Beyond visualizing catch-at-age models: Lessons learned from the r4ss package about software to support stock assessments

Stock assessment analysts are exploring an increasingly diverse and complex range of models while also facing higher expectations for consistency, documentation, and transparency in reports and management advice, all within a tight timeline. Meeting these goals requires increased efficiency at all s...

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Veröffentlicht in:Fisheries research 2021-07, Vol.239, p.105924, Article 105924
Hauptverfasser: Taylor, Ian G., Doering, Kathryn L., Johnson, Kelli F., Wetzel, Chantel R., Stewart, Ian J.
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container_end_page
container_issue
container_start_page 105924
container_title Fisheries research
container_volume 239
creator Taylor, Ian G.
Doering, Kathryn L.
Johnson, Kelli F.
Wetzel, Chantel R.
Stewart, Ian J.
description Stock assessment analysts are exploring an increasingly diverse and complex range of models while also facing higher expectations for consistency, documentation, and transparency in reports and management advice, all within a tight timeline. Meeting these goals requires increased efficiency at all steps in the assessment process from data processing, through model development and selection, to report writing and review. Here, we describe one widely used tool that has proven successful in increasing the efficiency of the assessment process: the r4ss package, which supports the use of the Stock Synthesis modeling framework. What began 15 years ago as a tool to provide simple model diagnostics, including plots showing data and model results, has grown into a large collection of R functions to support many aspects of the assessment process. We provide an overview of the r4ss features and illustrate its utility with examples from recent applications. Finally, we discuss lessons learned from the ongoing development of r4ss that can be applied to similar efforts associated with the next generation of stock assessment packages.
doi_str_mv 10.1016/j.fishres.2021.105924
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subjects Conditional age-at-length data
Fisheries
Life Sciences & Biomedicine
Model diagnostics
R packages
r4ss
Science & Technology
Stock Synthesis
title Beyond visualizing catch-at-age models: Lessons learned from the r4ss package about software to support stock assessments
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