Information
Program(s) in charge: Stock Assessment ProgramStaff: Carolina Minte-Vera
Instructors:Dr. Steven Teo (NOAA/SWFSC stock assessment scientist)
Dr. Carolina Minte-Vera (IATTC stock assessment scientist)
Teaching Assistant:
Dr. Yi Xu (NOAA/NRC Postdoctoral Scholar)
Agenda
| Type | Details | Dates | Theme | |
|---|---|---|---|---|
| T1 | Theoretical class | 24 Jun, Morning | Introduction to Fisheries Stock Assessment Simple Population Models Probability density functions Using Likelihoods Fitting Data to Models |
|
| Lab1 | Laboratory | 24 Jun, Afternoon | Fitting Surplus Production Models (Sum of Squares and Likelihoods) | |
| T2 | Theoretical class | 25 Jun, Morning | Introduction to Age-Structure (mortality, growth) Yield-Per-Recruit Analysis Stock and Recruitment Catchability and Selectivity Age-structured Stock Assessment Models |
|
| Lab2 | Laboratory | 25 Jun, Afternoon | Yield-Per-Recruit Analysis Combining Yield-Per-Recruit and Stock-Recruitment Simple Age-structured Production Model |
|
| T3 | Theoretical class | 26 Jun, Morning | Integrated Analysis: Statistical Catch-at-Age Models Introduction to Stock Synthesis (SS) Simple Models in SS Understanding and Plotting SS Output SS Model Development (examples of SS models in different configurations) Debugging SS |
|
| Lab3 | Laboratory | 26 Jun, Afternoon | Simple SS Models Debugging simple SS Models |
|
| T4 | Theoretical class | 27 Jun, Morning | Growth Maturity and Fecundity Recruitment Natural and Fishing Mortality Initial Conditions Catchability and Selectivity |
|
| Lab4 | Laboratory | 27 Jun, Afternoon | Group Project: Develop a SS model (Data provided or bring your own) | |
| Lab5 | Laboratory | 28 Jun, Full day | Group Project: Continue SS Model Development | |
| Lab6 | Laboratory | 30 Jun, Full day | Group Project: Continue SS Model Development | |
| Lab7 | Laboratory | 01 Jul, Full day | Group Project: Present SS Models (Student presentations) Final Discussion |
Description
Course Objective and Description
This 7-day course introduces modern statistical models used in fisheries stock assessment and natural resource modeling, through lectures, labs, and a small group project related to fishery stock assessment model development. It is organized as a series of morning sessions that focus on theoretical concepts and afternoon work sessions. These afternoon sessions will rely on different software environments such as R, MS Excel and the Stock Synthesis (SS) Stock Assessment modeling package. The first 2 days will be a quick review of introductory stock assessment topics like: 1) simple population models, 2) fitting models to data, 3) likelihoods, 4) yield-per-recruit analysis, and 5) age-structured models. In the next 5 days, we will concentrate on using Stock Synthesis as the modeling platform to perform a fully-integrated age-structured analysis, from runningand debugging simple models to constructing a basic SS model from provided data (or bring your own) as a small group project. Projects will be presented to the class on the final day.
Pre-requisites:
Some knowledge of basic probability/statistical theory, population dynamics, and familiarity with MS Excel and R is strongly preferred.
Recommended Readings:
This 7-day course introduces modern statistical models used in fisheries stock assessment and natural resource modeling, through lectures, labs, and a small group project related to fishery stock assessment model development. It is organized as a series of morning sessions that focus on theoretical concepts and afternoon work sessions. These afternoon sessions will rely on different software environments such as R, MS Excel and the Stock Synthesis (SS) Stock Assessment modeling package. The first 2 days will be a quick review of introductory stock assessment topics like: 1) simple population models, 2) fitting models to data, 3) likelihoods, 4) yield-per-recruit analysis, and 5) age-structured models. In the next 5 days, we will concentrate on using Stock Synthesis as the modeling platform to perform a fully-integrated age-structured analysis, from runningand debugging simple models to constructing a basic SS model from provided data (or bring your own) as a small group project. Projects will be presented to the class on the final day.
Pre-requisites:
Some knowledge of basic probability/statistical theory, population dynamics, and familiarity with MS Excel and R is strongly preferred.
Recommended Readings:
- Haddon, M. 2011. Modeling and Quantitative Methods in Fisheries, Chapman & Hall/CRC.
- Quinn, T., and R. Deriso. 1998. Quantitative Fish Dynamics. Oxford University Press.
- Fournier, D., and C.P. Archibald. 1982. A general theory for analyzing catch at age data. Canadian Journal of Fisheries and Aquatic Science 39: 1195-1207.
- Methot, R.D. Jr. and C.R. Wetzel. (2013) Stock synthesis: A biological and statistical framework for fish stock assessment and fishery management. Fisheries Research142: 86-99.
- Hilborn, R., and M. Mangel. 1997. The Ecological Detective: Confronting Models with Data. Monographs in Population Biology 28, Princeton University Press.