Calculates the mean maximum weight of the community through time. This can be calculated by numbers or biomass. The calculation is the sum of the w_inf * abundance of each species, divided by the total abundance community, where abundance is either in biomass or numbers. You can specify minimum and maximum weight or length range for the species. Lengths take precedence over weights (i.e. if both min_l and min_w are supplied, only min_l will be used). You can also specify the species to be used in the calculation.

getMeanMaxWeight(sim, species = NULL, measure = "both", ...)



A MizerSim object


The species to be selected. Optional. By default all target species are selected. A vector of species names, or a numeric vector with the species indices, or a logical vector indicating for each species whether it is to be selected (TRUE) or not.


The measure to return. Can be 'numbers', 'biomass' or 'both'


Arguments passed on to get_size_range_array


Smallest weight in size range. Defaults to smallest weight in the model.


Largest weight in size range. Defaults to largest weight in the model.


Smallest length in size range. If supplied, this takes precedence over min_w.


Largest length in size range. If supplied, this takes precedence over max_w.


Depends on the measure argument. If measure = “both” then you get a matrix with two columns, one with values by numbers, the other with values by biomass at each saved time step. If measure = “numbers” or “biomass” you get a vector of the respective values at each saved time step.

See also

Other functions for calculating indicators: getCommunitySlope(), getMeanWeight(), getProportionOfLargeFish()


mmw <- getMeanMaxWeight(NS_sim)
years <- c("1967", "2010")
mmw[years, ]
#>      mmw_numbers mmw_biomass
#> 1967    2640.075   10980.365
#> 2010    2716.657    7940.787
getMeanMaxWeight(NS_sim, species=c("Herring","Sprat","N.pout"))[years, ]
#>      mmw_numbers mmw_biomass
#> 1967    12.68424    20.07675
#> 2010    10.46315    22.66197
getMeanMaxWeight(NS_sim, min_w = 10, max_w = 5000)[years, ]
#>      mmw_numbers mmw_biomass
#> 1967    1313.207    3444.342
#> 2010    2316.711    6742.697