ss3sim: An R Package for Fisheries Stock Assessment Simulation with Stock Synthesis
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{"title"=>"ss3sim: An R package for fisheries stock assessment simulation with stock synthesis", "type"=>"journal", "authors"=>[{"first_name"=>"Sean C.", "last_name"=>"Anderson", "scopus_author_id"=>"25930284300"}, {"first_name"=>"Cole C.", "last_name"=>"Monnahan", "scopus_author_id"=>"56126475400"}, {"first_name"=>"Kelli F.", "last_name"=>"Johnson", "scopus_author_id"=>"56126980600"}, {"first_name"=>"Kotaro", "last_name"=>"Ono", "scopus_author_id"=>"55204726500"}, {"first_name"=>"Juan L.", "last_name"=>"Valero", "scopus_author_id"=>"7005131527"}], "year"=>2014, "source"=>"PLoS ONE", "identifiers"=>{"pui"=>"372921884", "sgr"=>"84899051327", "pmid"=>"24699270", "scopus"=>"2-s2.0-84899051327", "isbn"=>"9788578110796", "arxiv"=>"1312.6450", "doi"=>"10.1371/journal.pone.0092725", "issn"=>"19326203"}, "id"=>"c903dda9-8fde-34b8-b97c-278af7a39011", "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.", "link"=>"http://www.mendeley.com/research/ss3sim-r-package-fisheries-stock-assessment-simulation-stock-synthesis", "reader_count"=>58, "reader_count_by_academic_status"=>{"Unspecified"=>3, "Professor > Associate Professor"=>2, "Researcher"=>24, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>16, "Student > Postgraduate"=>1, "Student > Master"=>6, "Other"=>2, "Professor"=>2}, "reader_count_by_user_role"=>{"Unspecified"=>3, "Professor > Associate Professor"=>2, "Researcher"=>24, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>16, "Student > Postgraduate"=>1, "Student > Master"=>6, "Other"=>2, "Professor"=>2}, "reader_count_by_subject_area"=>{"Unspecified"=>5, "Environmental Science"=>14, "Materials Science"=>1, "Mathematics"=>2, "Agricultural and Biological Sciences"=>30, "Physics and Astronomy"=>2, "Computer Science"=>1, "Earth and Planetary Sciences"=>3}, "reader_count_by_subdiscipline"=>{"Materials Science"=>{"Materials Science"=>1}, "Physics and Astronomy"=>{"Physics and Astronomy"=>2}, "Earth and Planetary Sciences"=>{"Earth and Planetary Sciences"=>3}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>30}, "Computer Science"=>{"Computer Science"=>1}, "Mathematics"=>{"Mathematics"=>2}, "Unspecified"=>{"Unspecified"=>5}, "Environmental Science"=>{"Environmental Science"=>14}}, "reader_count_by_country"=>{"United States"=>3, "United Kingdom"=>2, "Mexico"=>1, "Italy"=>1, "Russia"=>2}, "group_count"=>5}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1448699"], "description"=>"<p>Functions that are called internally are shown in a monospaced font.</p>", "links"=>[], "tags"=>["Computational biology", "Biological data management", "Population modeling", "ecology", "Marine ecology", "Marine biology", "Fisheries science", "Marine conservation", "Marine monitoring", "Marine technology", "Population biology", "Population Dynamics", "Computerized simulations", "software engineering", "Software tools", "marine and aquatic sciences", "Aquatic environments", "Marine environments", "diagram", "steps", "ss3sim", "simulation", "carried"], "article_id"=>986104, "categories"=>["Biological Sciences", "Ecology"], "users"=>["Sean C. Anderson", "Cole C. Monnahan", "Kelli F. Johnson", "Kotaro Ono", "Juan L. Valero"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0092725.g001", "stats"=>{"downloads"=>1, "page_views"=>19, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Flow_diagram_of_the_main_steps_in_an_ss3sim_simulation_carried_out_using_run_ss3sim_/986104", "title"=>"Flow diagram of the main steps in an ss3sim simulation carried out using run_ss3sim.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-04-03 03:22:47"}
