teasel {popbio} | R Documentation |
Transition T and Fertility F matrices for the plant teasel
data(teasel)
A list with T and F matrices
Example 5.2
Caswell, H. 2001. Matrix population models: construction, analysis, and interpretation, Second edition. Sinauer, Sunderland, Massachusetts, USA.
data(teasel) A<-teasel$T + teasel$F A tea<-eigen.analysis(A, zero=FALSE) tea$lambda1 ## Summed elasticities. Growth in bottom-left triangle, stasis on diagonal, and # fertility in a prebreeding census for a monocarpic plant is in last column. elas<-tea$elasticities elas el<-c(fertility=sum(elas[,6]), stasis=sum(diag(elas)), growth=sum(elas[row(elas)>col(elas)])) el ## Some plotting examples for sensitivity/elasticity matrices tea$sensitivities ## also try dotplot in lattice package matplot(t(tea$sensitivities), las=1, xlab="Stage at time t", ylab="Sensitivity", main="Sensitivity matrix using matplot #1") legend(4,45, colnames(elas), pch=as.character(1:6), col=1:6, title="Fate at time t+1") ## log-scale matplot(t(tea$sensitivities), log='y', yaxt='n', xlab="Stage at time t", ylab="Sensitivity (log scale)", main="Sensitivity matrix using matplot #2") axis(2, at=c(0.0001, 0.01, 1), labels=expression(10^-4, 10^-2, 10^0) , las=1) # Matrix plots like figure 9.4 in Caswell (no 3d barplot in R) ## image plot with color key def.par <- par(no.readonly = TRUE) # save default, for resetting layout(matrix(c(1,2), nrow=1), wid=c(1,3)) clrs<-heat.colors(24) z<-range(log10(tea$sensitivities)) ## key plot(c(0,1), z, xaxs="i", type = "n", bty="n", xaxt="n", xlab="", ylab="Log10 sensitivity", las=1, cex.lab=0.9) i <- seq(z[1], z[2],length= length(clrs)+1 ) rect(0, i[-(length(clrs)+1)], 1, i[-1], col=clrs, border=NA) rect(0,z[1], 1, z[2], lwd=2) # plot image(1:6, 1:6, t(log10(tea$sensitivities)[6:1,]), col=clrs, yaxt='n', xlab = "Stage at time t", ylab = "Fate at time t+1") axis(2, 1:6, 6:1, las=1) box() par(xpd=NA) text(2,7, expression(bold("Sensitivity matrix using image")), cex=1.2) par(def.par) plot(log10(c(tea$sensitivities)), type="s", ylim=c(-5,2), las=1, xlab="Stage at time t", xaxt="n", ylab=expression(paste(Log[10], " sensitivity of ", lambda)), main="Sensitivity matrix using stair-step") axis(1, seq(1,36,6), 1:6) text(log10(c(tea$sensitivities)), cex=.7, pos=3, labels=paste(" ", 1:6, rep(1:6,each=6), sep=""))