tortoise {popbio} | R Documentation |
Transition matrix and fertility estimates for the desert tortoise Gopherus agassizii
data(tortoise)
A list of 1 average transition matrix (T) and 4 fertility matrix estimates (low, medium low, medium high, and high)
Table 5 in Doak et al (1994). Used by Caswell (2001) in chapter 9 on sensitivity analysis.
Caswell, H. 2001. Matrix population models: construction, analysis, and interpretation, Second edition. Sinauer, Sunderland, Massachusetts, USA.
Doak, D., P. Kareiva, and B. Kleptetka. 1994. Modeling population viability for the desert tortoise in the Western Mojave Desert. Ecological Applications 4:446-460.
data(tortoise) A<-tortoise$T + tortoise$F.med.high A ## log scale for coloring boxes not always needed image2(A, mar=c(1,3.5, 5,1), log=FALSE) title("Tortoise projection matrix", line=3) tor<-eigen.analysis(A, zero=FALSE) tor$lambda1 ## All 4 growth rates (first add T to all four F matrices) tor4<-lapply(tortoise[2:5], "+", tortoise$T) sapply(tor4, function(A){Re(eigen(A)$values[1])} ) elas<-tor$elasticities elas image2(elas, mar=c(1,3.5, 5,1), log=FALSE) title("Tortoise elasticity matrix", line=3) ## Summed elasticities, example 9.4. Growth on subdiagonal el<-c(F=sum(elas[1,]), P=sum(diag(elas)), G=sum(elas[row(elas)==col(elas)+1])) el ## Triangle plot like figure 9.11 in Caswell. ## Nicer triangle plots are found in many different packages. plot(c(0, 1, 2, 0), c(0, sqrt(3), 0, 0), type = "l", lwd = 2, xlab = "Summed elasticities", ylab = "", axes = FALSE) text(c(0, 2, 1), c(0,0, sqrt(3)), names(el), cex = 1.5, pos=c(1,1,3), xpd=TRUE) points(2 - 2 * el[1] - el[3], el[3] * sqrt(3), cex=1.5) ## Sensitivity plot like figure 9.3 in Caswell ## use text to add labels closer to x-axis sens<-tor$sensitivities def.par <- par(no.readonly = TRUE) par(mfrow=c(3,1), mar = c(1.5, 4.5, 1, 2) , oma=c(1.5,0,1.5,0), cex=1.2 ) ## F in top row ep<-barplot(sens[1,], ylim=c(0,.4), col="white", las=1, ylab=expression(paste("to ", italic(F[i]))), names="") box() text(ep, -.05, 1:8, xpd = TRUE) ## P on diagonal ep<-barplot(diag(sens), ylim=c(0,.4), col="white", las=1, ylab=expression(paste("to ", italic(P[i]))), names="") box() text(ep, -.05, 1:8, xpd = TRUE) # G on subdiagonal barplot(c(sens[row(sens)==col(sens)+1],0), ylim=c(0,.4), col="white", las=1, ylab=expression(paste("to ", italic(G[i]))) ) box() text(ep, -.05, c(1:7, NA), xpd = TRUE) mtext(expression(paste("Sensitivity of ", lambda, "...")), 3, outer=TRUE, cex=1.4) mtext(expression(paste("Size class ", italic(i))), 1, outer=TRUE, cex=1.2) par(def.par)