Description Usage Arguments Details Value References Examples
This function applies the Virtual Population Analysis (VPA) or Cohort analysis (CA). Methods used to estimate stock biomass and fishing mortality per age/length group.
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param 
a list consisting of following parameters:

catch_columns 
numerical; indicating the column of the catch matrix which should be used for the analysis. 
catch_unit 
optional; a character indicating if the catch is provided in weight ("tons" or "kg") or in thousand individuals ("'000") 
catch_corFac 
optional; correction factor for catch, in case provided catch does spatially or temporarily not reflect catch for fishing ground of a whole year. 
terminalF 
the fishing mortality rate of the last age/length group. 
terminalE 
the exploitation rate of the last age/length group. 
analysis_type 
determines which type of assessment should be done, options: "VPA" for age or lengthbased Virtual Population Analysis, "CA" for age or lengthbased Cohort Analysis. Default is "VPA". 
algorithm 
an Algorithm to use to solve for fishing mortality. The default
setting 
plus_group 
logical; indicating if the last length group is a plus group (default: TRUE). 
plot 
logical; indicating whether a plot should be printed 
The main difference between virtual population analysis (VPA) and cohort
analysis (CA) is the step of calculating the fishing mortality per age class or
length group. While CA works with an approximation by assuming that all fish are
caught during a single day, which makes the calcualtion easier, VPA assumes that
the fish are caught continuously, which has to be solved by the trial and error
method (Sparre and Venema, 1998).
For the agebased VPA/CA the catch has to be provided in numbers (or '000 numbers),
while for the lengthbased VPA/CA the catch can also be provided in weight (tons or kg) by
using the argument catch_unit
.
The catch has to be representative for fished species, that means there should not be
other fisheries fishing the same stock. If this is the case catch_corFac
can
be used as a raising factor to account for the proportion of fish caught by other
fisheries.
When the model should follow a real cohort instead of a pseudo cohort, catch
has to be provided as matrix. The model then starts to follow the first age class
in the first column.
If catch
matrix is shorter than the number of age classes, the age or length
classes without catch information are omitted. It is recommended to only
follow a real cohort if there is enough information for all age classes
(test with: dim(catch)[1] <= dim(catch)[2]
).
If plus_group
is TRUE a different calculation for the survivors of the last length group
is used (for more details please refer to Sparre & Venema (1998)).
A list with the input parameters and following list objects:
classes.num: numeric age classes or length groups (without plus sign),
catch.cohort: a vector with the catch values which were used for the analysis (exists only if catch was a matrix),
FM_calc: a vector with the ifshing mortality (M),
Z: a vector with the total mortality (Z),
survivors: a vector with the number of fish surviving to the next age class or length group (same unit than input catch vector),
annualMeanNr: ta vector with the mean number of fish per year (same unit than input catch vector),
meanBodyWeight: a vector with the mean body weight in kg,
meanBiomassTon: a vector with the mean biomass in tons,
YieldTon: a vector with the yield in tons,
natLoss: a vector with the number of fish died due to natural mortality,
plot_mat: matrix with rearranged survivors, nat losses and catches for plotting;
Jones, R., 1984. Assessing the effects of changes in exploitation pattern using length composition data (with notes on VPA and cohort analysis). FAO Fish.Tech.Pap., (256): 118p.
Jones, R., 1990. Lengthcohort analysis: the importance of choosing the correct growth parameters. Journal du Conseil: ICES Journal of Marine Science, 46(2), 133139
Pope, J.G., 1972. An investigation of the accuracy of virtual population analysis using cohort analysis. Res.Bull.ICNAF, (9):6574
Pope, J.G., 1979. A modified cohort analysis in which constant natural mortality is replaced by estimates of predation levels. ICES C.M. 1979/H:16:7p. (mimeo)
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.
References for weightlength relationship parameters (a & b): Dorel, D., 1986. Poissons del'Atlantique nordest relations taillepoids. Institut Francais de Recherche pour l'Exploitation de la Mer. Nantes, France. 165 p.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21  #_______________________________________________
# Virtual Popuation Analysis with agecomposition data
data(whiting)
output < VPA(param = whiting, catch_columns = 1, terminalE = 0.5, analysis_type = "VPA")
plot(output)
#_______________________________________________
# Pope's Cohort Analysis with agecomposition data
data(whiting)
VPA(whiting, terminalE = 0.5, catch_columns = 3, analysis_type = "CA",
plot= TRUE, plus_group = TRUE)
#_______________________________________________
# Virtual population analysis with lengthcomposition data
data(hake)
VPA(hake, terminalE = 0.5, analysis_type = "VPA", plot = TRUE,
catch_unit = "'000", plus_group = TRUE)
#_______________________________________________
# Jones's Cohort Analysis with lengthcomposition data
data(hake)
VPA(hake, terminalE = 0.5, analysis_type = "CA", plot = TRUE,
catch_unit = "'000", plus_group = TRUE)

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