rotif.env: Rotifers and environmental variables on TDWG level 4 regions...
In fuzzySim: Fuzzy Similarity in Species Distributions
rotif.env R Documentation
Rotifers and environmental variables on TDWG level 4 regions of the world
Description
These data were extracted from a database of monogonont rotifer species presence records on the geographical units used by the Biodiversity Information Standards (formerly Taxonomic Database Working Group, TDWG: https://www.tdwg.org) and a few environmental (including human and spatial) variables on the same spatial units. The original data were compiled and published by Fontaneto et al. (2012) in long (narrow, stacked) format. Here they are presented in wide or unstacked format (presence-absence table, obtained with the splist2presabs function), reduced to the species recorded in at least 100 (roughly one third) different TDWG level 4 units, and with abbreviations of the species' names (obtained with the spCodes function). Mind that this is not a complete picture of these species' distributions, due to insufficient sampling in many regions.
Usage
data(rotif.env)
Format
A data frame with 291 observations on the following 47 variables.
TDWG4a factor with 291 levels indicating the abbreviation code of each TDWG4 region
LEVEL_NAMEa factor with 291 levels indicating the name of each TDWG4 region
REGION_NAMEa factor with 47 levels indicating the name of the main geographical region to which each TDWG4 level belongs
CONTINENTa factor with 9 levels indicating the continent to which each TDWG4 level belongs
Areaa numeric vector
Altitudea numeric vector
AltitudeRangea numeric vector
HabitatDiversitya numeric vector
HumanPopulationa numeric vector
Latitudea numeric vector
Longitudea numeric vector
Precipitationa numeric vector
PrecipitationSeasonalitya numeric vector
TemperatureAnnualRangea numeric vector
Temperaturea numeric vector
TemperatureSeasonalitya numeric vector
UrbanAreaa numeric vector
Abrigha numeric vector
Afissaa numeric vector
Aprioda numeric vector
Bangula numeric vector
Bcalyca numeric vector
Bplicaa numeric vector
Bquadra numeric vector
Burceoa numeric vector
Cgibbaa numeric vector
Edilata numeric vector
Flongia numeric vector
Kcochla numeric vector
Kquadra numeric vector
Ktropia numeric vector
Lbullaa numeric vector
Lclosta numeric vector
Lhamata numeric vector
Llunaa numeric vector
Llunara numeric vector
Lovalia numeric vector
Lpatela numeric vector
Lquadra numeric vector
Mventra numeric vector
Ppatula numeric vector
Pquadra numeric vector
Pvulgaa numeric vector
Spectia numeric vector
Tpatina numeric vector
Tsimila numeric vector
Ttetraa numeric vector
Source
Fontaneto D., Barbosa A.M., Segers H. & Pautasso M. (2012) The 'rotiferologist' effect and other global correlates of species richness in monogonont rotifers. Ecography, 35: 174-182.
Examples
data(rotif.env)
head(rotif.env)
fuzzySim documentation built on Oct. 9, 2023, 5:09 p.m.
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| rotif.env | R Documentation |
Rotifers and environmental variables on TDWG level 4 regions of the world
Description
These data were extracted from a database of monogonont rotifer species presence records on the geographical units used by the Biodiversity Information Standards (formerly Taxonomic Database Working Group, TDWG: https://www.tdwg.org) and a few environmental (including human and spatial) variables on the same spatial units. The original data were compiled and published by Fontaneto et al. (2012) in long (narrow, stacked) format. Here they are presented in wide or unstacked format (presence-absence table, obtained with the splist2presabs function), reduced to the species recorded in at least 100 (roughly one third) different TDWG level 4 units, and with abbreviations of the species' names (obtained with the spCodes function). Mind that this is not a complete picture of these species' distributions, due to insufficient sampling in many regions.
Usage
data(rotif.env)Format
A data frame with 291 observations on the following 47 variables.
TDWG4a factor with 291 levels indicating the abbreviation code of each TDWG4 region
LEVEL_NAMEa factor with 291 levels indicating the name of each TDWG4 region
REGION_NAMEa factor with 47 levels indicating the name of the main geographical region to which each TDWG4 level belongs
CONTINENTa factor with 9 levels indicating the continent to which each TDWG4 level belongs
Areaa numeric vector
Altitudea numeric vector
AltitudeRangea numeric vector
HabitatDiversitya numeric vector
HumanPopulationa numeric vector
Latitudea numeric vector
Longitudea numeric vector
Precipitationa numeric vector
PrecipitationSeasonalitya numeric vector
TemperatureAnnualRangea numeric vector
Temperaturea numeric vector
TemperatureSeasonalitya numeric vector
UrbanAreaa numeric vector
Abrigha numeric vector
Afissaa numeric vector
Aprioda numeric vector
Bangula numeric vector
Bcalyca numeric vector
Bplicaa numeric vector
Bquadra numeric vector
Burceoa numeric vector
Cgibbaa numeric vector
Edilata numeric vector
Flongia numeric vector
Kcochla numeric vector
Kquadra numeric vector
Ktropia numeric vector
Lbullaa numeric vector
Lclosta numeric vector
Lhamata numeric vector
Llunaa numeric vector
Llunara numeric vector
Lovalia numeric vector
Lpatela numeric vector
Lquadra numeric vector
Mventra numeric vector
Ppatula numeric vector
Pquadra numeric vector
Pvulgaa numeric vector
Spectia numeric vector
Tpatina numeric vector
Tsimila numeric vector
Ttetraa numeric vector
Source
Fontaneto D., Barbosa A.M., Segers H. & Pautasso M. (2012) The 'rotiferologist' effect and other global correlates of species richness in monogonont rotifers. Ecography, 35: 174-182.
Examples
data(rotif.env)
head(rotif.env)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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