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Course profile

Environmental Bioanalytics (ENVM3010)

Study period
Sem 2 2026
Location
St Lucia
Attendance mode
In Person

Course overview

Study period
Semester 2, 2026 (27/07/2026 - 21/11/2026)
Study level
Undergraduate
Location
St Lucia
Attendance mode
In Person
Units
2
Administrative campus
St Lucia
Coordinating unit
The Environment School

Environmental bioanalytics refers to a wide range of methodological approaches that help environmental scientists to understand the biological components of ecosystems and how they are influenced by environmental issues. In brief, bioanalytics approaches involve the analysis of different pools of biomolecules (e.g., nucleic acids, proteins, and metabolites) and can provide insight into the diversity, function, and dynamics of ecological systems at multiple levels of organisation. The acquisition of knowledge and skills in environmental bioanalytics is an essential component of an environmental scientists’ training. This course will impart understanding of how bioanalytics approaches are applied in environmental studies. Students will be taught to analyse and evaluate bioanalytics datasets and to communicate their findings to different stakeholders. The course covers bioanalytics approaches that facilitate measurement of biodiversity, ecosystem function and biomass. Students will hear from people around the country using these methods for a range of impactful applications in environmental science, e.g.,: 1) biodiversity monitoring using marker gene sequencing, 2) ecosystem service evaluation using metagenomics and functional omics, 3) monitoring of rare/endangered species through analysis of environmental DNA (eDNA), and 4) eDNA detection of biological contaminants, pests and diseases.

Environmental Bioanalytics refers to a wide range of methodological approaches that help environmental scientists understand the biological components of ecosystems and how they are influenced by environmental issues.

This is important because we depend on the activities of diverse biological communities for the food, fibre, and clean air and water that keep us alive. Ironically though, our activities often have devasting consequences for life, especially when considering organisms that are too small to be seen.

Bioanalytics approaches involve the analyses of different pools of biomolecules (e.g., nucleic acids, proteins, and metabolites) and can provide insight into the diversity, function, biomass, and dynamics of ecological systems at multiple levels of organisation.

Hence, the acquisition of knowledge and skills in bioanalytical approaches provides environmental scientists with an essential toolkit to understand: 1) the biodiversity and functioning of organisms in the environment, and 2) how they are likely to respond to environmental change.

ENVM3010 Environmental Bioanalytics will provide students with this necessary training via weekly lectures and multiple laboratory and computer-based practical classes.ᅠ

Course requirements

Recommended prerequisites

We recommend completing the following courses before enrolling in this one:

SCIE2100

Course contact

Course staff

Lecturer

Tutor

Timetable

The timetable for this course is available on the UQ Public Timetable.

Aims and outcomes

This course will impart understanding of how bioanalytics approaches are applied in environmental studies. Students will be taught to analyse and evaluate bioanalytics datasets and to communicate their findings to different stakeholders. 

The course begins with an overview of bioanalytics approaches, and then demonstrates how these methods can be applied in environmental studies. Applications include: 1) biodiversity monitoring using marker gene sequencing, 2) ecosystem service evaluation using metagenomics and functional omics, 3) monitoring of rare/endangered species through analysis of environmental DNA (eDNA), 4) eDNA detection of biological contaminants (e.g., faecal bacteria), pests and diseases (e.g., Salmonella/COVID-19), and 5) the use of model systems to address hypotheses relating to biological systems using environmental bioanalytics.

Learning outcomes

After successfully completing this course you should be able to:

LO1.

Construct, test and evaluate scientific hypotheses regarding the biota of ecosystems using bioanalytics approaches

LO2.

Initiate and optimise sampling programs and experiments for answering biology-related questions in environmental science 

LO3.

Evaluate and critique biological research projects and assign priority to the outcomes 

LO4.

Identify appropriate analytical approaches for biological hypotheses and datasets

LO5.

Make inferences from bioanalytics analyses presented in primary environmental science literature

LO6.

Understand how environmental bioanalytics approaches can be applied to environmental studies and monitoring

LO7.

