DLMtool Userguide

DLMtool Cheat Sheets

Cheat Sheets

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Stock

Slot Description
Name The name of the Stock object. Single value. Character string
Common_Name Common name of the species. Character string
Species Scientific name of the species. Genus and species name. Character string
maxage The maximum age of individuals that is simulated (there is no plus group ). Single value. Positive integer
R0 The magnitude of unfished recruitment. Single value. Positive real number
M Natural mortality rate. Uniform distribution lower and upper bounds. Positive real number
M2 (Optional) Natural mortality rate at age. Vector of length maxage . Positive real number
Mexp Exponent of the Lorenzen function assuming an inverse relationship between M and weight. Uniform distribution lower and upper bounds. Real numbers <= 0.
Msd Inter-annual variability in natural mortality rate expressed as a coefficient of variation. Uniform distribution lower and upper bounds. Non-negative real numbers
Mgrad No longer used. Previously mean temporal trend in natural mortality rate, expressed as a percentage change in M per year.
h Steepness of the stock recruit relationship. Uniform distribution lower and upper bounds. Values from 1/5 to 1
SRrel Type of stock-recruit relationship. Single value, switch (1) Beverton-Holt (2) Ricker. Integer
Perr Process error, the CV of lognormal recruitment deviations. Uniform distribution lower and upper bounds. Non-negative real numbers
AC Autocorrelation in recruitment deviations rec(t)=ACrec(t-1)+(1-AC)sigma(t). Uniform distribution lower and upper bounds. Non-negative real numbers
Period (Optional) Period for cyclical recruitment pattern in years. Uniform distribution lower and upper bounds. Non-negative real numbers
Amplitude (Optional) Amplitude in deviation from long-term average recruitment during recruitment cycle (eg a range from 0 to 1 means recruitment decreases or increases by up to 100% each cycle). Uniform distribution lower and upper bounds. 0 < Amplitude < 1
Linf Maximum length. Uniform distribution lower and upper bounds. Positive real numbers
K von Bertalanffy growth parameter k. Uniform distribution lower and upper bounds. Positive real numbers
t0 von Bertalanffy theoretical age at length zero. Uniform distribution lower and upper bounds. Non-positive real numbers
LenCV Coefficient of variation of length-at-age (assumed constant for all age classes). Uniform distribution lower and upper bounds. Positive real numbers
Ksd Inter-annual variability in growth parameter k expressed as coefficient of variation. Uniform distribution lower and upper bounds. Non-negative real numbers
Kgrad No longer used. Previously mean temporal trend in growth parameter k, expressed as a percentage change in k per year.
Linfsd Inter-annual variability in maximum length expressed as a coefficient of variation. Uniform distribution lower and upper bounds. Non-negative real numbers
Linfgrad No longer used. Previously mean temporal trend in maximum length, expressed as a percentage change in Linf per year.
L50 Length at 50 percent maturity. Uniform distribution lower and upper bounds. Positive real numbers
L50_95 Length increment from 50 percent to 95 percent maturity. Uniform distribution lower and upper bounds. Positive real numbers
D Current level of stock depletion SSB(current)/SSB(unfished). Uniform distribution lower and upper bounds. Fraction
a Length-weight parameter alpha. Single value. Positive real number
b Length-weight parameter beta. Single value. Positive real number
Size_area_1 The size of area 1 relative to area 2. Uniform distribution lower and upper bounds. Positive real numbers
Frac_area_1 The fraction of the unfished biomass in stock 1. Uniform distribution lower and upper bounds. Positive real numbers
Prob_staying The probability of inviduals in area 1 remaining in area 1 over the course of one year. Uniform distribution lower and upper bounds. Positive fraction.
Fdisc Fraction of discarded fish that die. Uniform distribution lower and upper bounds. Non-negative real numbers
Source A reference to a website or article from which parameters were taken to define the stock object. Single value. Character string.

