Course overview
- Study period
- Semester 2, 2025 (28/07/2025 - 22/11/2025)
- Study level
- Undergraduate
- Location
- St Lucia
- Attendance mode
- In Person
- Units
- 2
- Administrative campus
- St Lucia
- Coordinating unit
- Mathematics & Physics School
The biggest challenge facing our planet is how to maintain and manage our natural systems such as fisheries, forestry and biodiversity in the face of habitat destruction, climate change, pollution and over harvesting. In this course you will learn how to apply deterministic differential and difference equation models to real world examples, and how to solve them using numerical methods. You will also learn how to quantify system uncertainties with the help of statistical and probabilistic methods. Students will be taught a range of methods that are employed in industry, research, consultancies and government to model complex natural resource problems. In the process, students will learn how certain fundamental mathematical concepts such as critical points, orthogonality, eigenvalues and singularity recur in different mathematical frameworks with different but, invariably, vitally important physical interpretations.
Mathematics is fundamental to managing the natural resources—such as fisheries, forests, water, and biodiversity—on which we depend. In this course, we will build mathematical models that are used to manage natural systems subjected to threats such as climate change, habitat destruction, pests, pollution and overexploitation. Students enrolling in this course will study systems of deterministic differential and difference equation models applied to real-world problems. Students will also learn some probability theory and statistical methods for model fitting, validation, and uncertainty quantification. Students will develop programming skills and also learn the entire modelling process; how to formulate, parameterise, code, visualise, test, interpret, and communicate mathematical and statistical models relevant to management and policy decisions. Emphasis will be placed on the appropriate choice of mathematical model for a given situation and the correct interpretation of results. These models allow us to investigate and forecast the response of systems to future conditions, of which there may be no prior experience.ᅠThe R programming language will be taught in this course to enhance learning and to enable students to analyse real-life mathematical problems. However, for assessments, students are welcome to program in anyᅠlanguage they choose, such as MATLAB or Python. Skills developed in this course are in high demand in government, industry and research sectors.
In the School of Mathematics and Physics we are committed to creating an inclusive and empowering learning environment for all students. We value and respect the diverse range of experiences our students bring to their education, and we believe that this diversity is crucial for fostering a rich culture of knowledge sharing and meaningful exploration. We hold both students and staff accountable for actively contributing to the establishment of a respectful and supportive learning environment.
Bullying, harassment, and discrimination in any form are strictly against our principles and against UQ Policy, and will not be tolerated. We have developed a suite of resources to assist you in recognising, reporting, and addressing such behaviour. If you have any concerns about your experience in this course, we encourage you to tell a member of the course teaching team, or alternatively contact an SMP Classroom Inclusivity Champion (see Blackboard for contact details). Our Inclusivity Champions are here to listen, to understand your concerns, and to explore potential actions that can be taken to resolve them. Your well-being and a positive learning atmosphere are of utmost importance to us.
Course requirements
Assumed background
The course assumes some understanding of random variables, their distributions, and conditional probability. STAT1301 or concurrent enrolment or completion of STAT2203 or STAT2003 is recommended. Students who have only completed STAT1201 may need to review extra material. A probability review sheet will be posted on the course website to assist with this review.
Some background in ordinary differential equations at the level of MATH2100 or MATH2010 will be helpful but not required. Essential material from Ordinary Differential Equations will be briefly reviewed and built upon in the lectures. The course also assumes that students have seen or written code in some scripting language (e.g. R, Python, MATLAB, or similar), and are familiar with variables, loops, and similar constructs. However, no specific detailed knowledge of R (or any other language) is assumed.
Prerequisites
You'll need to complete the following courses before enrolling in this one:
(STAT1201 or STAT1301), (MATH1052 or MATH1072)
Recommended prerequisites
We recommend completing the following courses before enrolling in this one:
(STAT2003 or STAT2203) & (MATH2010 or MATH2100)
Incompatible
You can't enrol in this course if you've already completed the following:
MATH2070, MATH7130 (co-taught).
Course contact
Course staff
Lecturer
Timetable
The timetable for this course is available on the UQ Public Timetable.
Additional timetable information
All classes will be conducted on campus. Consult your personal timetable for times and locations.
Students are expected to attend these sessions in person unless they have a valid reason for being unable to attend (such as illness).
