AICcmodavg (version 2.00)

salamander: Salamander capture-mark-recapture data

Description

This is a capture-mark-recapture data set on male and female Spotted Salamanders (Ambystoma maculatum) recorded by Husting (1965). A total of 1244 unique individuals were captured in pitfall traps at a breeding site between 1959 and 1963.

Usage

data(salamander)

source

Cormack, R. M. (1964) Estimates of survival from the sighting of marked animals. Biometrika 51, 429--438.

Husting, E. L. (1965) Survival and breeding structure in a population of Ambystoma maculatum. Copeia 1965, 352--362. Jolly, G. M. (1965) Explicit estimates from capture-recapture data with both death and immigration: stochastic model. Biometrika 52, 225--247.

Laake, J. L. (2013) RMark: an R interface for analysis of capture-recapture data with MARK. Alaska Fisheries Science Center (AFSC), National Oceanic and Atmospheric Administration, National Marine Fisheries Service, AFSC Report 2013-01. Lebreton, J.-D., Burnham, K. P., Clobert, J., Anderson, D. R. (1992) Modeling survival and testing biological hypotheses using marked animals: a unified approach with case-studies. Ecological Monographs 62, 67-118.

Seber, G. A. F. (1965) A note on the multiple-recapture census. Biometrika 52, 249--259.

Details

This data set is used to illustrate classic Cormack-Jolly-Seber and related models (Cormack 1964, Jolly 1965, Seber 1965, Lebreton et al. 1992).

Examples

data(salamander)
str(salamander)

##convert raw capture data to capture histories
captures <- salamander[, c("T1959", "T1960", "T1961", "T1962", "T1963")]
salam.ch <- apply(captures, MARGIN = 1, FUN = function(i)
                  paste(i, collapse = ""))

##organize as a data frame readable by RMark package (Laake 2013)
##RMark requires at least one column called "ch" 
##and another "freq" if summarized captures are provided
salam.full <- data.frame(ch = rep(salam.ch, 2),
                         freq = c(salamander$Males, salamander$Females),
                         Sex = c(rep("male", length(salam.ch)),
                           rep("female", length(salam.ch))))
str(salam.full)
salam.full$ch <- as.character(salam.full$ch)

##delete rows with 0 freqs
salam.full.orig <- salam.full[which(salam.full$freq != 0), ]

if(require(unmarked)) {
##process.data: format data, define time intervals and groups
salam.process <- process.data(salam.full.orig, model = "CJS",
                              begin.time = 1959, groups = "Sex",
                              nocc = 5)
##default dot model phi(.)p(.)
mark(salam.process, model = "CJS")
}