• Class Number 3035
  • Term Code 3330
  • Class Info
  • Unit Value 6 units
  • Mode of Delivery In Person
    • Dr Sasha Mikheyev
    • Prof Adrienne Nicotra
  • Class Dates
  • Class Start Date 20/02/2023
  • Class End Date 26/05/2023
  • Census Date 31/03/2023
  • Last Date to Enrol 27/02/2023
SELT Survey Results

Why do plants and animals occur where they do? Why these specific plants and animals, in these combinations and abundances? What will happen to them in the future? These are the big questions ecology addresses.


This course will focus on quantifying how interactions between individuals and their environment shape populations, and how populations of one species are, in turn, affected by other species. The core principles governing ecological interactions are universal, applying at scales ranging from the microscopic (e.g., bacteria and viruses) to those of ecosystems surrounding us. They play out over timescales ranging from minutes to millions of years. They apply to both natural and managed environments. By understanding and quantifying ecological interaction we can make models describing the past and predicting what will happen in the future. This way of thinking is particularly valuable today, as human behaviour drives the ecology around us, and we need to forecast the consequences of our actions.


This course will take a hands-on data-driven approach, with field trips, workshops and discussions focused on illustrating key ecological concepts. We will leverage the power of the R programming language to visualise data, whether empirical, or simulated by our mathematical models. One course highlight is a three-day field trip to the Kioloa Coastal Campus, that will allow you to design, carry out and analyse a small ecological study..

Note: Graduate students attend joint classes with undergraduates but are assessed separately.

Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

  1. Examine and summarise central ideas underpinning the ecology of individuals, populations, communities and/or ecosystems;
  2. Integrate ecological understanding of processes operating across multiple scales of space and time;
  3. Understand how observation, experimentation and modelling can be used to generate and test ecological hypotheses;
  4. Think critically about scientific evidence to understand ecological patterns and processes;
  5. Conduct basic ecological research, analyse ecological data using graphical, tabular and quantitative analysis, including an introduction to the R statistical programming language; and communicate the findings;
  6. Use the R statistical programming language to organise and visualise data in order to discover and describe ecological patterns, as well as to formulate and test hypotheses.
  7. Work as a research team and provide effective peer support;
  8. Synthesise understanding of ecological methods and data analysis, and represent this in a standard report format;
  9. Building evidence-based arguments in a report for how populations, communities and/or ecosystems might respond to differences in their biological and physical environments.

Research-Led Teaching

This course will connect a general background in ecology across the animal and plant sciences, reflecting the focus of each instructor. Principles and ideas will integrate across disciplines, whilst providing depth in areas that span from population ecology to ecosystem-level processes. The course will also be informed by current research into microbial ecology, forest ecology, plant functional ecology and animal ecology. Students will be encouraged to learn new measurements and analysis methods in both field and laboratory settings.

Field Trips

There will be two field trips. The first is an overnight field trip (17-19 March 2023), which will be based at the at Kosciuszko National Park. We will use the field trip to provide a hands-on illustration of how communities function and to conduct a short-term field experiment, which will be an assessable part of the course. Details of this part of the course are provided in the documentation and lectures at the start of the course in February. The second field trip on (21 April), will be local and conducted during the regularly scheduled hours on Friday. It will focus on using humans to estimate population parameters and will also result in an assessable writeup. Please note that these field trip may be altered depending on public health circumstances at the time and on university guidance.

Please see the trip information page for more information.

Additional Course Costs

Please see field trip cost ($250).

Examination Material or equipment

Please see above (required resources)

Required Resources

Additional course costs: field trip contribution - see above.

Recommended Resources

Lecture handouts will be periodically uploaded to WATTLE (https://wattle.anu.edu.au/). Please bring an electronic copy or your own hard copy printout to the relevant lecture if you need one, as hardcopies will not be provided. General course information, assignment information sheets, and tutorial instruction sheets will also be available on WATTLE ahead of the scheduled time for that activity. Key readings will tend to focus on individual research papers or reviews. We also suggest the general background text in ecology listed below. However, we emphasise the importance of using the readings provided by the lecturers, many of which may be more up-to-date or more focussed for your studies.