Fleet

Slot Description
Name Name of the Fleet object. Single value. Character string.
nyears The number of years for the historical spool-up simulation. Single value. Positive integer
Spat_targ Distribution of fishing in relation to spatial biomass: fishing distribution is proportional to B^Spat_targ. Uniform distribution lower and upper bounds. Real numbers
EffYears Years representing join-points (vertices) of time-varying effort. Vector. Non-negative real numbers
EffLower Lower bound on relative effort corresponding to EffYears. Vector. Non-negative real numbers
EffUpper Upper bound on relative effort corresponding to EffYears. Vector. Non-negative real numbers
Esd Additional inter-annual variability in fishing mortality rate. Uniform distribution lower and upper bounds. Non-negative real numbers
qinc Average percentage change in fishing efficiency (applicable only to forward projection and input controls). Uniform distribution lower and upper bounds. Non-negative real numbers
qcv Inter-annual variability in fishing efficiency (applicable only to forward projection and input controls). Uniform distribution lower and upper bounds. Non-negative real numbers
L5 Shortest length corresponding to 5 percent vulnerability. Uniform distribution lower and upper bounds. Positive real numbers
LFS Shortest length that is fully vulnerable to fishing. Uniform distribution lower and upper bounds. Positive real numbers
Vmaxlen The vulnerability of fish at Stock@Linf . Uniform distribution lower and upper bounds. Fraction
isRel Selectivity parameters in units of size-of-maturity (or absolute eg cm). Single value. Boolean.
LR5 Shortest length corresponding ot 5 percent retention. Uniform distribution lower and upper bounds. Non-negative real numbers
LFR Shortest length that is fully retained. Uniform distribution lower and upper bounds. Non-negative real numbers
Rmaxlen The retention of fish at Stock@Linf . Uniform distribution lower and upper bounds. Non-negative real numbers
DR Discard rate - the fraction of caught fish that are discarded. Uniform distribution lower and upper bounds. Fraction
SelYears (Optional) Years representing join-points (vertices) at which historical selectivity pattern changes. Vector. Positive real numbers
AbsSelYears (Optional) Calendar years corresponding with SelYears (eg 1951, rather than 1), used for plotting only. Vector (of same length as SelYears). Positive real numbers
L5Lower (Optional) Lower bound of L5 (use ChooseSelect function to set these). Vector. Non-negative real numbers
L5Upper (Optional) Upper bound of L5 (use ChooseSelect function to set these). Vector. Non-negative real numbers
LFSLower (Optional) Lower bound of LFS (use ChooseSelect function to set these). Vector. Non-negative real numbers
LFSUpper (Optional) Upper bound of LFS (use ChooseSelect function to set these). Vector. Non-negative real numbers
VmaxLower (Optional) Lower bound of Vmaxlen (use ChooseSelect function to set these). Vector. Fraction
VmaxUpper (Optional) Upper bound of Vmaxlen (use ChooseSelect function to set these). Vector. Fraction
CurrentYr The current calendar year (final year) of the historical simulations (eg 2011). Single value. Positive integer.
MPA (Optional) Matrix specifying spatial closures for historical years.

Obs

Slot Description
Name The name of the observation model object. Single value. Character string.
Cobs Log-normal catch observation error expressed as a coefficient of variation. Uniform distribution lower and upper bounds. Non-negative real numbers
Cbiascv Log-normal coefficient of variation controlling the sampling of bias in catch observations for each simulation. Uniform distribution lower and upper bounds. Non-negative real numbers
CAA_nsamp Number of catch-at-age observation per time step. Uniform distribution lower and upper bounds. Positive real numbers
CAA_ESS Effective sample size (independent age draws) of the multinomial catch-at-age observation error model. Uniform distribution lower and upper bounds. Positive integers
