## Installation
Install and load `traits` into the R session. Stable version from CRAN
```r
install.packages("traits")
```
Or development version from Github:
```r
if (!require("devtools")) install.packages("devtools")
devtools::install_github("ropensci/traits")
```
```r
library("traits")
```
## Usage
### BetyDB
Get trait data for Willow (_Salix_ spp.)
```r
(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 (dbl),
#> month (dbl), n (int), notes (chr), result_type (chr), scientificname
#> (chr), site_id (int), sitename (chr), species_id (int), stat (dbl),
#> statname (chr), trait (chr), trait_description (chr), treatment (chr),
#> treatment_id (int), units (chr), year (dbl)
```
```r
# equivalent:
# (out <- betydb_search("willow"))
```
Summarise data from the output `data.frame`
```r
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 8
```
### NCBI sequence data
Get sequences by id
```r
ncbi_byid(ids = "360040093")
```
```
#> taxon
#> 1 Eristalis transversa
#> gene_desc
#> 1 Eristalis transversa voucher CNC:Diptera:102013 cytochrome oxidase subunit 1 (COI) gene, partial cds; mitochondrial
#> gi_no acc_no length
#> 1 360040093 JN991986.1 658
#> sequence
#> 1 tactttatattttgtatttggaacatgagcgggtatagtaggaacttcattaagaattttaattcgagctgaattaggtcatccaggtgcattaattggtgatgatcaaatttataatgttattgtaacagctcatgcttttgttataattttttttatagtaatacctattataattggaggatttggaaattgattagtaccacttatattaggagctccagatatagcattccctcgaataaataatataagtttctgattattacctccttctttaactctattattagtaagaagtatagtagaaaatggggctggaacaggatgaacagtttatcctccattatcaagtaatattgcacatggaggagcctcagttgatttagcaattttttcacttcacttatcaggaatatcatctattttaggtgcagtaaattttattacaacagttattaatatacgatcaacaggaattacttatgatcgtatacctttatttgtttgatctgttgctattacagctttattattattattatcattaccagtactagcaggagctattacaatattattaactgatcgaaatttaaatacatcattctttgatccagcaggaggaggagaccctatcctgtaccaacacttattc
```
Get sequences searching by taxonomic name
```r
out <- ncbi_searcher(taxa = "Umbra limi", seqrange = "1:2000")
head(out)
```
```
#> taxon length
#> 1 Umbra limi 169
#> 2 Umbra limi 412
#> 3 Umbra limi 315
#> 4 Umbra limi 200
#> 5 Umbra limi 333
#> 6 Umbra limi 242
#> gene_desc
#> 1 Umbra limi mitochondrial gene for 12S rRNA, partial sequence
#> 2 Umbra limi tRNA-Glu gene, partial sequence; and cytochrome b (CYTB) gene, partial cds; mitochondrial
#> 3 Umbra limi 16S ribosomal RNA gene, partial sequence; mitochondrial
#> 4 Umbra limi 16S ribosomal RNA gene, partial sequence; mitochondrial
#> 5 Umbra limi 16S ribosomal RNA gene, partial sequence; mitochondrial
#> 6 Umbra limi 12S ribosomal RNA gene, partial sequence; mitochondrial
#> acc_no gi_no
#> 1 LC021016 985564997
#> 2 KM523322 725542537
#> 3 KM435059 725542420
#> 4 KM434991 725542361
#> 5 KM282516 725542294
#> 6 KM282453 725542240
```
### GISD invasive species data
> NOTE: we're moving all functions having to do with where species are native/invasive to a new package [https://github.com/ropenscilabs/originr](https://github.com/ropenscilabs/originr)
```r
sp <- c("Carpobrotus edulis", "Rosmarinus officinalis")
g_invasive(sp)
```
```
#> species status
#> 1 Carpobrotus edulis ;
#> 2 Rosmarinus officinalis ;
```
Or as simplified output
```r
g_invasive(sp, simplify = TRUE)
```
```
#> species status
#> 1 Carpobrotus edulis Invasive
#> 2 Rosmarinus officinalis Invasive
```
### EOL invasive species data
> NOTE: we're moving all functions having to do with where species are native/invasive to a new package [https://github.com/ropenscilabs/originr](https://github.com/ropenscilabs/originr)
```r
eol_invasive_('Brassica oleracea', dataset = 'gisd')
```
```
#> searched_name name eol_object_id db
#> 1 Brassica oleracea Brassica oleracea NaN gisd
```
Another example, with more species, and from
```r
eol_invasive_(c('Lymantria dispar','Cygnus olor',
'Hydrilla verticillata','Pinus concolor'),
dataset = 'i3n')
```
```
#> searched_name name eol_object_id db
#> 1 Lymantria dispar Lymantria dispar NaN i3n
#> 2 Cygnus olor Cygnus olor NaN i3n
#> 3 Hydrilla verticillata Hydrilla verticillata NaN i3n
#> 4 Pinus concolor Pinus concolor NaN i3n
```
### EOL's Traitbank data
Note that EOL's Traitbank does not allow us to search by trait.
