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'Opakapaka Stock Assessment Data

opaka_data.Rd

A comprehensive list containing biological parameters, catch and CPUE data, and Bayesian prior specifications prepared for RTMB (R Template Model Builder) stock assessment modeling. Extracted from a Stock Synthesis 3 (SS3) model and converted to opal data conventions.

Usage

opaka_data

Format

A list with 22 named elements combining dimensions, biological parameters, observed data (catch and CPUE), and Bayesian priors for RTMB model initialization.

Source

Extracted from Stock Synthesis 3 (SS3 v3.30.19) model input files (data_echo.ss_new, control.ss_new). Historical data only (1949-2023), forecast period excluded.

Details

Data structure (22 list elements)

Age and time dimensions:

age_a

Vector of integer ages (1:44). Length = 44. Internal opal ages mapping to SS3 ages 0-43 (opal age i = SS3 age i - 1).

n_age

Number of age classes (44).

n_season

Number of seasons per year (1).

n_fishery

Number of fisheries/fleets (3).

n_year

Number of years in model (75, representing 1949-2023).

first_yr

First year designation in model (1, representing 1949).

last_yr

Last year designation in model (75, representing 2023).

years

Vector of model years (1:75).

Length structure:

len_bin_start

First length bin lower edge (5 cm).

len_bin_width

Width of each length bin (5 cm).

n_len

Total number of length bins (17).

Catch data:

first_yr_catch

First year with catch data (1).

catch_units_f

Numeric vector of unit codes by fishery (3 elements). All fisheries use units = 1 (biomass).

catch_obs_ysf

Three-dimensional array of observed catch (75 years x 1 season x 3 fisheries). Dimensions follow (year, season, fishery). Fleet 3 (ResFish survey) has zero catch.

CPUE data:

cpue_switch

Indicator for CPUE inclusion (1 = included).

cpue_data

Data.table with 82 rows and 8 columns containing CPUE observations from two fleets:

  • year: Calendar year (1949-2023)

  • month: Observation month (7 for Comm fleet, 1 for ResFish)

  • ts: Sequential timestep (1-75)

  • fishery: Fleet identifier (1 = Comm, 3 = ResFish)

  • index: Integer index identifier (1 for Comm, 2 for ResFish)

  • metric: Data type ("cpue")

  • units: Unit code (1 for biomass)

  • value: CPUE observations

  • se: Log-space standard error (0.2 for Comm, 0.15 for ResFish)

Comm fleet (fleet 1) covers 1949-2023 (75 obs). ResFish survey (fleet 3) covers 2017-2023 (7 obs).

Biological parameters:

lw_a

Length-weight allometric coefficient (1.75e-05).

lw_b

Length-weight allometric exponent (2.99).

maturity

Maturity at length vector (17 elements). Logistic maturity probabilities at each data length bin midpoint (Mat50 = 40.7 cm, slope = -2.26).

fecundity

Fecundity at length vector (17 elements). Fecundity equals weight at each length bin midpoint (fecundity option: eggs = Wt).

M

Natural mortality at age vector (44 elements). Constant instantaneous rate (0.135) across all ages.

Growth reference ages (Schnute parameterization):

A1

Reference age for L1 (1). Corresponds to SS3 age 0.

A2

Reference age for L2 (44 = n_age). Corresponds to SS3 age 43.

Selectivity:

sel_type_f

Selectivity function type by fishery (3 elements). Integer codes: 1 = logistic, 2 = double-normal, 3 = double Richards.

Priors:

priors

List of 8 Bayesian prior specifications, each containing:

  • type: Prior distribution type ("none" = uninformative)

  • par1: First parameter (NA when type = "none")

  • par2: Second parameter (NA when type = "none")

  • index: Parameter index in the model

Priors cover: log_B0, log_cpue_q, par_sel, log_L1, log_L2, log_k, log_CV1, log_CV2.

Fleet definitions

Fleet 1 (Comm)

Commercial fishery. Catch fleet with logistic selectivity. CPUE and length composition data available 1949-2023.

Fleet 2 (Non_comm)

Non-commercial fishery. Catch fleet with logistic selectivity (fixed parameters). Catch data only, no CPUE or compositions.

Fleet 3 (ResFish)

Research fishery survey. Survey fleet with double-normal selectivity. CPUE and length composition data available 2017-2023.

Growth conversion

Growth parameters were converted from the SS3 standard von Bertalanffy parameterization (L_at_Amin = 6.0 at age 0, Linf = 67.5 at age 999, k = 0.242) to the opal Schnute parameterization with A1 = 1 and A2 = n_age. The conversion is exact to machine precision (~1e-14). The VB growth coefficient k is unchanged between parameterizations.

See also

opaka_parameters for starting parameter values, opaka_lf for length frequency composition data.

Examples

if (FALSE) { # \dontrun{
  data(opaka_data)
  str(opaka_data)
  # Access catch data
  head(opaka_data$cpue_data)
  # Get biological parameters
  opaka_data$M
  # Check dimensions
  cat("Ages:", opaka_data$n_age, "\n")
  cat("Years:", opaka_data$n_year, "\n")
  cat("Fleets:", opaka_data$n_fishery, "\n")
  cat("Length bins:", opaka_data$n_len, "\n")
} # }