Description Usage Arguments Details Value See Also Examples
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.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 | 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
)
|
inputs |
A |
outputs |
A |
... |
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 |
time_steps |
A numeric vector of the time steps that you wish to use to calculate the indicators. The default is |
prob |
A numeric value or vector between 0 and 1 denoting the length quantiles to be calculated. The default is |
length_LFI |
A numeric vector representing the thresholds to be used to calculate the LFI. The default value is |
N |
An array with dimensions |
wgt |
A matrix with dimensions |
mid |
A numeric vector of length |
l_bound |
A numeric vector of length |
u_bound |
A numeric vector of length |
Linf |
A numeric vector of length |
species_names |
A character vector of length |
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.
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,j
th element represents the LFI using the j
th length_LFI
in the i
th 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,j
th element is the LQ using thej
th prob
in the i
th 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,j
th element is the LFI using the j
th length_LFI
in the i
th 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,j
th element is the LQ using the the j
th prob
in the i
th time_steps
. If length(prob)==1
, the function will return a numeric vector of length length(time_steps)
.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | # 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)
|
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