warblers: Warblers Data Set

In psolymos/opticut: Likelihood Based Optimal Partitioning and Indicator Species Analysis

Warblers Data Set

Description

Five species of warblers were studied to determine the factors controlling the species abundances and competition (MacArthur 1958).

Usage

data("warblers")

Format

A list with 3 elements: xtab is a list of sample x species matrices (sec_prc: percentages of total number of seconds of observations, num_prc: percentages of total number of observations in seconds, sec_cnt: counts based on percentages and totals of seconds, num_cnt: counts based on percentages and totals), samp is a data frame with sample level attributes such as height (6 is the base, 1 is the top of trees, most trees were 50–60 feet tall) and depth of branches in the canopy (B: bare or lichen- covered base, M: middle zone of old needles, T: terminal zone of new, less than 1.5 years old, needles or buds) , taxa is a data frame with scientific and common names for the species.

Source

MacArthur 1958.

References

MacArthur, R. H., 1958. Population ecology of some warblers of northeastern coniferous forests. Ecology 39:599–619. <doi:10.2307/1931600>

Examples

data(warblers)
str(warblers)

warbh <- mefa4::groupSums(warblers$xtab$num_cnt, 1, warblers$samp$height)
warbd <- mefa4::groupSums(warblers$xtab$num_cnt, 1, warblers$samp$depth)
op <- par(mfrow=c(1,2))
matplot(rownames(warbh), warbh, type="b", xlab="height")
matplot(warbd, type="b", axes=FALSE, xlab="depth")
box()
axis(2)
axis(1, 1:3, rownames(warbd))
par(op)

psolymos/opticut documentation built on Nov. 27, 2022, 11:29 a.m.