Skip to contents

West Central Pacific Ocean Bigeye Tuna (WCPO BET) Length Frequency Data

wcpo_bet_lf.Rd

Length frequency composition data extracted from MFCL (Multifan-CL) frequency files and prepared for RTMB (R Template Model Builder) stock assessment modeling. Observations are organized by fishery, year, month, and 2 cm length bins.

Usage

wcpo_bet_lf

Format

A data.table with 7 columns: year (integer), month (numeric), ts (integer), fishery (numeric), bin (numeric), value (numeric), week (numeric). Multiple rows per fishery-year-month (one per 2 cm length bin).

Source

Extracted from MFCL (Multifan-CL) model frequency file outputs and prepared for RTMB model input.

Details

Data workflow

Preparation steps:

  1. Extract length composition data from MFCL frequency file using lnfrq() - Returns wide-format data with length bins as columns (10, 12, 14, ... 198 cm) - Observations grouped by fishery-year-month

  2. Reshape to long format (one row per fishery-year-month-length bin combination)

  3. Merge with timestep table to add model timestep indexing consistent with catch/CPUE

  4. Save as long-format data for RTMB model input

Output columns

year

Calendar year (1952-2018). Integer.

month

Fishing quarter month (2, 5, 8, 11 representing Q1-Q4 approx.). Numeric.

ts

Model timestep number (1-268 for 67 years × 4 quarters). Integer.

fishery

MFCL fleet index (1-15). Numeric.

bin

Length bin lower edge (cm). 2 cm bins: 10, 12, 14, ... 198. Numeric.

value

Observed count of fish in this length bin. Numeric.

week

Temporal indicator within quarter (typically 1 for aggregated data). Numeric.

Notes

  • MFCL data uses 2 cm length bins (10, 12, 14, ... 198 cm)

  • Data from lnfrq() represents observed length frequency

  • Sum of values across bins per fishery-year-month instance gives total input sample size

  • Bin values are left as counts for RTMB to handle (divide by sample size if proportions needed)

Examples

if (FALSE) { # \dontrun{
  data(wcpo_bet_lf)
  str(wcpo_bet_lf)
  # View sample data
  head(wcpo_bet_lf)
  # Get total sample size per fishery-year-month
  wcpo_bet_lf[, .(total_n = sum(value)), by = .(year, month, fishery)]
} # }