CAL_nsamp Number of catch-at-length observation per time step. Uniform distribution lower and upper bounds. Positive integers
CAL_ESS Effective sample size (independent length draws) of the multinomial catch-at-length observation error model. Uniform distribution lower and upper bounds. Positive integers
Iobs Observation error in the relative abundance indices expressed as a coefficient of variation. Uniform distribution lower and upper bounds. Positive real numbers
Ibiascv Log-normal coefficient of variation controlling error in observations of relative abundance index. Uniform distribution lower and upper bounds. Positive real numbers
Btobs Log-normal coefficient of variation controlling error in observations of current stock biomass among years. Uniform distribution lower and upper bounds. Positive real numbers
Btbiascv Uniform-log bounds for sampling persistent bias in current stock biomass. Uniform-log distribution lower and upper bounds. Positive real numbers
beta A parameter controlling hyperstability/hyperdepletion where values below 1 lead to hyperstability (an index that decreases slower than true abundance) and values above 1 lead to hyperdepletion (an index that decreases more rapidly than true abundance). Uniform distribution lower and upper bounds. Positive real numbers
LenMbiascv Log-normal coefficient of variation for sampling persistent bias in length at 50 percent maturity. Uniform distribution lower and upper bounds. Positive real numbers
Mbiascv Log-normal coefficient of variation for sampling persistent bias in observed natural mortality rate. Uniform distribution lower and upper bounds. Positive real numbers
Kbiascv Log-normal coefficient of variation for sampling persistent bias in observed growth parameter K. Uniform distribution lower and upper bounds. Positive real numbers
t0biascv Log-normal coefficient of variation for sampling persistent bias in observed t0. Uniform distribution lower and upper bounds. Positive real numbers
Linfbiascv Log-normal coefficient of variation for sampling persistent bias in observed maximum length. Uniform distribution lower and upper bounds. Positive real numbers
LFCbiascv Log-normal coefficient of variation for sampling persistent bias in observed length at first capture. Uniform distribution lower and upper bounds. Positive real numbers
LFSbiascv Log-normal coefficient of variation for sampling persistent bias in length-at-full selection. Uniform distribution lower and upper bounds. Positive real numbers
FMSYbiascv Log-normal coefficient of variation for sampling persistent bias in FMSY. Uniform distribution lower and upper bounds. Positive real numbers
FMSY_Mbiascv Log-normal coefficient of variation for sampling persistent bias in FMSY/M. Uniform distribution lower and upper bounds. Positive real numbers
BMSY_B0biascv Log-normal coefficient of variation for sampling persistent bias in BMSY relative to unfished. Uniform distribution lower and upper bounds. Positive real numbers
Irefbiascv Log-normal coefficient of variation for sampling persistent bias in relative abundance index at BMSY. Uniform distribution lower and upper bounds. Positive real numbers
Brefbiascv Log-normal coefficient of variation for sampling persistent bias in BMSY. Uniform distribution lower and upper bounds. Positive real numbers
Crefbiascv Log-normal coefficient of variation for sampling persistent bias in MSY. Uniform distribution lower and upper bounds. Positive real numbers
Dbiascv Log-normal coefficient of variation for sampling persistent bias in stock depletion. Uniform distribution lower and upper bounds. Positive real numbers
Dobs Log-normal coefficient of variation controlling error in observations of stock depletion among years. Uniform distribution lower and upper bounds. Positive real numbers
hbiascv Log-normal coefficient of variation for sampling persistent bias in steepness. Uniform distribution lower and upper bounds. Positive real numbers
Recbiascv Log-normal coefficient of variation for sampling persistent bias in recent recruitment strength. Uniform distribution lower and upper bounds. Positive real numbers

