On this Picostat.com statistics page, you will find information about the plantTraits data set which pertains to Plant Species Traits Data. The plantTraits data set is found in the cluster R package. You can load the plantTraits data set in R by issuing the following command at the console data("plantTraits"). This will load the data into a variable called plantTraits. If R says the plantTraits data set is not found, you can try installing the package by issuing this command install.packages("cluster") and then attempt to reload the data. If you need to download R, you can go to the R project website. You can download a CSV (comma separated values) version of the plantTraits R data set. The size of this file is about 17,957 bytes.

Plant Species Traits Data

Description

This dataset constitutes a description of 136 plant species according to biological attributes (morphological or reproductive)

Usage

data(plantTraits)

Format

A data frame with 136 observations on the following 31 variables.

pdias

Diaspore mass (mg)

longindex

Seed bank longevity

durflow

Flowering duration

height

Plant height, an ordered factor with levels 1 < 2 < ... < 8.

begflow

Time of first flowering, an ordered factor with levels 1 < 2 < 3 < 4 < 5 < 6 < 7 < 8 < 9

mycor

Mycorrhizas, an ordered factor with levels 0never < 1 sometimes< 2always

vegaer

aerial vegetative propagation, an ordered factor with levels 0never < 1 present but limited< 2important.

vegsout

underground vegetative propagation, an ordered factor with 3 levels identical to vegaer above.

autopoll

selfing pollination, an ordered factor with levels 0never < 1rare < 2 often< the rule3

insects

insect pollination, an ordered factor with 5 levels 0 < ... < 4.

wind

wind pollination, an ordered factor with 5 levels 0 < ... < 4.

lign

a binary factor with levels 0:1, indicating if plant is woody.

piq

a binary factor indicating if plant is thorny.

ros

a binary factor indicating if plant is rosette.

semiros

semi-rosette plant, a binary factor (0: no; 1: yes).

leafy

leafy plant, a binary factor.

suman

summer annual, a binary factor.

winan

winter annual, a binary factor.

monocarp

monocarpic perennial, a binary factor.

polycarp

polycarpic perennial, a binary factor.

seasaes

seasonal aestival leaves, a binary factor.

seashiv

seasonal hibernal leaves, a binary factor.

seasver

seasonal vernal leaves, a binary factor.

everalw

leaves always evergreen, a binary factor.

everparti

leaves partially evergreen, a binary factor.

elaio

fruits with an elaiosome (dispersed by ants), a binary factor.

endozoo

endozoochorous fruits, a binary factor.

epizoo

epizoochorous fruits, a binary factor.

aquat

aquatic dispersal fruits, a binary factor.

windgl

wind dispersed fruits, a binary factor.

unsp

unspecialized mechanism of seed dispersal, a binary factor.

Details

Most of factor attributes are not disjunctive. For example, a plant can be usually pollinated by insects but sometimes self-pollination can occured.

Source

Vallet, Jeanne (2005) Structuration de communautés végétales et analyse comparative de traits biologiques le long d'un gradient d'urbanisation. Mémoire de Master 2 'Ecologie-Biodiversité-Evolution'; Université Paris Sud XI, 30p.+ annexes (in french)

Examples

data(plantTraits)## Calculation of a dissimilarity matrix
library(cluster)
dai.b <- daisy(plantTraits,
               type = list(ordratio = 4:11, symm = 12:13, asymm = 14:31))## Hierarchical classification
agn.trts <- agnes(dai.b, method="ward")
plot(agn.trts, which.plots = 2, cex= 0.6)
plot(agn.trts, which.plots = 1)
cutree6 <- cutree(agn.trts, k=6)
cutree6## Principal Coordinate Analysis
cmdsdai.b <- cmdscale(dai.b, k=6)
plot(cmdsdai.b[, 1:2], asp = 1, col = cutree6)

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Dataset imported from https://www.r-project.org.