ss3sim: An R Package for Fisheries Stock Assessment Simulation with Stock Synthesis

Peer reviewed: 
Yes, item is peer reviewed.
Scholarly level: 
Faculty/Staff
Final version published as: 

Anderson SC, Monnahan CC, Johnson KF, Ono K, Valero JL (2014) ss3sim: An R Package for Fisheries Stock Assessment Simulation with Stock Synthesis. PLoS ONE 9(4): e92725. doi:10.1371/journal.pone.0092725

Date created: 
2014-04-03
Abstract: 

Simulation testing is an important approach to evaluating fishery stock assessment methods. In the last decade, the fisheries stock assessment modeling framework Stock Synthesis (SS3) has become widely used around the world. However, there lacks a generalized and scriptable framework for SS3 simulation testing. Here, we introduce ss3sim, an R package that facilitates reproducible, flexible, and rapid end-to-end simulation testing with SS3. ss3sim requires an existing SS3 model configuration along with plain-text control files describing alternative population dynamics, fishery properties, sampling scenarios, and assessment approaches. ss3sim then generates an underlying ‘truth’ from a specified operating model, samples from that truth, modifies and runs an estimation model, and synthesizes the results. The simulations can be run in parallel, reducing runtime, and the source code is free to be modified under an open-source MIT license. ss3sim is designed to explore structural differences between the underlying truth and assumptions of an estimation model, or between multiple estimation model configurations. For example, ss3sim can be used to answer questions about model misspecification, retrospective patterns, and the relative importance of different types of fisheries data. We demonstrate the software with an example, discuss how ss3sim complements other simulation software, and outline specific research questions that ss3sim could address.

Language: 
English
Document type: 
Article
File(s): 
Sponsor(s): 
Fulbright Canada
NSERC
Garfield Weston Foundation/B.C. Packers Ltd. Graduate Fellowship in Marine Sciences
Institute for the Study of the Atmosphere and Ocean (JISAO)
Center for the Advancement of Population Assessment Methodology (CAPAM)
Statistics: