antTraits: Ant data, with species traits

In mvabund: Statistical Methods for Analysing Multivariate Abundance Data

Ant data, with species traits

Description

Abundances of 41 epigaeic ant species across 30 sites in south-eastern Australia, with species trait and environmental data

Usage

data(antTraits)

Format

A list containing three elements:

abund

A data frame with observations at 30 different locations of abundances of 41 epigaeic ant species.

env

A data frame containing 7 environmental variables from transects at each of the 30 sites:

Bare.ground

Percent cover of bare ground, as estimated from ten 1x1 metre quadrats

Canopy.cover

Percent canopy cover, as estimated from two 20x20m transects

Shrub.cover

Percent canopy cover, as estimated from two 20x20m transects

Volume.lying.CWD

Estimated volume of Coarse Woody Debris in two 20x20m transects, including all debris >5cm diameter.

Feral.mammal.dung

Proportion of quadrats including mammal dung, out of ten 1x1m quadrats.

traits

A data frame containing 5 species traits measured for each of the 41 species. Weber's length was log-transformed, Femur length was log-transformed then regressed against log(Weber's length), to remove the effect of size.

Femur.length

Residuals from regression of log(Femur length) against log(Weber's length)

No.spines

Number of spines on propodeum and petioles, as an integer value

Pilosity

A factor with four levels of pilosity, 0 = No or very few hairs; 1 = a sparse but regular covering of hairs; 2 = a consistent, moderate covering of hair; 3 = very dense hair covering

Polymorphism

0 = Monomorphic, 1 = polymorphic, 2 = dimorphic

Webers.length

log transformed. Body length, measured as the distance from the anterodorsal margin of the pronotum to the posteroventral margin of the propodeum

References

Gibb H, Stoklosa J, Warton, DI, Brown, AM, Andrew, NR and Cunningham, SA (2015) Does morphology predict trophic position and habitat use of ant species and assemblages? Oecologia 177, 519-531.

Examples

data(antTraits)
ft = traitglm(antTraits$abund,antTraits$env,antTraits$traits) #to do a fourth corner analysis

mvabund documentation built on March 18, 2022, 7:25 p.m.