Length-based Beverton-Holt Equilibrium Total Instantaneous Mortality Estimator

Share:

Description

Calculate the equilibrium Beverton-Holt estimator of instantaneous total mortality (Z) from length data with bootstrapped standard errors or the same using the Ehrhardt and Ault(1992) bias-correction

Usage

1
bheq(len, type = c(1,2), K = NULL, Linf = NULL, Lc = NULL, La = NULL, nboot = 100)

Arguments

len

the vector of length data. Each row represents one record per individual fish.

type

numeric indicate which estimation method to use. 1 = Beverton-Holt, 2 = Beverton-Holt with bias correction. Default is both, c(1,2).

K

the growth coefficient from a von Bertalanffy growth model.

Linf

the L-infinity coefficient from a von Bertalanffy growth model.

Lc

the length at first capture.

La

the largest length of the largest size class.

nboot

the number of bootstrap runs. Default=100.

Details

The standard Beverton-Holt equilibrium estimator of instantaneous total mortality (Z) from length data (page 365 in Quinn and Deriso (1999)) is calculated. The mean length for lengths >=Lc is calculated automatically. Missing data are removed prior to calculation. Estimates of standard error are made by bootstrapping length data >=Lc using package boot.

Value

Dataframe of length 1 containing mean length>=Lc, sample size>=Lc, Z estimate and standard error.

Author(s)

Gary A. Nelson, Massachusetts Division of Marine Fisheries gary.nelson@state.ma.us

References

Ehrhardt, N. M. and J. S. Ault. 1992. Analysis of two length-based mortality models applied to bounded catch length frequencies. Trans. Am. Fish. Soc. 121:115-122.

Quinn, T. J. and R. B. Deriso. 1999. Quantitative Fish Dynamics. Oxford University Press, New York, New York. 542 pages.

See Also

bhnoneq

Examples

1
2
data(pinfish)
bheq(pinfish$sl,type=1,K=0.33,Linf=219.9,Lc=120,nboot=200)

Want to suggest features or report bugs for rdrr.io? Use the GitHub issue tracker.