check_length: Check of length classes in TC

In RoME: Multiple Checks on MEDITS Trawl Survey Data

Check of length classes in TC

Description

The function checks the consistency of length classes in the TC table for the MEDITS survey. It verifies that the recorded length classes for each species fall within the expected ranges reported in a reference table of species-specific length limits. Warnings for inconsistencies are written to a CSV file for easier downstream analysis instead of being printed extensively in the log file.

Usage

check_length(DataTC, DataSpecies = NA, year, wd, suffix,
             DataTargetSpecies = RoME::DataTargetSpecies)

Arguments

DataTC	Biological data table (TC) formatted according to the MEDITS protocol.
DataSpecies	A data frame with species-specific reference length limits. If not provided, the internal DataTargetSpecies dataset included in the package is used by default.
year	Reference year for the analysis.
wd	Working directory path defined by the user, where log files and CSV output will be saved.
suffix	Suffix string for naming the log and CSV files, allowing unique identification of output files from different runs.
DataTargetSpecies	Reference dataset with species-specific information on length ranges, used as default if DataSpecies is not provided.

Details

The function filters the TC data for the selected year and checks each length class recorded against the minimum (LMIN01) and maximum (LMAX99) length values defined for the corresponding species in the reference table. It also checks for negative or missing length class values. All detected issues are collected and saved in a CSV file for clear reporting, instead of generating verbose outputs in the log file.

Species with less than 50 observations in TC are excluded from the check by default, to focus the analysis on more frequently recorded species. The function ensures robust handling of missing (NA) values in both the TC table and the reference datasets to avoid false warnings.

A short summary of the check results is written to the .dat logfile. If no inconsistencies are detected, a message indicating successful validation is saved.

Value

Returns TRUE, invisibly. Detected inconsistencies are written to a CSV file in the working directory; if no issues are found, the CSV file remains empty apart from the header row.

Author(s)

W. Zupa, I. Bitetto

References

Anonymus. 2017. MEDITS-Handbook. Version n. 9. MEDITS Working Group. 106 pp.https://www.sibm.it/MEDITS%202011/principaledownload.htm

Examples

  wd <- tempdir()
  DataTC <- RoME::TC[1:20,]
  DataSpecies <- NA
  suffix <- "2020-03-05_time_h17m44s55"
  check_length(DataTC, DataSpecies = NA, year = 2007, wd, suffix)

RoME documentation built on April 24, 2026, 1:07 a.m.