BIOL336-23S1 (C) Semester One 2023

Ecological and Evolutionary Models

15 points

Start Date: Monday, 20 February 2023
End Date: Sunday, 25 June 2023
Withdrawal Dates
Last Day to withdraw from this course:
  • Without financial penalty (full fee refund): Sunday, 5 March 2023
  • Without academic penalty (including no fee refund): Sunday, 14 May 2023


Introduction to key ecological and evolutionary models. The course introduces how to solve basic mathematical models and how to use computational tools to explore their solutions. Students learn how to create simple models to understand how complex, real-world processes unfold.

The general aim of the course is to introduce you to the major concepts in developing theoretical biological models. This is achieved by examining key ecological and evolutionary models. The central focus is on understanding, creating, and analyzing basic biological models. We will highlight the importance of theoretical modelling to the fields of ecology and evolution and help you develop key computational and mathematical skills.

An understanding of basic ecological and evolutionary principles is assumed. If at any stage
you feel that you do not understand the assumed basics, refer to the general reference
materials listed below or seek help from the lecturer concerned as soon as possible.

Learning Outcomes

  • Hua Akoranga and Associated Assessment | Aromatawai
    As a student in this course, I will develop the ability to:
    ● Clearly understand the basic techniques in building theoretical models.
    Assessment tasks: Quizzes, mid-term, research project
    Related graduate attributes: GP1, GP2
    ● Understand mathematical models and their applications to ecology and evolution.
    Assessment tasks: Quizzes, mid-term, research project
    Related graduate attributes: GP1, GP2, GP3 (K1), GP5
    ● Demonstrate proficiency in analyzing mathematical models.
    Assessment tasks: Quizzes, mid-term, research project
    Related graduate attributes: GP1, GP2
    ● Develop new models that reduce complex biological realities to a manageable representation.
    Assessment tasks: Research project
    Related graduate attributes: GP1, GP2, GP3 (K1), GP5
    ● Synthesise outcomes of mathematical models to clearly communicate their meaning and their relevance in a biological context.
    Assessment tasks: Research project
    Related graduate attributes: GP1, GP2, GP3 (K1), GP5

    Transferable Skills Register | Pūkenga Ngaio
    As a student in this course, I will develop the following skills:
    ● Understand theoretical models presented in research papers. This skill is invaluable for students pursuing further academic study, but is also a form of problem solving that is applicable to daily live.
    Related graduate attributes: GP1, GP2, GP5
    ● Ability to build and analyze a mathematical model. This ability is a useful way of taking a complicated world (or problem) and turning it into a manageable representation that can be solved with the skills in your toolbox. This way of approaching problems will be broadly applicable to most professional careers.
    Related graduate attributes: GP1, GP2, GP3 (K1), GP5
    ● Basic modeling skills in R. The development of these computational skills will be useful to anyone pursuing a career in science and technology.
    Related graduate attributes: GP1, GP2
    ● Preparing an oral presentation on findings. Clear written communication of complex problems is essential for most professional careers.
    Related graduate attributes: GP1, GP2, GP3 (K1)

    Graduate Profile | Āhuatanga Taura
    This course will provide students with an opportunity to develop these UC Graduate Attributes (GP) ( profile/students/what-are-the-graduate-attributes/):
  • GP1 Critically competent in a core academic discipline.
  • GP2 Employable, innovative and enterprising.
  • GP3 Biculturally competent and confident: K1 A process of self-reflection on the nature of ‘knowledge’ and ‘norms’
  • GP5 Globally aware.


BIOL209 or 15 Points of 200-level COSC or DATA or EMTH or ENCE or PHYS or MATH or STAT. RP: BIOL270, BIOL271 or BIOL274

Recommended Preparation

BIOL270, BIOL271 or BIOL274

Timetable Note

Lectures will be held during the first 8 weeks of the semester, during which we will have two 2-hour lectures per week. During this time we will have a mix of whiteboard lectures and computer work.

Project tutorials will be organised for weeks 8 to 11 of the semester and will last 1 hour each. These sessions have been included to provide students with an opportunity for structured time to work on their Research Project. The latter three are optional, but we highly recommend that students make use of this time to take advantage of our help. During the last week of the semester, there will also be a Presentation session during which students will give oral presentations about their Research Project.

Students should note that they are responsible for 10 hours of study per credit point – this equates to approximately an average of 9-10 hours of additional study per week of the course at the 300-level. In this course, we expect students to require fewer out-of-class hours during the first 8 weeks but students will spend much more time working outside of class during final weeks of the semester while working on their project.

The research project is a key component of this course. We will provide a list of papers presenting evolutionary or ecological models as applied to a relevant biological example. For the project, you will choose one of the provided models, dedicate yourself to understanding the assumptions and mathematics of that model, and determine a reasonable biological component that could be added to it. You will then give a short presentation to the lecturers and rest of the class leveraging the mathematical and computational skills learned during the first 8 weeks of the course. This will likely include things such as plots of different model components, simulations of the model dynamics, reproduction of findings from the original study, etc. You will also submit R code developed during your analysis of the model for assessment.

Course Coordinator / Lecturer

Daniel Stouffer


Sarah Flanagan


Assessment Due Date Percentage  Description
Quizzes 30% via Learn
Research Project & Presentation ( Final Exam) 30%
Mid-course Test 40% Online via Learn

Textbooks / Resources

We do not expect you to purchase a textbook, but we recommend accessing the suggested book through the library. During the course you will be directed to additional books and to primary scientific papers. This allows us to include in this course the most current scientific knowledge available, and to provide greater breadth than would be found in a single textbook. To do well on the mid-semester test, you must show evidence that you have read and understood this material.  

Suggested book: A Biologist’s Guide to Mathematical Modeling in Ecology and Evolution by Sarah P. Otto and Troy Day. A hardcopy and e-book of this text are currently available in the library.

Resources used or referred to in lectures will be available on-line on the course link in Learn.

Quizzes will be on LEARN. Please also note that we will occasionally be requesting that you submit written work in both hard copy (for grading) and in electronic form (for assessment of originality using “Turnitin”). Instructions will be given on how you do this via Learn.

Course links

Course outline

Indicative Fees

Domestic fee $951.00

International fee $4,750.00

* All fees are inclusive of NZ GST or any equivalent overseas tax, and do not include any programme level discount or additional course-related expenses.

For further information see School of Biological Sciences .

All BIOL336 Occurrences

  • BIOL336-23S1 (C) Semester One 2023