traits

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R client for various sources of species trait data.

Included in traits with the associated function prefix or function name:

Talk to us on the issues page if you know of a source of traits data with an API, and we’ll see about including it.

For an introduction to the package, see the vignette.

Installation

Stable CRAN version

install.packages("traits")

Or development version from GitHub

devtools::install_github("ropensci/traits")
library("traits")
library("dplyr")

BETYdb

Get trait data for Willow (Salix spp.)

(salix <- betydb_search("Salix Vcmax"))
#> # A tibble: 14 x 36
#>    access_level       author checked citation_id citation_year  city
#>  *        <int>        <chr>   <int>       <int>         <int> <chr>
#>  1            4 Wullschleger       1          51          1993  <NA>
#>  2            4         Wang       1         381          2010  <NA>
#>  3            4       Merilo       1         430          2005 Saare
#>  4            4       Merilo       1         430          2005 Saare
#>  5            4       Merilo       1         430          2005 Saare
#>  6            4       Merilo       1         430          2005 Saare
#>  7            4       Merilo       1         430          2005 Saare
#>  8            4       Merilo       1         430          2005 Saare
#>  9            4       Merilo       1         430          2005 Saare
#> 10            4       Merilo       1         430          2005 Saare
#> 11            4       Merilo       1         430          2005 Saare
#> 12            4       Merilo       1         430          2005 Saare
#> 13            4       Merilo       1         430          2005 Saare
#> 14            4       Merilo       1         430          2005 Saare
#> # ... with 30 more variables: commonname <chr>, cultivar <chr>,
#> #   cultivar_id <int>, date <chr>, dateloc <chr>, entity <lgl>,
#> #   genus <chr>, id <int>, lat <dbl>, lon <dbl>, mean <dbl>,
#> #   method_name <lgl>, month <int>, n <int>, notes <chr>, raw_date <chr>,
#> #   result_type <chr>, scientificname <chr>, site_id <int>,
#> #   sitename <chr>, species_id <int>, stat <dbl>, statname <chr>,
#> #   time <chr>, trait <chr>, trait_description <chr>, treatment <chr>,
#> #   treatment_id <int>, units <chr>, year <int>
# equivalent:
# (out <- betydb_search("willow"))

Summarise data from the output data.frame

library("dplyr")
salix %>%
  group_by(scientificname, trait) %>%
  mutate(.mean = as.numeric(mean)) %>%
  summarise(mean = round(mean(.mean, na.rm = TRUE), 2),
            min = round(min(.mean, na.rm = TRUE), 2),
            max = round(max(.mean, na.rm = TRUE), 2),
            n = length(n))
#> # A tibble: 4 x 6
#> # Groups:   scientificname [?]
#>                    scientificname trait  mean   min   max     n
#>                             <chr> <chr> <dbl> <dbl> <dbl> <int>
#> 1                           Salix Vcmax 65.00 65.00 65.00     1
#> 2                Salix dasyclados Vcmax 46.08 34.30 56.68     4
#> 3 Salix sachalinensis × miyabeana Vcmax 79.28 79.28 79.28     1
#> 4                 Salix viminalis Vcmax 43.04 19.99 61.29     8

EOL’s traitbank trait data

Searching for Balaenoptera musculus (blue whale), page id 328574

res <- traitbank(328574)
res$graph %>%
  select(`dwc:measurementtype`) %>%
  filter(!is.na(`dwc:measurementtype`))
#> # A tibble: 181 x 1
#>                                   `dwc:measurementtype`
#>                                                   <chr>
#>  1 http://eol.org/schema/terms/MineralCompositionOfMilk
#>  2 http://eol.org/schema/terms/MineralCompositionOfMilk
#>  3 http://eol.org/schema/terms/MineralCompositionOfMilk
#>  4 http://eol.org/schema/terms/MineralCompositionOfMilk
#>  5 http://eol.org/schema/terms/MineralCompositionOfMilk
#>  6 http://eol.org/schema/terms/MineralCompositionOfMilk
#>  7 http://eol.org/schema/terms/MineralCompositionOfMilk
#>  8 http://eol.org/schema/terms/MineralCompositionOfMilk
#>  9 http://eol.org/schema/terms/MineralCompositionOfMilk
#> 10 http://eol.org/schema/terms/MineralCompositionOfMilk
#> # ... with 171 more rows

Coral

Get the species list and their ids

coral_species()
#> # A tibble: 1,548 x 2
#>                          name    id
#>                         <chr> <chr>
#>  1        Acanthastrea brevis     3
#>  2      Acanthastrea echinata     4
#>  3     Acanthastrea hemprichi     6
#>  4 Acanthastrea ishigakiensis     8
#>  5     Acanthastrea regularis    12
#>  6  Acanthastrea rotundoflora    13
#>  7   Acanthastrea subechinata    14
#>  8     Acropora abrolhosensis    16
#>  9      Acropora abrotanoides    17
#> 10           Acropora aculeus    18
#> # ... with 1,538 more rows

Get data by taxon

coral_taxa(80)
#> # A tibble: 3,540 x 25
#>    observation_id access user_id specie_id         specie_name location_id
#>             <int>  <int>   <int>     <int>               <chr>       <int>
#>  1         157133      1      10        80 Acropora hyacinthus           1
#>  2         156961      1      14        80 Acropora hyacinthus         409
#>  3           5781      1       1        80 Acropora hyacinthus           1
#>  4         156610      1       2        80 Acropora hyacinthus         500
#>  5         158118      1      10        80 Acropora hyacinthus         409
#>  6         119211      1      49        80 Acropora hyacinthus           1
#>  7         158211      1      10        80 Acropora hyacinthus         413
#>  8          90294      1      15        80 Acropora hyacinthus         341
#>  9          90294      1      15        80 Acropora hyacinthus         341
#> 10          90294      1      15        80 Acropora hyacinthus         341
#> # ... with 3,530 more rows, and 19 more variables: location_name <chr>,
#> #   latitude <dbl>, longitude <dbl>, resource_id <int>,
#> #   resource_secondary_id <int>, measurement_id <int>, trait_id <int>,
#> #   trait_name <chr>, standard_id <int>, standard_unit <chr>,
#> #   methodology_id <int>, methodology_name <chr>, value <chr>,
#> #   value_type <chr>, precision <dbl>, precision_type <chr>,
#> #   precision_upper <dbl>, replicates <int>, notes <chr>

Birdlife International

Habitat data

birdlife_habitat(22721692)
#>         id Habitat (level 1)                  Habitat (level 2) Importance
#> 1 22721692            Forest           Subtropical/Tropical Dry   suitable
#> 2 22721692            Forest Subtropical/Tropical Moist Montane      major
#> 3 22721692            Forest                          Temperate   suitable
#> 4 22721692         Shrubland Subtropical/Tropical High Altitude   suitable
#>     Occurrence
#> 1     breeding
#> 2 non-breeding
#> 3     breeding
#> 4     breeding

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