WK_WKNSMSE_cod.27.47d20

a4a cod4 MSE

Introduction

This repository contains the Management Strategy Evaluation (MSE) for North Sea cod (Cod (Gadus morhua) in Subarea 4, Division 7.d, and Subdivision 20 (North Sea, eastern English Channel, Skagerrak), cod.27.47d20) conducted in 2018/2019 for ICES WKNSMSE (https://doi.org/10.17895/ices.pub.5090).

The simulation is based on the Fisheries Library in R (FLR) and makes use of the Assessment for All (a4a) standard MSE framework (FLR/mse) developed during the Workshop on development of MSE algorithms with R/FLR/a4a (Jardim et al., 2017).

Disclaimer

The content of this repository is licensed under the GNU General Public License v3.0, see LICENSE for more information. The content in this repository is provided as is, without any support by the contributors listed in this GitHub repository.

Repository structure

The root folder contains the following R scripts:

• OM.R: This script creates the baseline operating model (OM.md is the corresponding R Markdown file),
• OM_alt1.R, OM_alt2.Rand OM_alt1.R are scripts for creating alternative operating models,
• a4a_mse_WKNSMSE_funs.R contains functions and methods used for the creation of the operating models and for running the MSE,
• run_mse.R is an R script for running MSE scenarios and is called from a job submission script
• run_mse.bsub and run_mse.qsub are job submission scripts which are used on a high performance computing cluster and call run_mse.R
• run_mse_analyse.R is for analysing the MSE results

and the following subdirectories:

• legacy_code/: Legacy code with original MSE approach and original a4a mse framework. This is no longer supported.

R, R packages and version info

The MSE simulation was run on a high performance computing cluster:

sessionInfo()
R version 3.5.0 (2018-04-23)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: CentOS release 6.7 (Final)

The framework uses FLR and requires the following FLR packages:

• FLCore 2.6.11.9001
• FLash 2.5.11
• FLBRP 2.5.3
• FLAssess 2.6.3
• ggplotFL 2.6.5
• mse 0.9.1

The FLR package versions as used for the simulation can be installed with devtools:

devtools::install_github(repo = "flr/FLCore", ref = "d55bc6570c0134c6bea6c3fc44be20378691e042")
devtools::install_github(repo = "flr/FLash", ref = "7c47560cf57627068259404bb553f2b644682726")
devtools::install_github(repo = "flr/FLBRP", ref = "5644cfccefb0ec3965b1d028090bbf75b1e59da2")
devtools::install_github(repo = "flr/FLAssess", ref = "f1e5acb98c106bcdfdc81034f1583f76bb485514")
devtools::install_github(repo = "flr/ggplotFL", ref = "e9e0d74e872815c1df3f172522da35ade5c70638")
devtools::install_github(repo = "flr/mse", ref = "e39ddd75cdb2bb693601e31428404d48ea810308")

The cod MSE uses SAM as stockassessment method and requires the stockassessment R package from GitHub:

• stockassessment 0.8.1

Install this version with

install.packages("TMB") ### required to use stockassessment
devtools::install_github("fishfollower/SAM/stockassessment", ref = "362d4b661742ed418ce1af890ced05b374f6d6ed")

In order to use SAM within FLR, the functionality of the inofficial package FLfse is used:

• FLfse 0.0.0.9003

devtools::install_github("shfischer/FLfse/FLfse", ref = "c561f5bf28cbad0f711ef53a49bde7e9868dc257")

This package also contains the latest data for cod and can recreate the assessment as conducted during wGNSSK 2018.

Furthermore, some more R packages available from CRAN are required:

install.packages(c("foreach", "DoParallel", "dplyr", "tidyr", "data.table"))