Skip to contents

The following tables describe all elements contained within input_list$data, which is generated using the SPoRC::Setup_x functions. Note that they do not detail how the SPoRC::Setup_x functions should be utilized. Rather, they detail the components of input_list$data. Thus, for further details on how arguments for SPoRC::Setup_x functions should be defined, users should refer to the function documentation. Furthermore, note that when n_sexes > 1, the first dimension will always be females and the second dimension will always be males. Similarly, when n_pop > 1, populations are indexed in the order they are defined.

Data Inputs for Defining Model Dimensions

Name Description
years Vector specifying number of years to model
ages Vector specifying number of ages to model
lens Vector specifying number of lengths to model
n_pop Value specifying number of populations to model
n_regions Value specifying number of regions to model
n_sexes Value specifying number of sexes to model
n_fish_fleets Value specifying number of fishery fleets to model
n_srv_fleets Value specifying number of survey fleets to model
n_seas Value specifying number of seasons to model within a year
seasdur Numeric vector of length n_seas specifying the duration of each season as a fraction of the year (must sum to 1)
spawn_seas Integer specifying which season spawning occurs in
natal_region Integer vector of length n_pop specifying the natal region for each population. Used when n_pop > 1 to define population-specific recruitment and density dependence
n_proj_yrs_devs Number of years to project deviations / random effect parameters forward
do_internal_comp_osa Boolean. Whether or not internal composition OSAs are planned to be used
do_internal_conv_tag_osa Boolean. Whether or not internal tagging OSAs are planned to be used

Data Inputs for Defining Recruitment Processes

Name Description
rec_lag Value specifying the delay between spawning and when recruits enter the population. For example, if recruits enter the population as age 2, rec_lag would be specified as 2, such that the spawning biomass from year – 2 produces these recruits. A special case, rec_lag = 0 (age-0 recruitment), uses the same year’s own spawning biomass instead of a prior year’s; because that year’s SSB isn’t known until the spawning season is reached, recruits may only enter in the spawning season itself or later that same year
Use_h_prior Value specifying whether steepness priors are used. 0: Don’t use priors, 1: Use Priors. Steepness priors are bounded between 0.2 and 1 with a scaled beta penalty
h_prior Data frame specifying prior distributions for steepness parameters. Must include columns: pop (population index), region (region index), mu (mean of the prior in normal space), and sd (standard deviation of the prior in normal space). For each row, a beta distribution is scaled to the interval [0.2, 1], and the corresponding h_trans value is transformed and penalized using the log-density from the scaled beta distribution
do_rec_bias_ramp Value specifying whether or not the Methot and Taylor recruitment bias ramp is conducted. 0: Don’t do bias ramp, 1: Do bias ramp
max_bias_ramp_fct Value specifying the maximum bias correction factor applied to the recruitment bias ramp
bias_year Vector of years specifying when to change the bias ramp. Can be specified with an NA if do_rec_bias_ramp = 0
sigmaR_switch Value specifying when to transition between using an early period sigma and late period sigma R for penalizing initial age deviations and recruitment deviations. Specify as 0 if sigmaR early is equal to sigmaR late
init_age_strc Value specifying how the population age structure should be initialized. 0: Initialize via iteration to equilibrium, 1: Initialize with geometric series solution
equil_init_age_strc Value specifying how initial age deviations arise.

0 ("equil") == deterministic equilibrium; 1 ("stoch_no_plus") == stochastic for all ages except the plus group; 2 ("stoch_all") == stochastic for all ages including the plus group; 3 ("stoch_shared_ages") == stochastic with user-defined age sharing via init_age_devs_shared | | init_F_prop | Array specifying the proportion of fishing mortality to apply to the initial age deviations relative to the mean fishing mortality parameter for regions, seasons, and fishery fleets | | rec_model | Value specifying the recruitment model. 0 == Mean Recruitment, 1 == Beverton-Holt with steepness parameterization | | rec_dd | Value specifying the recruitment density dependence (only used when there is a stock-recruitment relationship). 0 == local density dependence (region-specific SSB drives regional recruitment), 1 == global density dependence (summed SSB across regions drives recruitment), 999 == no density-dependent stock-recruitment form is used | | rec_region_prop_spec | Integer specifying how recruitment regional apportionment is handled when n_pop > 1. 0 == recruitment dispersal (recruits can be distributed across regions via estimated proportions), 1 == strict natal homing (recruits are assigned entirely to each population’s natal region) | | t_spawn | Fraction of year in which spawning occurs | | use_fixed_stray_rate | Integer specifying whether stray rates are supplied as a fixed external array (1) or estimated as model parameters via stray_rate_pars (0). Default 1. Only relevant when n_pop > 1 | | fixed_stray_rate | Array dimensioned by n_pop, n_years specifying fixed stray rate values used when use_fixed_stray_rate = 1. Values should be in [0, 1]. Ignored when use_fixed_stray_rate = 0 | | stray_rate_blocks | Array dimensioned by n_pop, n_years specifying the time block index for stray rate parameters for each population and year. Unique integer values denote distinct stray rate parameter blocks | | use_stray_rate_prior | Integer specifying whether a Beta prior is placed on estimated stray rate parameters. 0: Don’t use prior, 1: Use prior. Only relevant when use_fixed_stray_rate = 0 and n_pop > 1. Prior contributions accumulate into rec_prop_nLL | | stray_rate_prior | Data frame specifying Beta prior parameters for stray rates. Must include columns: pop (population index), block (time block index matching stray_rate_blocks), mu (prior mean in (0,1)), and sd (prior standard deviation). One row per population × block combination when stray_rate_spec = “est_all”; one row per block only when stray_rate_spec = “est_shared_p” | | use_rec_region_prop_prior | Value specifying whether a Dirichlet prior is placed on recruitment regional apportionment proportions. 0: Don’t use prior, 1: Use prior | | rec_region_prop_prior | Data frame specifying Dirichlet prior parameters for recruitment regional apportionment. Must include columns: pop (population index) and alpha (list column containing Dirichlet concentration parameter vectors of length n_regions) | | use_fixed_rec_seas_prop | Integer specifying whether seasonal recruitment apportionment proportions are fixed (1) or estimated (0) | | fixed_rec_seas_prop | Array dimensioned by n_pop, n_seas specifying fixed seasonal recruitment proportions when use_fixed_rec_seas_prop = 1. Ignored otherwise | | use_rec_seas_prop_prior | Value specifying whether a Dirichlet prior is placed on estimated seasonal recruitment apportionment proportions. 0: Don’t use prior, 1: Use prior. Only relevant when use_fixed_rec_seas_prop = 0 | | rec_seas_prop_prior | Data frame specifying Dirichlet prior parameters for seasonal recruitment apportionment. Must include columns: pop (population index) and alpha (list column containing Dirichlet concentration parameter vectors of length n_seas) | | sexratio_blocks | Array specifying sex-ratio blocks dimensioned by n_pop, n_regions, n_years | | use_rinit | Integer specifying whether a separate initial recruitment scalar is used to initialise the population independently of ln_global_R0. 0: Population initialised using ln_global_R0 (default), 1: Population initialised using ln_rinit, with ln_global_R0 governing only the recruitment relationship | | init_age_devs_shared | Integer vector of length n_ages - 1 specifying explicit age-sharing for ln_InitDevs. Positions with the same value share a single estimated parameter (e.g. c(1:42, rep(42, 9)) shares the last 9 ages with age 42, giving 42 free parameters). Required when equil_init_age_strc = 3; NULL (default) uses standard behaviour. | | use_r0_prior | Integer specifying whether a lognormal prior is placed on R0. 0: Don’t use prior (default), 1: Use prior | | r0_prior | Data frame specifying lognormal prior parameters for R0. Must include columns: pop (population index), mu (prior mean on the natural scale), and sd (prior standard deviation on the log scale) |