Important: if you are ill, do not attend any classes in person. Videos will be available to aid students in catching up when sick. There will be no recording of practicals to encourage in-person attendance. However, solution sketches will be posted to help students catch up when ill.
Lectures or practicals will be cancelled on public holidays. However, a quick video may be posted for you to watch if we are running behind.
Aims and outcomes
Mathematics is fundamental to managing the natural resources—such as fisheries, forests, water and biodiversity—on which we depend. In this course we will build mathematical models that are used to manage natural systems subjected to threats such as climate change, habitat destruction, pests, pollution and overexploitation. Students enrolling in this course will use systems ofᅠdeterministic differential and difference equation models applied to real world problems and solve them using numerical methods. You will also learn some statistical methods for model development and parameter estimation.ᅠ You will develop programming skills and also learn the entire modelling process; how to formulate, parameterise, code, visualise, test, interpret, and communicate models relevant to management and policy decisions. Emphasis is placed on the appropriate choice of mathematical model for a given situation and the correct interpretation of results. These models allow us to investigate and forecast the response of systems to future conditions, of which there may be no prior experience.ᅠThe R programming language will be used throughout to enhance learning and to enable students to analyse real-life mathematical problems. Skills developed in this course are in high demand in government, industry and research sectors.
Learning outcomes
After successfully completing this course you should be able to:
LO1.
Have a broad understanding of mathematical approaches to modelling natural resource and environmental management challenges, involving tools ranging from well-established theory to current advances in statistics and modelling.
LO2.
Choose, construct and analyse suitable mathematical and statistical models to describe dynamics of biological and environmental systems with sufficient adequacy to use for applied problems.
LO3.
Clearly present complex mathematical ideas and results.
LO4.
Use objective approaches to address diverse goals of natural resource management, such as establishing economically and ecologically acceptable harvesting regimes.
Assessment
Assessment summary
Category | Assessment task | Weight | Due date |
---|---|---|---|
Computer Code, Tutorial/ Problem Set | Assignment 1 | 15% |
10/09/2025 3:00 pm |
Computer Code, Tutorial/ Problem Set | Assignment 2 | 15% |
29/10/2025 3:00 pm |
Quiz |
Quizzes
|
70% |
15/08/2025 12:00 pm 5/09/2025 12:00 pm 26/09/2025 12:00 pm 24/10/2025 12:00 pm
Quizzes take place during the applied class on Fridays from 12:00 - 12:50 pm and are to be turned in at or before 12:50 pm in class. |
Assessment details
Assignment 1
- Mode
- Written
- Category
- Computer Code, Tutorial/ Problem Set
- Weight
- 15%
- Due date
10/09/2025 3:00 pm
- Learning outcomes
- L01, L02, L03, L04
Task description
Problem set on topics covered in weeks 1 - 6 of the lecture.
Submission guidelines
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 7 days. Extensions are given in multiples of 24 hours.
Assignment extensions are limited to 7 days because solutions will be released after that time to help students prepare for quizzes.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
You are required to submit assessable items on time. If you fail to meet the submission deadline for any assessment item then the listed penalty will be deducted per day for up to 7 calendar days, at which point any submission will not receive any marks unless an extension has been approved. Each 24-hour block is recorded from the time the submission is due.
Assignment 2
- Mode
- Written
- Category
- Computer Code, Tutorial/ Problem Set
- Weight
- 15%
- Due date
29/10/2025 3:00 pm
- Learning outcomes
- L01, L02, L03, L04
Task description
Problem set on topics covered in weeks 6 - 12 of the lectures.
Submission guidelines
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 7 days. Extensions are given in multiples of 24 hours.
Assignment extensions are limited to 7 days because solutions will be released after that time to help students prepare for quizzes.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
You are required to submit assessable items on time. If you fail to meet the submission deadline for any assessment item then the listed penalty will be deducted per day for up to 7 calendar days, at which point any submission will not receive any marks unless an extension has been approved. Each 24-hour block is recorded from the time the submission is due.
Quizzes
- Identity Verified
- In-person
- Mode
- Written
- Category
- Quiz
- Weight
- 70%
- Due date
15/08/2025 12:00 pm
5/09/2025 12:00 pm
26/09/2025 12:00 pm
24/10/2025 12:00 pm
Quizzes take place during the applied class on Fridays from 12:00 - 12:50 pm and are to be turned in at or before 12:50 pm in class.
