• Class Number 6495
  • Term Code 3370
  • Class Info
  • Unit Value 6 units
  • Mode of Delivery In Person
    • Dr Matthew Brookhouse
    • Dr Matthew Brookhouse
  • Class Dates
  • Class Start Date 20/11/2023
  • Class End Date 18/12/2023
  • Census Date 24/11/2023
  • Last Date to Enrol 24/11/2023
SELT Survey Results

Ecosystems worldwide are under stress. Recent global and local assessments of biodiversity have reported deterioration of ecosystems and species loss, leading to potentially irreversible changes from baseline conditions. In the face of the challenges presented by multiple degrading processes, measuring and monitoring ecosystems is as important as ever. Ecosystem change may be manifest in an array of ecosystem attributes expressed as changes in number or size, or presence of species, functions, or services within an ecosystem. Despite the array of changes ecosystems may express, ecologists call upon the same broad concepts when designing and implementing approaches to quantitatively assess change and difference. This course aims to introduce the concepts at the core of measurement and monitoring for detection of ecosystem change.

This course aims to build on quantitative modelling skills using approaches that underpin the bulk of ecological studies. The intent is to provide the next step (after pre-requisite introductory courses) for students in building competence in widely applicable field-survey, data-handling and statistical methods. The ultimate aims are to provide an essential quantitative skill set for future researchers, managers, consultants, analysts, and policy-makers alike.

The dizzying array of attributes that may change in ecosystems means that the course cannot meaningfully cover a substantial number if ecosystems, attributes, or processes. The intensive timeline of the course, and uncertain public-health landscape, means we cannot travel to remote sites. The course focusses on local case studies that offer the opportunity to explore the use of data experimental sites as well as native ecosystems. While these case studies may seem, at times, distant from the idealised landscapes ecologists work in, they embody the basic question types that ecologists seek to answer when monitoring ecosystems in an approachable setting. They also support integration of lecture, workshop and reading material. Individual sessions will focus on specific examples of measurement and the impact of instrument selection and use; experimental design and implicit consequences; common and advanced analysis techniques

Learning Outcomes

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

  1. Demonstrate advanced conceptual understanding of measurement and modelling approaches in ecological studies.
  2. Critically apply advanced concepts and methods of quantitative analysis in the context of environmental data, with special reference to experimental design and monitoring environmental dynamics and change.
  3. Effectively critique and communicate quantitative outputs and data collection/analysis strategies to a scientific/management community.

Research-Led Teaching

Students work closely with lecturers and support teaching staff and will engage in aspects of current research. Discussions allow students to integrate their understanding of the discipline with these current research advances and issues.

Field Trips

The course includes a number local area field trips. Please refer to the course Wattle site for further information.

For more information, please see the College of Science – Field trip page .

Additional Course Costs

There are no additional costs or resources required beyond those routinely required by coursework students. Students will be expected to provide their own food and drink throughout the intensive sessions.

Examination Material or equipment

This course does not include a formal examination.

Required Resources

Enclosed walking shoes/boots, and clothing appropriate to likely cold, damp and windy weather conditions. Field sessions will comprise half and full-day activities over in both weeks. Students should bring sufficient food and water, and necessary medications to support a full-day's work. The course will require ongoing engagement throughout the scheduled teaching sessions. Students will be expected to allocate sufficient time resources to learning activities between 9:00 a.m. and 5:00 p.m. each day.

Students are strongly encouraged to bring personal laptops. Downloadable versions of JMP will be made available. Students will be asked to respond to questions live

during the course using smart phones or laptops. A small number of Surface computers will be made available for students who do not have their own.

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. Mobile devices may work well but in some situations a computer/laptop may be more appropriate.
  • 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:

  1. Computer-based feedback on quizzes and practical assessment pieces
  2. Written feedback on the major assessment

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). Feedback can also be provided to Course Conveners and teachers via the Student Experience of Learning & Teaching (SELT) feedback program. SELT surveys are confidential and also provide the Colleges and ANU Executive with opportunities to recognise excellent teaching, and opportunities for improvement.

Other Information

Students are asked to submit any assessment extension requests for this course via the School's application.

Class Schedule

Week/Session Summary of Activities Assessment
1 Week 1; Monday
  • Course introduction
  • Principles of measurement and monitoring
  • Normality and transformation 
  • Linear effects model (univariate ANOVA)

Required independent learning
  • Refresher on t and p
  • The first day of the course comprises an introduction to the course structure as well as our expectations around engagement. Subsequent theory sessions will comprise mixed theory and practice. Students will need to make use of Microsoft Excel and JMP throughout the day. Support for downloading and installing JMP will be available during the first part of the day.
2 Week 1; Tuesday
  • Monitoring a controlled field experiment (Sparrow Hill)
  • Involves a full day of fieldwork in Sparrow Hill pine plantation. Students must be appropriately dressed and have food/water for a full day of measurement. Students may travel to the site in personal or ANU vehicles. Travel on-site will be strictly restricted to ANU vehicles only.
3 Week 1; Wednesday
  • Nested models
  • Factorial models
  • Sessions will comprise mixed theory and practice. Students will need to make use of Microsoft Excel and JMP throughout the day.
4 Week 1; Thursday
  • General linear modelling
  • Interpreting regression
  • Sessions will comprise mixed theory and practice. Students will need to make use of Microsoft Excel and JMP throughout the day.
5 Week 1; Friday
  • Transformation and influence
  • Curvilinear regression
  • Multivariate regression

