Life history parameters

data(wklife)

wklife
                      species             name          area    stock sex
1             Clupea harengus          Herring   Celtic Seas  her-nis   F
2       Pollachius pollachius          Pollack     North Sea pol-nsea   C
3                 Molva molva             Ling        Widely lin-comb   C
4         Sebastes norvegicus        Rose fish      Northern  smn-con   C
5           Mullus surmuletus       Red mullet   Celtic Seas mut-comb   F
6         Scopthalmus maximus           Turbot     North Sea tur-nsea   F
7            Microstomus kitt       Lemon sole     North Sea lem-nsea   C
8  Lepidorhombus whiffiagonis           Megrim     North Sea meg-4a6a   C
9              Ammodytes spp.         Sandeels     North Sea  san-ns4   C
10      Pleuronectes platessa           Plaice   Celtic Seas ple-celt   F
11       Merlangius merlangus          Whiting   Celtic Seas whg-7e-k   F
12   Melanogrammus aeglefinus          Haddock   Celtic Seas had-iris   C
13        Lophius piscatorius White anglerfish   Celtic Seas ang-78ab   C
14        Lophius piscatorius White anglerfish     North Sea ang-ivvi   C
15                   Nephrops        Shellfish Biscay-Iberia nep-2829   F
         a    b  linf     k    t0 lmax  l50 a50
1  0.00480 3.20  33.0 0.606    NA   NA 23.0  NA
2  0.00760 3.07  85.6 0.190    NA   NA 47.1  NA
3  0.00360 3.11 119.0 0.140    NA   NA 74.0 7.2
4  0.01780 2.97  50.2 0.110  0.08   NA 40.3  NA
5  0.00570 3.24  47.5 0.210    NA   NA 16.9  NA
6  0.01490 3.08  66.7 0.320  0.29   NA 34.2 2.2
7  0.01230 2.97  37.0 0.420    NA   NA 27.0  NA
8  0.00220 3.34  54.0 0.120    NA   NA 23.0 3.0
9  0.00490 2.78  24.0 1.000    NA   NA 12.0  NA
10 0.01100 2.96  48.0 0.230    NA   NA 22.9  NA
11 0.01030 2.40  38.0 0.380 -1.01   NA 28.0  NA
12 0.01130 2.96  79.9 0.200 -0.36   NA   NA 2.0
13 0.01980 2.90 105.6 0.180 -0.38  133 73.0  NA
14 0.02970 2.84 106.0 0.180    NA   NA 61.0  NA
15 0.00056 3.03  65.0 0.065    NA   NA 30.0  NA

Figure 1 Pairwise scatter plots of life history parameters.

Equilibrium Dynamics

Create an FLPar

wkpar=as(wklife[,6:13],"FLPar")
attributes(wkpar)[names(wklife)[1:5]]=wklife[,1:5]

Then use life history relationships to estimate missing values

par <- lhPar(wkpar)

and then to derive vectors for processses such as natural mortality

eql=lhEql(par)
sel<-function(x) 
  catch.sel(x)%/%fapex(catch.sel(x))

ggplot(FLQuants(eql,"m","catch.sel"=sel,"mat","catch.wt"))+
  geom_line(aes(age,data,col=attributes(wkpar)$stock[as.numeric(iter)]))+
  facet_wrap(~qname,scale="free")+
  scale_x_continuous(limits=c(0,15))+
  guides(colour=guide_legend(title="Species",title.position="top"))

Figure 2 Vectors of m, selection pattern, maturity and weight-at-age.

and estimate equilibrium dynamics and reference points, e.g. for lemon sole

plot(iter(eql,3))

Figure 3 Equilibrium curves for ling.

Simulation

Create a forward projection, i.e. an FLStock from an equilibrium object

lmsl=as(iter(eql,7),"FLStock")

units(mat(lmsl))="NA"
units(harvest(lmsl))="f"
plot(lmsl)

Figure 4 Simulate a stock with increasing F

Software Versions

  • R version 4.2.1 (2022-06-23)
  • FLCore: 2.6.19
  • FLPKG:
  • Compiled: Tue Aug 30 21:13:12 2022
  • Git Hash: f4ea8e3

Author information

Laurence KELL. laurie.kell.es

Acknowledgements

This vignette and many of the methods documented in it were developed under the MyDas project funded by the Irish exchequer and EMFF 2014-2020. The overall aim of MyDas is to develop and test a range of assessment models and methods to establish Maximum Sustainable Yield (MSY) reference points (or proxy MSY reference points) across the spectrum of data-limited stocks.

References