- Other conditions
- Time limited.
- Learning outcomes
- L01, L02, L03, L04
Task description
There are four quizzes in this course, each containing problems based on material covered in lectures, applied classes, and practical sessions. The first three quizzes are not cumulative. The final quiz is cumulative. All quizzes are weighted equally.
Submission guidelines
Deferral or extension
You cannot defer or apply for an extension for this assessment.
If you are unavailable to attend any of the first three quizzes (for an approved reason), you may apply to have your mark from the missed quiz(zes) replaced by the final (fourth) quiz, which is cumulative and therefore will cover topics on the quiz(zes) you missed.
To do this, both contact the instructor by email and SMP Student Administration Team smp.studentadmin@uq.edu.au, so that there is an official record of your application with your documentation. If approved, the mark from your missed quiz(zes) will be replaced by your mark on the 4th quiz.
If you are unavailable to attend the 4th quiz, you may apply to take an oral quiz. In the oral quiz, you will present your solution verbally on a whiteboard in front of the instructor.
Course grading
Full criteria for each grade is available in the Assessment Procedure.
Grade | Description |
---|---|
1 (Low Fail) |
Absence of evidence of achievement of course learning outcomes. Course grade description: Students will receive this grade if their final mark is below 20% |
2 (Fail) |
Minimal evidence of achievement of course learning outcomes. Course grade description: Students will receive this grade if their final mark is at least 20% and less than 45% |
3 (Marginal Fail) |
Demonstrated evidence of developing achievement of course learning outcomes Course grade description: Students will receive this grade if their final mark is at least 45% and less than 50% |
4 (Pass) |
Demonstrated evidence of functional achievement of course learning outcomes. Course grade description: Students will receive this grade if their final mark is at least 50% and less than 65% |
5 (Credit) |
Demonstrated evidence of proficient achievement of course learning outcomes. Course grade description: Students will receive this grade if their final mark is at least 65% and less than 75% |
6 (Distinction) |
Demonstrated evidence of advanced achievement of course learning outcomes. Course grade description: Students will receive this grade if their final mark is at least 75% and less than 85% |
7 (High Distinction) |
Demonstrated evidence of exceptional achievement of course learning outcomes. Course grade description: Students will receive this grade if their final mark is at least 85% |
Supplementary assessment
Supplementary assessment is available for this course.
Should you fail a course with a grade of 3, you may be eligible for supplementary assessment. Refer to my.UQ for information on supplementary assessment and how to apply.
Supplementary assessment provides an additional opportunity to demonstrate you have achieved all the required learning outcomes for a course.
If you apply and are granted supplementary assessment, the type of supplementary assessment set will consider which learning outcome(s) have not been met.
Supplementary assessment in this course will be a 1-hour oral examination. To receive a passing grade of 3S4, you must obtain a mark of 50% or more on the supplementary assessment.
Additional assessment information
Artificial Intelligence
To pass this course, students will be required to demonstrate a detailed understanding of course material together with a range of associated skills independent of Artificial Intelligence (AI) and Machine Translation (MT) tools.
For assessment tasks that are completed in-person (including examinations) termed “secure assessment”, the use of generative Artificial Intelligence (AI) or Machine Translation (MT) tools will not be permitted unless otherwise advised. Any attempted use of AI or MT may constitute student misconduct under the Student Code of Conduct.
Other non-secure assessment tasks (such as assignments) are designed to help you develop your understanding and skills, and to prepare you for secure assessment. You are thus generally encouraged to complete such assessment without the use of AI/MT, unless explicitly advised to the contrary in the assessment item. In any event, if you choose to use such tools, then you must clearly reference any such use within your submitted work. A failure to reference AI or MT use may constitute student misconduct under the Student Code of Conduct.
Applications for Extensions to Assessment Due Dates
Extension requests are submitted online via my.UQ – applying for an extension. Extension requests received in any other way will not be approved. Additional details associated with extension requests, including acceptable and unacceptable reasons, may be found at my.UQ.
Please note:
- Requests for an extension to an assessment due date must be submitted through your my.UQ portal and you must provide documentation of your circumstances, as soon as it becomes evident that an extension is needed. Your application must be submitted on or before the assessment item's due date and time.
- Applications for extension can take time to be processed so you should continue to work on your assessment item while awaiting a decision. We recommend that you submit any completed work by the due date, and this will be marked if your application is not approved. Should your application be approved, then you will be able to resubmit by the agreed revised due date.
