README.md

In RS-eco/traitdata: Easy access to various ecological trait data

traitdata: R package for easy access to various ecological trait data

Installation

You can install traitdata from Github with:

# Install devtools if not available
if(!"remotes" %in% installed.packages()[,"Package"]) install.packages("remotes")

# Install traitdata package from Github
remotes::install_github("RS-eco/traitdata", build_vignettes = T, force=T)

After installation, simply load the traitdata package:

library(traitdata)

If you encounter a bug or if you have any problems, please file an issue on Github.

Data overview

There are 32 different data sets, which are included in this package:

| datasetName | basisOfRecord | rightsHolder | DOI | |-------------------|----------------|---------------------------|--------------------------------------------------------------------------------------------------------------------------| | amniota | traitDatabase | Myrhvold et al. 2016 | 10.1890/15-0846R.1 | | amphi_lifehist | traitDatabase | Trochet et al. 2014 | 10.3897/BDJ.2.e4123 | | amphibio | traitDatabase | Oliveira et al. 2017 | 10.1038/sdata.2017.123 | | an_age | traitDatabase | Tacutu et al. 2018 | 10.1093/nar/gkx1042 | | anuran_morpho | traitDatabase | Mendoza-Henao et al. 2019 | 10.1002/ecy.2685 | | arthropods | traitDatabase | Gossner et al. 2015 | 10.1038/sdata.2015.13 | | atlantic_birds | traitDatabase | Rodrigues et al. 2019 | 10.1002/ecy.2647 | | australian_birds | traitDatabase | Garnett et al. 2015 | 10.1038/sdata.2015.61 | | AvianBodySize | traitDatabase | Lislevand et al. 2007 | 10.1890/06-2054 | | bird_behav | traitDatabase | Tobias & Pigot 2019 | 10.1098/rstb.2019.0012 | | carabids | traitDatabase | van der Plas et al. 2017 | 10.5061/dryad.53ds2 | | climber | traitDatabase | Schweiger et al. 2014 | 10.3897/zookeys.367.6185 | | disperse | traitDatabase | Sarremejane et al. 2020 | 10.1038/s41597-020-00732-7 | | elton_birds | traitDatabase | Wilman et al. 2014 | 10.1890/13-1917.1 | | elton_mammals | traitDatabase | Wilman et al. 2014 | 10.1890/13-1917.1 | | epiphytes | traitDatabase | Hietz et al. 2021 | 10.1111/1365-2745.13802 | | eubirds | traitDatabase | Storchová & Hořák 2017 | 10.1111/geb.12709 | | fishmorph | traitDatabase | Brosse et al. 2021 | 10.1111/geb.13395 | | globalHWI | traitDatabase | Sheard et al. 2020 | 10.1038/s41467-020-16313-6 | | globTherm | traitDatabase | Bennett et al. 2018 | 10.1038/sdata.2018.22 | | heteroptera | traitDatabase | Gossner et al. 2016 | 10.6084/m9.figshare.c.3307611.v1 | | heteropteraRaw | traitDatabase | Gossner et al. 2016 | 10.6084/m9.figshare.c.3307611.v1 | | lizard_traits | traitDatabase | Meiri 2018 | 10.1111/geb.12773 | | mammal_diet | traitDatabase | Kissling et al. 2014 | 10.1002/ece3.1136 | | mammal_diet2 | traitDatabase | Gainsbury et al. 2018 | 10.1111/mam.12119 | | marsupials | traitDatabase | Fisher et al. 2001 | 10.1890/0012-9658(2001)082[3531:TEBOLH]2.0.CO;2 | | migbehav_birds | literatureData | Eyres & Fritz | 10.12761/SGN.2017.10058 | | pantheria | traitDatabase | Jones et al. 2009 | 10.1890/08-1494.1 | | passerines | traitDatabase | Ricklefs 2017 | 10.1002/ecy.1783 | | primates | traitDatabase | Galán-Acedo et al. 2020 | 10.1038/s41597-019-0059-9 | | reptile_lifehist | traitDatabase | Grimm et al. 2014 | 10.3897/natureconservation.9.8908 | | tetra_density | traitDatabase | Santini et al. 2018 | 10.1111/geb.12756 |

Note: The code for how these datatsets were downloaded and processed can be found in the data-raw folder.

