pfister.plot: Create log-log plots of variance vs. sensitivity and CV vs....

Description Usage Arguments Details Value Author(s) References Examples

View source: R/pfister.plot.R

Description

Create log-log plots of both variance vs. sensitivity and CV vs. elasticity in matrix elements. Plots are based on Figure 2 in Pfister(1998).

Usage

1

Arguments

A

A list of two or more annual projection matrices

Details

Calculates mean, variance and coefficient of variation (CV) of matrix elements from a list of two or more projection matrices. The sensitivity and elasticity matrices are then calculated from the mean matrix using eigen.analysis

Value

Creates two log-log plots similar to Figure 2 in Pfister(1998) and outputs a data.frame with 5 columns listing mean, variance, CV, sensitivity and elasticity for matrix elements with a mean and variance > 0.

Author(s)

Chris Stubben

References

Pfister, CA. 1998. Patterns of variance in stage-structured populations: Evolutionary predictions and ecological implications. PNAS 95:213-218.

Examples

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## 4 Hudsonia matrices
data(hudsonia)
pfister.plot(hudsonia)

## 3 Mimulus cardinalis matrices at Carlon
data(monkeyflower)
mim <- subset(monkeyflower, species == "cardinalis" & 
    site == "Carlon" & year != "pooled", select = c(4:19))
## convert data frame to list of matrices using split
mim1 <-split(mim, 2000:2002)
mim2 <-lapply(mim1, matrix, nrow=4, byrow=TRUE)
vr1 <- pfister.plot(mim2)
vr1

## PLOT using labels
plot(vr1$cv, vr1$elas, xlab="CV", ylab="Elasticity", log="xy", type='n')

# Split matrix elements into transitions representing F (fertility),
# S (survival), G (growth), and R (retrogression).  
# Fertility on top row, survival on diagonal, growth is above diagonal 
# and retrogression below diagonal.

rownames(vr1)
y2 <- expression(S[11],G[21],G[31],G[41],
                 F[12],S[22],G[32],G[42],
                 F[13],R[23],S[33],G[43],
                 F[14],R[34],S[44])
text(vr1$cv, vr1$elas, y2)

### add trend line
 abline(lm(log10(vr1$elas)~log10(vr1$cv)), col="red")

## include Spearman's rank correlation
a <- cor.test(vr1$cv, vr1$elas, method="spearman")
a
text(10, .0015, substitute(rho == x, list(x=round(a$estimate,2))), col="blue")

popbio documentation built on May 4, 2018, 1:04 a.m.