get_indicators: Calculate indicators

In LeMaRns: Length-Based Multispecies Analysis by Numerical Simulation

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)

LeMaRns documentation built on Dec. 9, 2019, 5:09 p.m.