Evaluate and design strategies to communicate bioanalytics to different environmental stakeholders

LO8.

Create, analyse and evaluate bioanalytics datasets

LO9.

Work productively in a group setting to assess and define problems in environmental science and formulate possible bioanalytics responses

LO10.

Demonstrate skills in time management and working independently to complete written exercises on time

Assessment

Assessment summary

Category Assessment task Weight Due date
Notebook/ Logbook Practical class journal 15%

9/10/2026 5:00 pm

Computer Code, Paper/ Report/ Annotation Analytical report 15%

9/10/2026 5:00 pm

Participation/ Student contribution, Presentation Group presentations
  • Identity Verified
  • Team or group-based
  • In-person
15%

21/10/2026 - 22/10/2026

Examination End of Semester Exam
  • Hurdle
  • Identity Verified
  • In-person
55%

End of Semester Exam Period

7/11/2026 - 21/11/2026

A hurdle is an assessment requirement that must be satisfied in order to receive a specific grade for the course. Check the assessment details for more information about hurdle requirements.

Assessment details

Practical class journal

Mode
Written
Category
Notebook/ Logbook
Weight
15%
Due date

9/10/2026 5:00 pm

Task description

Students will be marked for participation in all lab and computer practicals and for recording notes and reflections for each of the topics covered in each session.

Notes from the practical classes should be recorded on the left page.

Reflections should be recorded on the right page.

For each practical:

Notes should include relevant facts, figures, drawings and/or statistics from each activity.

Reflections should include how the activities relate to the subjects in your course.

 Use of Artificial Intelligence (AI) and Machine Translation (MT)

This assessment task is to be completed in-person. The use of generative Artificial Intelligence (AI) or Machine Translation (MT) tools will not be permitted. Any attempted use of AI or MT may constitute student misconduct under the Student Code of Conduct.

Assessment security

Open assessment: In this assessment you can use resources such as your notes, course materials, and other tools, including AI, while completing the task. The focus is not on memorising information, but on understanding, applying judgement, and demonstrating your own thinking.

Submission guidelines

Please submit your journal in-class during class hours to course staff.

Deferral or extension

You may be able to apply for an extension.

The maximum extension allowed is 28 days. Extensions are given in multiples of 24 hours.

See the Additional assessment information section below for information relating to extension applications.

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 10% of the maximum possible mark for the assessment item (the assessment ‘marked from’ value) will be deducted as a late penalty for every day (or part day) late after the due date.

For example, if you submit your assignment 1 hour late, you will be penalised 10%; if your assignment is 24.5 hours late, you will be penalised 20% (because it is late by one 24-hour period plus part of another 24-hour period). 

Analytical report

Mode
Written
Category
Computer Code, Paper/ Report/ Annotation
Weight
15%
Due date

9/10/2026 5:00 pm

Learning outcomes
L01, L06, L08, L10

Task description

Each student will be assigned a dataset and a series of questions. To address the questions, students will need to analyse the data using R and report their results and interpretations.

Reports should be saved as a pdf and uploaded to Turnitin by the deadline.

Use of Artificial Intelligence (AI) and Machine Translation (MT)

Artificial Intelligence (AI) and Machine Translation (MT) are emerging tools that may support students in completing this assessment task. Students may appropriately use AI and/or MT in completing this assessment task. Students must clearly reference any use of AI or MT in each instance. A failure to reference generative AI or MT use may constitute student misconduct under the Student Code of Conduct.

Assessment security

Open assessment: In this assessment you can use resources such as your notes, course materials, and other tools, including AI, while completing the task. The focus is not on memorising information, but on understanding, applying judgement, and demonstrating your own thinking.

Submission guidelines

Online submission by Turnitin only by the due date and time. Refer to Blackboard for the submission link. No hard copy or assignment cover sheets are required. Submission via email is not accepted.

Deferral or extension

You may be able to apply for an extension.

The maximum extension allowed is 28 days. Extensions are given in multiples of 24 hours.

See the Additional assessment information section below for information relating to extension applications.

