ss3sim: ss3sim: Fisheries stock assessment simulation testing with...

In ss3sim: Fisheries Stock Assessment Simulation Testing with Stock Synthesis

Description

The ss3sim R package is designed to facilitate rapid, reproducible, and flexible simulation with the widely-used Stock Synthesis 3 (SS3) statistical catch-at-age stock assessment framework.

Details

An ss3sim simulation requires three types of input: (1) a base model of the underlying truth (an SS3 operating model), (2) a base model of how you will assess that truth (an SS3 estimation model), (3) and a set of cases that deviate from these base models that you want to compare (configuration arguments provided as plain-text cases files).

You can find examples of these SS3 operating and estimation models within the package data (inst/extdata/models/). The package data also contains example plain-text control files in the folder inst/extdata/cases and inst/extdata/eg-cases.

To carry out ss3sim simulations with the version from CRAN, you will need to have SS3 installed on your computer and the binary needs to be in the path that R sees. See the section "Installing the ss3sim R package" in the vignette vignette("ss3sim-vignette") for instructions on installing SS3. See the Appendix A "Putting SS3 in your path" in the vignette for instructions on making sure SS3 will work from within R.

The main ss3sim functions are divided into three types:

1. change and sample functions that manipulate SS3 configuration files. These manipulations generate an underlying "truth" (operating models) and control our assessment of those models (estimation models).

• change_f: Controls fishing mortality.

• change_tv: Adds time-varying features. For example, time-varying natural mortality, growth, or selectivity.

• sample_lcomp: Controls how length composition data are sampled.

• sample_agecomp: Controls how age composition data are sampled.

• sample_index: Controls how the fishery and survey indices are sampled.

• change_e: Controls which and how parameters are estimated.

• change_retro: Controls the number of years to discard for a retrospective analysis.

• change_rec_devs: Substitutes recruitment deviations.

• change_lcomp_constant: Set the robustification constant for length composition data.

• change_tail_compression: Replace tail compression value for length composition data.

2. run functions that conduct simulations. These functions generate a folder structure, call manipulation functions, run SS3 as needed, and save the output.

• run_ss3sim: Main function to run ss3sim simulations.

• ss3sim_base: Underlying base simulation function. Can also be called directly.

3. get functions for synthesizing the output.

• get_results_scenario: Extract the results for a single scenario.

• get_results_all: Extract results from a series of scenarios.

See the introductory vignette vignette("introduction", package = "ss3sim") for more extensive explanation of how to use the ss3sim R package.

ss3sim was developed by graduate students and post doctoral researchers at the University of Washington (School of Aquatic and Fishery Sciences and Quantitative Ecology and Resource Management departments) and Simon Fraser University. The authors of individual functions are listed within the function documentation and all contributors are listed in the DESCRIPTION file.

If you use ss3sim in a publication, please cite the package as indicated by running citation("ss3sim") in the R console.

ss3sim documentation built on Nov. 9, 2019, 1:06 a.m.