Fall 2022 - REM 423 D100

Research Methods in Fisheries Assessment (4)

Class Number: 4365

Delivery Method: In Person


  • Course Times + Location:

    Sep 7 – Dec 6, 2022: Tue, Thu, 8:30–10:20 a.m.

  • Prerequisites:

    BISC 204 or GEOG 215 or REM 211; REM 225; STAT 201 or STAT 203 or STAT 205 or GEOG 251 or equivalent; MATH 151 or MATH 154 or MATH 157 or equivalent; and 60 units; or permission of instructor.



Introduction to quantitative methods for providing scientific advice on the status, productivity and effects of fishing of fish stocks. Includes development and application fish population dynamics models, data analysis, and the quantification of uncertainty. Focus will be primarily on biological aspects of fisheries assessment while illustrating how these interface with economic, social and institutional concerns of management agencies.


Environmental decision-makers need to make explicit choices about regulating harmful activities, developing resources, and investing in restoration to meet biological, social and economic objectives across a broad range of stakeholder values. Decisions can be made via ad hoc approaches, usually in response to problems and conflicts as they arise, or by applying the formalism of structured decision-making that anticipates potential problems by explicitly considering objectives, alternative actions, uncertainties, and risks.


Research Methods in Fisheries Assessment will help students improve their ability to think critically about data and quantitative analytical methods used in contemporary decision-making for fishery resources. After completing the course, students will be able to:

A) Data:
1. Understand the critical role of study design in generating informative and reliable data on exploited fish populations
2. Organize and manipulate fisheries data in the R statistical programming language

B) Quantitative methods:
3. Summarize fisheries data sets using statistical methods and graphics in R
4. Estimate parameters of fisheries models using both linear and non-linear estimation methods in R and Stan
5. Quantify uncertainty and risk for fisheries decisions using Bayesian statistics and Monte Carlo methods via the Stan package
6. Translate fisheries models from mathematical equations to computer programming code in R and Stan

C) Decision-making:
7.Develop research questions and approaches to support decision-making for sustainable fisheries


  • Participation in classes and weekly tutorials 10%
  • Quizzes (approx. weekly) 25%
  • Midterm exam 25%
  • Major project assignment (25%) and presentation (15%) 40%


Students must adhere to the exact stated deadlines for classes, tutorials, and assignments (i.e., all quizzes, assignments, and projects). Specifically, assignments will be eligible for a maximum of

  • 100% of potential marks if submitted on or before the stated deadline;
  • 80% of potential marks if submitted anytime within the first 24 hrs after the stated deadline;
  • 50% of potential marks if submitted 24-48 hrs past the stated deadline;
  • 0% of potential marks and not graded after 48 hrs past the stated deadline.



  1. All students will require a laptop in classes and tutorials. The SFU library has free, 4-hr loans of laptops:
  2. R statistical computing software: free to download from www.r-project.org
  3. RStudio: free download: www.rstudio.com
  4. rstan (R package): free to download as R package (will do this in class)


REM 423 uses two textbooks for general introductory material in fisheries assessment and quantitative methods. Other resources and readings are provided on specific topics.

  • Hilborn, R. and Walters, C.J. 1992. Quantitative Fisheries Stock Assessment: choice, dynamics, and uncertainty. Kluwer Academic Publishers, Norwell, MA (Provided in PDF)
  • Hilborn, R. and Mangel, M. 1997. The Ecological Detective. Princeton (Provided in PDF)


Your personalized Course Material list, including digital and physical textbooks, are available through the SFU Bookstore website by simply entering your Computing ID at: shop.sfu.ca/course-materials/my-personalized-course-materials.

Registrar Notes:


SFU’s Academic Integrity website http://www.sfu.ca/students/academicintegrity.html is filled with information on what is meant by academic dishonesty, where you can find resources to help with your studies and the consequences of cheating. Check out the site for more information and videos that help explain the issues in plain English.

Each student is responsible for his or her conduct as it affects the university community. Academic dishonesty, in whatever form, is ultimately destructive of the values of the university. Furthermore, it is unfair and discouraging to the majority of students who pursue their studies honestly. Scholarly integrity is required of all members of the university. http://www.sfu.ca/policies/gazette/student/s10-01.html