Training and workshops: Mastering fisheries data with the Fisheries Library in R (FLR)

Join us for this comprehensive training organised by the Joint Research Centre to enhance your skills in fisheries data analysis and management using the FLR toolset. This training will provide valuable insights and practical experience to scientists with some background in R and fisheries science.

The Fisheries Library in R (FLR; Kell et al., 2007) has been meticulously developed over the past 18 years to equip fisheries scientists with a comprehensive suite of packages for processing fisheries data. This powerful toolset includes capabilities for performing quantitative analyses, fitting various models such as age-structured stock assessment models, running forward simulations, and conducting management strategy evaluations.

Programme

• 19 May 2025 , 09:00 - 17:30 (CEST)
  • Introduction (am) - Loading data, handling FLR objects and plotting (pm)
• 20 May 2025 , 09:00 - 17:30 (CEST)
  • Stock assessment with FLa4a (am) - Assessment diagnostics (pm)
• 21 May 2025 , 09:00 - 17:30 (CEST)
  • Stock-recruit relationships and reference points (am) - Running short-term forecasts (pm)
• 22 May 2025 , 09:00 - 17:30 (CEST)
  • Stock assessment continued (am) - Simulation and a brief introduction to MSE (pm)
• 23 May 2025 , 09:00 - 17:30 (CEST)
  • Review of case studies (am) - Wrap-up (pm)

Practical Information

When: Monday 19 May 2025, 09:00 - Friday 23 May 2025, 17:30 (CEST)

Where: Joint Research Centre, Via Enrico Fermi, Ispra VA, Italy

Languages: English

Description Objectives

The primary goal of this training is to introduce and familiarise participants with the structure and capabilities of the FLR toolset. Through a detailed example, participants will explore the use of different packages at various stages of the stock advice process.

Key activities will include:

• Detailed Analysis: Participants will analyze a complete example, inspecting, modifying, and testing example code for each element in the analysis.
• Forward Simulations: Using various life history traits, stock recruitment relationships (SRR), and available stock objects, participants will perform forward simulations.
• Statistical Catch-at-Age: Participants will learn to run a statistical catch-at-age analysis using an example stock object, as implemented in a4a (Jardim et al., 2013).
• Parameter Improvement: With the aid of the diagnostic package a4adiags (Mosqueira and Winker, 2020), participants will work on improving the parameterization of a4a.

Syllabus

• Overview of FLR capabilities and packages for fisheries advice
• Loading, manipulating and plotting data in FLR
• Running a stock assessment with a4a: fits, diagnostics and reporting
• Fitting stock recruitment relationships
• Computing reference points using FLBRP
• Simulating stocks with FLife and FLasher
• An introduction to simulating the fishery system using MSE
• How to organize analyses using the Transparent Assessment Framework

Target Audience

The participants should already have a good knowledge of R and some knowledge of fisheries data analysis and stock assessment modelling.

Fees: There will be no fees for this course. Participants should pay for their travelling and accommodation.

Contacts

• Michael Gras: [email protected]
• Danai Mantopoulou Palouka: [email protected]