1 What is fishLengthAssess?

fishLengthAssess acts as an aggregator of length-based stock assessment models. The package imposes a standardized formatting and metadata structure on length data sets, which can then be used in a variety of length-based assessment methods that are aggregated within the package. It also provides wrapper functions to link standardized formatting of length data sets with external R packages that contain length-based assessment methods (e.g. LBSPR package).

1.1 Installation

fishLengthAssess depends on other packages to run its functions. These are the devtools and fishSimGTG (Harford 2024) R packages, which should be installed as follows:

install.packages("devtools")
devtools::install_github("natureanalytics-ca/fishSimGTG")

The user then can install the development version of fishLengthAssess from GitHub with:

devtools::install_github("natureanalytics-ca/fishLengthAssess")

1.2 How to use fishLengthAssess?

The fishLengthAssess package aggregates data-limited methods that can be used for evaluating the condition of a fish stock based on length data sets. The methods are split in two categories: indicator-based functions and model-based functions. Indicator-based functions are based on metrics that include compliance with established size limits, 3 metrics proposed by Froese (2004), and trend-based metrics like mean length in the catch. Model-based methods consist of length-based stock assessment approaches, and includes for example, an interface for estimation of SPR from observed length-frequency data, based on the LB-SPR method developed by Adrian R. Hordyk et al. (2016a).

The main functions in the package rely on several S4-type objects known as life history and length composition objects (class LifeHistory from fishSimGTG and class LengthComp from fishLengthAssess, respectively). Once a user standardizes their length data to fit the requirements of the length composition object and gathers the necessary information for creating a life history object, then many of the functions within the fishLengthAssess package become straightforward to use having these objects as function arguments. The next chapter describes in more detail how to structure the data into the necessary R objects.

References

Froese, Rainer. 2004. “Keep It Simple: Three Indicators to Deal with Overfishing.” Fish and Fisheries 5 (1): 86–91. https://doi.org/10.1111/j.1467-2979.2004.00144.x.
Harford, W. 2024. “fishSimGTG: Numerical Simulations of Fish Population Dynamics. R Package Version 1.0.6.” https://github.com/natureanalytics-ca/fishSimGTG.
Hordyk, Adrian R., Kotaro Ono, Jeremy D. Prince, and Carl J. Walters. 2016a. “A Simple Length-Structured Model Based on Life History Ratios and Incorporating Size-Dependent Selectivity: Application to Spawning Potential Ratios for Data-Poor Stocks.” Canadian Journal of Fisheries and Aquatic Sciences 73 (12): 1787–99. https://doi.org/10.1139/cjfas-2015-0422.