Access iNaturalist data through APIs

Edmund Hart, Stéphane Guillou

2022-06-14

About

rinat is a wrapper for iNaturalist APIs for accessing the observations. The detailed documentation of the API is available on the iNaturalist website and is part of our larger species occurrence searching packages SPOCC.

Quickstart guide

Get observations

get_inat_obs() is the primary function that retrieves observations from iNaturalist. The text or taxon search can be refined by observation date, record quality and location.

It is recommended to set the quality argument to "research" in order to get more reliable data that has been validated by several contributors.

Other functions

Get information and observations by project

You can get all the observations for a project if you know its ID or name as an iNaturalist slug.

## Just get info about a project
vt_crows <- get_inat_obs_project("crows-in-vermont", type = "info", raw = FALSE)
#> 206 records
## Now get all the observations for that project
vt_crows_obs <- get_inat_obs_project(vt_crows$id, type = "observations")
#> 206 records
#> Getting records 0-200
#> Getting records up to 400
#> Done.
#> Note: mismatch between number of observations reported and returned by the API.

Get observation details

Detailed information about a specific observation can be retrieved by observation ID. The easiest way to get the ID is from a previous search for that taxon.

head(get_inat_obs_id(monarch_chrysalis$id[1]))
#> $id
#> [1] 121193310
#> 
#> $observed_on
#> [1] "2022-06-09"
#> 
#> $description
#> [1] "Hatched on 5/21, formed J and chrysalis both on 6/9 within about 12 hours, host was Asclepias syriaca"
#> 
#> $latitude
#> [1] "38.6252520294"
#> 
#> $longitude
#> [1] "-90.3803088003"
#> 
#> $map_scale
#> NULL

Get all observations by user

If you just want all the observations by a user you can download all their observations by user ID. A word of warning though, this can be quite large (easily into the 1000’s).

user_obs <- get_inat_obs_user(monarch_chrysalis$user_login[1], maxresults = 20)
head(user_obs)[,1:5]
#>                scientific_name                  datetime                description
#> 1                     Baptisia 2022-06-07 19:16:13 -0500   Large cultivar planting 
#> 2                        Salix 2022-06-07 18:45:13 -0500             Dixon Prairie 
#> 3        Tradescantia ohiensis 2022-06-07 18:46:09 -0500             Dixon Prairie 
#> 4             Silene latifolia 2022-06-07 18:46:31 -0500             Dixon Prairie 
#> 5                   Neuroterus 2022-06-07 18:48:00 -0500 Host plant Quercus bicolor
#> 6 Symphyotrichum novae-angliae 2022-06-07 18:51:00 -0500             Dixon Prairie 
#>                               place_guess latitude
#> 1 Chicago Botanic Garden, Glencoe, IL, US 42.14471
#> 2 Chicago Botanic Garden, Glencoe, IL, US 42.14246
#> 3 Chicago Botanic Garden, Glencoe, IL, US 42.14241
#> 4 Chicago Botanic Garden, Glencoe, IL, US 42.14238
#> 5 Chicago Botanic Garden, Glencoe, IL, US 42.14238
#> 6 Chicago Botanic Garden, Glencoe, IL, US 42.14263

Stats by taxa

Basic statistics are available for taxa counts by date, date range, place ID (numeric ID), or user ID (string). Only the top 5 species are listed.

## By date
counts <- get_inat_taxon_stats(date = "2020-06-14")
counts$total
#> [1] 25763
### Top 5 species
counts$species_counts
#>   count taxon.id           taxon.name taxon.rank taxon.rank_level taxon.default_name.id
#> 1   380    48484    Harmonia axyridis    species               10                 89147
#> 2   332    56057 Leucanthemum vulgare    species               10                924783
#> 3   330    52821 Achillea millefolium    species               10                942097
#> 4   319    51875   Trifolium pratense    species               10                942055
#> 5   304    55745     Trifolium repens    species               10                943715
#>   taxon.default_name.name taxon.default_name.is_valid taxon.default_name.lexicon
#> 1       Asian Lady Beetle                        TRUE                    English
#> 2             oxeye daisy                        TRUE                    English
#> 3           Common Yarrow                        TRUE                    English
#> 4              red clover                        TRUE                    English
#> 5            white clover                        TRUE                    English
#>                                                             taxon.image_url taxon.iconic_taxon_name
#> 1                 https://static.inaturalist.org/photos/30978499/square.jpg                 Insecta
#> 2 https://inaturalist-open-data.s3.amazonaws.com/photos/71002344/square.jpg                 Plantae
#> 3     https://inaturalist-open-data.s3.amazonaws.com/photos/4902/square.jpg                 Plantae
#> 4                 https://static.inaturalist.org/photos/38032773/square.jpg                 Plantae
#> 5 https://inaturalist-open-data.s3.amazonaws.com/photos/86716150/square.jpg                 Plantae
#>   taxon.conservation_status_name
#> 1                           <NA>
#> 2                           <NA>
#> 3                  least_concern
#> 4                  least_concern
#> 5                           <NA>
### Most common taxon ranks
counts$rank_counts
#> $species
#> [1] 18886
#> 
#> $genus
#> [1] 3645
#> 
#> $subspecies
#> [1] 758
#> 
#> $family
#> [1] 611
#> 
#> $subfamily
#> [1] 373
#> 
#> $tribe
#> [1] 338
#> 
#> $variety
#> [1] 233
#> 
#> $subgenus
#> [1] 159
#> 
#> $order
#> [1] 120
#> 
#> $hybrid
#> [1] 95
#> 
#> $superfamily
#> [1] 85
#> 
#> $section
#> [1] 84
#> 
#> $subtribe
#> [1] 80
#> 
#> $complex
#> [1] 76
#> 
#> $class
#> [1] 39
#> 
#> $suborder
#> [1] 39
#> 
#> $infraorder
#> [1] 29
#> 
#> $phylum
#> [1] 22
#> 
#> $subclass
#> [1] 20
#> 
#> $form
#> [1] 12
#> 
#> $subsection
#> [1] 9
#> 
#> $subphylum
#> [1] 8
#> 
#> $infraclass
#> [1] 6
#> 
#> $kingdom
#> [1] 5
#> 
#> $superorder
#> [1] 4
#> 
#> $genushybrid
#> [1] 3
#> 
#> $zoosection
#> [1] 3
#> 
#> $epifamily
#> [1] 2
#> 
#> $subterclass
#> [1] 2
#> 
#> $zoosubsection
#> [1] 2

