fishmethods (version 1.3-0)

bhnoneq: Length-based Beverton-Holt Nonequilibrium Z Estimator

Description

A nonequilibrium Beverton-Holt estimator of instantaneous total mortality (Z) from length data.

Usage

bhnoneq(year=NULL,mlen=NULL, ss=NULL, K = NULL, Linf = NULL, 
Lc = NULL, nbreaks = NULL, styrs = NULL, stZ = NULL, 
stsigma = NULL)

Arguments

year

the vector of year values associated with mean length data. The number of year values must correspond to the number of length records. Include year value even if mean length and numbers (see below) are missing.

mlen

the vector of mean lengths for lengths >=Lc. One record for each year.

ss

the vector of numbers of observations associated with the mean length.

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.

nbreaks

the number of times (breaks) mortality is thought to change over the time series. Must be 1 or greater

styrs

the starting guess(es) of the year(s) during which mortality is thought to change. The number of starting guesses must match the number of mortality breaks, should be separated by commas within the concatentation function and should be wi

stZ

the starting guesses of Z values enclosed within the concatentation function. There should be nbreaks+1 values provided.

stsigma

the starting guess of sigma.

Value

• results
  list element containing table of parameters with estimates, standard errors, and t-values.
• obs
  list element containing year, mean length of lengths >=Lc, and sample size.
• pred
  list element containing year and predicted mean lengths.

Details

The mean lengths for each year for lengths>=Lc. Following Gedamke and Hoening(2006), the model estimates nbreaks+1 Z values, the year(s) in which the changes in mortality began, the standard deviation of lengths>=Lc, and standard errors of all parameters. An AIC value is produced for model comparison. The estimated parameters for the number of nbreaks is equal to 2*nbreaks+2. Problematic parameter estimates may have extremely large t-values or extremely small standard error. Try different starting values to ensure consistent parameter estimates.

References

Gedamke, T. and J. M. Hoenig. 2006. Estimating mortality from mean length data in nonequilibrium situations, with application to the assessment of goosefish. Trans. Am. Fish. Soc. 135:476-487

See Also

bheq2 bheq2

Examples

data(goosefish)
bhnoneq(year=goosefish$year,mlen=goosefish$mlen, ss=goosefish$ss,
K=0.108,Linf=126,Lc=30,nbreaks=1,styrs=c(1982),stZ=c(0.1,0.3),
stsigma=20)