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West Central Pacific Ocean Bigeye Tuna (WCPO BET) Assessment Data

wcpo_bet_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 of western central Pacific bigeye tuna.

Usage

wcpo_bet_data

Format

A list with 25 named elements combining dimensions, biological parameters, observed data (catch and CPUE), and Bayesian priors for RTMB model initialization.

Source

Prepared from MFCL (Multifan-CL) model outputs and frequency files, with biological parameters and priors derived from assessment modeling.

Details

Data structure (25 list elements)

Age and time dimensions:

age_a

Vector of integer ages (1:40). Length = 40.

n_age

Number of age classes (40).

n_season

Number of seasons per year (1).

n_fishery

Number of fisheries/fleets (15).

n_year

Number of years in model (268, equivalent to 67 years × 4 quarters).

first_yr

First year designation in model (1, representing 1952).

last_yr

Last year designation in model (268, representing 2018).

years

Vector of model years (1:268).

Length structure:

len_bin_start

First length bin lower edge (10 cm).

len_bin_width

Width of each length bin (2 cm).

n_len

Total number of length bins (95).

Catch data:

first_yr_catch

First year with catch data (1).

catch_units_f

Numeric vector of unit codes by fishery (15 elements). 1 = metric tons (fisheries 8-14), 2 = thousands of fish (fisheries 1-7, 15).

catch_obs_ysf

Three-dimensional array of observed catch (268 years × 1 season × 15 fisheries). Dimensions follow (year, season, fishery). Units follow catch_units_f.

CPUE data:

cpue_switch

Indicator for CPUE inclusion (1 = included, typically for fishery 15).

cpue_data

Tibble with 268 rows and 8 columns containing standardized CPUE observations:

  • year: Calendar year (1952-2018)

  • month: Quarter month (2, 5, 8, 11 for Q1-Q4)

  • ts: Sequential timestep (1-268)

  • fishery: Fleet identifier (usually 15 for survey fleet)

  • metric: Data type ("cpue")

  • units: Unit code (typically 2 for fishery 15)

  • value: Normalized CPUE observations

  • se: Log-space standard error of CPUE observations

Biological parameters:

lw_a

Length-weight allometric coefficient (6.48e-05).

lw_b

Length-weight allometric exponent (2.78).

maturity

Maturity at length vector (95 elements). Ogive-based maturity probabilities by length bin.

fecundity

Fecundity at length vector (95 elements). Relative fecundity by length bin.

M

Natural mortality at age vector (40 elements). Age-specific instantaneous mortality rates.

Age bounds:

A1

Minimum age for credibility interval (1).

A2

Maximum age for credibility interval (40).

Selectivity:

sel_type_f

Selectivity function type by fishery (15 elements). Integer codes representing selectivity curve shapes (e.g., 2 = double-normal).

Priors:

priors

List of 8 Bayesian prior specifications, each containing:

  • type: Prior distribution type ("normal", etc.)

  • par1: First parameter (mean or location)

  • par2: Second parameter (std dev or scale)

  • 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.

Length composition data:

lf_minbin

Integer vector (n_fishery). Per-fishery minimum bin index for lower-tail aggregation. Bins from 1 to lf_minbin[f] are summed into bin lf_minbin[f]. Default is 1 (no aggregation).

lf_maxbin

Integer vector (n_fishery). Per-fishery maximum bin index for upper-tail aggregation. Bins from lf_maxbin[f] to n_len are summed into bin lf_maxbin[f]. Default is n_len (no aggregation).

Examples

if (FALSE) { # \dontrun{
  data(wcpo_bet_data)
  str(wcpo_bet_data)
  # Access catch data
  head(wcpo_bet_data$cpue_data)
  # Get biological parameters
  wcpo_bet_data$M
} # }