Data Inputs for Defining Biological Processes

Name Description
WAA Weight-at-age values dimensioned by n_pop, n_regions, n_years, n_seas, n_ages, n_sexes
WAA_fish Fishery weight-at-age values dimensioned by n_pop, n_regions, n_years, n_seas, n_ages, n_sexes, n_fish_fleets
WAA_srv Survey weight-at-age values dimensioned by n_pop, n_regions, n_years, n_seas, n_ages, n_sexes, n_srv_fleets
MatAA Maturity-at-age values dimensioned by n_pop, n_regions, n_years, n_seas, n_ages, n_sexes
AgeingError Ageing error matrix dimensioned by n_years, n_modelled_ages, n_observed_ages, where rows across modelled ages sum to 1
fit_lengths Value describing whether or not to fit length composition data. 0: Don’t fit lengths, 1: Fit lengths
SizeAgeTrans Size-age transition matrix dimensioned by n_pop, n_regions, n_years, n_seas, n_lens, n_ages, n_sexes. Can be specified as NA if length compositions are not fit
addtocomp Constant to add to all composition data
addtofishidx Constant to add to all fishery index data
addtosrvidx Constant to add to all survey index data
addtotag Constant to add to all tagging data
Use_M_prior Value specifying whether natural mortality priors are used. 0: Don’t use prior, 1: Use prior
M_prior A data frame specifying how natural mortality priors should be applied. Must include columns: popblk (population block index), regionblk (region block index), yearblk (year block index), ageblk (age block index), sexblk (sex block index), mu (prior mean on natural scale), and sd (prior standard deviation on log scale)
Fixed_natmort Natural mortality array dimensioned by n_pop, n_regions, n_years, n_ages, n_sexes
M_blocks Array that specifies the natural mortality blocking structure, dimensioned by n_pop, n_regions, n_years, n_ages, n_sexes. Unique integer values denote distinct natural mortality parameter blocks

Data Inputs for Defining Spawning and Multi-Population Processes

Name Description
sgl_seas_spawning_movement Movement matrix applied during the spawning event when n_seas == 1 and n_pop > 1, representing fish returning to natal areas to spawn. Dimensioned by n_pop, n_regions, n_regions, n_years, n_ages, n_sexes. Ignored when n_seas > 1 or n_pop == 1

Data Inputs for Defining Movement Processes

Name Description
do_recruits_move Value specifying whether recruits are allowed to move. 0: Recruits don’t move, 1: Recruits move
use_fixed_movement Value specifying whether or not to use a fixed movement matrix. 0: Don’t use fixed movement, 1: Use fixed movement
Fixed_Movement Fixed movement matrix dimensioned by n_pop, n_regions, n_regions, n_years, n_seas, n_ages, n_sexes
Use_Movement_Prior Value specifying whether or not to use movement priors. 0: Don’t use movement prior, 1: Use movement prior
Movement_prior Data frame with columns representing population (pop), origin region (region_from), year (year), season (seas), representative age (age), sex (sex), and a list column (alpha) containing Dirichlet prior parameters. Each element of alpha is a numeric vector of length n_regions, specifying the prior concentration values for movement among destination regions
cont_vary_movement Integer indicating whether movement is continuously varying across regions, years, and ages. 0 = none, 1 = iid deviations
map_move_devs Array dimensioned by n_regions, n_regions - 1, n_years, n_ages, and n_sexes specifying which movement parameters are shared and mapped off
move_type Integer indicating movement model type. 0 = unstructured Markov (multinomial logit), 1 = Continuous Time Markov Chain (CTMC)
ctmc_move_dat Data frame with CTMC covariates (regions, years, ages, sexes, plus formula variables) used to build design matrices for diffusion and preference when move_type == 1. Can include projection years with projected covariate values
diffusion_formula R formula specifying diffusion covariates for CTMC movement (when move_type == 1)
preference_formula R formula specifying preference covariates for CTMC movement (when move_type == 1)
adjacency_mat Square adjacency matrix (n_regions × n_regions) defining allowed transitions between regions for CTMC movement
adjacency_collapsed Collapsed adjacency matrix (n_regions × n_regions - 1) defining allowed transitions between regions for CTMC movement, excluding diagonals
area_r Numeric vector of region areas (length n_regions) used to scale diffusion rates in CTMC movement
ctmc_diffusion_bounds Integer flag (0 or 1) indicating whether diffusion bounds are applied to ensure the generator matrix is Metzler (1 = bounds enforced)

