2024-npo-sma-shiny

Model output and code needed to produce a Shiny dashboard for the 2024 ISC stock assessment of North Pacific Ocean shortfin mako shark. The full assessment report can be found here, and is a product of the ISC Shark Working Group (SHARKWG).

A companion repository housing the input data, model code, and executables needed to reproduce the full 2024 ISC stock assessment of North Pacific Ocean shortfin mako shark can be found here.

Running the models locally

Users should clone this repository on their local machine.

Using base R

Users should open up an R terminal (version 4.4.0; with RTools 4.4 already installed) and change the working directory to the directory that they cloned the repository into:

setwd("path/to/2024-npo-sma-shiny/")

Next they should source the .Rprofile:

source(".Rprofile")

This should prompt the renv package to bootstrap itself. renv is used for R package management to ensure a consistent work environment is set-up. Follow the in terminal prompts to install all packages. This should take a few minutes as there are a number of packages to load. If renv does not bootstrap automatically then run:

renv::restore()

Once all packages have been installed the user can run the following to launch the Shiny application:

setwd("./shiny")
source("app.R")

Using Rstudio

Users should use Rstudio with R version 4.4.0 and RTools 4.4 installed, and open the 2024-npo-sma-shiny project. The renv package to bootstrap itself as described above and once all packages have been installed the user can launch the app using:

setwd("./shiny")
source("app.R")

If renv does not bootstrap automatically then run:

renv::restore()

Using Visual Studio Code

Users should use Visual Studio Code with R version 4.4.0 and RTools 4.4 installed (set-up instructions here). In order to configure Visual Studio Code to work with renv the user should follow the configuration steps located here. Once Visual Studio Code has been configured properly, open the 2024-npo-sma-shiny folder using Visual Studio Code. Opening an R terminal should prompt the renv package to bootstrap itself as described above. Once all packages have been installed the user can launch the app using:

setwd("./shiny")
source("app.R")

If renv does not bootstrap automatically then run:

renv::restore()

Running the models remotely

Alternatively, models can be run in the cloud using GitHub Codespaces. A virtual Linux machine has already been configured so users can simply open a Codespace using default options. Initial creation of the Codespace can take 15-20 minutes. Once the Codespace is created, open an R terminal. This should prompt the renv package to bootstrap itself as described above. Once all packages have been installed the user can launch the app using:

setwd("./shiny")
source("app.R")

If renv does not bootstrap automatically then run:

renv::restore()

Note

The following convergence criteria was used to determine models retained for the final ensemble:

• $\hat{R} < 1.01$
• Bulk effective sample size (ESS) greater than 100 samples per chain. Five chains were used so $ESS > 500$.
• No divergent transitions in posterior samples.

Criteria were based on Monnahan 2024.

The original model runs to produce management advice used R version 4.3.1 and identified that models 5, 8, 12, and 30 failed to meet these conversion criteria. Models within this repository were run with R version 4.4.0 to address an identified security risk in earlier versions of R. Doing so resulted in estimates that were virtually identical. However, using R version 4.4.0 resulted in model 16 having $\hat{R}=1.012$ which is marginally higher than the convergence criteria. All other convergence criteria for all other models were unchanged between the two versions. Including/excluding model 16 from the ensemble does not change the management advice.

License

The code contained in this repository is licensed under the GNU GENERAL PUBLIC LICENSE version 3 (GPLv3).

Disclaimer

This repository is a scientific product and is not official communication of the National Oceanic and Atmospheric Administration, or the United States Department of Commerce. All NOAA GitHub project code is provided on an ‘as is’ basis and the user assumes responsibility for its use. Any claims against the Department of Commerce or Department of Commerce bureaus stemming from the use of this GitHub project will be governed by all applicable Federal law. Any reference to specific commercial products, processes, or services by service mark, trademark, manufacturer, or otherwise, does not constitute or imply their endorsement, recommendation or favoring by the Department of Commerce. The Department of Commerce seal and logo, or the seal and logo of a DOC bureau, shall not be used in any manner to imply endorsement of any commercial product or activity by DOC or the United States Government.