R client for various sources of species trait data.
Included in traits with the associated function prefix:
betydb_ncbi_g_eol_traitbank_coral_fe_birdlife_leda_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.
Stable CRAN version
install.packages("traits")Or development version from GitHub
devtools::install_github("ropensci/traits")library("traits")
library("dplyr")Get trait data for Willow (Salix spp.)
(salix <- betydb_search("Salix Vcmax"))
#> Source: local data frame [14 x 31]
#>
#> access_level author checked citation_id citation_year city
#> (int) (chr) (int) (int) (int) (chr)
#> 1 4 Merilo 1 430 2005 Saare
#> 2 4 Merilo 1 430 2005 Saare
#> 3 4 Merilo 1 430 2005 Saare
#> 4 4 Merilo 1 430 2005 Saare
#> 5 4 Wullschleger 1 51 1993 NA
#> 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 Wang 1 381 2010 NA
#> Variables not shown: commonname (chr), cultivar_id (int), date (chr),
#> dateloc (chr), genus (chr), id (int), lat (dbl), lon (dbl), mean (chr),
#> month (dbl), n (int), notes (chr), result_type (chr), scientificname
#> (chr), site_id (int), sitename (chr), species_id (int), stat (chr),
#> statname (chr), trait (chr), trait_description (chr), treatment (chr),
#> treatment_id (int), units (chr), year (dbl)
# 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))
#> Source: local data frame [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 8sp <- c("Carpobrotus edulis", "Rosmarinus officinalis")
g_invasive(sp)
#> species
#> 1 Carpobrotus edulis
#> 2 Rosmarinus officinalis
#> status
#> 1 Carpobrotus edulis is a mat-forming succulent native to South Africa which is invasive primarily in coastal habitats in many parts of the world. It was often introduced as an ornamental plant or used for planting along roadsides, from which it has spread to become invasive. Its main impacts are smothering, reduced regeneration of native flora and changes to soil pH and nutrient regimes.; (succulent); Common Names: balsamo, Cape fig, figue marine, freeway iceplant, ghaukum, ghoenavy, highway ice plant, higo del Cabo, higo marino, Hottentosvy, hottentot fig, Hottentottenfeige, iceplant, ikhambi-lamabulawo, Kaapsevy, patata frita, perdevy, pigface, rankvy, sea fig, sour fig, suurvy, umgongozi, vyerank; Synonyms: Mesembryanthemum edule L., Mesembryanthemum edulis
#> 2 Not in GISDOr as simplified output
g_invasive(sp, simplify = TRUE)
#> species status
#> 1 Carpobrotus edulis Invasive
#> 2 Rosmarinus officinalis Not in GISDeol_invasive_('Brassica oleracea', dataset = 'gisd')
#> searched_name name eol_object_id db
#> 1 Brassica oleracea Brassica oleracea NaN gisdAnother example, with more species, and from
eol_invasive_(c('Lymantria dispar','Cygnus olor','Hydrilla verticillata','Pinus concolor'),
dataset = 'i3n')
#> searched_name name eol_object_id
#> 1 Lymantria dispar Lymantria dispar NaN
#> 2 Cygnus olor Cygnus olor (Gmelin 1789) 913227
#> 3 Hydrilla verticillata Hydrilla verticillata (L. f.) Royle 1088921
#> 4 Pinus concolor Pinus concolor NaN
#> db
#> 1 i3n
#> 2 i3n
#> 3 i3n
#> 4 i3nSearching for Mesoplodon bidens, page id 328566
res <- traitbank(846827)
res$graph %>%
select(`dwc:measurementtype.@id`, `dwc:measurementtype.rdfs:label.en`) %>%
filter(!is.na(`dwc:measurementtype.rdfs:label.en`))
#> Source: local data frame [6 x 2]
#>
#> dwc:measurementtype.@id
#> (chr)
#> 1 http://eol.org/schema/terms/TypeSpecimenRepository
#> 2 http://eol.org/schema/terms/TypeSpecimenRepository
#> 3 http://eol.org/schema/terms/Habitat
#> 4 http://eol.org/schema/terms/Habitat
#> 5 http://eol.org/schema/terms/ExtinctionStatus
#> 6 http://eol.org/schema/terms/ExtinctionStatus
#> Variables not shown: dwc:measurementtype.rdfs:label.en (chr)Get the species list and their ids
coral_species()
#> Source: local data frame [1,547 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
#> .. ... ...Get data by taxon
coral_taxa(80)
#> Source: local data frame [3,121 x 25]
#>
#> observation_id access user_id specie_id specie_name location_id
#> (int) (int) (int) (int) (chr) (int)
#> 1 119211 1 49 80 Acropora hyacinthus 1
#> 2 109330 1 2 80 Acropora hyacinthus 1
#> 3 88793 1 14 80 Acropora hyacinthus 0
#> 4 115791 1 10 80 Acropora hyacinthus 1
#> 5 115792 1 10 80 Acropora hyacinthus 1
#> 6 5696 1 2 80 Acropora hyacinthus 1
#> 7 5741 1 1 80 Acropora hyacinthus 1
#> 8 5751 1 1 80 Acropora hyacinthus 1
#> 9 5773 1 5 80 Acropora hyacinthus 1
#> 10 5766 1 1 80 Acropora hyacinthus 1
#> .. ... ... ... ... ... ...
#> Variables not shown: 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)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 breedingtraits in R doing citation(package = 'traits')