Data Inputs for Defining Tagging Processes

Name Description
use_conv_fish_tagging Integer vector of length n_fish_fleets indicating whether conventional fishery tagging data are used for each fleet. 0: Don’t use tagging data, 1: Use tagging data
conv_tag_release_indicator Matrix dimensioned by n_conv_tag_cohorts, 3. Columns represent the tag release region (column 1), tag release year (column 2), and tag release season (column 3) for each cohort
n_conv_tag_cohorts Value specifying the number of conventional tag cohorts released
conv_tag_max_liberty Value specifying the maximum years at liberty to track tag cohorts
conv_tagged_fish Array specifying the number of tagged fish for a given cohort, dimensioned by n_conv_tag_cohorts, n_pop, n_ages, n_sexes
obs_conv_tag_fish_recap Array of observed conventional tag recaptures dimensioned by conv_tag_max_liberty, n_seas, n_conv_tag_cohorts, n_pop, n_regions, n_ages, n_sexes, n_fish_fleets. If no age or sex information is available, the array can be initialized with 0s and recaptured individuals input into the first age and first sex dimension, coupled with conv_tag_age_pool and conv_tag_sex_pool to sum across those dimensions when computing the likelihood
conv_fish_tag_like Integer specifying the tag likelihood to use. 0: Poisson, 1: Negative Binomial, 2: Multinomial release-conditioned, 3: Multinomial recapture-conditioned, 4: Dirichlet-Multinomial release-conditioned, 5: Dirichlet-Multinomial recapture-conditioned
conv_tag_mixing_period Value specifying the mixing period for tag cohorts in seasonal (or annual if model is annual) time steps. Tag observations within the mixing period are excluded from the likelihood
conv_tag_t_tagging Fraction of the season in which tagging occurs. Specify as 1 if tagging happens at the start of the season such that mortality is not discounted
use_conv_tag_fishrep_prior Value specifying whether or not a tag reporting rate prior should be used. 0: Don’t use prior, 1: Use prior
conv_tag_fishrep_prior Data frame containing prior specifications for conventional fishery tag reporting parameters. Must include columns: region (region index), block (time block index), fleet (fleet index), mu (numeric mean for reporting rate prior in normal space; use NA if symmetric beta is used), sd (prior standard deviation in normal space), and type (0 = symmetric beta, 1 = regular beta)
conv_tag_pop_pool List specifying how tag recaptures along the population axis should be pooled when computing the likelihood. Each element of the list contains the population indices to sum across for a given pooled group
conv_tag_age_pool List specifying how tag recaptures along the age axis should be pooled when computing the likelihood. Each element of the list contains the age indices to sum across for a given pooled group. For example, if no age information is available: list(c(1:n_ages)) sums all ages together
conv_tag_sex_pool List specifying how tag recaptures along the sex axis should be pooled when computing the likelihood. Each element of the list contains the sex indices to sum across for a given pooled group. For example, if no sex information is available: list(c(1:n_sexes)) sums both sexes together
conv_tag_fish_reporting_blocks Array dimensioned by n_regions, n_years, n_fish_fleets indicating the time block index for tag reporting rate parameters in each region and fleet
conv_fish_tag_attr Data object specifying how tagged fish attributes (e.g., age, sex, population) are apportioned at release when full individual-level data are unavailable. Passed to the internal release_conv_tag_attr function
conv_tag_release_platform Matrix dimensioned by n_conv_tag_cohorts specifying the release platform (e.g., population, fishery or survey fleet) used to attribute selectivity and effort to tagged fish at the time of release

Data Inputs for Defining Catch and Fishing Mortality Processes

Name Description
ObsCatch Observed catch data dimensioned by n_regions, n_years, n_seas, n_fish_fleets. Used in region-aggregated catch likelihoods
ObsCatch_pop Population-specific observed catch data dimensioned by n_pop, n_regions, n_years, n_seas, n_fish_fleets. Used in population-specific catch likelihoods
catch_units Array dimensioned by n_fish_fleets describing catch units. 0 == Abundance, 1 == Biomass (default)
UseCatch Array dimensioned by n_regions, n_years, n_seas, n_fish_fleets describing whether to fit to catch data in a given year, season, and fleet. 0: Don’t fit catch, 1: Fit catch
UseCatch_pop Array dimensioned by n_pop, n_regions, n_years, n_seas, n_fish_fleets describing whether to fit to population-specific catch data. 0: Don’t fit catch, 1: Fit catch
Use_F_pen Value specifying whether to use a fishing mortality penalty to regularize fishing mortality deviations. 0: Don’t use regularity penalty, 1: Use regularity penalty
ObsDiscard Observed discard data dimensioned by n_regions, n_years, n_seas, n_fish_fleets. Used in region-aggregated discard likelihoods
discard_units Array dimensioned by n_fish_fleets describing discard units. 0 == Abundance, 1 == Biomass
UseDiscard Array dimensioned by n_regions, n_years, n_seas, n_fish_fleets describing whether to fit to discard data in a given year, season, and fleet. 0: Don’t fit discard, 1: Fit discard
UseDiscard_pop Array dimensioned by n_pop, n_regions, n_years, n_seas, n_fish_fleets describing whether to fit to population-specific discard data. 0: Don’t fit discard, 1: Fit discard
Use_dmr_pen Value specifying whether to use a discard mortality rate penalty. 0: Don’t use penalty, 1: Use penalty

Data Inputs for Defining Fishery Indices and Compositions

Region-aggregated observations (summed across populations) and population-specific observations are handled separately. Region-aggregated inputs use dimensions beginning with n_regions; population-specific inputs use dimensions beginning with n_pop, n_regions.