Stats by user

Similar statistics can be gotten for users. The same input parameters can be used.

## By date
counts <- get_inat_user_stats(date = "2010-06-14")
counts$total
#> [1] 341
counts$most_observations[1:10,]
#>    count user.id      user.login       user.name
#> 1    129  245282  hughmcguinness Hugh McGuinness
#> 2     53  811118     sandbankspp                
#> 3     50 3334393 koniakin_serhii Serhii Koniakin
#> 4     34  541847      billhubick     Bill Hubick
#> 5     31    6930       tgosliner  Terry Gosliner
#> 6     31 2883853      linkmdavis      Link Davis
#> 7     30   46945             abe    T. Abe Lloyd
#> 8     26  280446         mtjones      Mike Jones
#> 9     25  761669 kathleenfspicer            <NA>
#> 10    21    2616     alice_abela     Alice Abela
#>                                                                     user.user_icon_url
#> 1   https://static.inaturalist.org/attachments/users/icons/245282/thumb.jpg?1475532481
#> 2  https://static.inaturalist.org/attachments/users/icons/811118/thumb.jpeg?1535236899
#> 3  https://static.inaturalist.org/attachments/users/icons/3334393/thumb.jpg?1650572950
#> 4   https://static.inaturalist.org/attachments/users/icons/541847/thumb.jpg?1582771190
#> 5     https://static.inaturalist.org/attachments/users/icons/6930/thumb.jpg?1475530872
#> 6  https://static.inaturalist.org/attachments/users/icons/2883853/thumb.jpg?1647293664
#> 7    https://static.inaturalist.org/attachments/users/icons/46945/thumb.jpg?1624289207
#> 8   https://static.inaturalist.org/attachments/users/icons/280446/thumb.jpg?1635600681
#> 9                                                                                 <NA>
#> 10    https://static.inaturalist.org/attachments/users/icons/2616/thumb.jpg?1475528533
counts$most_species[1:10,]
#>    count user.id      user.login           user.name
#> 1     89  245282  hughmcguinness     Hugh McGuinness
#> 2     47  811118     sandbankspp                    
#> 3     36 3334393 koniakin_serhii     Serhii Koniakin
#> 4     25    6930       tgosliner      Terry Gosliner
#> 5     24   46945             abe        T. Abe Lloyd
#> 6     24  761669 kathleenfspicer                <NA>
#> 7     17    2616     alice_abela         Alice Abela
#> 8     17  495266        maxa11an Max Allan Niklasson
#> 9     17  541847      billhubick         Bill Hubick
#> 10    15  280446         mtjones          Mike Jones
#>                                                                     user.user_icon_url
#> 1   https://static.inaturalist.org/attachments/users/icons/245282/thumb.jpg?1475532481
#> 2  https://static.inaturalist.org/attachments/users/icons/811118/thumb.jpeg?1535236899
#> 3  https://static.inaturalist.org/attachments/users/icons/3334393/thumb.jpg?1650572950
#> 4     https://static.inaturalist.org/attachments/users/icons/6930/thumb.jpg?1475530872
#> 5    https://static.inaturalist.org/attachments/users/icons/46945/thumb.jpg?1624289207
#> 6                                                                                 <NA>
#> 7     https://static.inaturalist.org/attachments/users/icons/2616/thumb.jpg?1475528533
#> 8  https://static.inaturalist.org/attachments/users/icons/495266/thumb.jpeg?1579782546
#> 9   https://static.inaturalist.org/attachments/users/icons/541847/thumb.jpg?1582771190
#> 10  https://static.inaturalist.org/attachments/users/icons/280446/thumb.jpg?1635600681
## By place_ID
vt_crows <- get_inat_obs_project("crows-in-vermont", type = "info", raw = FALSE)
#> 206 records
place_counts <- get_inat_user_stats(place = vt_crows$place_id)
place_counts$total
#> [1] 19115
place_counts$most_observations[1:10,]
#>    count user.id    user.login       user.name
#> 1  89462   12158 erikamitchell  Erika Mitchell
#> 2  41524    2179       charlie    Charlie Hohn
#> 3  21073   12610  susanelliott   Susan Elliott
#> 4  12368   20198 joshualincoln  Joshua Lincoln
#> 5  11978   12045      larry522  Larry Clarfeld
#> 6  11906 1168695       trscavo       Tom Scavo
#> 7  10906  171529        nsharp Nathaniel Sharp
#> 8  10848    6624   joannerusso                
#> 9  10444  108365     judywelna                
#> 10  9906     317   kpmcfarland  Kent McFarland
#>                                                                     user.user_icon_url
#> 1    https://static.inaturalist.org/attachments/users/icons/12158/thumb.jpg?1586465563
#> 2     https://static.inaturalist.org/attachments/users/icons/2179/thumb.jpg?1569109298
#> 3    https://static.inaturalist.org/attachments/users/icons/12610/thumb.jpg?1475533475
#> 4    https://static.inaturalist.org/attachments/users/icons/20198/thumb.jpg?1475538276
#> 5    https://static.inaturalist.org/attachments/users/icons/12045/thumb.jpg?1475533238
#> 6  https://static.inaturalist.org/attachments/users/icons/1168695/thumb.png?1535480090
#> 7   https://static.inaturalist.org/attachments/users/icons/171529/thumb.jpg?1544399969
#> 8     https://static.inaturalist.org/attachments/users/icons/6624/thumb.jpg?1639690628
#> 9   https://static.inaturalist.org/attachments/users/icons/108365/thumb.jpg?1475547470
#> 10     https://static.inaturalist.org/attachments/users/icons/317/thumb.png?1634743248
place_counts$most_species[1:10,]
#>    count user.id    user.login       user.name
#> 1   3561   12158 erikamitchell  Erika Mitchell
#> 2   2465   12610  susanelliott   Susan Elliott
#> 3   2390   12045      larry522  Larry Clarfeld
#> 4   2033    2179       charlie    Charlie Hohn
#> 5   1926   13355        beeboy   Spencer Hardy
#> 6   1877    6624   joannerusso                
#> 7   1854  171529        nsharp Nathaniel Sharp
#> 8   1830   20198 joshualincoln  Joshua Lincoln
#> 9   1754 2860446      er-birds                
#> 10  1550     317   kpmcfarland  Kent McFarland
#>                                                                     user.user_icon_url
#> 1    https://static.inaturalist.org/attachments/users/icons/12158/thumb.jpg?1586465563
#> 2    https://static.inaturalist.org/attachments/users/icons/12610/thumb.jpg?1475533475
#> 3    https://static.inaturalist.org/attachments/users/icons/12045/thumb.jpg?1475533238
#> 4     https://static.inaturalist.org/attachments/users/icons/2179/thumb.jpg?1569109298
#> 5    https://static.inaturalist.org/attachments/users/icons/13355/thumb.jpg?1475533838
#> 6     https://static.inaturalist.org/attachments/users/icons/6624/thumb.jpg?1639690628
#> 7   https://static.inaturalist.org/attachments/users/icons/171529/thumb.jpg?1544399969
#> 8    https://static.inaturalist.org/attachments/users/icons/20198/thumb.jpg?1475538276
#> 9  https://static.inaturalist.org/attachments/users/icons/2860446/thumb.jpg?1588019864
#> 10     https://static.inaturalist.org/attachments/users/icons/317/thumb.png?1634743248

