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Course profile

Biodiversity & Systematics (BIOL3209)

Study period
Sem 1 2026
Location
St Lucia
Attendance mode
In Person

Course overview

Study period
Semester 1, 2026 (23/02/2026 - 20/06/2026)
Study level
Undergraduate
Location
St Lucia
Attendance mode
In Person
Units
2
Administrative campus
St Lucia
Coordinating unit
The Environment School

This course examines the processes that drive the diversity and distributions of plants and animals. It will cover topics about the basic units of biodiversity - species -and how new species are discovered, recognised and described. We cover the phylogenetic basis of classification systems, and the different methods used to reconstruct evolutionary history and to test the origin of traits, including those relevant for ecology and adaption. We discuss processes that are thought to contribute to lineage diversity, and how biodiversity has changed through time and over large geographic scales. Case studies come primarily from plants and animals (both terrestrial and marine), but with some reference to other organisms. Examples will largely be drawn from, but not limited to, Australian examples.

This course examines the processes that drive the evolution, diversity and distributions of plants and animals, and how organisms are named, described and classified. It will cover topics about the basic units of biodiversity—species—and how new species are discovered, recognised, described and classified (Systematics). We cover the phylogenetic basis of classification systems, and the different methods used to reconstruct evolutionary history and to test the origin of traits, including those relevant for ecology and adaption. We also consider biodiversity below the species level, includingᅠgenetic and morphological variation among populations, and speciation with and without gene flow.ᅠ

We include phylogenetic and comparative approaches that test hypotheses about the generation and maintenance of biodiversity. The course takes an evolutionary approach to addressing these questions, primarily for plants and animals. Examples will largely be drawn from, but not limited to, Australian examples.ᅠ

Systematics and comparative and phylogenetic approaches form the basis of our understanding of ecology and evolution. "Species" are the primary units of biodiversity and ecological studies, and conservation legislation. This course will provide the knowledge of how species are defined and categorised by taxonomists, which is critical for fully understanding and interpreting ecological and biodiversity studies. The course places emphases on phylogenetic analysis and comparative analyses, which are critical in inferences of trait evolution and assumptions of ecological associations.

Course requirements

Assumed background

A general biology background with completion of second level subjects in zoology, plant science, evolution, genetics or ecology.

Recommended prerequisites

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

BIOL2201, BIOL2205 and/or BIOL2204

Course contact

Course staff

Lecturer

Tutor

Timetable

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

Additional timetable information

It is expected that students will attend all lectures and practicals in person. Lectures will not be routinely recorded, although small sections of the session might be. Practicals are not recorded.

Aims and outcomes

The major aims of this course are to:

• explain how biodiversity is discovered, named and classified, 

• assess patterns of bioversity at local and global scales,

• explore evolutionary processes that lead to diversification above and below the species level, and

• examine the role of modern biological collections in understanding biodiersity.

Learning outcomes

After successfully completing this course you should be able to:

LO1.

Use tools in the Spatial Portal of Atlas of Living Australia to address questions about biodiversity

LO2.

Obtain observation data and map species occurrences (in R)

LO3.

Construct maps of species richness (in R)

LO4.

estimate a phylogeny using DNA sequence data

LO5.

use DNA-barcoding to identify an unknown organism

LO6.

implement species distribution modelling (environmental niche modelling) using maxent

LO7.

interpret population genetic data

LO8.

explain the meaning of "systematics" and why it is important in understanding biodiversity

LO9.

demonstrate an understanding of biodiversity and diversification, and how these are reflected in present-day environments.

LO10.

explain how organisms are classified and how the different schools of classification differ

LO11.

critically evaluate inferences of phylogenetic relationships

LO12.

interpret a phylogeny in a biological context

LO13.

critically evaluate a taxonomic paper

LO14.

elucidate the importance of biodiversity to modern human society

LO15.

present the results of biodiversity and evolutionary studies orally

LO16.

explain the importance of biodiversity collections (museums and herbaria

LO17.

demonstrate an understanding of how organisms are named and the importance of type specimens

Assessment

Assessment summary

Category Assessment task Weight Due date
Paper/ Report/ Annotation, Essay/ Critique, Quiz, Reflection Weekly in-class quizzes for each learning module
  • Hurdle
  • Identity Verified
  • In-person
50%

1) Quiz 1 Week 1, Fri 9:00 am

2) Quiz 2 Week 2, Tue 12:00 pm

3) Quiz 3 Week 3, Fri 9:00 am

4) Quiz 4 Week 4, Fri 9:00 am

5) Quiz 5 Week 5, Fri 9:00 am

6) Quiz 6 Week 6, Tue 12:00 pm

7) Quiz 7 Week 7, Fri 9:00 am

8) Quiz 8 Week 8, Fri 9:00 am

9) Quiz 9 Week 9, Fri 9:00 am

10) Quiz 10 Week 10, Fri 9:00 am

11) Quiz 11 Week 11, Fri 9:00 am

12) Quiz 12 Week 12, Fri 9:00 am

13) Quiz 13 Week 13, Fri 9:00 am

In-person during class.