Imp

Slot Description
Name The name of the Implementation error object. Single value. Character string.
TACFrac Mean fraction of TAC taken. Uniform distribution lower and upper bounds. Positive real number.
TACSD Log-normal coefficient of variation in the fraction of Total Allowable Catch (TAC) taken. Uniform distribution lower and upper bounds. Non-negative real numbers.
TAEFrac Mean fraction of TAE taken. Uniform distribution lower and upper bounds. Positive real number.
TAESD Log-normal coefficient of variation in the fraction of Total Allowable Effort (TAE) taken. Uniform distribution lower and upper bounds. Non-negative real numbers.
SizeLimFrac The real minimum size that is retained expressed as a fraction of the size. Uniform distribution lower and upper bounds. Positive real number.
SizeLimSD Log-normal coefficient of variation controlling mismatch between a minimum size limit and the real minimum size retained. Uniform distribution lower and upper bounds. Non-negative real numbers.

OM

Slot Description
1 Name Name of the operating model
2 Agency Name of the agency responsible for the management of the fishery. Character string
3 Region Name of the general geographic region of the fishery. Character string
4 Sponsor Name of the organization who sponsored the OM. Character string
5 Latitude Latitude (decimal degrees). Negative values represent the South of the Equator. Numeric. Single value
6 Longitude Longitude (decimal degrees). Negative values represent the West of the Prime Meridian. Numeric. Single value
7 nsim The number of simulations
8 proyears The number of projected years
9 interval The assessment interval - how often would you like to update the management system?
10 pstar The percentile of the sample of the management recommendation for each method
11 maxF Maximum instantaneous fishing mortality rate that may be simulated for any given age class
12 reps Number of samples of the management recommendation for each method. Note that when this is set to 1, the mean value of the data inputs is used.
13 cpars A list of custom parameters. Time series are a matrix nsim rows by nyears columns. Single parameters are a vector nsim long
14 seed A random seed to ensure users can reproduce results exactly
15 Source A reference to a website or article from which parameters were taken to define the operating model
16 Common_Name Common name of the species. Character string
17 Species Scientific name of the species. Genus and species name. Character string
18 maxage The maximum age of individuals that is simulated (there is no plus group ). Single value. Positive integer
19 R0 The magnitude of unfished recruitment. Single value. Positive real number
20 M Natural mortality rate. Uniform distribution lower and upper bounds. Positive real number
21 M2 (Optional) Natural mortality rate at age. Vector of length maxage . Positive real number
22 Mexp Exponent of the Lorenzen function assuming an inverse relationship between M and weight. Uniform distribution lower and upper bounds. Real numbers <= 0.
23 Msd Inter-annual variability in natural mortality rate expressed as a coefficient of variation. Uniform distribution lower and upper bounds. Non-negative real numbers
24 Mgrad No longer used. Previously mean temporal trend in natural mortality rate, expressed as a percentage change in M per year.
25 h Steepness of the stock recruit relationship. Uniform distribution lower and upper bounds. Values from 1/5 to 1
26 SRrel Type of stock-recruit relationship. Single value, switch (1) Beverton-Holt (2) Ricker. Integer
27 Perr Process error, the CV of lognormal recruitment deviations. Uniform distribution lower and upper bounds. Non-negative real numbers
28 AC Autocorrelation in recruitment deviations rec(t)=ACrec(t-1)+(1-AC)sigma(t). Uniform distribution lower and upper bounds. Non-negative real numbers
29 Period (Optional) Period for cyclical recruitment pattern in years. Uniform distribution lower and upper bounds. Non-negative real numbers
30 Amplitude (Optional) Amplitude in deviation from long-term average recruitment during recruitment cycle (eg a range from 0 to 1 means recruitment decreases or increases by up to 100% each cycle). Uniform distribution lower and upper bounds. 0 < Amplitude < 1
31 Linf Maximum length. Uniform distribution lower and upper bounds. Positive real numbers
32 K von Bertalanffy growth parameter k. Uniform distribution lower and upper bounds. Positive real numbers
33 t0 von Bertalanffy theoretical age at length zero. Uniform distribution lower and upper bounds. Non-positive real numbers
34 LenCV Coefficient of variation of length-at-age (assumed constant for all age classes). Uniform distribution lower and upper bounds. Positive real numbers
35 Ksd Inter-annual variability in growth parameter k expressed as coefficient of variation. Uniform distribution lower and upper bounds. Non-negative real numbers
36 Kgrad No longer used. Previously mean temporal trend in growth parameter k, expressed as a percentage change in k per year.
37 Linfsd Inter-annual variability in maximum length expressed as a coefficient of variation. Uniform distribution lower and upper bounds. Non-negative real numbers
