agesurv {fishmethods}

Age-based Survival Estimators

Description

Calculates annual survival (S) and instantaneous total mortality rates (Z) from age frequency by using linear regression (standard and weighted), Heincke, Chapman-Robson, Poisson GLM and GLMER methods.

Usage

agesurv(type=1, age=NULL, number=NULL, full=NULL, last=NULL, estimate=c("s","z"),
method=c("lr","he","cr","crcb","ripois","wlr","pois"), sign.est=3, sign.se=3, 
 glmer.control=glmerControl(optCtrl=list(maxfun=10000),optimizer="bobyqa"))

Arguments

type

the format of data. 1 = a single vector, each row represents the age of an individual (default), 2 = summarized, one column of age and one column of numbers-at-age.

age

the vector of ages.

number

if type = 2, a vector of numbers-at-age matching the length of the age vector.

full

the fully-recruited age

last

the maximum age to include in the calculation. If not specified, the oldest age is used.

estimate

argument to select estimate type: "s" for annual survival, "z" for instantaneous total mortality. Default is both.

method

argument to select the estimation method: "lr" for standard linear regression, "he" for Heincke, "cr" for Chapman-Robson, "crcb" for Chapman-Robson Z estimate with bias-correction (Seber p. 418) and over-dispersion correction (Smith et al., 2012), "ripois" for Millar (2015) random-intercept Poisson mixed model estimator, "wlr" for Maceine-Bettoli weighted regression, "pois" for Poisson generalized linear model with overdispersion correction. Default is all.

sign.est

significant digits for survival estimates.

sign.se

significant digits for standard error of survival estimates.

glmer.control

controls for function glmer used in the random-intercept Poisson mixed model. See glmerControl.

Details

If type = 1, the individual age data are tabulated. The age data are then subsetted based on the full and last arguments. Most calculations follow descriptions in Seber(1982), pages 414-418. If only two ages are present, a warning message is generated and the catch curve method is not calculated. Plus groups are not allowed. Any NAs represent no estimates due to some issue with model fit like convergence. If age samples were collected via a survey using gears such as seines or trawl, or were subsampled from catch, the least biased estimators are the "pois" and "crcb" methods (Nelson, 2019).

Value

results

list element containing table of parameters and standard errors.

data

list element containing the age frequency data used in the analysis.

Author(s)

Gary A. Nelson, Massachusetts Division of Marine Fisheries [e-mail]

References

Seber, G. A. F. 1982. The Estimation of Animal Abundance and Related Parameters, Second Edition. The Blackburn Press, Caldwell, New Jersey. 654 pages.

Maceina, M. J. and P. W. Bettoli. 1998. Variation in largemouth bass recruitment in four mainstream impoundments of the Tennessee River. N. Am. J. Fish. Manage. 18: 990-1003.

Millar, R. B. 2015. A better estimator of mortality rate from age-frequency data. Can. J. Fish. Aquat. Sci. 72: 364-375.

Nelson, G. A. 2019. Bias in common catch-curve methods applied to age frequency data from fish surveys. ICES J. Mar. Sci. doi:10.1093/icesjms/fsz085.

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

Smith, M. W. and 5 others. 2012. Recommendations for catch-curve analysis. N. Am. J. Fish. Manage. 32: 956-967.

Examples

data(rockbass)
agesurv(age=rockbass$age,full=6)