‘Quantitative Ecology: A New Unified Approach’ (2019), Clarence Lehman, Shelby Loberg, Adam Clark. Available at: http://hdl.handle.net/11299/204551


You may also like to try these resources for high-quality information:

Literature searches

ANU Library http://libguides.anu.edu.au/content.php?pid=405919&sid=3467071

ISI Web of Knowledge  http://www.isiwebofknowledge.com/

Google Scholar http://scholar.google.com.au

Scopus http://www.scopus.com/

Please see above (required resources)

Recommended student system requirements 

ANU courses commonly use a number of online resources and activities including:

  • video material, similar to YouTube, for lectures and other instruction
  • two-way video conferencing for interactive learning
  • email and other messaging tools for communication
  • interactive web apps for formative and collaborative activities
  • print and photo/scan for handwritten work
  • home-based assessment.

To fully participate in ANU learning, students need:

  • A computer or laptop.
  • Webcam
  • Speakers and a microphone (e.g. headset)
  • Reliable, stable internet connection. Broadband recommended. If using a mobile network or wi-fi then check performance is adequate.
  • Suitable location with minimal interruptions and adequate privacy for classes and assessments.
  • Printing, and photo/scanning equipment

For more information please see https://www.anu.edu.au/students/systems/recommended-student-system-requirements

Staff Feedback

Students will be given feedback in the following forms in this course:
  • Written comments
  • Verbal comments
  • Feedback to the whole class, to groups, to individuals, focus groups

Student Feedback

ANU is committed to the demonstration of educational excellence and regularly seeks feedback from students. Students are encouraged to offer feedback directly to their Course Convener or through their College and Course representatives (if applicable). The feedback given in these surveys is anonymous and provides the Colleges, University Education Committee and Academic Board with opportunities to recognise excellent teaching, and opportunities for improvement. The Surveys and Evaluation website provides more information on student surveys at ANU and reports on the feedback provided on ANU courses.

Other Information

This class is held in tandem with BIOL2131; the student groups are combined, which leads to gains for both groups.

Class Schedule

Week/Session Summary of Activities Assessment
1 Ecological data visualisation Assignment 1
2 Single population models Assignment 2
3 Human population growth Assignment 3
4 Community assembly and species interactions I Assignment 4, Field course 17-19 March
5 Community assembly and species interactions II Assignment 5
6 Age-structured populations I Assignment 6
7 Age-structured populations II
8 Predators and prey Assignment 7
9 Humans as predators Assignment 8
10 Competition and mutualism Assignment 9
11 Theory of disease Assignment 10
12 Ecology and conservation Assignment 11

Tutorial Registration

ANU utilises MyTimetable to enable students to view the timetable for their enrolled courses, browse, then self-allocate to small teaching activities / tutorials so they can better plan their time. Find out more on the Timetable webpage.

Assessment Summary

Assessment task Value
Weekly assignments 80 %
Scientific report 20 %

* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details


ANU has educational policies, procedures and guidelines, which are designed to ensure that staff and students are aware of the University’s academic standards, and implement them. Students are expected to have read the Academic Misconduct Rule before the commencement of their course. Other key policies and guidelines include:

Assessment Requirements

The ANU is using Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. For additional information regarding Turnitin please visit the ANU Online website Students may choose not to submit assessment items through Turnitin. In this instance you will be required to submit, alongside the assessment item itself, hard copies of all references included in the assessment item.

Moderation of Assessment

Marks that are allocated during Semester are to be considered provisional until formalised by the College examiners meeting at the end of each Semester. If appropriate, some moderation of marks might be applied prior to final results being released.


The field trips (or their replacement) and the practicals are all compulsory; they are not repeated.

Full attendance at the lectures and workshops is strongly recommended to enhance understanding and intellectual synthesis.


There will be no examinations.