Paper/ Report/ Annotation Project applying practical skills 50%

29/05/2026 1:00 pm

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

Weekly in-class quizzes for each learning module

  • Hurdle
  • Identity Verified
  • In-person
Mode
Written
Category
Paper/ Report/ Annotation, Essay/ Critique, Quiz, Reflection
Weight
50%
Due date

1) Quiz 1 Week 1, Fri 9:00 am

2) Quiz 2 Week 2, Tue 12:00 pm

3) Quiz 3 Week 3, Fri 9:00 am

4) Quiz 4 Week 4, Fri 9:00 am

5) Quiz 5 Week 5, Fri 9:00 am

6) Quiz 6 Week 6, Tue 12:00 pm

7) Quiz 7 Week 7, Fri 9:00 am

8) Quiz 8 Week 8, Fri 9:00 am

9) Quiz 9 Week 9, Fri 9:00 am

10) Quiz 10 Week 10, Fri 9:00 am

11) Quiz 11 Week 11, Fri 9:00 am

12) Quiz 12 Week 12, Fri 9:00 am

13) Quiz 13 Week 13, Fri 9:00 am

In-person during class.

Other conditions
Time limited.

See the conditions definitions

Task description

Each week, there is required pre-class learning material (related to the topic for the week), which is to be completed before the lecture. During each lecture, there will be a quiz that focusses on the pre-class learning materials for that week and the activities undertaken in the current or previous week's lecture. There is no final exam and these quizzes form the major theory and content-based assessment.

"Quizzes" include quizzes, summations, writing assignments or critical thinking challenges based on the pre-class learning material and the previous and/or current week's lecture. The assessment is designed to assess understanding of assigned readings and the week's learning material, and to keep students on track for successfully incorporating biodiversity and systematics concepts. Quizzes are administered via Learn.UQ or via paper-copy during lectures. They are to be done in-person during class.

There are 13 quizzes but only the best 9 scores will be included in your final mark. Each will be equally weighted and averaged for your final score. This means you can miss several quizzes wthout needing a medical certificate, but if you miss more you should contact the course coordinator.

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.

Hurdle requirements

See Additional Course Grading Information for the hurdle information relating to this assessment item.

Submission guidelines

Submission is at the end of the quiz during class time.

Deferral or extension

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

Extensions are not available for this assessment as these quizzes are completed in class each week based on the topic of the week. The best 9 of 13 quiz scores count toward your final mark so you may miss some sessions if you are unable to attend, but if you miss more you should contact the course coordinator.

Late submission

You will receive a mark of 0 if this assessment is submitted late.

As this assessment is to be completed and submitted during class, late penalties apply if not submitted by the end of the allocated time. If unable to complete, the best 9 of 13 quizzes count toward the final grade allowing a small number of non-submissions.

Project applying practical skills

Mode
Written
Category
Paper/ Report/ Annotation
Weight
50%
Due date

29/05/2026 1:00 pm

Task description

New analytical skills are covered in practicals each week, related to the weekly topic. Using skills learned in practicals, students will design and implement analyses to address questions relating to those topics covered in the course. The topic for assessment will be randomly assigned from among those covered in class shortly before the due date. There may also be an identification quiz during one of the practicals.

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.

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 (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).

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: Fail: Falls short of satisfying all basic requirements for a Pass.ᅠWork of a very poor quality showing a very limited understanding of subject matter and a very low level of appreciation of issues covered in course content, including laboratory and field-based activities (as relevant to the course). The minimum percentage required for this grade is: 0%

2 (Fail)

Minimal evidence of achievement of course learning outcomes.

Course grade description: Fail: Falls short of satisfying all basic requirements for a Pass.ᅠWork of poor quality showing a very limited understanding of subject matter and a low level of appreciation of issues covered in course content, including laboratory and field-based activities (as relevant to the course). The minimum percentage required for this grade is: 30%

3 (Marginal Fail)

Demonstrated evidence of developing achievement of course learning outcomes

Course grade description: Fail: Falls short of satisfying all basic requirements for a Pass. The minimum percentage required for this grade is: 45%

4 (Pass)

Demonstrated evidence of functional achievement of course learning outcomes.

Course grade description: Work of fair quality demonstrating a basic understanding of most aspects of subject matter and a modest appreciation of issues covered in the course, including laboratory and field-based activities (as relevant to the course), but with serious deficiencies in some areas. The minimum percentage required for this grade is: 50%

5 (Credit)

Demonstrated evidence of proficient achievement of course learning outcomes.

Course grade description: Work of a good quality demonstrating a good understanding of most subject matter and a competent level of appreciation of issues covered ᅠthe course, including laboratory and field-based activities (as relevant to the course), although with some lapses and inadequacies.. The minimum percentage required for this grade is: 65%

6 (Distinction)

Demonstrated evidence of advanced achievement of course learning outcomes.

