popbio (version 2.4.4)

monkeyflower: Projection matrices for monkeyflower

Description

Pooled and annual projection matrices of central and marginal populations of monkeyflowers (Mimulus cardinalis and M. lewisii)

Usage

data(monkeyflower)

Format

A data frame with 32 projection matrices, arranged with one matrix per row

species

M. cardinalis or M. lewisii

site

Study site

year

Start year of projection interval or pooled for all three years

a11

matrix element a11; seed to seed transition or seed bank survival

a12

matrix element a12; small nr to seed - fertility

a13

matrix element a13; large nr to seed - fertility

a14

matrix element a14; reprod to seed - fertility

a21

matrix element a21; seed to small nr - growth

a22

matrix element a22; small nr to small nr -stasis

a23

matrix element a23; large nr to small nr - regress

a24

matrix element a24; reprod to small nr - regress

a31

matrix element a31; seed to large nr - growth

a32

matrix element a32; small nr to large nr - growth

a33

matrix element a33; large nr to large nr - stasis

a34

matrix element a34; reprod to large nr - regress

a41

matrix element a41; seed to reprod - growth

a42

matrix element a42; small nr to reprod - growth

a43

matrix element a43; large nr to reprod - growth

a44

matrix element a44; reprod to reprod - stasis

Details

Matrix constructed using a post-breeding census with four stage classes: Seeds, small non-reproductive, large non-reproductive, and reproductive.

References

Amy Lauren Angert. 2006. Demography of central and marginal populations of monkeyflowers (Mimulus cardinalis and M. lewisii). Ecology 87:2014-2025.

Examples

# NOT RUN {
data(monkeyflower)
## convert M. cardinalis rows to list of 16 matrices
A <- subset(monkeyflower, species=="cardinalis")
# use as.matrix to convert data.frame to numeric matrix
A<-split( as.matrix(A[, 4:19]),  paste(A$site, A$year))
stages<-c("seed", "sm.nr", "lg.nr", "repro")
## convert to list of 16 matrices
A<-lapply(A, matrix, nrow=4, byrow=TRUE, dimnames=list(stages,stages))
A[8]
image2(A[[8]], round=8, mar=c(1,3,4.5,1))
title( paste("M. cardinalis - ", names(A[8])), line=2.5)


## plot like figure 1A
x<- matrix(sapply(A, lambda), ncol=4)
colnames(x)<-c("BU",  "CA", "RP", "WA")
rownames(x)<-c(2000:2002, "pooled")
x<-x[,c(1,3,4,2)]
colrs<-gray(0:3 / 3)[c(1,3,2,4)]
barplot(x, beside=TRUE, las=1, col=colrs, ylim=c(0,2),
ylab="Population growth rate", main="Mimulus cardinalis")
box()
abline(h=1, lwd=.5)
legend(1,1.95, rownames(x), fill=colrs, bty='n')

# }