The only interface we have is to search by taxon page ID.
Searching for _Potus flavus_, page id `328067`
```r
res <- traitbank(pageid = 328067)
res$graph %>%
select(dwc.measurementtype,
dwc.measurementvalue) %>%
filter(!is.na(dwc.measurementvalue))
```
```
#> Source: local data frame [77 x 2]
#>
#> dwc.measurementtype
#> (chr)
#> 1 http://www.owl-ontologies.com/unnamed.owl#Metabolic_rate
#> 2 http://iucn.org/population_trend
#> 3 http://rs.tdwg.org/dwc/terms/habitat
#> 4 http://purl.obolibrary.org/obo/VT_0001661
#> 5 http://eol.org/schema/terms/LittersPerYear
#> 6 http://purl.obolibrary.org/obo/VT_0001933
#> 7 http://eol.org/schema/terms/InterBirthInterval
#> 8 http://semanticscience.org/resource/SIO_000319
#> 9 http://semanticscience.org/resource/SIO_000318
#> 10 http://semanticscience.org/resource/SIO_000318
#> .. ...
#> Variables not shown: dwc.measurementvalue (chr)
```
### Coral
Get the species list and their ids
```r
coral_species()
```
```
#> Source: local data frame [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
#> .. ... ...
```
Get data by taxon
```r
coral_taxa(80)
```
```
#> Source: local data frame [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
#> .. ... ... ... ... ... ...
#> 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)
```
Get data by trait
```r
coral_traits(105)
```
```
#> Source: local data frame [0 x 25]
#>
#> Variables not shown: observation_id (lgl), access (lgl), user_id (lgl),
#> specie_id (lgl), specie_name (lgl), location_id (lgl), location_name
#> (lgl), latitude (lgl), longitude (lgl), resource_id (lgl),
#> resource_secondary_id (lgl), measurement_id (lgl), trait_id (lgl),
#> trait_name (lgl), standard_id (lgl), standard_unit (lgl), methodology_id
#> (lgl), methodology_name (lgl), value (lgl), value_type (lgl), precision
#> (lgl), precision_type (lgl), precision_upper (lgl), replicates (lgl),
#> notes (lgl)
```
### Flora Europaea
```r
sp <- c("Lavandula stoechas", "Carpobrotus edulis",
"Rhododendron ponticum", "Alkanna lutea", "Anchusa arvensis")
sapply(sp, fe_native, simplify = FALSE)
```
```
#> $`Lavandula stoechas`
#> $`Lavandula stoechas`$native
#> [1] "Islas_Baleares" "Corse" "Kriti" "France"
#> [5] "Greece" "Spain" "Italy" "Portugal"
#> [9] "Sardegna" "Sicilia" "Turkey"
#>
#> $`Lavandula stoechas`$exotic
#> [1] NA
#>
#> $`Lavandula stoechas`$status_doubtful
#> [1] NA
#>
#> $`Lavandula stoechas`$occurrence_doubtful
#> [1] NA
#>
#> $`Lavandula stoechas`$extinct
#> [1] NA
#>
#>
#> $`Carpobrotus edulis`
#> $`Carpobrotus edulis`$native
#> [1] NA
#>
#> $`Carpobrotus edulis`$exotic
#> [1] "Albania" "Azores" "Belgium" "Islas_Baleares"
#> [5] "Britain" "Corse" "France" "Greece"
#> [9] "Ireland" "Spain" "Italy" "Portugal"
#> [13] "Sicilia"
#>
#> $`Carpobrotus edulis`$status_doubtful
#> [1] NA
#>
#> $`Carpobrotus edulis`$occurrence_doubtful
#> [1] NA
#>
#> $`Carpobrotus edulis`$extinct
#> [1] NA
#>
#>
#> $`Rhododendron ponticum`
#> $`Rhododendron ponticum`$native
#> [1] "Bulgaria" "Spain" "Portugal" "Turkey"
#>
#> $`Rhododendron ponticum`$exotic
#> [1] "Belgium" "Britain" "France" "Ireland"
#>
#> $`Rhododendron ponticum`$status_doubtful
#> [1] NA
#>
#> $`Rhododendron ponticum`$occurrence_doubtful
#> [1] NA
#>
#> $`Rhododendron ponticum`$extinct
#> [1] NA
#>
#>
#> $`Alkanna lutea`
#> $`Alkanna lutea`$native
#> [1] "Islas_Baleares" "Corse" "France" "Spain"
#> [5] "Italy" "Sardegna"
#>
#> $`Alkanna lutea`$exotic
#> [1] NA
#>
#> $`Alkanna lutea`$status_doubtful
#> [1] NA
#>
#> $`Alkanna lutea`$occurrence_doubtful
#> [1] "Portugal"
#>
#> $`Alkanna lutea`$extinct
#> [1] NA
#>
#>
#> $`Anchusa arvensis`
#> $`Anchusa arvensis`$native
#> [1] "Albania" "Austria"
