removal {FSA}R Documentation

Computes population estimates for k-, 3-, or 2-pass removal data.

Description

Computes estimates, with confidence intervals, of the population size and probability of capture from the number of fish removed in k-, 3-, or 2-passes in a closed population.

Usage

removal(catch,type=c("Zippin","CarleStrub","Seber3","Seber2","RobsonRegier2"),
        alpha=1,beta=1)

## S3 method for class 'Removal':
summary(object,...)

## S3 method for class 'Removal':
confint(object,parm=c("both","all","No","p"),level=conf.level,
        conf.level=0.95,...)

Arguments

catch a numerical vector of catches of fish at each pass.
type a string that identifies the type of removal method to use for the calculations. See details.
alpha a numeric value for the alpha parameter in the CS method (default is 1).
beta a numeric value for the beta parameter in the CS method (default is 1).
object An object saved from the removal.pass call (i.e., of class Removal).
parm a specification of which parameters are to be given confidence intervals, either a vector of numbers or a vector of names. If missing, all parameters are considered.
level Same as conf.level but used for compatability with generic confint function.
conf.level a number representing the level of confidence to use for constructing confidence intervals.
... Additional arguments for methods.

Details

The main function computes teh estimates and associated standard errors for the initial population size, No, and probability of capture, p, for six possible methods chosen with the type argument. The types of methods that can be used are listed below.

type="Zippin"
The general k-pass estimator generally attributed to Zippin. This function iteratively solves for No in equation 3 of Carle and Strub (1978).
type="CarleStrub"
The general weighted k-pass estimator proposed by Carle and Strub (1978). This function iteratively solves for No in equation 7 of Carle and Strub (1978).
type="Seber3"
The special case for k=3 estimator shown by Seber(1982).
type="Seber2"
The special case for k=2 estimator shown by Seber(1982).
type="RobsonRegier2"
The special case for k=2 estimator shown by Robson and Regier (1968).

Confidence intervals are computed using standard large-sample normal distribution theory. Note that the confidence intervals for the 2- and 3-pass special cases are only approximately correct if the estimated population size is greater than 200. If the estimated population size is between 50 and 200 then a 95% CI behaves more like a 90% CI.

Value

A list with the following items,

catch the original vector of observed catches.
type The type of method used (provided by the user).
meth A label for the type of method used.
est A 2x2 matrix that contains the estimates and standard errors for No and p.

Author(s)

Derek H. Ogle, dogle@northland.edu

References

Carle, F.L. and M.R. Strub. 1978. A new method for estimating population size from removal data. Biometrics, 34:621-630.

Seber, G.A.F. 1982. The Estimation of Animal Abundance. Edward Arnold, second edition.

Robson, D.S., and H.A. Regier. 1968. Estimation of population number and mortality rates. pp. 124-158 in Ricker, W.E. (editor) Methods for Assessment of Fish Production in Fresh Waters. IBP Handbook NO. 3 Blackwell Scientific Publications, Oxford.

Cowx, I.G. 1983. Review of the methods for estimating fish population size from survey removal data. Fisheries Management, 14:67-82.

See Also

depletion

Examples

## First example -- 3 passes
ct3 <- c(77,50,37)

# Zippin (default) method
p1 <- removal(ct3)
summary(p1)
confint(p1)  

# Carle Strub method
p2 <- removal(ct3,type="CarleStrub")
summary(p2)
confint(p2)

# Seber method
p3 <- removal(ct3,type="Seber3")
summary(p3)
confint(p3)

## Second example -- 2 passes
ct2 <- c(77,37)

# Seber method
p4 <- removal(ct2,type="Seber2")
summary(p4)
confint(p4)

# Robson-Regier method
p5 <- removal(ct2,type="RobsonRegier2")
summary(p5)
confint(p5)
[Package FSA version 0.0-13 Index]