  • {"files"=>["https://ndownloader.figshare.com/files/1448708"], "description"=>"<p>We ran a crossed simulation in which we considered (1) the effect of fixing natural mortality (<i>M</i>) at its true value (0.2; case E0) or estimating <i>M</i> (case E1) and (2) the effect of high survey effort (; case D0) or low survey effort (; case D1). Upper panels (blue) show time series of relative error in spawning stock biomass (SSB). Lower panels (grey) show the distribution of relative error across four scalar variables: depletion (the ratio of terminal year spawning biomass to unfished spawning biomass), <i>M</i>, SSB at maximum sustainable yield (), and fishing mortality () in the terminal year. We show the values across simulation iterations with dots and the distributions with beanplots (kernel density smoothers).</p>", "links"=>[], "tags"=>["Computational biology", "Biological data management", "Population modeling", "ecology", "Marine ecology", "Marine biology", "Fisheries science", "Marine conservation", "Marine monitoring", "Marine technology", "Population biology", "Population Dynamics", "Computerized simulations", "software engineering", "Software tools", "marine and aquatic sciences", "Aquatic environments", "Marine environments", "ss3sim"], "article_id"=>986112, "categories"=>["Biological Sciences", "Ecology"], "users"=>["Sean C. Anderson", "Cole C. Monnahan", "Kelli F. Johnson", "Kotaro Ono", "Juan L. Valero"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0092725.g003", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Example_output_from_an_ss3sim_simulation_/986112", "title"=>"Example output from an ss3sim simulation.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-04-03 03:22:47"}
  • {"files"=>["https://ndownloader.figshare.com/files/1448705"], "description"=>"<p>Folders are shown in blue, input files in orange, and output files in grey. All input and output files are in plain text format. OM refers to operating model and EM to estimation model. Case files (orange files at bottom left) combine cases (e.g. M0 for a given natural mortality trajectory) with species or life-history OMs and EMs (e.g. cod-like or sardine-like). Alternatively, a user can skip setting up case files and specify the simulation cases directly in R code (see the vignette).</p>", "links"=>[], "tags"=>["Computational biology", "Biological data management", "Population modeling", "ecology", "Marine ecology", "Marine biology", "Fisheries science", "Marine conservation", "Marine monitoring", "Marine technology", "Population biology", "Population Dynamics", "Computerized simulations", "software engineering", "Software tools", "marine and aquatic sciences", "Aquatic environments", "Marine environments", "folder", "ss3sim"], "article_id"=>986110, "categories"=>["Biological Sciences", "Ecology"], "users"=>["Sean C. Anderson", "Cole C. Monnahan", "Kelli F. Johnson", "Kotaro Ono", "Juan L. Valero"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0092725.g002", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Illustration_of_input_and_output_folder_and_file_structure_for_an_ss3sim_simulation_/986110", "title"=>"Illustration of input and output folder and file structure for an ss3sim simulation.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-04-03 03:22:47"}
  • {"files"=>["https://ndownloader.figshare.com/files/1448709"], "description"=>"<p>Simulations can be run through the run_ss3sim function, which then calls the change functions. Users can control what the change functions do through a series of plain-text case files. For example, the case ID d1 corresponds to the case files lcomp1, agecomp1, and index1, as described in the table. Users can also skip setting up case files and specify arguments to ss3sim_base directly, or use the change functions as part of their own simulation structure (see the vignette).</p>", "links"=>[], "tags"=>["Computational biology", "Biological data management", "Population modeling", "ecology", "Marine ecology", "Marine biology", "Fisheries science", "Marine conservation", "Marine monitoring", "Marine technology", "Population biology", "Population Dynamics", "Computerized simulations", "software engineering", "Software tools", "marine and aquatic sciences", "Aquatic environments", "Marine environments", "ss3sim", "functions"], "article_id"=>986113, "categories"=>["Biological Sciences", "Ecology"], "users"=>["Sean C. Anderson", "Cole C. Monnahan", "Kelli F. Johnson", "Kotaro Ono", "Juan L. Valero"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0092725.t001", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Main_ss3sim_functions_and_a_description_of_their_purpose_/986113", "title"=>"Main ss3sim functions and a description of their purpose.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-04-03 03:22:47"}

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