#> [3] "Belgium" "Islas_Baleares"
#> [5] "Britain" "Bulgaria"
#> [7] "Corse" "Czechoslovakia"
#> [9] "Denmark" "Finland"
#> [11] "France" "Germany"
#> [13] "Greece" "Switzerland"
#> [15] "Netherlands" "Spain"
#> [17] "Hungary" "Italy"
#> [19] "Jugoslavia" "Portugal"
#> [21] "Norway" "Poland"
#> [23] "Romania" "USSR"
#> [25] "USSR_Northern_Division" "USSR_Baltic_Division"
#> [27] "USSR_Central_Division" "USSR_South_western"
#> [29] "USSR_Krym" "USSRSouth_eastern_Division"
#> [31] "Sicilia" "Sweden"
#>
#> $`Anchusa arvensis`$exotic
#> [1] "Faroer"
#>
#> $`Anchusa arvensis`$status_doubtful
#> [1] "Ireland" "Sardegna"
#>
#> $`Anchusa arvensis`$occurrence_doubtful
#> [1] NA
#>
#> $`Anchusa arvensis`$extinct
#> [1] NA
```
### Birdlife International
Habitat data
```r
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
```
Threats data
```r
birdlife_threats(22721692)
```
```
#> id threat1
#> 1 22721692 Agriculture & aquaculture
#> 2 22721692 Agriculture & aquaculture
#> 3 22721692 Biological resource use
#> 4 22721692 Energy production & mining
#> 5 22721692 Invasive and other problematic species, genes & diseases
#> 6 22721692 Residential & commercial development
#> threat2
#> 1 Annual & perennial non-timber crops / Agro-industry farming
#> 2 Annual & perennial non-timber crops / Small-holder farming
#> 3 Logging & wood harvesting / Unintentional effects: (subsistence/small scale) [harvest]
#> 4 Mining & quarrying
#> 5 Problematic native species/diseases
#> 6 Housing & urban areas
#> stresses timing scope
#> 1 Ecosystem degradation, Ecosystem conversion Ongoing
#> 2 Ecosystem degradation, Ecosystem conversion Ongoing
#> 3 Ecosystem degradation Ongoing
#> 4 Ecosystem degradation, Ecosystem conversion Ongoing
#> 5 Species mortality Ongoing
#> 6 Ecosystem degradation, Ecosystem conversion Ongoing
#> severity impact
#> 1 Majority (50-90%) NA
#> 2 Majority (50-90%) NA
#> 3 Majority (50-90%) NA
#> 4 Majority (50-90%) NA
#> 5 Minority ( NA
#> 6 Minority ( NA
```
### Nativity
> NOTE: we're moving all functions having to do with where species are native/invasive to a new package [https://github.com/ropenscilabs/originr](https://github.com/ropenscilabs/originr)
```r
sp <- c("Lavandula stoechas", "Carpobrotus edulis", "Rhododendron ponticum",
"Alkanna lutea", "Anchusa arvensis")
```
Native in the continental USA?
```r
sapply(sp, is_native, where = "Continental US", region = "america")
```
```
#> Lavandula stoechas Carpobrotus edulis Rhododendron ponticum
#> name "Lavandula stoechas" "Carpobrotus edulis" "Rhododendron ponticum"
#> origin "Introduced" "Introduced" "species not in itis"
#> Alkanna lutea Anchusa arvensis
#> name "Alkanna lutea" "Anchusa arvensis"
#> origin "species not in itis" "Introduced"
```
Native on Islas Baleares?
```r
sapply(sp, is_native, where = "Islas_Baleares", region = "europe")
```
```
#> Lavandula stoechas Carpobrotus edulis
#> name "Lavandula stoechas" "Carpobrotus edulis"
#> origin "Native" "Introduced"
#> Rhododendron ponticum Alkanna lutea
#> name "Rhododendron ponticum" "Alkanna lutea"
#> origin "Species not present in your selected region" "Native"
#> Anchusa arvensis
#> name "Anchusa arvensis"
#> origin "Native"
```
## Citing
To cite `traits` in publications use:
> Scott Chamberlain, Zachary Foster, Ignasi Bartomeus, David LeBauer, and David Harris (2015). traits: Species Trait Data from Around the Web. R package version 0.2.0. https://github.com/ropensci/traits
## License and bugs
* License: [MIT](http://opensource.org/licenses/MIT)
* Report bugs at [our Github repo for traits](https://github.com/ropensci/traits/issues?state=open)
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