38 Linfgrad No longer used. Previously mean temporal trend in maximum length, expressed as a percentage change in Linf per year.
39 L50 Length at 50 percent maturity. Uniform distribution lower and upper bounds. Positive real numbers
40 L50_95 Length increment from 50 percent to 95 percent maturity. Uniform distribution lower and upper bounds. Positive real numbers
41 D Current level of stock depletion SSB(current)/SSB(unfished). Uniform distribution lower and upper bounds. Fraction
42 a Length-weight parameter alpha. Single value. Positive real number
43 b Length-weight parameter beta. Single value. Positive real number
44 Size_area_1 The size of area 1 relative to area 2. Uniform distribution lower and upper bounds. Positive real numbers
45 Frac_area_1 The fraction of the unfished biomass in stock 1. Uniform distribution lower and upper bounds. Positive real numbers
46 Prob_staying The probability of inviduals in area 1 remaining in area 1 over the course of one year. Uniform distribution lower and upper bounds. Positive fraction.
47 Fdisc Fraction of discarded fish that die. Uniform distribution lower and upper bounds. Non-negative real numbers
49 nyears The number of years for the historical spool-up simulation. Single value. Positive integer
50 Spat_targ Distribution of fishing in relation to spatial biomass: fishing distribution is proportional to B^Spat_targ. Uniform distribution lower and upper bounds. Real numbers
51 EffYears Years representing join-points (vertices) of time-varying effort. Vector. Non-negative real numbers
52 EffLower Lower bound on relative effort corresponding to EffYears. Vector. Non-negative real numbers
53 EffUpper Upper bound on relative effort corresponding to EffYears. Vector. Non-negative real numbers
54 Esd Additional inter-annual variability in fishing mortality rate. Uniform distribution lower and upper bounds. Non-negative real numbers
55 qinc Average percentage change in fishing efficiency (applicable only to forward projection and input controls). Uniform distribution lower and upper bounds. Non-negative real numbers
56 qcv Inter-annual variability in fishing efficiency (applicable only to forward projection and input controls). Uniform distribution lower and upper bounds. Non-negative real numbers
57 L5 Shortest length corresponding to 5 percent vulnerability. Uniform distribution lower and upper bounds. Positive real numbers
58 LFS Shortest length that is fully vulnerable to fishing. Uniform distribution lower and upper bounds. Positive real numbers
59 Vmaxlen The vulnerability of fish at Stock@Linf . Uniform distribution lower and upper bounds. Fraction
60 isRel Selectivity parameters in units of size-of-maturity (or absolute eg cm). Single value. Boolean.
61 LR5 Shortest length corresponding ot 5 percent retention. Uniform distribution lower and upper bounds. Non-negative real numbers
62 LFR Shortest length that is fully retained. Uniform distribution lower and upper bounds. Non-negative real numbers
63 Rmaxlen The retention of fish at Stock@Linf . Uniform distribution lower and upper bounds. Non-negative real numbers
64 DR Discard rate - the fraction of caught fish that are discarded. Uniform distribution lower and upper bounds. Fraction
65 SelYears (Optional) Years representing join-points (vertices) at which historical selectivity pattern changes. Vector. Positive real numbers
66 AbsSelYears (Optional) Calendar years corresponding with SelYears (eg 1951, rather than 1), used for plotting only. Vector (of same length as SelYears). Positive real numbers
67 L5Lower (Optional) Lower bound of L5 (use ChooseSelect function to set these). Vector. Non-negative real numbers
68 L5Upper (Optional) Upper bound of L5 (use ChooseSelect function to set these). Vector. Non-negative real numbers
69 LFSLower (Optional) Lower bound of LFS (use ChooseSelect function to set these). Vector. Non-negative real numbers
70 LFSUpper (Optional) Upper bound of LFS (use ChooseSelect function to set these). Vector. Non-negative real numbers
71 VmaxLower (Optional) Lower bound of Vmaxlen (use ChooseSelect function to set these). Vector. Fraction
72 VmaxUpper (Optional) Upper bound of Vmaxlen (use ChooseSelect function to set these). Vector. Fraction
73 CurrentYr The current calendar year (final year) of the historical simulations (eg 2011). Single value. Positive integer.
74 MPA (Optional) Matrix specifying spatial closures for historical years.
75 Cobs Log-normal catch observation error expressed as a coefficient of variation. Uniform distribution lower and upper bounds. Non-negative real numbers
76 Cbiascv Log-normal coefficient of variation controlling the sampling of bias in catch observations for each simulation. Uniform distribution lower and upper bounds. Non-negative real numbers
77 CAA_nsamp Number of catch-at-age observation per time step. Uniform distribution lower and upper bounds. Positive real numbers
78 CAA_ESS Effective sample size (independent age draws) of the multinomial catch-at-age observation error model. Uniform distribution lower and upper bounds. Positive integers
