aLBI is a specialized R package for fish stock assessment in data-limited scenarios. It implements a simplified framework for estimating life-history parameters and assessing stock status using length-frequency data, following the methods of Froese (2004) and Cope & Punt (2009).
- Enhanced Reliability: Direct user input for
LinfandLmatis now supported to improve model accuracy and allow for sensitivity analysis. - Statistical Robustness: Integrated Monte Carlo simulations and non-parametric bootstrapping for reliable parameter estimation.
- New Functionality:
LWR: Fits and visualizes length-weight relationships.FreqTM: Handles multi-month length-frequency data structures.- Updated
FrequencyTable,FishPar, andFishSSwith automated decision-making logic for selectivity.
#installing pacakge from CRAN #install.packages("aLBI")
Enhanced Reliability: Direct user input for Linf and Lmat is now supported to improve model accuracy and allow for sensitivity analysis.
Statistical Robustness: Integrated Monte Carlo simulations and non-parametric bootstrapping for reliable parameter estimation.
-
LWR: Fits and visualizes length-weight relationships.
-
FreqTM: Handles multi-month length-frequency data structures.
-
Updated FrequencyTable, FishPar, and FishSS with automated decision-making logic for selectivity.
Install the stable version from CRAN:
#install.packages("aLBI")
For the latest development version with advanced sensitivity features, install from GitHub:
devtools::install_github("Ataher76/aLBI", force = TRUE) Quick Start R library(aLBI)
results <- FishPar(data = your_data, resample = 1000, Linf = NULL, Lmat = NULL)
results$estimated_length_par results$estimated_froese_par
StockStatus <- FishSS(data = CPdata, LM_ratio = results$LM_ratio, Pmat = results$estimated_froese_par[1,2], Popt = results$estimated_froese_par[2,2]) How to Cite If you use aLBI in your research, please cite both the software and the methodology paper:
Journal Article:
Ali, A., Sarker, M. R., & Alam, M. S. (2025). Development of a simple R package (aLBI) for the estimation of stock status from the length frequency data. Fisheries Research, 288, 107467. https://doi.org/10.1016/j.fishres.2025.107467
Software:
Ali, A., & Alam, M. S. (2024). aLBI: Estimating Length-Based Indicators for Fish Stock (Version 0.1.9).
Contact Ataher Ali – University of Chittagong, Bangladesh
Email: ataher.cu.ms@gmail.com
GitHub: Ataher76