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 10% of the maximum possible mark for the assessment item (the assessment ‘marked from’ value) will be deducted as a late penalty for every day (or part day) late after the due date.

For example, if you submit your assignment 1 hour late, you will be penalised 10%; if your assignment is 24.5 hours late, you will be penalised 20% (because it is late by one 24-hour period plus part of another 24-hour period). 

Group presentations

  • Identity Verified
  • Team or group-based
  • In-person
Mode
Activity/ Performance, Oral
Category
Participation/ Student contribution, Presentation
Weight
15%
Due date

21/10/2026 - 22/10/2026

Task description

In Teaching Week 12 students will present (in groups) a summary of the content of a lecture provided during the course.

You will be assigned to a group comprising 3-6 students (depending on class size).

Each group will then be assigned a lecture from the course. Within your group you will summarise the key points of that lecture and prepare a presentation to emphasise those points.

This will help to reinforce the learning objectives of the lectures in previous weeks.

All students must attend the workshops in Teaching weeks 10 and 11 to ensure that they contribute to their group's performance.

Use of Artificial Intelligence (AI) and Machine Translation (MT)

Artificial Intelligence (AI) and Machine Translation (MT) are emerging tools that may support students in completing this assessment task. Students may appropriately use AI and/or MT in completing this assessment task. Students must clearly reference any use of AI or MT in each instance.

A failure to reference generative AI or MT use may constitute student misconduct under the Student Code of Conduct.

Assessment security

Open assessment: In this assessment you can use resources such as your notes, course materials, and other tools, including AI, while completing the task. The focus is not on memorising information, but on understanding, applying judgement, and demonstrating your own thinking.

Submission guidelines

Deferral or extension

You cannot defer or apply for an extension for this assessment.

Group presentations are designed not only to assess content knowledge, but also to develop essential collaborative, organisational, and time management skills that mirror real-world professional scenarios. In most professional settings, project deadlines are fixed, and teams must coordinate to meet them despite individual challenges. Allowing extensions for group presentations undermines this learning objective by:

  • Disrupting the collaborative process: An extension for one or more members can unfairly burden others or require reorganisation of the group’s work and presentation schedule.
  • Reducing the incentive to plan and manage contingencies: One purpose of group work is to foster accountability and strategic delegation when unexpected issues arise.
  • Interfering with course logistics: Presentations are typically scheduled to ensure fairness and allow peer feedback or assessment moderation. Changing the schedule for one group can affect the whole cohort.

Students will be scheduled to deliver their assessment. You may only be eligible for alternative arrangement if exceptional circumstances arise on the day of the scheduled presentation. Please contact your course coordinator with supporting documentation of the exceptional circumstances that prevented you from attending for consideration of an alternate arrangement.

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.

End of Semester Exam

  • Hurdle
  • Identity Verified
  • In-person
Mode
Written
Category
Examination
Weight
55%
Due date

End of Semester Exam Period

7/11/2026 - 21/11/2026

Other conditions
Secure.

See the conditions definitions

Learning outcomes
L01, L04, L06, L07, L10

Task description

This will be a 2 hour exam consisting of short essay-style questions based around your knowledge and understanding of the issues examined.

Use of Artificial Intelligence (AI) and Machine Translation (MT)

This assessment task is to be completed in-person. The use of generative Artificial Intelligence (AI) or Machine Translation (MT) tools will not be permitted. Any attempted use of AI or MT may constitute student misconduct under the Student Code of Conduct.

Assessment security

Secure assessment: This assessment is designed to protect academic integrity and assess your understanding of course concepts. You must only use the approved materials and tools for this assessment task. Use of prohibited materials in this task may be investigated and treated as academic misconduct. See assessment instructions for more details.

Hurdle requirements

See ADDITIONAL COURSE GRADING INFORMATION for the hurdle relating to this assessment item.

Exam details

Planning time 10 minutes
Duration 120 minutes
Calculator options

Casio FX82 series calculator only

Open/closed book Closed book examination - no written materials permitted
Exam platform Paper based
Invigilation

Invigilated in person

Submission guidelines

Deferral or extension

You may be able to defer this exam.

