lgl>, ## # obsReviewed <lgl>, locationPrivate <lgl>
¶ Search by location ID and species name, as well as some additional parameter settings	`ebirdregion(loc = 'L99381', species = species_code('larus delawarensis'), max = 10, provisional = TRUE, hotspot = TRUE)` `## Ring-billed Gull (Larus delawarensis): ribgul` `## # A tibble: 1 x 12 ## speciesCode comName sciName locId locName obsDt howMany lat lng ## <chr> <chr> <chr> <chr> <chr> <chr> <int> <dbl> <dbl> ## 1 ribgul Ring-bil… Larus de… L993… Stewar… 2018-… 110 42.5 -76.5 ## # ... with 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: 27 x 12 ## speciesCode comName sciName locId locName obsDt howMany lat lng ## <chr> <chr> <chr> <chr> <chr> <chr> <int> <dbl> <dbl> ## 1 cangoo Canada … Branta … L186… Cheri A.… 2018… 4 42.1 -75.9 ## 2 cangoo Canada … Branta … L207… Workwalk 2018… 26 42.1 -75.9 ## 3 cangoo Canada … Branta … L287… Vestal R… 2018… 49 42.1 -76.0 ## 4 cangoo Canada … Branta … L527… R Tee Go… 2018… 53 42.2 -75.9 ## 5 cangoo Canada … Branta … L728… State Ga… 2018… 23 41.9 -75.7 ## 6 cangoo Canada … Branta … L504… Rt. 12A … 2018… 65 42.2 -75.9 ## 7 cangoo Canada … Branta … L468… "Boland … 2018… 12 42.2 -75.9 ## 8 cangoo Canada … Branta … L285… Camp Sus… 2018… 2 42.0 -75.9 ## 9 cangoo Canada … Branta … L447… Binghamt… 2018… 2 42.1 -76.0 ## 10 cangoo Canada … Branta … L501… William … 2018… 50 42.1 -76.0 ## # ... with 17 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 = species_code('Setophaga caerulescens'))` `## Black-throated Blue Warbler (Setophaga caerulescens): btbwar` ## # A tibble: 1,041 x 12 ## speciesCode comName sciName locId locName obsDt howMany lat lng ## <chr> <chr> <chr> <chr> <chr> <chr> <int> <dbl> <dbl> ## 1 btbwar Black-t… Setopha… L3572… Cornell… 2018… 2 42.4 -76.5 ## 2 btbwar Black-t… Setopha… L7962… Pisgah … 2018… 1 36.2 -81.7 ## 3 btbwar Black-t… Setopha… L2785… Kiwanis… 2018… 1 27.0 -82.1 ## 4 btbwar Black-t… Setopha… L1109… Enchant… 2018… 3 25.9 -80.2 ## 5 btbwar Black-t… Setopha… L7814… Wissahi… 2018… 2 40.1 -75.2 ## 6 btbwar Black-t… Setopha… L5987… Codding… 2018… 2 42.3 -76.4 ## 7 btbwar Black-t… Setopha… L4023… Home - … 2018… 1 40.2 -75.4 ## 8 btbwar Black-t… Setopha… L5862… Indrio … 2018… 1 27.5 -80.4 ## 9 btbwar Black-t… Setopha… L1301… Ashland… 2018… 2 39.8 -75.7 ## 10 btbwar Black-t… Setopha… L1877… Pinecra… 2018… 1 27.3 -82.5 ## # ... with 1,031 more rows, and 3 more variables: obsValid <lgl>, ## # obsReviewed <lgl>, locationPrivate <lgl>
¶ Search by location ID and species name, as well as some additional parameter settings. Note that we use `US-OH` to represent Ohio within the US.	