domed {MQMF}

domed calculates domed selectivity curves

Description

domed uses 6 parameters and a set of mean size or age classes to calculate a domed selectivity curve with a maximum of 1.0 (rescaling can be done outside the function), but has parameters for the selectivity of the initial and final size/age classes. There is an ascending limb and a descending limb with the potential of a plateau in between. The six parameters are 1) the age/size where selectivity first becomes 1.0, 2) the size/age where selectivity first begins to decline, 3) the steepness of the ascending limb, 4) the steepness of the descending limb, 5) the selectivity of the first age/size class, and 6) the selectivity of the last age/size class. The descending limb of any dome shaped selectivity curves imply that the fishing gear used is unable to collect all representatives of the larger or older classes. The predicted numbers of smaller or younger animals, that are only partially selected, are inflated because of the partial selection. If any larger or older animals are, in fact, caught, then the same inflation can happen to those animals as a result of the partial selection implied by the dome shape. Small and young animals weight very little, the same cannot be said for the larger or older animals. Some people refer to the extra biomass this phenomenon can imply as 'ghost biomass', even though it might be real. Whatever the case, when using dome shaped selectivity it is best to be aware of this issue and to be cautious about how this is interpreted.

Usage

domed(p, L)

Arguments

p

a vector of six parameters.

L

a vector of the mean of nL age/size classes

Value

a vector of selectivities

References

Methot, R.D. and C.R, Wetzel (2013) Stock synthesis: A biological and statistical framework for fish stock assessment and fishery management. Supplementary material, Appendix A. Equs A1.30 onwards. Fisheries Research 142:86-99.

Examples

  L <- seq(1,30,1)
  p <- c(10,11,16,33,-5,-2)
  sel <- domed(p,L)
  plot1(L,sel,xlab="Age",ylab="Selectivity",lwd=2)