- If an extension is approved, you will be notified via your my.UQ portal and the new date and time for submission provided. It is important that you check the revised date as it may differ from the date that you requested.
- If the basis of the application is a medical condition, applications should be accompanied by a medical certificate dated prior to the assignment due date. If you are unable to provide documentation to support your application by the due date and time you must still submit your application on time and attach a written statement (Word document) outlining why you cannot provide the documentation. You must then upload the documentation to the portal within 24 hours.
- If an extension is being sought on the basis of exceptional circumstances, it must be accompanied by supporting documentation (eg. Statutory declaration).
- For extensions based on a SAP you may be granted a maximum of 7 days (if no earlier maximum timeframe applies). See the Extension or Deferral availability section of each assessment for details. Your SAP is all that is required as documentation to support your application. However, additional extension requests for the assessment item will require the submission of additional supporting documentation e.g., a medical certificate. All extension requests must be received by the assessment due date and time.
- An extension for an assessment item due within the teaching period in which the course is offered, must not exceed four weeks in total. If you are incapacitated for a period exceeding four weeks of the teaching period, you are advised to apply for Removal of Course.
- If you have been ill or unable to attend class for more than 14 days, you are advised to carefully consider whether you are capable of successfully completing your courses this semester. You might be eligible to withdraw without academic penalty - seek advice from the Faculty that administers your program.
- Students may be asked to submit evidence of work completed to date. Lack of adequate progress on your assessment item may result in an extension being denied.
- There are no provisions for exemption from an assessment item within UQ rules. If you are unable to submit an assessment piece then, under special circumstances, you may be granted an exemption, but may be required to submit alternative assessment to ensure all learning outcomes are met.
Applications to defer an exam
In certain circumstances you can apply to take a deferred examination for in-semester and end-of-semester exams. You'll need to demonstrate through supporting documentation how unavoidable circumstances prevented you from sitting your exam. If you can’t, you can apply for a one-off discretionary deferred exam.
Deferred Exam requests are submitted online via mySi-net. Requests received in any other way will not be approved. Additional details associated with deferred examinations, including acceptable and unacceptable reasons may be found at my.UQ.
Please note:
- Applications can be submitted no later than 5 calendar days after the date of the original exam.
- There are no provisions to defer a deferred exam. You need to be available to sit your deferred examination.
- Your deferred examination request(s) must have a status of "submitted" in mySI-net to be assessed.
- All applications for deferred in-semester examinations are assessed by the relevant school. Applications for deferred end-of-semester examinations are assessed by the Academic Services Division.
- You’ll receive an email to your student email account when the status of your application is updated.
- If you have a medical condition, mental health condition or disability and require alternative arrangements for your deferred exam you’ll need to complete the online alternative exam arrangements through my.UQ. This is in addition to your deferred examinations request. You need to submit this request on the same day as your request for a deferred exam or supplementary assessment. Contact Student Services if you need assistance completing your alternative exam arrangements request.
Learning resources
You'll need the following resources to successfully complete the course. We've indicated below if you need a personal copy of the reading materials or your own item.
Library resources
Find the required and recommended resources for this course on the UQ Library website.
Additional learning resources information
This course is self-contained and does not require any mandatory external resources.
Learning activities
The learning activities for this course are outlined below. Learn more about the learning outcomes that apply to this course.
Filter activity type by
Please select
Learning period | Activity type | Topic |
---|---|---|
Multiple weeks From Week 1 To Week 13 |
Lecture |
Lectures Lectures on mathematical modelling, optimisation and statistics as used to understand and manage natural resources. Learning outcomes: L01, L03, L04 |
Multiple weeks From Week 2 To Week 13 |
Practical |
Case study practicals Problem-solving sessions based on lectures and/or discussion of questions pertaining to assignments. Will include computing lab problems. Learning outcomes: L01, L02, L03, L04 |
Policies and procedures
University policies and procedures apply to all aspects of student life. As a UQ student, you must comply with University-wide and program-specific requirements, including the:
- Student Code of Conduct Policy
- Student Integrity and Misconduct Policy and Procedure
- Assessment Procedure
- Examinations Procedure
- Reasonable Adjustments for Students Policy and Procedure
Learn more about UQ policies on my.UQ and the Policy and Procedure Library.