`ebirdregion(loc = 'US-OH', max = 10, provisional = TRUE, hotspot = TRUE)` ## # A tibble: 10 x 12 ## speciesCode comName sciName locId locName obsDt howMany lat lng ## <chr> <chr> <chr> <chr> <chr> <chr> <int> <dbl> <dbl> ## 1 belkin1 Belted … Megacer… L416… Big Cree… 2018… 1 41.4 -81.8 ## 2 norcar Norther… Cardina… L416… Big Cree… 2018… 2 41.4 -81.8 ## 3 greegr Great E… Ardea a… L416… Big Cree… 2018… 6 41.4 -81.8 ## 4 grbher3 Great B… Ardea h… L416… Big Cree… 2018… 3 41.4 -81.8 ## 5 cangoo Canada … Branta … L416… Big Cree… 2018… 54 41.4 -81.8 ## 6 blujay Blue Jay Cyanoci… L416… Big Cree… 2018… 2 41.4 -81.8 ## 7 amecro America… Corvus … L500… Hueston … 2018… 1 39.6 -84.8 ## 8 carwre Carolin… Thryoth… L500… Hueston … 2018… 3 39.6 -84.8 ## 9 bongul Bonapar… Chroico… L500… Hueston … 2018… 1 39.6 -84.8 ## 10 barswa Barn Sw… Hirundo… L500… Hueston … 2018… 1 39.6 -84.8 ## # ... with 3 more variables: obsValid <lgl>, obsReviewed <lgl>, ## # locationPrivate <lgl>
¶ Frequency of observations at hotspots or regions
¶ Obtain historical frequencies of bird occurrences at a given hotspot	`ebirdfreq(loctype = 'hotspots', loc = 'L196159')` ## # A tibble: 9,072 x 4 ## comName monthQt frequency sampleSize ## <chr> <chr> <dbl> <dbl> ## 1 Snow Goose January-1 0. 27. ## 2 Greater White-fronted Goose January-1 0. 27. ## 3 Cackling Goose January-1 0. 27. ## 4 Canada Goose January-1 0. 27. ## 5 Cackling/Canada Goose January-1 0. 27. ## 6 Trumpeter Swan January-1 0. 27. ## 7 Wood Duck January-1 0.185 27. ## 8 Blue-winged Teal January-1 0. 27. ## 9 Cinnamon Teal January-1 0. 27. ## 10 Blue-winged/Cinnamon Teal January-1 0. 27. ## # ... with 9,062 more rows
¶ Same, but in wide format (for making bar charts)	`ebirdfreq(loctype = 'hotspots', loc = 'L196159', long = FALSE)` ## # A tibble: 190 x 49 ## comName `January-1` `January-2` `January-3` `January-4` `February-1` ## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> ## 1 Sample Si… 27.0 27.0 39.0 102. 41.0 ## 2 Snow Goose 0. 0. 0. 0. 0. ## 3 Greater W… 0. 0. 0. 0. 0. ## 4 Cackling … 0. 0. 0. 0. 0. ## 5 Canada Go… 0. 0. 0.00150 0.0980 0.220 ## 6 Cackling/… 0. 0. 0. 0. 0. ## 7 Trumpeter… 0. 0. 0. 0. 0. ## 8 Wood Duck 0.185 0.0370 0. 0.0196 0.0488 ## 9 Blue-wing… 0. 0. 0. 0. 0. ## 10 Cinnamon … 0. 0. 0. 0. 0. ## # ... with 180 more rows, and 43 more variables: `February-2` <dbl>, ## # `February-3` <dbl>, `February-4` <dbl>, `March-1` <dbl>, ## # `March-2` <dbl>, `March-3` <dbl>, `March-4` <dbl>, `April-1` <dbl>, ## # `April-2` <dbl>, `April-3` <dbl>, `April-4` <dbl>, `May-1` <dbl>, ## # `May-2` <dbl>, `May-3` <dbl>, `May-4` <dbl>, `June-1` <dbl>, ## # `June-2` <dbl>, `June-3` <dbl>, `June-4` <dbl>, `July-1` <dbl>, ## # `July-2` <dbl>, `July-3` <dbl>, `July-4` <dbl>, `August-1` <dbl>, ## # `August-2` <dbl>, `August-3` <dbl>, `August-4` <dbl>, ## # `September-1` <dbl>, `September-2` <dbl>, `September-3` <dbl>, ## # `September-4` <dbl>, `October-1` <dbl>, `October-2` <dbl>, ## # `October-3` <dbl>, `October-4` <dbl>, `November-1` <dbl>, ## # `November-2` <dbl>, `November-3` <dbl>, `November-4` <dbl>, ## # `December-1` <dbl>, `December-2` <dbl>, `December-3` <dbl>, ## # `December-4` <dbl>