Mapping

Basic maps can be created with the inat_map() function to quickly visualize search results. The plot = FALSE option can be used to avoid displaying the initial plot when further customising it with ggplot2 functions.

library(ggplot2)

## Map 100 spotted salamanders
a_mac <- get_inat_obs(taxon_name = "Ambystoma maculatum", year = 2021)
salamander_map <- inat_map(a_mac, plot = FALSE)

### Further customise the returned ggplot object
salamander_map + borders("state") + theme_bw()

plot of chunk unnamed-chunk-13

inat_map() is useful for quickly mapping single-species data obtained with rinat. However, more complicated plots are best made from scratch. Here is an example of customised map that does not make use of it. (Note the use of quality = "research" to restrict the search to the more reliable observations.)

## A more elaborate map of Colibri sp.
colibri <- get_inat_obs(taxon_name = "Colibri",
                        quality = "research",
                        maxresults = 500)
ggplot(data = colibri, aes(x = longitude,
                         y = latitude,
                         colour = scientific_name)) +
  geom_polygon(data = map_data("world"),
                   aes(x = long, y = lat, group = group),
                   fill = "grey95",
                   color = "gray40",
                   size = 0.1) +
  geom_point(size = 0.7, alpha = 0.5) +
  coord_fixed(xlim = range(colibri$longitude, na.rm = TRUE),
              ylim = range(colibri$latitude, na.rm = TRUE)) +
  theme_bw()

plot of chunk unnamed-chunk-14

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