/eutaccc

his repository is intended to support the project related to EU fisheries quota allocation under climate change

Primary LanguageRApache License 2.0Apache-2.0

Changes in the EU fisheries quota allocation under climate change

This repository is intended to support the project Changes in the EU fisheries quota allocation under climate change

Authors

Elena Ojea 1, Alex Tidd 1 & Juliano Palacios-Abrantes2,

  1. Future Oceans Lab, Universidad de Vigo, Vigo, Spain

  2. Institute for the Oceans and Fisheries, University of British Columbia, Vancouver, Canada.

Files and folders organization:

In this repository you will find all of the code related to the project. Note that due to the large volume of the (raw) data used in the analysis, we will not able to upload all data to GitHub. Please email the corresponding authors to discuss ways to share the data.

Folders

  • data (external): Folder where processed data is stored. Data folder is sub-divided in spatial; everything related to spatial analysis (e.g. shapefiles),tacs; everything related to ICES and EU tac system (e.g. current TAC allocation), species; data related to the specific species analyzed, dbem; processed outputs from the DBEM model.

Note: Data will not be located here as it exceeds GitHub's size cap

  • figures: Contains the Exploratory and Selected project figures (Part of Results)

  • functions: Folder with the functions needed for the analysis. Function folder is sub-divided in analysis and results to spread functions needed in each section.

  • tables: Contains project's tables (Part of Results)

  • references: Documents needed for the references of the manuscript including the reference list

  • results: Intended to have the analyzed data of the project, e.g. the final results.

  • scripts: Scripts for analysis a manuscript

Files

  • analysis.RMD: This script has the main analysis of the project

  • manuscript_draft.RMD: Manuscript draft for project.

Guidelines

Data

  • Locate data according to sub-folders
  • If data is included, updated data_readme.md
  • All data should be named in low caps and underscores (e.g. some_data.csv)
  • All variables within data will be cleaned to lower caps and underscore with janitor::clean_names()

Scripts

  • Identify yourself with initials (e.g. #JEPA) in parts of the script when modifying it -Use <- to name variables not =
  • Keep all functions and variables names with first capital and then low caps and underscores (e.g. tac_future <- function()), this is to differentiate from variables within tables)

Shiny app

https://clock-espana.shinyapps.io/EUTAC/