See also https://opentraits.org/datasets.html for an extensive list of Trait datasets.

An overview of the different datasets can also be found here: vignette("data_info").

Variables

• All published datasets contain their original variables and species names. Species names were split into 2 columns (Genus and Species) and where applicable into a 3rd column with Subspecies names.
• All datasets also have a scientificNameStd column, which is a standardised scientific name, in order to be able to merge the different datasets by species.

Note: Not all species names could be standardised, therefore some data entries might not contain a scientificNameStd value, please then refer to the Genus and Species column. In case you are interested in which species could not be standardised have a look at the names_nonStd file. Please also check out the synonyms data file, for species where an alternative name has been used for standardising the scientific name.

An overview of all variables with a description of each variable can be found in the trait_glossary data file:

data(trait_glossary)

or in the glossary vignette:

vignette("trait_glossary")

Data query

To connect to one or more datasets, we simply use the data() function.

# Load Elton Traits
data("elton_birds")

Now we can use standard R calls to have a look at the data.

First, we look at the column names of our dataset.

# Look at the variable names
colnames(elton_birds)

##  [1] "SpecID"                 "PassNonPass"            "Order"                 
##  [4] "Family"                 "BLFamilyEnglish"        "BLFamSequID"           
##  [7] "Taxo"                   "Genus"                  "Species"               
## [10] "English"                "Diet.Inv"               "Diet.Vend"             
## [13] "Diet.Vect"              "Diet.Vfish"             "Diet.Vunk"             
## [16] "Diet.Scav"              "Diet.Fruit"             "Diet.Nect"             
## [19] "Diet.Seed"              "Diet.PlantO"            "Diet.5Cat"             
## [22] "Diet.Source"            "Diet.Certainty"         "Diet.EnteredBy"        
## [25] "ForStrat.watbelowsurf"  "ForStrat.wataroundsurf" "ForStrat.ground"       
## [28] "ForStrat.understory"    "ForStrat.midhigh"       "ForStrat.canopy"       
## [31] "ForStrat.aerial"        "PelagicSpecialist"      "ForStrat.Source"       
## [34] "ForStrat.SpecLevel"     "ForStrat.EnteredBy"     "Nocturnal"             
## [37] "BodyMass.Value"         "BodyMass.Source"        "BodyMass.SpecLevel"    
## [40] "BodyMass.Comment"       "Record.Comment"         "Full.Reference"        
## [43] "scientificNameStd"

Then, we check the class and first 6 rows of the first 10 columns of the elton_traits dataset:

class(elton_birds)

## [1] "data.frame"

head(elton_birds[,1:10])

##   SpecID      PassNonPass            Order        Family BLFamilyEnglish
## 1     28 Nonpasseriformes Struthioniformes Struthionidae       Ostriches
## 2     37 Nonpasseriformes       Rheiformes       Rheidae           Rheas
## 3     38 Nonpasseriformes       Rheiformes       Rheidae           Rheas
## 4     45 Nonpasseriformes   Casuariiformes   Casuariidae     Cassowaries
## 5     46 Nonpasseriformes   Casuariiformes   Casuariidae     Cassowaries
## 6     47 Nonpasseriformes   Casuariiformes   Casuariidae     Cassowaries
##   BLFamSequID Taxo     Genus          Species            English
## 1           2  BL3  Struthio          camelus            Ostrich
## 2           3  BL3      Rhea        americana       Greater Rhea
## 3           3  BL3      Rhea          pennata        Lesser Rhea
## 4           4  BL3 Casuarius        casuarius Southern Cassowary
## 5           4  BL3 Casuarius         bennetti    Dwarf Cassowary
## 6           4  BL3 Casuarius unappendiculatus Northern Cassowary

For more information on how to use the data within the package, check out the access-data and all the other vignettes.

vignette("access-data")

Additional examples of how to use the different trait datasets can be found in the following vignettes:

vignette("island-birds")
vignette("migbehav_birds")
vignette("morpho-indices")
vignette("pantheria")
vignette("passerines")

RS-eco/traitdata documentation built on Oct. 29, 2022, 7:52 p.m.