get_indicators: Calculate indicators

In CefasRepRes/LeMaRns: Length-Based Multispecies Analysis by Numerical Simulation

Calculate indicators

Description

Calculates Mean Maximum Length (MML), the Large Fish Indicator (LFI), Typical Length (TyL) and Length Quantiles (LQ) of the whole community or a subset of the species.

Usage

get_indicators(inputs, outputs, ...)

## S4 method for signature 'LeMans_param,LeMans_outputs'
get_indicators(
  inputs,
  outputs,
  species = 1:dim(outputs@N)[2],
  time_steps = 1:dim(outputs@N)[3],
  prob = 0.5,
  length_LFI = 40
)

## S4 method for signature 'LeMans_param,missing'
get_indicators(
  inputs,
  N,
  species = 1:dim(N)[2],
  time_steps = 1:dim(N)[3],
  prob = 0.5,
  length_LFI = 40
)

## S4 method for signature 'missing,LeMans_outputs'
get_indicators(
  wgt,
  mid,
  l_bound,
  u_bound,
  Linf,
  outputs,
  species = 1:dim(outputs@N)[2],
  time_steps = 1:dim(outputs@N)[3],
  species_names = NULL,
  prob = 0.5,
  length_LFI = 40
)

## S4 method for signature 'missing,missing'
get_indicators(
  wgt,
  mid,
  l_bound,
  u_bound,
  Linf,
  N,
  species = 1:dim(N)[2],
  time_steps = 1:dim(N)[3],
  species_names = NULL,
  prob = 0.5,
  length_LFI = 40
)

get_LFI(inputs, outputs, ...)

## S4 method for signature 'LeMans_param,LeMans_outputs'
get_LFI(
  inputs,
  outputs,
  species = 1:dim(outputs@N)[2],
  time_steps = 1:dim(outputs@N)[3],
  length_LFI = 40
)

## S4 method for signature 'LeMans_param,missing'
get_LFI(
  inputs,
  N,
  species = 1:dim(N)[2],
  time_steps = 1:dim(N)[3],
  length_LFI = 40
)

## S4 method for signature 'missing,LeMans_outputs'
get_LFI(
  wgt,
  l_bound,
  u_bound,
  outputs,
  species = 1:dim(outputs@N)[2],
  time_steps = 1:dim(outputs@N)[3],
  species_names = NULL,
  length_LFI = 40
)

## S4 method for signature 'missing,missing'
get_LFI(
  wgt,
  l_bound,
  u_bound,
  N,
  species = 1:dim(N)[2],
  time_steps = 1:dim(N)[3],
  species_names = NULL,
  length_LFI = 40
)

get_MML(inputs, outputs, ...)

## S4 method for signature 'LeMans_param,LeMans_outputs'
get_MML(
  inputs,
  outputs,
  species = 1:dim(outputs@N)[2],
  time_steps = 1:dim(outputs@N)[3]
)

## S4 method for signature 'LeMans_param,missing'
get_MML(inputs, N, species = 1:dim(N)[2], time_steps = 1:dim(N)[3])

## S4 method for signature 'missing,LeMans_outputs'
get_MML(
  wgt,
  Linf,
  outputs,
  species = 1:dim(outputs@N)[2],
  time_steps = 1:dim(outputs@N)[3],
  species_names = NULL
)

## S4 method for signature 'missing,missing'
get_MML(
  wgt,
  Linf,
  N,
  species = 1:dim(N)[2],
  time_steps = 1:dim(N)[3],
  species_names = NULL
)

get_TyL(inputs, outputs, ...)

## S4 method for signature 'LeMans_param,LeMans_outputs'
get_TyL(
  inputs,
  outputs,
  species = 1:dim(outputs@N)[2],
  time_steps = 1:dim(outputs@N)[3]
)

## S4 method for signature 'LeMans_param,missing'
get_TyL(inputs, N, species = 1:dim(N)[2], time_steps = 1:dim(N)[3])

## S4 method for signature 'missing,LeMans_outputs'
get_TyL(
  wgt,
  mid,
  outputs,
  species = 1:dim(outputs@N)[2],
  time_steps = 1:dim(outputs@N)[3],
  species_names = NULL
)

## S4 method for signature 'missing,missing'
get_TyL(
  wgt,
  mid,
  N,
  species = 1:dim(N)[2],
  time_steps = 1:dim(N)[3],
  species_names = NULL
)

get_LQ(inputs, outputs, ...)