Name Description
ObsFishIdx Fishery index dimensioned by n_regions, n_years, n_seas, n_fish_fleets
ObsFishIdx_SE Fishery index standard errors dimensioned by n_regions, n_years, n_seas, n_fish_fleets
UseFishIdx Array dimensioned by n_regions, n_years, n_seas, n_fish_fleets describing whether to fit to the fishery index in a given year, season, and fleet. 0: Don’t fit fishery index, 1: Fit fishery index
fish_idx_type Matrix dimensioned by n_fish_fleets specifying the index type for a given fishery fleet. 0: Abundance index, 1: Biomass index (uses WAA_fish for calculations), 999: None Available
ObsFishIdx_pop Population-specific fishery index dimensioned by n_pop, n_regions, n_years, n_seas, n_fish_fleets
ObsFishIdx_pop_SE Population-specific fishery index standard errors dimensioned by n_pop, n_regions, n_years, n_seas, n_fish_fleets
UseFishIdx_pop Array dimensioned by n_pop, n_regions, n_years, n_seas, n_fish_fleets describing whether to fit to population-specific fishery indices. 0: Don’t fit, 1: Fit
ObsFishAgeComps Observed fishery age compositions dimensioned by n_regions, n_years, n_seas, n_ages, n_sexes, n_fish_fleets. Can be input as proportions or numbers, as these are normalized within the model
UseFishAgeComps Array dimensioned by n_regions, n_years, n_seas, n_fish_fleets specifying whether or not to fit to fishery age compositions. 0: Don’t fit, 1: Fit
ISS_FishAgeComps Array dimensioned by n_regions, n_years, n_seas, n_sexes, n_fish_fleets specifying the input sample size for a multinomial or Dirichlet-multinomial likelihood
Wt_FishAgeComps Array dimensioned by n_regions, n_years, n_seas, n_sexes, n_fish_fleets specifying a multinomial weight to apply to fishery age compositions, ideally derived using Francis re-weighting
ObsFishAgeComps_pop Population-specific observed fishery age compositions dimensioned by n_pop, n_regions, n_years, n_seas, n_ages, n_sexes, n_fish_fleets. Can be input as proportions or numbers
UseFishAgeComps_pop Array dimensioned by n_pop, n_regions, n_years, n_seas, n_fish_fleets specifying whether to fit to population-specific fishery age compositions. 0: Don’t fit, 1: Fit
ISS_FishAgeComps_pop Array dimensioned by n_pop, n_regions, n_years, n_seas, n_sexes, n_fish_fleets specifying the input sample size for population-specific fishery age composition likelihoods
Wt_FishAgeComps_pop Array dimensioned by n_pop, n_regions, n_years, n_seas, n_sexes, n_fish_fleets specifying a multinomial weight to apply to population-specific fishery age compositions
ObsFishLenComps Observed fishery length compositions dimensioned by n_regions, n_years, n_seas, n_lens, n_sexes, n_fish_fleets. Can be input as proportions or numbers, as these are normalized within the model
UseFishLenComps Array dimensioned by n_regions, n_years, n_seas, n_fish_fleets specifying whether or not to fit to fishery length compositions. 0: Don’t fit, 1: Fit
ISS_FishLenComps Array dimensioned by n_regions, n_years, n_seas, n_fish_fleets specifying the input sample size for a multinomial or Dirichlet-multinomial likelihood
Wt_FishLenComps Array dimensioned by n_regions, n_years, n_seas, n_sexes, n_fish_fleets specifying a multinomial weight to apply to fishery length compositions, ideally derived using Francis re-weighting
ObsFishLenComps_pop Population-specific observed fishery length compositions dimensioned by n_pop, n_regions, n_years, n_seas, n_lens, n_sexes, n_fish_fleets. Can be input as proportions or numbers
UseFishLenComps_pop Array dimensioned by n_pop, n_regions, n_years, n_seas, n_fish_fleets specifying whether to fit to population-specific fishery length compositions. 0: Don’t fit, 1: Fit
ISS_FishLenComps_pop Array dimensioned by n_pop, n_regions, n_years, n_seas, n_fish_fleets specifying the input sample size for population-specific fishery length composition likelihoods
Wt_FishLenComps_pop Array dimensioned by n_pop, n_regions, n_years, n_seas, n_sexes, n_fish_fleets specifying a multinomial weight to apply to population-specific fishery length compositions
FishAgeComps_LikeType Vector dimensioned by n_fish_fleets specifying the likelihood for region-aggregated fishery age compositions. 0: Multinomial, 1: Dirichlet-multinomial, 2: Logistic-normal with iid covariance, 999: None Available. Further options in Get_Comp_Likelihoods.R
FishAgeComps_pop_LikeType Vector dimensioned by n_fish_fleets specifying the likelihood for population-specific fishery age compositions. Same options as FishAgeComps_LikeType
FishLenComps_LikeType Vector dimensioned by n_fish_fleets specifying the likelihood for region-aggregated fishery length compositions. 0: Multinomial, 1: Dirichlet-multinomial, 2: Logistic-normal with iid covariance, 999: None Available. Further options in Get_Comp_Likelihoods.R
FishLenComps_pop_LikeType Vector dimensioned by n_fish_fleets specifying the likelihood for population-specific fishery length compositions. Same options as FishLenComps_LikeType