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: The minimum percentage required for this grade is: 0%

2 (Fail)

Minimal evidence of achievement of course learning outcomes.

Course grade description: The minimum percentage required for this grade is: 30%

3 (Marginal Fail)

Demonstrated evidence of developing achievement of course learning outcomes

Course grade description: The minimum percentage required for this grade is: 45%

4 (Pass)

Demonstrated evidence of functional achievement of course learning outcomes.

Course grade description: The minimum percentage required for this grade is: 50%

5 (Credit)

Demonstrated evidence of proficient achievement of course learning outcomes.

Course grade description: The minimum percentage required for this grade is: 65%

6 (Distinction)

Demonstrated evidence of advanced achievement of course learning outcomes.

Course grade description: The minimum percentage required for this grade is: 75%

7 (High Distinction)

Demonstrated evidence of exceptional achievement of course learning outcomes.

Course grade description: The minimum percentage required for this grade is: 85%

Additional course grading information

Assessment Hurdle

In order to pass this course, you must meet the following requirements (if you do not meet these requirements, the maximum grade you will receive will be a 3):

You must obtain 45% or more on the End of Semester exam.

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 the link above 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 can take any form (such as a written report, oral presentation, examination or other appropriate assessment) and may test specific learning outcomes tailored to the individual student, or all learning outcomes.

To receive a passing grade of 3S4, you must obtain a mark of 50% or more on the supplementary assessment.

Additional assessment information

Applications for Extensions to Assessment Due Dates

Read the information contained in the following links carefully before submitting an application for extension to assessment due date.

For guidance on applying for an extension, information is available here: https://my.uq.edu.au/information-and-services/manage-my-program/exams-and-assessment/applying-assessment-extension

For the policy relating to extensions, information is available here (Part D): https://policies.uq.edu.au/document/view-current.php?id=184

Please note the University's requirements for medical certificates here: https://my.uq.edu.au/information-and-services/manage-my-program/uq-policies-and-rules/requirements-medical-certificates


Turnitin

By submitting work through Turnitin you are deemed to have accepted the following declaration “I certify that this assignment is my own work and has not been submitted, either previously or concurrently, in whole or in part, to this University or any other educational institution, for marking or assessment.”

All students must ensure they receive their Turnitin receipt on submission of any assessments. A valid Turnitin receipt will be the only evidence accepted if assessments are missing. Without evidence, the assessment will receive the standard late penalty, or after seven days, will receive zero.

In the case of a Blackboard outage, please contact the Course Coordinator as soon as possible to confirm the outage with ITS.

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

Library resources are available on the UQ Library website.

Learning activities

The learning activities for this course are outlined below. Learn more about the learning outcomes that apply to this course.

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Learning period Activity type Topic
Multiple weeks
Lecture

Lectures

Two 50 min lectures weekly providing context and theory for each topic.

Lectures link with the practical sessions within the same week.

Practical

A series of laboratory and computer-based sessions

Laboratory practical classes teaching methods used to generate data.

Computing practical classes teaching how to process, analyse and interpret bioanalytical datasets.

Workshops to discuss methods and analyses.

Not Timetabled

Practical class journal

During each practical class you will be asked to record your notes and reflections in a notebook. You will also be given some questions to address based on your learning. You will be given the opportunity to ask quesstions about your answers in the next practical class. This will help to reinforce your understanding of the key points and how to apply what you've learned.

Not Timetabled

Analytical report

You will be assigned a question/problem to address along with a dataset to analyse and interpret. You will then write an analytical report and interpret your analyses relative to the literature.

Learning outcomes: L01, L06, L08, L10

Workshop

Group presentations

During the course you will form groups. In Teaching Week 10 each group will identify an environmental issue and prepare a case for addressing that issue with Environmental Bioanalytical methods. In Week 12 each group will guide the class through their proposal in an oral presentation. The presentations will be 10-15 min long followed by up to 5 min questions from the audience.

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:

Learn more about UQ policies on my.UQ and the Policy and Procedure Library.