Methods to compute total quant-aggregated catch, landings, discards and stock biomass from age or length-structured numbers and mean weights.
Methods to compute total quant-aggregated catch, landings, discards and stock biomass from age or length-structured numbers and mean weights.
Usage
computeLandings(object, ...)
computeDiscards(object, ...)
computeCatch(object, ...)
computeStock(object, ...)
computeHarvest(object, catch, ...)
computeLandings(object, ...)
computeDiscards(object, ...)
computeCatch(object, ...)
computeStock(object, ...)
# S4 method for class 'FLS'
computeLandings(object, na.rm = TRUE)
# S4 method for class 'FLS'
computeDiscards(object, na.rm = TRUE)
# S4 method for class 'FLS'
computeCatch(object, slot = "catch", na.rm = TRUE)
# S4 method for class 'FLS'
computeStock(object, na.rm = TRUE)Details
These methods compute the total catch, landings, discards and stock biomass
from the quant-structured values in numbers and weight per individual. The
calculation for landings, discards and stock involves the product of the
landings/discards/stock in numbers (landings.n, discards.n or
stock.n) by the individual weight-at-quant (landings.wt,
discards.wt or stock.wt), as in
$$L=L_n * L_{wt}$$
By selecting slot="catch", computeCatch can calculate in the
same way the total catch from the catch-at-quant and weight in the catch.
Those two values (in slots catch.n and catch.wt) can also be
calculated (from landings and discards) by specifying slot="n" and
slot="wt" respectively. Calling computeCatch with option
slot="all" will carry out the three calculations. In this case, the
returned object will be of class FLQuants, with element names
catch, catch.n and catch.wt, which can then be passed
directly to the catch<- replacement method.
These methods compute the total catch, landings, discards and stock biomass
from the quant-structured values in numbers and weight per individual. The
calculation for landings, discards and stock involves the product of the
landings/discards/stock in numbers (landings.n, discards.n or
stock.n) by the individual weight-at-quant (landings.wt,
discards.wt or stock.wt), as in
$$L=L_n * L_{wt}$$
By selecting slot="catch", computeCatch can calculate in the
same way the total catch from the catch-at-quant and weight in the catch.
Those two values (in slots catch.n and catch.wt) can also be
calculated (from landings and discards) by specifying slot="n" and
slot="wt" respectively. Calling computeCatch with option
slot="all" will carry out the three calculations. In this case, the
returned object will be of class FLQuants, with element names
catch, catch.n and catch.wt, which can then be passed
directly to the catch<- replacement method.
Generic function
computeCatch(object, ...)
computeLandings(object, ...)
computeDiscards(object, ...)
computeStock(object, ...)
computeCatch(object, ...)
computeLandings(object, ...)
computeDiscards(object, ...)
computeStock(object, ...)
Examples
data(ple4)
summary(computeLandings(ple4))
#> An object of class "FLQuant" with:
#>
#> dim: age year unit season area iter
#> 1 61 1 1 1 1
#> units: t
#>
#> Min. 1st Qu. Median Mean 3rd Qu. Max. %NAs
#> 59713 82875 103162 108795 130443 187666 0
summary(computeCatch(ple4, slot="all"))
#> An object of class "FLQuants"
#>
#> Elements: catch.wt catch.n catch landings discards
#>
#> Name: catch.wt
#> dim : 10 61 1 1 1 1
#> quant: age
#> units: kg
#>
#> Min : 0.02500463
#> 1st Qu.: 0.2190491
#> Mean : 0.4378413
#> Median : 0.4175921
#> 3rd Qu.: 0.6279721
#> Max : 1.126954
#> NAs : 0 %
#> Name: catch.n
#> dim : 10 61 1 1 1 1
#> quant: age
#> units: 1000
#>
#> Min : 541.6833
#> 1st Qu.: 7740.584
#> Mean : 79380
#> Median : 32437.93
#> 3rd Qu.: 114974.9
#> Max : 1083226
#> NAs : 0 %
#> Name: catch
#> dim : 1 61 1 1 1 1
#> quant: age
#> units: t
#>
#> Min : 78360.36
#> 1st Qu.: 131216.1
#> Mean : 160583.9
#> Median : 149389.9
#> 3rd Qu.: 175881.4
#> Max : 315244.7
#> NAs : 0 %
#> Name: landings
#> dim : 1 61 1 1 1 1
#> quant: age
#> units: t
#>
#> Min : 59712.83
#> 1st Qu.: 82874.98
#> Mean : 108795.2
#> Median : 103161.8
#> 3rd Qu.: 130443
#> Max : 187666.1
#> NAs : 0 %
#> Name: discards
#> dim : 1 61 1 1 1 1
#> quant: age
#> units: t
#>
#> Min : 7434.188
#> 1st Qu.: 35985.66
#> Mean : 51788.75
#> Median : 46770.16
#> 3rd Qu.: 61510.89
#> Max : 153474.4
#> NAs : 0 %
stock(ple4) <- computeStock(ple4)
landings(ple4) <- computeLandings(ple4)
catch.n(ple4) <- computeCatch(ple4, slot="n")
catch(ple4) <- computeCatch(ple4, slot="all")
data(ple4)
summary(computeLandings(ple4))
#> An object of class "FLQuant" with:
#>
#> dim: age year unit season area iter
#> 1 61 1 1 1 1
#> units: t
#>
#> Min. 1st Qu. Median Mean 3rd Qu. Max. %NAs
#> 59713 82875 103162 108795 130443 187666 0
summary(computeCatch(ple4, slot="all"))
#> An object of class "FLQuants"
#>
#> Elements: catch.wt catch.n catch landings discards
#>
#> Name: catch.wt
#> dim : 10 61 1 1 1 1
#> quant: age
#> units: kg
#>
#> Min : 0.02500463
#> 1st Qu.: 0.2190491
#> Mean : 0.4378413
#> Median : 0.4175921
#> 3rd Qu.: 0.6279721
#> Max : 1.126954
#> NAs : 0 %
#> Name: catch.n
#> dim : 10 61 1 1 1 1
#> quant: age
#> units: 1000
#>
#> Min : 541.6833
#> 1st Qu.: 7740.584
#> Mean : 79380
#> Median : 32437.93
#> 3rd Qu.: 114974.9
#> Max : 1083226
#> NAs : 0 %
#> Name: catch
#> dim : 1 61 1 1 1 1
#> quant: age
#> units: t
#>
#> Min : 78360.36
#> 1st Qu.: 131216.1
#> Mean : 160583.9
#> Median : 149389.9
#> 3rd Qu.: 175881.4
#> Max : 315244.7
#> NAs : 0 %
#> Name: landings
#> dim : 1 61 1 1 1 1
#> quant: age
#> units: t
#>
#> Min : 59712.83
#> 1st Qu.: 82874.98
#> Mean : 108795.2
#> Median : 103161.8
#> 3rd Qu.: 130443
#> Max : 187666.1
#> NAs : 0 %
#> Name: discards
#> dim : 1 61 1 1 1 1
#> quant: age
#> units: t
#>
#> Min : 7434.188
#> 1st Qu.: 35985.66
#> Mean : 51788.75
#> Median : 46770.16
#> 3rd Qu.: 61510.89
#> Max : 153474.4
#> NAs : 0 %
stock(ple4) <- computeStock(ple4)
landings(ple4) <- computeLandings(ple4)
catch.n(ple4) <- computeCatch(ple4, slot="n")
catch(ple4) <- computeCatch(ple4, slot="all")