FishAgeComps_Type Matrix dimensioned by n_years, n_fish_fleets specifying how region-aggregated age composition data should be structured. 0: Aggregated across sexes and regions, 1: Split by sexes and regions, 2: Joint by sex but split by region, 999: None Available. Further options in Get_Comp_Likelihoods.R
FishAgeComps_pop_Type Matrix dimensioned by n_years, n_fish_fleets specifying how population-specific age composition data should be structured. Same options as FishAgeComps_Type
FishLenComps_Type Matrix dimensioned by n_years, n_fish_fleets specifying how region-aggregated length composition data should be structured. 0: Aggregated across sexes and regions, 1: Split by sexes and regions, 2: Joint by sex but split by region, 999: None Available. Further options in Get_Comp_Likelihoods.R
FishLenComps_pop_Type Matrix dimensioned by n_years, n_fish_fleets specifying how population-specific length composition data should be structured. Same options as FishLenComps_Type
ObsFishAgeComps_discard Observed discard age compositions dimensioned by n_regions, n_years, n_seas, n_ages, n_sexes, n_fish_fleets. Can be input as proportions or numbers, as these are normalized within the model
UseFishAgeComps_discard Array dimensioned by n_regions, n_years, n_seas, n_fish_fleets specifying whether or not to fit to discard age compositions. 0: Don’t fit, 1: Fit
ISS_FishAgeComps_discard Array dimensioned by n_regions, n_years, n_seas, n_sexes, n_fish_fleets specifying the input sample size for a multinomial or Dirichlet-multinomial discard age composition likelihood
ObsFishLenComps_discard Observed discard length compositions dimensioned by n_regions, n_years, n_seas, n_lens, n_sexes, n_fish_fleets. Can be input as proportions or numbers, as these are normalized within the model
UseFishLenComps_discard Array dimensioned by n_regions, n_years, n_seas, n_fish_fleets specifying whether or not to fit to discard length compositions. 0: Don’t fit, 1: Fit
ISS_FishLenComps_discard Array dimensioned by n_regions, n_years, n_seas, n_fish_fleets specifying the input sample size for a multinomial or Dirichlet-multinomial discard length composition likelihood
ObsFishAgeComps_discard_pop Population-specific observed discard age compositions dimensioned by n_pop, n_regions, n_years, n_seas, n_ages, n_sexes, n_fish_fleets. Can be input as proportions or numbers
UseFishAgeComps_discard_pop Array dimensioned by n_pop, n_regions, n_years, n_seas, n_fish_fleets specifying whether to fit to population-specific discard age compositions. 0: Don’t fit, 1: Fit
ISS_FishAgeComps_discard_pop Array dimensioned by n_pop, n_regions, n_years, n_seas, n_sexes, n_fish_fleets specifying the input sample size for population-specific discard age composition likelihoods
UseFishLenComps_discard_pop Array dimensioned by n_pop, n_regions, n_years, n_seas, n_fish_fleets specifying whether to fit to population-specific discard length compositions. 0: Don’t fit, 1: Fit
ISS_FishLenComps_discard_pop Array dimensioned by n_pop, n_regions, n_years, n_seas, n_fish_fleets specifying the input sample size for population-specific discard length composition likelihoods
FishAgeComps_discard_LikeType Vector dimensioned by n_fish_fleets specifying the likelihood for region-aggregated discard age compositions. 0: Multinomial, 1: Dirichlet-multinomial, 2: Logistic-normal with iid covariance, 999: None Available
FishLenComps_discard_LikeType Vector dimensioned by n_fish_fleets specifying the likelihood for region-aggregated discard length compositions. 0: Multinomial, 1: Dirichlet-multinomial, 2: Logistic-normal with iid covariance, 999: None Available
FishAgeComps_discard_pop_LikeType Vector dimensioned by n_fish_fleets specifying the likelihood for population-specific discard age compositions. Same options as FishAgeComps_discard_LikeType
FishLenComps_discard_pop_LikeType Vector dimensioned by n_fish_fleets specifying the likelihood for population-specific discard length compositions. Same options as FishLenComps_discard_LikeType
FishAgeComps_discard_Type Matrix dimensioned by n_years, n_fish_fleets specifying how region-aggregated discard age composition data should be structured. 0: Aggregated across sexes and regions, 1: Split by sexes and regions, 2: Joint by sex but split by region, 999: None Available
FishLenComps_discard_Type Matrix dimensioned by n_years, n_fish_fleets specifying how region-aggregated discard length composition data should be structured. Same options as FishAgeComps_discard_Type
FishAgeComps_discard_pop_Type Matrix dimensioned by n_years, n_fish_fleets specifying how population-specific discard age composition data should be structured. Same options as FishAgeComps_discard_Type
FishLenComps_discard_pop_Type Matrix dimensioned by n_years, n_fish_fleets specifying how population-specific discard length composition data should be structured. Same options as FishAgeComps_discard_Type

