monkeyflower {popbio} | R Documentation |
Pooled and annual projection matrices of central and marginal populations of monkeyflowers (Mimulus cardinalis and M. lewisii)
data(monkeyflower)
A data frame with 32 projection matrices, arranged with one matrix per row
species
site
year
a11
a12
a13
a14
a21
a22
a23
a24
a31
a32
a33
a34
a41
a42
a43
a44
Matrix constructed using a post-breeding census with four stage classes: Seeds, small non-reproductive, large non-reproductive, and reproductive.
http://www.esapubs.org/archive/ecol/E087/126/appendix-E.htm
Amy Lauren Angert. 2006. Demography of central and marginal populations of monkeyflowers (Mimulus cardinalis and M. lewisii). Ecology 87:2014-2025.
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(1,3,4,1)) title( paste("M. cardinalis - ", names(A[8])), line=3) eigen.analysis(A[['Carlon pooled']]) ## plot like figure 1A x<- matrix(sapply(lapply(A, eigen.analysis), '[[', "lambda1"), 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')