¶ Obtain frequency data for a given state	`ebirdfreq(loctype = 'states', loc = 'CA-BC')` ## # A tibble: 35,424 x 4 ## comName monthQt frequency sampleSize ## <chr> <chr> <dbl> <dbl> ## 1 Fulvous Whistling-Duck January… 0. 14197. ## 2 Emperor Goose January… 0.00150 14197. ## 3 Snow Goose January… 0.0279 14197. ## 4 Ross's Goose January… 0. 14197. ## 5 Snow x Ross's Goose (hybrid) January… 0. 14197. ## 6 Snow/Ross's Goose January… 0. 14197. ## 7 Swan Goose (Domestic type) January… 0.0000704 14197. ## 8 Graylag x Swan Goose (Domestic type) (hy… January… 0. 14197. ## 9 Greater White-fronted Goose January… 0.00768 14197. ## 10 Pink-footed Goose January… 0. 14197. ## # ... with 35,414 more rows
¶ Or county	`ebirdfreq(loctype = 'counties', loc = 'CA-BC-GV')` ## # A tibble: 24,624 x 4 ## comName monthQt frequency sampleSize ## <chr> <chr> <dbl> <dbl> ## 1 Emperor Goose January-1 0. 4714. ## 2 Snow Goose January-1 0.0653 4714. ## 3 Ross's Goose January-1 0. 4714. ## 4 Snow/Ross's Goose January-1 0. 4714. ## 5 Greater White-fronted Goose January-1 0.00530 4714. ## 6 Brant January-1 0.0255 4714. ## 7 Cackling Goose January-1 0.0119 4714. ## 8 Canada Goose January-1 0.200 4714. ## 9 Graylag x Canada Goose (hybrid) January-1 0. 4714. ## 10 Cackling/Canada Goose January-1 0.00170 4714. ## # ... with 24,614 more rows
¶ Obtain frequency data within a range of years and months	`ebirdfreq(loctype = 'hotspots', loc = 'L196159', startyear = 2010, endyear = 2014, startmonth = 1, endmonth = 3)` ## # A tibble: 3,792 x 4 ## comName monthQt frequency sampleSize ## <chr> <chr> <dbl> <dbl> ## 1 Canada Goose January-1 0. 10. ## 2 Wood Duck January-1 0.400 10. ## 3 Northern Shoveler January-1 0.800 10. ## 4 Gadwall January-1 0. 10. ## 5 Eurasian Wigeon January-1 0.400 10. ## 6 American Wigeon January-1 1.00 10. ## 7 Eurasian x American Wigeon (hybrid) January-1 0. 10. ## 8 Mallard January-1 1.00 10. ## 9 Northern Pintail January-1 0. 10. ## 10 Green-winged Teal January-1 0. 10. ## # ... with 3,782 more rows
¶ Recent notable sightings
¶ Search for notable sightings at a given latitude and longitude	`ebirdnotable(lat = 42, lng = -70)` ## # A tibble: 802 x 12 ## speciesCode comName sciName locId locName obsDt howMany lat lng ## <chr> <chr> <chr> <chr> <chr> <chr> <int> <dbl> <dbl> ## 1 rthhum Ruby-th… Archilo… L584… US-New H… 2018… 1 42.9 -71.0 ## 2 ameoys America… Haemato… L765… Basket I… 2018… 2 43.5 -70.4 ## 3 rthhum Ruby-th… Archilo… L497… stakeout… 2018… 1 42.3 -71.6 ## 4 ycnher Yellow-… Nyctana… L382… Lake War… 2018… 1 42.4 -72.6 ## 5 ovenbi1 Ovenbird Seiurus… L168… Brenton … 2018… 1 41.5 -71.4 ## 6 hoowar Hooded … Setopha… L514… 000 31 … 2018… 1 43.3 -71.0 ## 7 ycnher Yellow-… Nyctana… L796… Mt. Warn… 2018… 1 42.4 -72.6 ## 8 ycnher Yellow-… Nyctana… L796… Lake War… 2018… 1 42.4 -72.6 ## 9 ycnher Yellow-… Nyctana… L796… Lake War… 2018… 1 42.4 -72.6 ## 10 sora Sora Porzana… L420… Tiogue L… 2018… 1 41.7 -71.6 ## # ... with 792 more rows, and 3 more variables: obsValid <lgl>, ## # obsReviewed <lgl>, locationPrivate <lgl>