Data Inputs for Defining Survey Indices and Compositions

Region-aggregated observations (summed across populations) and population-specific observations are handled separately. Region-aggregated inputs use dimensions beginning with n_regions; population-specific inputs use dimensions beginning with n_pop, n_regions.

Name Description
ObsSrvIdx Survey index dimensioned by n_regions, n_years, n_seas, n_srv_fleets
ObsSrvIdx_SE Survey index standard errors dimensioned by n_regions, n_years, n_seas, n_srv_fleets
UseSrvIdx Array dimensioned by n_regions, n_years, n_seas, n_srv_fleets describing whether to fit to the survey index in a given year, season, and fleet. 0: Don’t fit, 1: Fit
srv_idx_type Matrix dimensioned by n_srv_fleets specifying the index type for a given survey fleet. 0: Abundance index, 1: Biomass index (uses WAA_srv for calculations), 999: None Available
ObsSrvIdx_pop Population-specific survey index dimensioned by n_pop, n_regions, n_years, n_seas, n_srv_fleets
ObsSrvIdx_pop_SE Population-specific survey index standard errors dimensioned by n_pop, n_regions, n_years, n_seas, n_srv_fleets
UseSrvIdx_pop Array dimensioned by n_pop, n_regions, n_years, n_seas, n_srv_fleets describing whether to fit to population-specific survey indices. 0: Don’t fit, 1: Fit
ObsSrvAgeComps Observed survey age compositions dimensioned by n_regions, n_years, n_seas, n_ages, n_sexes, n_srv_fleets. Can be input as proportions or numbers, as these are normalized within the model
UseSrvAgeComps Array dimensioned by n_regions, n_years, n_seas, n_srv_fleets specifying whether or not to fit to survey age compositions. 0: Don’t fit, 1: Fit
ISS_SrvAgeComps Array dimensioned by n_regions, n_years, n_seas, n_sexes, n_srv_fleets specifying the input sample size for a multinomial or Dirichlet-multinomial likelihood
Wt_SrvAgeComps Array dimensioned by n_regions, n_years, n_seas, n_sexes, n_srv_fleets specifying a multinomial weight to apply to survey age compositions, ideally derived using Francis re-weighting
ObsSrvAgeComps_pop Population-specific observed survey age compositions dimensioned by n_pop, n_regions, n_years, n_seas, n_ages, n_sexes, n_srv_fleets. Can be input as proportions or numbers
UseSrvAgeComps_pop Array dimensioned by n_pop, n_regions, n_years, n_seas, n_srv_fleets specifying whether to fit to population-specific survey age compositions. 0: Don’t fit, 1: Fit
ISS_SrvAgeComps_pop Array dimensioned by n_pop, n_regions, n_years, n_seas, n_sexes, n_srv_fleets specifying the input sample size for population-specific survey age composition likelihoods
Wt_SrvAgeComps_pop Array dimensioned by n_pop, n_regions, n_years, n_seas, n_sexes, n_srv_fleets specifying a multinomial weight to apply to population-specific survey age compositions
ObsSrvLenComps Observed survey length compositions dimensioned by n_regions, n_years, n_seas, n_lens, n_sexes, n_srv_fleets. Can be input as proportions or numbers, as these are normalized within the model
UseSrvLenComps Array dimensioned by n_regions, n_years, n_seas, n_srv_fleets specifying whether or not to fit to survey length compositions. 0: Don’t fit, 1: Fit
ISS_SrvLenComps Array dimensioned by n_regions, n_years, n_seas, n_srv_fleets specifying the input sample size for a multinomial or Dirichlet-multinomial likelihood
Wt_SrvLenComps Array dimensioned by n_regions, n_years, n_seas, n_sexes, n_srv_fleets specifying a multinomial weight to apply to survey length compositions, ideally derived using Francis re-weighting
ObsSrvLenComps_pop Population-specific observed survey length compositions dimensioned by n_pop, n_regions, n_years, n_seas, n_lens, n_sexes, n_srv_fleets. Can be input as proportions or numbers
UseSrvLenComps_pop Array dimensioned by n_pop, n_regions, n_years, n_seas, n_srv_fleets specifying whether to fit to population-specific survey length compositions. 0: Don’t fit, 1: Fit
ISS_SrvLenComps_pop Array dimensioned by n_pop, n_regions, n_years, n_seas, n_srv_fleets specifying the input sample size for population-specific survey length composition likelihoods
Wt_SrvLenComps_pop Array dimensioned by n_pop, n_regions, n_years, n_seas, n_sexes, n_srv_fleets specifying a multinomial weight to apply to population-specific survey length compositions
SrvAgeComps_LikeType Vector dimensioned by n_srv_fleets specifying the likelihood for region-aggregated survey age compositions. 0: Multinomial, 1: Dirichlet-multinomial, 2: Logistic-normal with iid covariance, 999: None Available. Further options in Get_Comp_Likelihoods.R
SrvAgeComps_pop_LikeType Vector dimensioned by n_srv_fleets specifying the likelihood for population-specific survey age compositions. Same options as SrvAgeComps_LikeType
SrvLenComps_LikeType Vector dimensioned by n_srv_fleets specifying the likelihood for region-aggregated survey length compositions. 0: Multinomial, 1: Dirichlet-multinomial, 2: Logistic-normal with iid covariance, 999: None Available. Further options in Get_Comp_Likelihoods.R
SrvLenComps_pop_LikeType Vector dimensioned by n_srv_fleets specifying the likelihood for population-specific survey length compositions. Same options as SrvLenComps_LikeType
SrvAgeComps_Type Matrix dimensioned by n_years, n_srv_fleets specifying how region-aggregated age composition data should be structured. 0: Aggregated across sexes and regions, 1: Split by sexes and regions, 2: Joint by sex but split by region, 999: None Available. Further options in Get_Comp_Likelihoods.R
SrvAgeComps_pop_Type Matrix dimensioned by n_years, n_srv_fleets specifying how population-specific survey age composition data should be structured. Same options as SrvAgeComps_Type
SrvLenComps_Type Matrix dimensioned by n_years, n_srv_fleets specifying how region-aggregated length composition data should be structured. 0: Aggregated across sexes and regions, 1: Split by sexes and regions, 2: Joint by sex but split by region, 999: None Available. Further options in Get_Comp_Likelihoods.R
SrvLenComps_pop_Type Matrix dimensioned by n_years, n_srv_fleets specifying how population-specific survey length composition data should be structured. Same options as SrvLenComps_Type
t_srv Array dimensioned by n_regions, n_seas, n_srv_fleets specifying survey timing as a proportion of the season
do_srv_q_cov Numeric value indicating whether a survey catchability covariate is used. 0 == Not used, 1 == Used
srv_q_cov Array dimensioned by n_regions, n_years, n_srv_fleets, n_covariates representing the covariates used to compute survey catchability