79 CAL_nsamp Number of catch-at-length observation per time step. Uniform distribution lower and upper bounds. Positive integers
80 CAL_ESS Effective sample size (independent length draws) of the multinomial catch-at-length observation error model. Uniform distribution lower and upper bounds. Positive integers
81 Iobs Observation error in the relative abundance indices expressed as a coefficient of variation. Uniform distribution lower and upper bounds. Positive real numbers
82 Ibiascv Log-normal coefficient of variation controlling error in observations of relative abundance index. Uniform distribution lower and upper bounds. Positive real numbers
83 Btobs Log-normal coefficient of variation controlling error in observations of current stock biomass among years. Uniform distribution lower and upper bounds. Positive real numbers
84 Btbiascv Uniform-log bounds for sampling persistent bias in current stock biomass. Uniform-log distribution lower and upper bounds. Positive real numbers
85 beta A parameter controlling hyperstability/hyperdepletion where values below 1 lead to hyperstability (an index that decreases slower than true abundance) and values above 1 lead to hyperdepletion (an index that decreases more rapidly than true abundance). Uniform distribution lower and upper bounds. Positive real numbers
86 LenMbiascv Log-normal coefficient of variation for sampling persistent bias in length at 50 percent maturity. Uniform distribution lower and upper bounds. Positive real numbers
87 Mbiascv Log-normal coefficient of variation for sampling persistent bias in observed natural mortality rate. Uniform distribution lower and upper bounds. Positive real numbers
88 Kbiascv Log-normal coefficient of variation for sampling persistent bias in observed growth parameter K. Uniform distribution lower and upper bounds. Positive real numbers
89 t0biascv Log-normal coefficient of variation for sampling persistent bias in observed t0. Uniform distribution lower and upper bounds. Positive real numbers
90 Linfbiascv Log-normal coefficient of variation for sampling persistent bias in observed maximum length. Uniform distribution lower and upper bounds. Positive real numbers
91 LFCbiascv Log-normal coefficient of variation for sampling persistent bias in observed length at first capture. Uniform distribution lower and upper bounds. Positive real numbers
92 LFSbiascv Log-normal coefficient of variation for sampling persistent bias in length-at-full selection. Uniform distribution lower and upper bounds. Positive real numbers
93 FMSYbiascv Log-normal coefficient of variation for sampling persistent bias in FMSY. Uniform distribution lower and upper bounds. Positive real numbers
94 FMSY_Mbiascv Log-normal coefficient of variation for sampling persistent bias in FMSY/M. Uniform distribution lower and upper bounds. Positive real numbers
95 BMSY_B0biascv Log-normal coefficient of variation for sampling persistent bias in BMSY relative to unfished. Uniform distribution lower and upper bounds. Positive real numbers
96 Irefbiascv Log-normal coefficient of variation for sampling persistent bias in relative abundance index at BMSY. Uniform distribution lower and upper bounds. Positive real numbers
97 Brefbiascv Log-normal coefficient of variation for sampling persistent bias in BMSY. Uniform distribution lower and upper bounds. Positive real numbers
98 Crefbiascv Log-normal coefficient of variation for sampling persistent bias in MSY. Uniform distribution lower and upper bounds. Positive real numbers
99 Dbiascv Log-normal coefficient of variation for sampling persistent bias in stock depletion. Uniform distribution lower and upper bounds. Positive real numbers
100 Dobs Log-normal coefficient of variation controlling error in observations of stock depletion among years. Uniform distribution lower and upper bounds. Positive real numbers
101 hbiascv Log-normal coefficient of variation for sampling persistent bias in steepness. Uniform distribution lower and upper bounds. Positive real numbers
102 Recbiascv Log-normal coefficient of variation for sampling persistent bias in recent recruitment strength. Uniform distribution lower and upper bounds. Positive real numbers
103 TACFrac Mean fraction of TAC taken. Uniform distribution lower and upper bounds. Positive real number.
104 TACSD Log-normal coefficient of variation in the fraction of Total Allowable Catch (TAC) taken. Uniform distribution lower and upper bounds. Non-negative real numbers.
105 TAEFrac Mean fraction of TAE taken. Uniform distribution lower and upper bounds. Positive real number.
106 TAESD Log-normal coefficient of variation in the fraction of Total Allowable Effort (TAE) taken. Uniform distribution lower and upper bounds. Non-negative real numbers.
107 SizeLimFrac The real minimum size that is retained expressed as a fraction of the size. Uniform distribution lower and upper bounds. Positive real number.
108 SizeLimSD Log-normal coefficient of variation controlling mismatch between a minimum size limit and the real minimum size retained. Uniform distribution lower and upper bounds. Non-negative real numbers.