Required independent learning
  • Allometry               
  • Sessions will comprise mixed theory and practice. Students will need to make use of Microsoft Excel and JMP throughout the day.
6 Week 2; Monday
  • GLMs and logistic regression
  • Model selection and validation

Required independent learning
  • Ecosystem structure and complexity
  • Sessions will comprise mixed theory and practice. Students will need to make use of Microsoft Excel and JMP throughout the day.
7 Week 2; Tuesday
  • Fundamentals of plant morphology and identification
  • Sessions will comprise mixed theory and practice, including sessions in a laboratory setting and outdoors on campus.
8 Week 2; Wednesday
  • Eucalypt identification
  • Sessions will comprise mixed theory and practice. Students will need to make use of Microsoft Excel and JMP throughout the day.
9 Week 2; Thursday
  • Species presence fieldwork
  • After a short briefing, sessions will partially comprise field-based activities in Black Mountain Nature Reserve. Students must be appropriately dressed and have food/water for a full day.
10 Week 2; Friday
  • Two-step modelling
  • Species presence and abundance modelling
  • Sessions will comprise mixed theory and practice. Students will need to make use of Microsoft Excel and JMP throughout the day.

Tutorial Registration


Assessment Summary

Assessment task Value Due Date Return of assessment Learning Outcomes
Experimental-effects model 20 % 23/11/2023 25/11/2023 1,2
Validated allometric model 30 % 30/11/2023 01/12/2023 1,2
Species-presence modelling 50 % 08/12/2023 16/12/2023 1,2,3

* 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 Integrity 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 Academic Skills website. In rare cases where online submission using Turnitin software is not technically possible; or where not using Turnitin software has been justified by the Course Convener and approved by the Associate Dean (Education) on the basis of the teaching model being employed; students shall submit assessment online via ‘Wattle’ outside of Turnitin, or failing that in hard copy, or through a combination of submission methods as approved by the Associate Dean (Education). The submission method is detailed below.

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 intensive nature of this course assumes an ongoing and consistent commitment to learning activities during the teaching period. Face-to-face learning activities are scheduled during 9:30am to 2:30pm each day of the course. Students are reasonably expected to attend during these hours. Meaningful engagement in measurement activities is required for all students and will be actively assessed.


This course does not include an examination.

Assessment Task 1

Value: 20 %
Due Date: 23/11/2023
Return of Assessment: 25/11/2023
Learning Outcomes: 1,2

Experimental-effects model

Maximum 500-word report outlining a proposed model for estimation of treatment and environmental effects within a field-based experimental setting.

Assessment Task 2

Value: 30 %
Due Date: 30/11/2023
Return of Assessment: 01/12/2023
Learning Outcomes: 1,2

Validated allometric model

Maximum 800-word report outlining a proposed and validated model aimed at volume/mass modelling.

Assessment Task 3

Value: 50 %
Due Date: 08/12/2023
Return of Assessment: 16/12/2023
Learning Outcomes: 1,2,3

Species-presence modelling

A 2500-word consultancy report written for government clients aimed at establishing models of Ogmograptis moth galleries.

Academic Integrity

Academic integrity is a core part of the ANU culture as a community of scholars. The University’s students are an integral part of that community. The academic integrity principle commits all students to engage in academic work in ways that are consistent with, and actively support, academic integrity, and to uphold this commitment by behaving honestly, responsibly and ethically, and with respect and fairness, in scholarly practice.

The University expects all staff and students to be familiar with the academic integrity principle, the Academic Integrity Rule 2021, the Policy: Student Academic Integrity and Procedure: Student Academic Integrity, and to uphold high standards of academic integrity to ensure the quality and value of our qualifications.

The Academic Integrity Rule 2021 is a legal document that the University uses to promote academic integrity, and manage breaches of the academic integrity principle. The Policy and Procedure support the Rule by outlining overarching principles, responsibilities and processes. The Academic Integrity Rule 2021 commences on 1 December 2021 and applies to courses commencing on or after that date, as well as to research conduct occurring on or after that date. Prior to this, the Academic Misconduct Rule 2015 applies.


The University commits to assisting all students to understand how to engage in academic work in ways that are consistent with, and actively support academic integrity. All coursework students must complete the online Academic Integrity Module (Epigeum), and Higher Degree Research (HDR) students are required to complete research integrity training. The Academic Integrity website provides information about services available to assist students with their assignments, examinations and other learning activities, as well as understanding and upholding academic integrity.

Online Submission

Assignments are submitted using Turnitin in the course Wattle site. You will be required to electronically sign a declaration as part of the submission of your assignment. Please keep a copy of the assignment for your records.

Hardcopy Submission

Nil expected.

Late Submission

Late submission of assessment tasks without an extension are penalised at the rate of 5% of the possible marks available per working day or part thereof. Late submission of assessment tasks is not accepted after 10 working days after the due date, or on or after the date specified in the course outline for the return of the assessment item. Late submission is not accepted for take-home examinations.

Referencing Requirements

The Academic Skills website has information to assist you with your writing and assessments. The website includes information about Academic Integrity including referencing requirements for different disciplines. There is also information on Plagiarism and different ways to use source material.

Returning Assignments

Final report and comments will be returned after the relevant Fenner School Examination processes have been completed.

Extensions and Penalties

Extensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure. Extensions may be granted 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 proposed.

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 Matthew Brookhouse
6125 2745

Research Interests

Forest dynamics, plant ecophysiology, sub-alpine ecology, dendrochronology, stable isotopic methods, plant culture

Dr Matthew Brookhouse

By Appointment
Dr Matthew Brookhouse
6125 2745

Research Interests

Dr Matthew Brookhouse

By Appointment

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