Data Inputs for Defining Fishery Selectivity and Catchability

Name Description
cont_tv_fish_sel Matrix dimensioned by n_regions, n_fish_fleets specifying whether and how continuous time-varying selectivity is applied. 0: None, 1: iid deviations, 2: random walk, 3: 3D GMRF with marginal variance (semi-parametric), 4: 3D GMRF with conditional variance (semi-parametric). Further details in Get_PE_loglik.R, Get_3d_precision.R, and Get_Selex.R
cont_tv_fish_sel_penalty Boolean specifying whether penalties are applied to continuous time-varying fishery selectivity deviations
fish_sel_blocks Array dimensioned by n_regions, n_years, n_fish_fleets specifying selectivity time blocks. Unique integers denote distinct selectivity parameter blocks
fish_sel_model Array dimensioned by n_regions, n_years, n_fish_fleets specifying the selectivity functional form. 0: Logistic (a50 and slope), 1: Gamma dome-shaped, 2: Power function, 3: Logistic (a50 and a95), 4: Double Normal (6 parameters). Further details in Get_Selex.R
fish_selex_type Integer specifying whether fishery selectivity is age-based (0) or length-based (1)
use_fixed_fish_sel Integer specifying whether fishery selectivity is fixed externally (1) or estimated (0)
fish_q_blocks Array dimensioned by n_regions, n_years, n_fish_fleets specifying catchability time blocks. Unique integers denote distinct catchability parameter blocks
Use_fish_q_prior Fishery catchability prior indicator. 0 == don’t use, 1 == use
fish_q_prior Data frame containing prior specifications for fishery catchability parameters. Must include columns: region, fleet, block, mu (prior mean on natural scale), and sd (prior standard deviation on log scale). Each row specifies a log-normal prior for one catchability parameter
map_ln_fishsel_devs Array dimensioned by n_regions, n_years, n_ages, n_sexes, n_fish_fleets indicating which continuous time-varying selectivity deviation values are fixed (mapped off)
Use_fish_selex_prior Integer (0 or 1). Flag to enable log-normal priors on fishery selectivity parameters as specified in fish_selex_prior
fish_selex_prior Data frame containing prior specifications for fishery selectivity parameters. Must include columns: region, fleet, block, sex, par (parameter index), mu (prior mean on natural scale), and sd (prior standard deviation on log scale). Each row specifies a log-normal prior for one selectivity parameter
fishsel_devs_min_shared_bins Integer vector specifying the reference (minimum) bin index within each shared deviation group, used to subset the bin dimension when evaluating GMRF or 2D AR(1) likelihoods (PE models 3–5). Defaults to 1:n_ages when no bin sharing is specified

Data Inputs for Defining Retention Selectivity

Name Description
cont_tv_ret_sel Matrix dimensioned by n_regions, n_fish_fleets specifying whether and how continuous time-varying retention selectivity is applied. Same options as cont_tv_fish_sel
cont_tv_ret_sel_penalty Boolean specifying whether penalties are applied to continuous time-varying retention selectivity deviations
ret_sel_blocks Array dimensioned by n_regions, n_years, n_fish_fleets specifying retention selectivity time blocks. Unique integers denote distinct retention selectivity parameter blocks
ret_sel_model Array dimensioned by n_regions, n_years, n_fish_fleets specifying the retention selectivity functional form. Same options as fish_sel_model
ret_selex_type Integer specifying whether retention selectivity is age-based (0) or length-based (1)
use_fixed_ret_sel Integer specifying whether retention selectivity is fixed externally (1) or estimated (0)
ret_sel_input Array specifying fixed retention selectivity values when use_fixed_ret_sel = 1
Use_ret_selex_prior Integer (0 or 1). Flag to enable log-normal priors on retention selectivity parameters
retsel_devs_min_shared_bins Integer vector specifying the reference (minimum) bin index within each shared deviation group for retention selectivity, used when evaluating GMRF or 2D AR(1) likelihoods. Defaults to 1:n_ages when no bin sharing is specified
map_ln_retsel_devs Array indicating which continuous time-varying retention selectivity deviation values are fixed (mapped off)