## S4 method for signature 'LeMans_param,LeMans_outputs'
get_LQ(
  inputs,
  outputs,
  species = 1:dim(outputs@N)[2],
  time_steps = 1:dim(outputs@N)[3],
  prob = 0.5
)

## S4 method for signature 'LeMans_param,missing'
get_LQ(inputs, N, species = 1:dim(N)[2], time_steps = 1:dim(N)[3], prob = 0.5)

## S4 method for signature 'missing,LeMans_outputs'
get_LQ(
  wgt,
  u_bound,
  outputs,
  species = 1:dim(outputs@N)[2],
  time_steps = 1:dim(outputs@N)[3],
  species_names = NULL,
  prob = 0.5
)

## S4 method for signature 'missing,missing'
get_LQ(
  wgt,
  u_bound,
  N,
  species = 1:dim(N)[2],
  time_steps = 1:dim(N)[3],
  species_names = NULL,
  prob = 0.5
)

Arguments

inputs	A LeMans_param object containing the parameter values of the current LeMans model.
outputs	A LeMans_outputs object containing the outputs of the model run.
...	Additional arguments.
species	A numeric value or vector or a character string representing the species that you wish to use to calculate the indicators. The default is 1:dim(N)[2].
time_steps	A numeric vector of the time steps that you wish to use to calculate the indicators. The default is 1:dim(N)[3].
prob	A numeric value or vector between 0 and 1 denoting the length quantiles to be calculated. The default is 0.5.
length_LFI	A numeric vector representing the thresholds to be used to calculate the LFI. The default value is 40.
N	An array with dimensions nsc, nfish and tot_time representing the number of individuals in each length class for each time step.
wgt	A matrix with dimensions nsc and nfish representing the weight of each species in each length class.
mid	A numeric vector of length nfish representing the mid-point of the length classes in the model.
l_bound	A numeric vector of length nsc representing the lower bounds of the length classes.
u_bound	A numeric vector of length nsc representing the upper bounds of the length classes.
Linf	A numeric vector of length nfish representing the asymptotic length of each species.
species_names	A character vector of length nfish that denotes the names of the species in the model.

Details

The LFI represents the proportion of biomass with a length larger than length_LFI. The MML is the biomass weighted mean of Linf:

sum(biomass[species]*Linf[species])/sum(biomass[species])

where biomass is a numeric vector of length nfish representing the biomass of each species. TyL is the biomass-weighted geometric mean length of the community:

exp(sum(biomass_*log(mid))/sum(Bio_l))

where biomass_ is a numeric vector of length nsc representing the biomass of all the species in each length class. The LQ is the length at which the biomass exceeds a given proportion prob of the total biomass.

Value

get_indicators returns a list object with names 'LFI', 'MML', 'TYL' and 'LQ'. If length(length_LFI)>1, 'LFI' is a matrix with dimensions length(time_steps) by length(length_LFI) where the i,jth element represents the LFI using the jth length_LFI in the ith time_steps. If length(length_LFI)==1, the function will return a numeric vector of length length(time_steps). 'MML' is a numeric vector of length time_steps where each element is the MML for the species in species. 'TYL' is a numeric vector of length time_steps where each element is the TyL for the species in species. If length(prob)==1, 'LQ' is a matrix with dimensions length(time_steps) by length(prob) where the i,jth element is the LQ using thejth prob in the ith time_steps. If length(prob)==1, the function will return a numeric vector of length length(time_steps).

If length(length_LFI)==1, get_LFI returns a matrix with dimensions length(time_steps) by length(length_LFI) where the i,jth element is the LFI using the jth length_LFI in the ith time_steps. If length(length_LFI)==1, the function will return a numeric vector of length length(time_steps).

get_MML returns a numeric vector of length time_steps where each element is the MML for the species in species.

If length(prob)>1, get_LQ returns a matrix with dimensions length(time_steps) and length(prob) where the i,jth element is the LQ using the the jth prob in the ith time_steps. If length(prob)==1, the function will return a numeric vector of length length(time_steps).

See Also

plot_indicators

Examples

# Set up and run the model
NS_params <- LeMansParam(NS_par, tau=NS_tau, eta=rep(0.25, 21), L50=NS_par$Lmat, other=1e12)
effort <- matrix(0.5, 10, dim(NS_params@Qs)[3])
model_run <- run_LeMans(NS_params, years=10, effort=effort)

# Calculate the indicators
get_indicators(inputs=NS_params, outputs=model_run)

# Calculate the LFI
get_LFI(inputs=NS_params, outputs=model_run)

# Calculate MML
get_MML(inputs=NS_params, outputs=model_run)

# Calculate TyL
get_TyL(inputs=NS_params, outputs=model_run)

# Calculate LQs
get_LQ(inputs=NS_params, outputs=model_run)

CefasRepRes/LeMaRns documentation built on Jan. 27, 2023, 4:01 p.m.