popbio (version 2.7)

test.census: Census data for hypothetical plant

Description

Three years of census data for a hypothetical plant with three stage classes

Usage

test.census

Format

A data frame with 41 census rows and 4 columns:

plant

Plant id number

year

Year of census

stage

Stage class: seedling, vegetative, or reproductive

fruits

Total number of fruits

Examples

test.census
stages <- c("seedling", "vegetative", "reproductive")
## Cross-tabulate stage vectors and order rows by stage
sv <- table(test.census$stage, test.census$year)[stages, ]
sv
stage.vector.plot(sv)
## set xaxt='n' to avoid fractions of a year (2002.5)
stage.vector.plot(sv, prop = FALSE, xaxt = "n", las = 1)
axis(1, 2001:2003, c(2001, 2002, 2003))
## Convert census data to state-fate transition table using reshape
reshape(test.census, direction = "wide", idvar = "plant", timevar = "year")
## Convert census data  to state-fate transition table using merge
trans <- subset(
  merge(test.census, test.census, by = "plant", sort = FALSE),
  year.x == year.y - 1
)
trans
## Format column and row names
trans <- trans[, c(1:4, 6)]
colnames(trans)[2:5] <- c("year", "stage", "fruits", "fate")
rownames(trans) <- 1:nrow(trans)
## Order stage and fate columns
trans$stage <- ordered(trans$stage, levels = stages)
trans$fate <- ordered(trans$fate, levels = c(stages, "dead"))
## Select transitions for 2001-2002 and count offspring (seedlings)
trans01 <- subset(trans, year == 2001)
seedlings <- nrow(subset(test.census, year == 2002 & stage == "seedling"))
## Add individual fertilities using "anonymous reproduction"  based on the
## proportional reproductive outputs of flowering plants and the total number
## of seedlings at the end of the projection interval
trans01$seedling <- trans01$fruits / sum(trans01$fruits) * seedlings
trans01
##  Create transition frequency table  and build T matrix
tf <- table(trans01$fate, trans01$stage)
tf
## remove "dead" fate from matrix
## T.mat<-prop.table(tf,2)[-4,]
T.mat <- prop.table(tf, 2)[stages, ]
T.mat
## Summarize stage-specific fertility rates and build F matrix
fert <- tapply(trans01$seedling, trans01$stage, mean)
fert
F.mat <- T.mat * 0
F.mat[1, ] <- fert
F.mat
## The final projection matrix is just
T.mat + F.mat
## OR use projection matrix function -
projection.matrix(trans01)