MSE

Slot Description
Name Name of the MSE object. Single value. Character string
nyears The number of years for the historical simulation. Single value. Positive integer
proyears The number of years for the projections - closed loop simulations. Single value. Positive integer
nMPs Number of management procedures simulation tested. Single value. Positive integer.
MPs The names of the MPs that were tested. Vector of length nMPs. Character strings.
nsim Number of simulations. Single value. Positive integer
OM A table of sampled parameter of the operating model. Table object of nsim rows. Real numbers
  • A: abundance (biomass) updated in each management update
  • AC: autocorrelation in recruitment
  • ageM: age at 50 per cent maturity
  • B0: unfished total biomass
  • Blow: SSB where it takes MGThorizon x MGT to reach Bfrac
  • BMSY: BMSY in last historical year (total biomass)
  • BMSY_B0: ratio of BMSY to unfished total biomass in last
  • Depletion: stock depletion (spawning biomass / unfished
  • dFfinal: gradient in fishing mortality rate over final
  • DR: the fraction of caught fish that are discarded
  • Esd: inter-annual variability in fishing mortality rate
  • Fdisc: fraction of discarded fish that die
  • FMSY: fishing mortality at MSY in last historical year
  • FMSY_M: ratio of FMSY to M in last historical year
  • Frac_area_1: fraction of the unfished biomass in stock 1
  • hs: steepness of the stock recruitment relationship (the
  • K: maximum growth rate (von Bertalanffy K parameter)
  • Kgrad: mean gradient in maximum growth rate (per cent per
  • Ksd: interannual variability in maximum growth rate (log
  • L5: length at 5/
  • L50: length at 50/
  • L95: length at 95/
  • LFC: length at first capture
  • LFR: first length at full retention
  • LFS: first length at full selection
  • Linf: asymptotic length
  • Linfgrad: mean gradient in maximum length (per cent per
  • Linfsd: interannual variability in maximum length (log
  • LR5: first length at 5/
  • M: instantaneous natural mortality rate
  • Mexp: exponent of Lorezen M-weight relationship
  • Mgrad: mean average percentage gradient in natural
  • MGT: mean generation time
  • Msd: interannual variability in natural mortality rate
  • MSY: maximum sustainable yield in last historical year
  • N0: equilibrium unfished total numbers
  • OFLreal: A * FMSY the true simulated Over Fishing Limit
  • Prob_staying: probability of inviduals in area 1
  • procsd: process error - CV in log-normal recruitment
  • qcv: interannual variability in future fishing efficiency
  • qinc: mean percentage increase in fishing efficiency
  • RefY: reference yield, the highest long-term yield (mean
  • Rmaxlen: retention of fish at asymptotic length
  • Size_area_1: size of Area 1 relative to Area 2
  • SizeLimFrac: fraction of average implementation error of
  • SizeLimSD: log-normal coefficient of variation
  • Spat_targ: distribution of fishing in relation to spatial
  • SSB0: unfished spawning biomass
  • SSBMSY: spawning biomass MSY in last historical year
  • SSBMSY_SSB0: ratio of SSB_MSY/SSB0 in last historical
  • t0: theoretical length at age zero (von Bertalanffy t0
  • TACFrac: mean fraction of TAC taken
  • TACSD: log-normal coefficient of variation in the
  • TAEFrac: mean fraction of TAE taken
  • TAESD: log-normal coefficient of variation in the
  • Vmaxlen: selection of fish at asymptotic length
Obs A table of sampled parameters of the observation model. Table of nsim rows. Real numbers
  • Abias: bias in observed current absolute stock biomass
  • Aerr: error in observed current absolute stock biomass
  • betas: hyper-stability/hyper-depletion parameter
  • BMSY_B0bias: bias in ratio of most productive stock size
  • Brefbias: bias in BMSY stock levels (target or reference
  • CAA_ESS: the effective sample size of multinomial
  • CAA_nsamp: the number of catch-at-age observations per
  • CAL_ESS: the effective sample size of multinomial
  • CAL_nsamp: the number of catch-at-length observations per
  • Cbias: bias in observed catches
  • Crefbias: bias in MSY prediction (target or reference
  • Csd: observation error in observed catches (lognormal CV)
  • Dbias: bias in observed stock depletion (also applies to
  • Derr: error in observed stock depletion
  • FMSY_Mbias: bias in ratio of FMSY to natural mortality
  • hbias: bias in observed steepness of the stock
  • Irefbias: bias in abundance index corresponding to BMSY
  • Isd: observation error in relative abundance index
  • Kbias: bias in maximum growth rate (von Bertalanffy K
  • lenMbias: bias in length at 50 per cent maturity
  • LFCbias: bias in length at first capture
  • LFSbias: bias in length at full selection
  • Linfbias: bias in maximum length (von Bertalanffy Linf
  • Mbias: bias in observed natural mortality rate
  • Recsd: error in observed recruitment
  • t0bias: bias in theoretical length at age zero (von
B_BMSY Simulated biomass relative to BMSY over the projection. An array with dimensions: nsim, nMPs, proyears. Non-negative real numbers
F_FMSY Simulated fishing mortality rate relative to FMSY over the projection. An array with dimensions: nsim, nMPs, proyears. Non-negative real numbers
B Simulated stock biomass over the projection. An array with dimensions: nsim, nMPs, proyears. Non-negative real numbers
SSB Simulated spawning stock biomass over the projection. An array with dimensions: nsim, nMPs, proyears. Non-negative real numbers
VB Simulated vulnerable biomass over the projection. An array with dimensions: nsim, nMPs, proyears. Non-negative real numbers
FM Simulated fishing mortality rate over the projection. An array with dimensions: nsim, nMPs, proyears. Non-negative real numbers
C Simulated catches (taken) over the projection. An array with dimensions: nsim, nMPs, proyears. Non-negative real numbers
TAC Simulated Total Allowable Catch (prescribed) over the projection (this is NA for input controls). An array with dimensions: nsim, nMPs, proyears. Non-negative real numbers
SSB_hist Simulated historical spawning stock biomass. An array with dimensions: nsim, nages, nyears, nareas. Non-negative real numbers
CB_hist Simulated historical catches in weight. An array with dimensions: nsim, nages, nyears, nareas. Non-negative real numbers
FM_hist Simulated historical fishing mortality rate. An array with dimensions: nsim, nages, nyears, nareas. Non-negative real numbers
Effort Simulated relative fishing effort in the projection years. An array with dimensions: nsim, nMPs, proyears. Non-negative real numbers
PAA Population at age in last projection year. An array with dimensions: nsim, nMPs, nages. Non-negative real numbers
CAA Catch at age in last projection year. An array with dimensions: nsim, nMPs, nages. Non-negative real numbers
CAL Catch at length in last projection year. An array with dimensions: nsim, nMPs, nCALbins. Non-negative real numbers
CALbins Mid-points of the catch-at-length bins. Vector of length nCALbins. Positive real numbers.
Misc Miscellanenous output such as posterior predictive data