¶ or a region	`ebirdnotable(locID = 'US-NY-109')` ## # A tibble: 71 x 12 ## speciesCode comName sciName locId locName obsDt howMany lat lng ## <chr> <chr> <chr> <chr> <chr> <chr> <int> <dbl> <dbl> ## 1 buggna Blue-gra… Poliopt… L177… Sapsuck… 2018… 1 42.5 -76.4 ## 2 comgal1 Common G… Gallinu… L518… Hile Sc… 2018… 1 42.5 -76.4 ## 3 buggna1 Blue-gra… Poliopt… L124… Sapsuck… 2018… 1 42.5 -76.5 ## 4 buggna Blue-gra… Poliopt… L515… Sapsuck… 2018… 1 42.5 -76.5 ## 5 comnig Common N… Chordei… L518… Hile Sc… 2018… 1 42.5 -76.4 ## 6 blkvul Black Vu… Coragyp… L398… 14## Ha… 2018… 1 42.5 -76.5 ## 7 blkvul Black Vu… Coragyp… L286… Sapsuck… 2018… 1 42.5 -76.5 ## 8 blkvul Black Vu… Coragyp… L212… Stevens… 2018… 1 42.4 -76.4 ## 9 sora Sora Porzana… L594… Ridgewa… 2018… 1 42.3 -76.4 ## 10 conwar Connecti… Opororn… L446… Durland… 2018… 1 42.4 -76.4 ## # ... with 61 more rows, and 3 more variables: obsValid <lgl>, ## # obsReviewed <lgl>, locationPrivate <lgl>
¶ eBird taxonomy
¶ Returns a data.frame of all species in the eBird taxonomy for the given parameter inputs	`ebirdtaxonomy()` ## # A tibble: 16,248 x 14 ## sciName comName speciesCode category taxonOrder bandingCodes ## <chr> <chr> <chr> <chr> <dbl> <chr> ## 1 Struthio came… Common Ost… ostric2 species 1. <NA> ## 2 Struthio moly… Somali Ost… ostric3 species 6. <NA> ## 3 Struthio came… Common/Som… y00934 slash 7. <NA> ## 4 Rhea americana Greater Rh… grerhe1 species 8. <NA> ## 5 Rhea pennata Lesser Rhea lesrhe2 species 14. <NA> ## 6 Rhea pennata … Lesser Rhe… lesrhe4 issf 15. <NA> ## 7 Rhea pennata … Lesser Rhe… lesrhe3 issf 18. <NA> ## 8 Nothocercus j… Tawny-brea… tabtin1 species 19. <NA> ## 9 Nothocercus b… Highland T… higtin1 species 20. HITI ## 10 Nothocercus b… Highland T… higtin2 issf 21. <NA> ## # ... with 16,238 more rows, and 8 more variables: comNameCodes <chr>, ## # sciNameCodes <chr>, order <chr>, familyComName <chr>, ## # familySciName <chr>, reportAs <chr>, extinct <lgl>, extinctYear <int>
¶ Search for hybrid species only	`ebirdtaxonomy(cat = "hybrid")` ## # A tibble: 415 x 11 ## sciName comName speciesCode category taxonOrder bandingCodes ## <chr> <chr> <chr> <chr> <dbl> <chr> ## 1 Dendrocygna… Spotted x Wh… x00721 hybrid 219. <NA> ## 2 Dendrocygna… Black-bellie… x00775 hybrid 224. <NA> ## 3 Dendrocygna… Black-bellie… x00875 hybrid 226. <NA> ## 4 Anser caeru… Snow x Ross'… sxrgoo1 hybrid 243. SRGH ## 5 Anser anser… Graylag x Sw… x00776 hybrid 251. <NA> ## 6 Anser indic… Bar-headed x… x00755 hybrid 259. <NA> ## 7 Anser caeru… Snow x Great… x00627 hybrid 260. <NA> ## 8 Anser caeru… Snow Goose x… x00685 hybrid 280. <NA> ## 9 Anser brach… Pink-footed … x00756 hybrid 282. <NA> ## 10 Anser albif… Greater Whit… x00757 hybrid 283. <NA> ## # ... with 405 more rows, and 5 more variables: comNameCodes <chr>, ## # sciNameCodes <chr>, order <chr>, familyComName <chr>, ## # familySciName <chr>
¶ Check eBird region
¶ Obtain information on any region	`ebirdregioninfo(loc = '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`
¶

Intro to the rebird package

Installation

Usage

Sightings at location determined by latitude/longitude

Recent sightings from location IDs

Nearest observations of a species

Recent observations at a region

Frequency of observations at hotspots or regions

Recent notable sightings

eBird taxonomy

Check eBird region