Course grade description: Work of a very good quality demonstrating a strong understanding of a wide, but not complete, range of subject matter and a good level of appreciation of issues, although not necessarily of the finer points, ᅠacross the course content and activities, including laboratory and field-based activities (as relevant to the course). The minimum percentage required for this grade is: 75%

7 (High Distinction)

Demonstrated evidence of exceptional achievement of course learning outcomes.

Course grade description: Work of exceptional quality showing a deep understanding of a wide range of subject matter and a clear appreciation of issues covered in across the course content and activities, including laboratory and field-based activities (as relevant to the course). 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 achieve a minimum of 50% for the combined quiz scores.

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

AI policy BIOL3209

Artificial Intelligence (AI) and Machine Translation (MT) are emerging tools that may support students in learning. We encourage students to use AI as a tool in this course but the assessment items need to be their own work.

In-class non-assessed activities

·      Students may appropriately use AI and/or MT in completing these activities.

Quizzes

·      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.

Practicals

·      AI can be used for checking and modifying R code and for providing explanations of terms and concepts.

Project

·      This task has been designed to be challenging, authentic and complex. Whilst students may use AI and/or MT technologies, successful completion of this assessment will require students to critically engage in specific contexts and tasks for which artificial intelligence will provide only limited support and guidance.

·      Students may appropriately use AI and/or MT in completing some of this assessment task.

·      Acceptable use: generating ideas and R code, and checking spelling, grammar and flow.

·      Not acceptable: generating data, images or text.

·      Students must clearly reference all uses of AI or MT in the acknowledgments section of their report.

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

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

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.

Additional learning resources information

Electronic notes and reading materials are provided for lectures and practicals.ᅠIt is preferrable that students bring a laptop or other smart device to activities.

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
Week 1

(23 Feb - 01 Mar)

Lecture

Introduction to biodiversity & systematics

Overview of course. What is biodiversity and why is it important. How does systematics underpin our understanding of biodiversity. The Linnaean system of naming and classification.
Lyn Cook

Practical

Biodiversity databases

Exploring the relationships between the Australian Faunal Directory, the Australian Plant Census, The Australian Virtual Herbarium, the Atlas of Living Australia (ALA) and the Global Biodiversity Information Facility (GBIF), and the roles of citizen science databases such as Questagame, iNaturalist and Birdlife Australia in contributing to biodiversity data.
Lyn Cook

Week 2

(02 Mar - 08 Mar)

Lecture

Importance of biodiversity collections, IUCN, Nagoya Protocol

Species as the basic units of biodiversity. What are the current estimates for the number of species on the planet, and how is species diversity estimated when there are so many unknowns.

Excursion

Optional visit to the QLD Herbarium 10 am

Species accumulation curves for estimating diversity. Dichotomous, multi-entry, computer vision & AI, and pictorial keys are used for identifying species.
Lyn Cook

Week 3

(09 Mar - 15 Mar)

Lecture

How many species are there? And Nomenclature

Where is biodiversity? Geographic structuring of biodiversity, such as the latitudinal gradient.
Lyn Cook

Practical

Estimating & identifying biodiversity—mapping species richness

Obtain occurrence data for a group of organisms and produce a species richness map. Determine biodiversity hotspots for the taxon.
Lyn Cook

Week 4

(16 Mar - 22 Mar)

Lecture

Species concepts & speciation

How species are named and described. The role of biodiversity collections (museums and Herbarium).
Lyn Cook

Excursion

Applying species concepts—Antechinus

Optional behind the scenes visit to the Queensland Herbarium. Meet with research scientists and see how specimens are stored and used at QLD's premier herbarium.
There is no in-class practical this week.

Week 5

(23 Mar - 29 Mar)

Lecture

Homology and classification

What are species? How do species form? Are species real?
Simone Blomberg

Practical

Classifications

Applying different approaches to delimit species of Antechinus: how does concept and method affect our interpretation of species boundaries.
Simone Blomberg

Week 6

(30 Mar - 05 Apr)

Workshop

TBA

Covers how classification systems have changed over time in Western civilisations. Is it necessary to have "scientific names" as a distinct system from indigenous naming and classification.
Simone Blomberg

No student involvement (Breaks, information)

Easter Friday

Testing classifications of real organisms
Simone Blomberg

Week 7

(13 Apr - 19 Apr)

Lecture

Comparative methods

Practical

Phylomorphospace and PGLS

Week 8

(20 Apr - 26 Apr)

Lecture

Cryptic species—distributions

Practical

SDM (ENM)

Week 9

(27 Apr - 03 May)

Lecture

Phylogeography and population genetics

Practical

Phylgoegraphy

Phylogeography examines the spatial distribution of diversity below the species level

Nigel Beebe

Week 10

(04 May - 10 May)

Lecture

Cryptic species—DNA barcoding

Practical

PCA, STRUCTURE, Popgen

Week 11

(11 May - 17 May)

Lecture

Identification

Practical

Work on project

Week 12

(18 May - 24 May)

Lecture

Australian biota and biogeography

Practical

Work on project

Week 13

(25 May - 31 May)

Lecture

Global patterns of biodiversity

Practical

Finalise and submit project

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.