Assessment Task 1

Value: 80 %
Learning Outcomes: 

Weekly assignments

Fridays will be dedicated to a hands-on exploration of ecology, which will take the form of field trips, lab exercises, data analysis and discussion. Almost all of these will have associated write-ups or problem sets, which will be explained in detail during the exercises. Except around the semester break, assignments will be due the following Monday, at 17:00, with the expectation that they will be graded the next day and discussed during the subsequent lecture. Late submissions will not be accepted, though the lowest score of the 11 assignments will be dropped prior to computing the final course grade. As a result, each assignment will be worth 8% of the overall course grade.


The goal of the practical sessions will be to develop skills in data analysis and interpretation. All of the course material will be accessible to students who are unable to attend the practical sessions. However, there is no real substitute for the hands-on components, particularly when it comes to asking questions and receiving immediate feedback from the teaching staff. As a result, students are strongly encouraged to attend in person.


The structure of the assignments will be as follows, though changes may be made with at least two-week advance notice to students. Detailed rubrics for each assignment will be provided alongside each assignment in class.

Assignments 1-3, 8-11:

These will be individual assignments aimed at applying course material and analysing data to make inferences about underlying ecological processes. They will take the form of quantitative exercises, such as ecological modelling and data visualisation, and short-answer questions critically evaluating the results. Content for these assessments will be drawn from the lectures, workshop and textbook.

Assignment 4:

Students will individually submit reflective answers to a set of questions based on an elevational gradient walk in Kosciuszko National Park, integrating personal experiences in the context of the theory covered in class. People who do not attend the field trip will need to do the reflections as well, based on the lecture materials and readings. 

Assignment 5:

Up to a 1000-word report summarising research objectives, hypotheses, results and inferences from the experiment carried out during the Kosciuszko National Park field trip.

Assignment 6:

Working in groups of 4 to 5, you will prepare up to a 1,000-word research proposal outlining your hypotheses, goals and sampling strategy for a field trip to the Queanbeyan Riverside Cemetery. The goal of the project will be to compare human demographic trends across two or more categories chosen by the students.

Assignment 7:

Working in the same groups as for Assignment 6, students will write a 1,000-word report (50% of the assignment 7 grade) and make a seven-minute video presenting the data (another 50%).

Assessment Task 2

Value: 20 %
Learning Outcomes: 

Scientific report

The goal of this assignment is to bring together the knowledge you have built in the course and related practicals so that you begin to synthesise across different areas of enquiry. Your goal will be to conduct a data-driven quantitative analysis of an ecological topic using data sourced from public repositories, such as datasets associated with scientific papers, deposited in repositories or published by governments of non-governmental organizations. You will be expected to present an analysis conducted in R, using skills developed during the course, using figures to support your argument, and providing code necessary to reproduce your analysis.

Choice of topic and proposal

You will be able to pick a topic of your choice and investigate it further, based on the knowledge you have acquired during this course. To help you choose a topic that’s appropriate in scope, you are required to submit a proposal beforehand to Prof. Mikheyev (no later than the first lecture after the semester break). The proposal should be no longer than 250 words and outline the topic you would like to investigate. It should include the following elements:

·     A specific scientific objective that you would like to explore

·     A brief survey of the literature on the topic to frame your investigation

·     What hypotheses will you test? What are the predictions?

·     Make sure to explain any data sets that you plan to use

Rubric (10 points for each item, except Discussion, which is worth 20)

Objective: Clearly stated, and specific.

Hypotheses: Hypotheses and their predictions are logical, testable and non-trivial.

Report organization: Properly organized, with correctly cited figures and citations.

Data display: Figures are aesthetically rendered and the plot type is appropriate to the data. Figures directly address the hypotheses.

Sampling considerations: Sample size adequate to test the hypotheses. Without statistics, this is somewhat subjective, but a verbal argument should be made as to the sufficiency.

Methods: Is the R code available, reproducible and easy to read? Are the data sufficiently described vis-à-vis the hypotheses being tested?

Results: Present the results in the text of the results without interpretations (those go into the Discussion). Are the results specific? Do they test they hypotheses and correspond to the stated methods?

Discussion: Are the conclusions based solely on the data and supported by the results? Are limitations of the analysis acknowledged? Does the discussion suggest further angles for investigation? (20 pts)

Writing: Is the report grammatically correct? Is it written in a succinct technical style?

