TropFishR (version 1.6.2)

prod_mod: Production models

Description

Production models are holistic models, which can be used to estimate maximum sustainable yield (MSY) and virgin biomass. This function uses the equilibrium approach to estimate parameters (Schaefer model and Fox model).

Usage

prod_mod(data, plot = FALSE)

Arguments

data

a dataframe consisting of:

  • year year vector,

  • Y catch in weight per year, and

  • f fishing effort per year, or

  • CPUE catch per unit of effort per year (optional).

plot

logical; if TRUE, a graph is displayed

Value

A list with the input parameters and following list objects:

  • Schaefer_lm: intercept and slope of linear model following the Schaefer model,

  • Fox_lm: intercept and slope of linear model following the Fox model,

  • Schaefer_MSY: MSY according to Schaefer model,

  • Schaefer_fMSY: fishing effort yielding in MSY according to Schaefer model,

  • Schaefer_Bv: virgin biomass according to Schaefer model,

  • ln_CPUE: natural logarithm of CPUE values,

  • Fox_MSY: MSY according to Fox model,

  • Fox_fMSY: fishing effort yielding in MSY according to Fox model,

  • Fox_Bv: virgin biomass according to Fox model.

Details

Production models are also called surplus production models or biomass dynamic models. They can be applied if sufficient data are available: effort and yield parameters have to be expended over a certain number of years. Furthermore, the fishing effort must have undergone substantial changes over the period covered (Sparre and Venema, 1998). Either the catch per unit of effort (CPUE) is inserted into the model directly (objectname: CPUE) or the CPUE is calculated from the catch and effort, then these two vectors should have required units. There are three ways of estimating paramaters of production models, (i) assuming equlibrium conditions, (ii) transforming equation to linear form, or (iii) time-series fitting (Hilborn and Walters, 1992). The first approach corresponds to the Schaefer and Fox model and thus the methodology of this function. The authors recommend to use dynamic fitting methods when possible rather than the equilibrium approach. For dynamic production models please refer to prod_mod_ts.

References

Fox, W. W. Jr., 1970. An exponential surplus-yield model for optimizing exploited fish populations. Trans.Am.Fish.Soc., 99:80-88

Graham, M., 1935. Modern theory of exploiting a fishery and application to North Sea trawling. J.Cons.CIEM, 10(3):264-274

Hilborn, R., Walters, C. J. (1992). Quantitative fisheries stock assessment: choice, dynamics and uncertainty. Reviews in Fish Biology and Fisheries, 2(2), 177-178.

Schaefer, M., 1954. Some aspects of the dynamics of populations important to the management of the commercial marine fisheries. Bull.I-ATTC/Bol. CIAT, 1(2):27-56

Schaefer, M., 1957. A study of the dynamics of the fishery for yellowfin tuna of the eastern tropical Pacific Ocean [in English and Spanish]. Ibid., 2(6): 245-285

Sparre, P., Venema, S.C., 1998. Introduction to tropical fish stock assessment. Part 1. Manual. FAO Fisheries Technical Paper, (306.1, Rev. 2). 407 p.

Examples

Run this code
# NOT RUN {
data(trawl_fishery_Java)
prod_mod(data = trawl_fishery_Java, plot = TRUE)

# }

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