Data

Slot Description
Name The name of the Data object. Single value. Character string
Common_Name Common name of the species. Character string
Species Scientific name of the species. Genus and species name. Character string
Region Name of the general geographic region of the fishery. Character string
Year Years that corresponding to catch and relative abundance data. Vector nyears long. Positive integer
Cat Total annual catches. Matrix of nsim rows and nyears columns. Non-negative real numbers
Ind Relative abundance index. Matrix of nsim rows and nyears columns. Non-negative real numbers
Type Type of abundance index, corresponding with rows in RInd . Types are: Biomass , VBiomass , and SpBiomass for indices of total, vulnerable, and spawning biomass respectively. Character string.
RInd One or more vectors of abundance indices. Non-negative real numbers
Rec Recent recruitment strength. Matrix of nsim rows and nyears columns. Non-negative real numbers
t The number of years corresponding to AvC and Dt. Single value. Positive integer
AvC Average catch over time t. Vector nsim long. Positive real numbers
Dt Depletion over time t SSB(now)/SSB(now-t+1). Vector nsim long. Fraction
Mort Natural mortality rate. Vector nsim long. Positive real numbers
FMSY_M An assumed ratio of FMSY to M. Vector nsim long. Positive real numbers
BMSY_B0 The most productive stock size relative to unfished. Vector nsim long. Fraction
L50 Length at 50 percent maturity. Vector nsim long. Positive real numbers
L95 Length at 95 percent maturity. Vector nsim long. Positive real numbers
ML Mean length time series. Matrix of nsim rows and nyears columns. Non-negative real numbers
Lbar Mean length of catches over Lc. Matrix of nsim rows and nyears columns. Positive real numbers
Lc Modal length of catches. Matrix of nsim rows and nyears columns. Positive real numbers
LFC Length at first capture. Vector nsim long. Positive real numbers
LFS Shortest length at full selection. Vector nsim long. Positive real numbers
CAA Catch at Age data. Array of dimensions nsim x nyears x MaxAge. Non-negative integers
Dep Stock depletion SSB(current)/SSB(unfished). Vector nsim long. Fraction.
Abun An estimate of absolute current vulnerable abundance. Vector nsim long. Positive real numbers
SpAbun An estimate of absolute current spawning stock abundance. Vector nsim long. Positive real numbers
vbK The von Bertalanffy growth coefficient K. Vector nsim long. Positive real numbers
vbLinf Maximum length. Vector nsim long. Positive real numbers
vbt0 Theoretical age at length zero. Vector nsim long. Non-positive real numbers
LenCV Coefficient of variation of length-at-age (assumed constant for all age classes). Vector nsim long. Positive real numbers
wla Weight-Length parameter alpha. Vector nsim long. Positive real numbers
wlb Weight-Length parameter beta. Vector nsim long. Positive real numbers
steep Steepness of stock-recruitment relationship. Vector nsim long. Value in the range of one-fifth to 1
sigmaR Recruitment variability. Vector nsim long. Positive real numbers
CV_Cat Coefficient of variation in annual catches. Vector nsim long. Positive real numbers
CV_Dt Coefficient of variation in depletion over time t. Vector nsim long. Positive real numbers
CV_AvC Coefficient of variation in average catches over time t. Vector nsim long. Positive real numbers
CV_Ind Coefficient of variation in the relative abundance index. Vector nsim long. Positive real numbers
CV_Mort Coefficient of variation in natural mortality rate. Vector nsim long. Positive real numbers
CV_FMSY_M Coefficient of variation in the ratio in FMSY/M. Vector nsim long. Positive real numbers
CV_BMSY_B0 Coefficient of variation in the position of the most productive stock size relative to unfished. Vector nsim long. Positive real numbers
CV_Dep Coefficient of variation in current stock depletion. Vector nsim long. Positive real numbers
CV_Abun Coefficient of variation in estimate of absolute current stock size. Vector nsim long. Positive real numbers
CV_vbK Coefficient of variation in the von Bertalanffy K parameter. Vector nsim long. Positive real numbers
CV_vbLinf Coefficient of variation in maximum length. Vector nsim long. Positive real numbers
CV_vbt0 Coefficient of variation in age at length zero. Vector nsim long. Positive real numbers
CV_L50 Coefficient of variation in length at 50 per cent maturity. Vector nsim long. Positive real numbers
CV_LFC Coefficient of variation in length at first capture. Vector nsim long. Positive real numbers
CV_LFS Coefficient of variation in length at full selection. Vector nsim long. Positive real numbers
CV_wla Coefficient of variation in weight-length parameter a. Vector nsim long. Positive real numbers
CV_wlb Coefficient of variation in weight-length parameter b. Vector nsim long. Positive real numbers
CV_steep Coefficient of variation in steepness. Vector nsim long. Positive real numbers
sigmaL Assumed observaton error of the length composition data. Vector nsim long. Positive real numbers
MaxAge Maximum age. Vector nsim long. Positive integer
CAL_bins The values delimiting the length bins for the catch-at-length data. Vector. Non-negative real numbers
CAL Catch-at-length data. An array with dimensions nsim x nyears x length(CAL_bins). Non-negative integers
TAC The calculated catch limits (function TAC). An array with dimensions PosMPs x replicate TAC samples x nsim. Positive real numbers
Sense The results of the sensitivity analysis (function Sense). An array with dimensions PosMPs x sensitivity increments. Positive real numbers
Units Units of the catch/absolute abundance estimates. Single value. Character string
Ref A reference management level (eg a catch limit). Single value. Positive real number
Ref_type Type of reference management level (eg 2009 catch limit). Single value. Character string
Log A record of events. Single value. Character string
params A place to store estimated parameters. An object. R list
PosMPs The methods that can be applied to these data. Vector. Character strings
MPs The methods that were applied to these data. Vector. Character strings
OM A table of operating model conditions. R table object of nsim rows. Real numbers
Obs A table of observation model conditions. R table object of nsim rows. Real numbers
Cref Reference or target catch level (eg MSY). Vector of length nsim. Positive real numbers
Iref Reference or target relative abundance index level (eg BMSY / B0). Vector of length nsim. Positive real numbers
Bref Reference or target biomass level (eg BMSY). Vector of length nsim. Positive real numbers
CV_Cref Log-normal CV for reference or target catch level. Vector of length nsim. Positive real numbers
CV_Iref Log-normalCV for reference or target relative abundance index level. Vector of length nsim. Positive real numbers
CV_Bref Log-normal CV for reference or target biomass level. Vector of length nsim. Positive real numbers
CV_Rec Log-normal CV for recent recruitment strength. Vector of length nsim. Positive real numbers
MPrec The previous recommendation of a management procedure. Vector of length nsim. Positive real numbers
MPeff The current level of effort. Vector of length nsim. Positive real numbers
LHYear The last historical year of the simulation (before projection). Single value. Positive integer
nareas Number of fishing areas. Vector of length nsim. Non-negative integer
Misc Other information for MPs. An object. R list