Academic Integrity

Academic integrity is a core part of our culture as a community of scholars. At its heart, academic integrity is about behaving ethically. This means that all members of the community commit to honest and responsible scholarly practice and to upholding these values with respect and fairness. The Australian National University commits to embedding the values of academic integrity in our teaching and learning. We ensure that all members of our community understand how to engage in academic work in ways that are consistent with, and actively support academic integrity. The ANU expects staff and students to uphold high standards of academic integrity and act ethically and honestly, to ensure the quality and value of the qualification that you will graduate with. The University has policies and procedures in place to promote academic integrity and manage academic misconduct. Visit the following Academic honesty & plagiarism website for more information about academic integrity and what the ANU considers academic misconduct. The ANU offers a number of services to assist students with their assignments, examinations, and other learning activities. The Academic Skills and Learning Centre offers a number of workshops and seminars that you may find useful for your studies.

Online Submission

The ANU uses Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. While the use of Turnitin is not mandatory, the ANU highly recommends Turnitin is used by both teaching staff and students. For additional information regarding Turnitin please visit the ANU Online website.

Hardcopy Submission

For some forms of assessment (hand written assignments, art works, laboratory notes, etc.) hard copy submission is appropriate when approved by the Associate Dean (Education). Hard copy submissions must utilise the Assignment Cover Sheet. Please keep a copy of tasks completed for your records.

Late Submission

As the assessment tasks will be graded and discussed the week they are due, no late submissions will be accepted. However, the lowest assessment grade will be dropped.

Referencing Requirements

Accepted academic practice for referencing sources that you use in presentations can be found via the links on the Wattle site, under the file named “ANU and College Policies, Program Information, Student Support Services and Assessment”. Alternatively, you can seek help through the Students Learning Development website.

Returning Assignments

All student work is to be returned via Turnitin, unless you are informed otherwise: this information will be provided through Wattle and/or verbally to the class.

Extensions and Penalties

Extensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure The Course Convener may grant extensions for assessment pieces that are not examinations or take-home examinations. If you need an extension, you must request an extension in writing on or before the due date. If you have documented and appropriate medical evidence that demonstrates you were not able to request an extension on or before the due date, you may be able to request it after the due date.

Resubmission of Assignments

Resubmission of assignments is not accepted

Privacy Notice

The ANU has made a number of third party, online, databases available for students to use. Use of each online database is conditional on student end users first agreeing to the database licensor’s terms of service and/or privacy policy. Students should read these carefully. In some cases student end users will be required to register an account with the database licensor and submit personal information, including their: first name; last name; ANU email address; and other information. In cases where student end users are asked to submit ‘content’ to a database, such as an assignment or short answers, the database licensor may only use the student’s ‘content’ in accordance with the terms of service — including any (copyright) licence the student grants to the database licensor. Any personal information or content a student submits may be stored by the licensor, potentially offshore, and will be used to process the database service in accordance with the licensors terms of service and/or privacy policy. If any student chooses not to agree to the database licensor’s terms of service or privacy policy, the student will not be able to access and use the database. In these circumstances students should contact their lecturer to enquire about alternative arrangements that are available.

Distribution of grades policy

Academic Quality Assurance Committee monitors the performance of students, including attrition, further study and employment rates and grade distribution, and College reports on quality assurance processes for assessment activities, including alignment with national and international disciplinary and interdisciplinary standards, as well as qualification type learning outcomes. Since first semester 1994, ANU uses a grading scale for all courses. This grading scale is used by all academic areas of the University.

Support for students

The University offers students support through several different services. You may contact the services listed below directly or seek advice from your Course Convener, Student Administrators, or your College and Course representatives (if applicable).
Dr Sasha Mikheyev

Research Interests

Understanding how organisms coevolve, particularly focusing on the interaction of hosts with parasites and diseases and also with beneficial microbes.

Dr Sasha Mikheyev

By Appointment
Prof Adrienne Nicotra

Research Interests

Prof Adrienne Nicotra

Responsible Officer: Registrar, Student Administration / Page Contact: Website Administrator / Frequently Asked Questions