Data Inputs for Defining Survey Selectivity and Catchability

Name Description
cont_tv_srv_sel Matrix dimensioned by n_regions, n_srv_fleets specifying whether and how continuous time-varying selectivity is applied. 0: None, 1: iid deviations, 2: random walk, 3: 3D GMRF with marginal variance (semi-parametric), 4: 3D GMRF with conditional variance (semi-parametric). Further details in Get_PE_loglik.R, Get_3d_precision.R, and Get_Selex.R
cont_tv_srv_sel_penalty Boolean specifying whether penalties are applied to continuous time-varying survey selectivity deviations
srv_sel_blocks Array dimensioned by n_regions, n_years, n_srv_fleets specifying selectivity time blocks. Unique integers denote distinct selectivity parameter blocks
srv_sel_model Array dimensioned by n_regions, n_years, n_srv_fleets specifying the selectivity functional form. 0: Logistic (a50 and slope), 1: Gamma dome-shaped, 2: Power function, 3: Logistic (a50 and a95), 4: Double Normal (6 parameters). Further details in Get_Selex.R
srv_selex_type Integer specifying whether survey selectivity is age-based (0) or length-based (1)
use_fixed_srv_sel Integer specifying whether survey selectivity is fixed externally (1) or estimated (0)
srv_q_blocks Array dimensioned by n_regions, n_years, n_srv_fleets specifying catchability time blocks. Unique integers denote distinct catchability parameter blocks
Use_srv_q_prior Survey catchability prior indicator. 0 == don’t use, 1 == use
srv_q_prior Data frame containing prior specifications for survey catchability parameters. Must include columns: region, fleet, block, mu (prior mean on natural scale), and sd (prior standard deviation on log scale). Each row specifies a log-normal prior for one catchability parameter
map_ln_srvsel_devs Array dimensioned by n_regions, n_years, n_ages, n_sexes, n_srv_fleets indicating which continuous time-varying selectivity deviation values are fixed (mapped off)
Use_srv_selex_prior Integer (0 or 1). Flag to enable log-normal priors on survey selectivity parameters as specified in srv_selex_prior
srv_selex_prior Data frame containing prior specifications for survey selectivity parameters. Must include columns: region, fleet, block, sex, par (parameter index), mu (prior mean on natural scale), and sd (prior standard deviation on log scale). Each row specifies a log-normal prior for one selectivity parameter
srvsel_devs_min_shared_bins Integer vector specifying the reference (minimum) bin index within each shared deviation group, used to subset the bin dimension when evaluating GMRF or 2D AR(1) likelihoods (PE models 3–5). Defaults to 1:n_ages when no bin sharing is specified

Data Inputs for Defining Model Weighting

Name Description
Wt_Catch Weight applied to region-aggregated fishery catch likelihoods. Either a numeric scalar or an array dimensioned by n_regions, n_years, n_seas, n_fish_fleets
Wt_Catch_pop Weight applied to population-specific fishery catch likelihoods. Either a numeric scalar or an array dimensioned by n_pop, n_regions, n_years, n_seas, n_fish_fleets
Wt_FishIdx Weight applied to region-aggregated fishery index likelihoods. Either a numeric scalar or an array dimensioned by n_regions, n_years, n_seas, n_fish_fleets
Wt_FishIdx_pop Weight applied to population-specific fishery index likelihoods. Either a numeric scalar or an array dimensioned by n_pop, n_regions, n_years, n_seas, n_fish_fleets
Wt_SrvIdx Weight applied to region-aggregated survey index likelihoods. Either a numeric scalar or an array dimensioned by n_regions, n_years, n_seas, n_srv_fleets
Wt_SrvIdx_pop Weight applied to population-specific survey index likelihoods. Either a numeric scalar or an array dimensioned by n_pop, n_regions, n_years, n_seas, n_srv_fleets
Wt_Rec Weight applied to initial age deviations and recruitment deviations
Wt_F Weight applied to fishing mortality deviations
Wt_D Weight applied to discard mortality rate deviations
Wt_Tagging Weight applied to tagging data likelihoods
Wt_Discard Weight applied to region-aggregated discard likelihoods. Either a numeric scalar or an array dimensioned by n_regions, n_years, n_seas, n_fish_fleets
Wt_Discard_pop Weight applied to population-specific discard likelihoods. Either a numeric scalar or an array dimensioned by n_pop, n_regions, n_years, n_seas, n_fish_fleets
Wt_FishAgeComps Array dimensioned by n_regions, n_years, n_seas, n_sexes, n_fish_fleets specifying a multinomial weight applied to region-aggregated fishery age compositions, ideally derived using Francis re-weighting
Wt_FishAgeComps_pop Array dimensioned by n_pop, n_regions, n_years, n_seas, n_sexes, n_fish_fleets specifying a multinomial weight applied to population-specific fishery age compositions
Wt_FishLenComps Array dimensioned by n_regions, n_years, n_seas, n_sexes, n_fish_fleets specifying a multinomial weight applied to region-aggregated fishery length compositions, ideally derived using Francis re-weighting
Wt_FishLenComps_pop Array dimensioned by n_pop, n_regions, n_years, n_seas, n_sexes, n_fish_fleets specifying a multinomial weight applied to population-specific fishery length compositions
Wt_SrvAgeComps Array dimensioned by n_regions, n_years, n_seas, n_sexes, n_srv_fleets specifying a multinomial weight applied to region-aggregated survey age compositions, ideally derived using Francis re-weighting
Wt_SrvAgeComps_pop Array dimensioned by n_pop, n_regions, n_years, n_seas, n_sexes, n_srv_fleets specifying a multinomial weight applied to population-specific survey age compositions
Wt_SrvLenComps Array dimensioned by n_regions, n_years, n_seas, n_sexes, n_srv_fleets specifying a multinomial weight applied to region-aggregated survey length compositions, ideally derived using Francis re-weighting
Wt_SrvLenComps_pop Array dimensioned by n_pop, n_regions, n_years, n_seas, n_sexes, n_srv_fleets specifying a multinomial weight applied to population-specific survey length compositions
Wt_FishAgeComps_discard Array dimensioned by n_regions, n_years, n_seas, n_sexes, n_fish_fleets specifying a multinomial weight applied to region-aggregated discard age compositions
Wt_FishAgeComps_discard_pop Array dimensioned by n_pop, n_regions, n_years, n_seas, n_sexes, n_fish_fleets specifying a multinomial weight applied to population-specific discard age compositions
Wt_FishLenComps_discard Array dimensioned by n_regions, n_years, n_seas, n_sexes, n_fish_fleets specifying a multinomial weight applied to region-aggregated discard length compositions
Wt_FishLenComps_discard_pop Array dimensioned by n_pop, n_regions, n_years, n_seas, n_sexes, n_fish_fleets specifying a multinomial weight applied to population-specific discard length compositions