This is an intensive course offered on an annual basis. The course will be delivered from 19 - 30 June 2017.
Ecosystems worldwide are under stress. Global and local assessments of biodiversity continue to report deteriorating ecosystems and species loss. Measuring, monitoring and modelling these changes, as well as designing and analysing experiments aimed at testing potential management actions are central to restoration and conservation responses. Despite the array of attributes ecosystems express, the same broad concepts are consistently called upon when quantitatively expressing change and difference. This course aims to introduce the concepts that underpin quantitative modelling relevant to understanding organismal and ecosystem response and difference. Specifically, this course aims to build on quantitative modelling skills using approaches that underpin the vast majority of ecological studies with an emphasis upon general linear models integrating complex ANOVA and univariate and multivariate least-squares regression, and generalised linear modelling. 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, delivering an essential skill set for ecology- and environment-based professionals. The partial field focus of the course, and it’s contextual emphasis on vegetated ecosystems, also necessitates the development of field botany skills. We introduce basic concepts associated with the description of floral and leaf forms and their application to consistently differentiating plant families, genera and species with particular emphasis on eucalypt identification.
Learning Outcomes
Upon successful completion, students will have the knowledge and skills to:
- Demonstrate advanced conceptual understanding and ability in, measurement of ecological attributes.
- Apply understanding of advanced quantitative-analysis concepts and methods in the context of environmental, ecological and experimental data.
- Effectively communicate process and outcomes of quantitative modelling.
- Demonstrate familiarity with, and skill in, botanical traits and use of dichotomous keys for plant identification.
- Exhibit an appreciation for, and demonstrated capacity in, delivering timely data sets consistent with required measurement/ monitoring protocols
Work Integrated Learning
Fieldwork
Students may engage with WIL partners (internal/external) as a component of the course
Other Information
The course includes a number local area field trips. Please refer to the course site in the Learning Management System for further information.
Indicative Assessment
- Complex ANOVA linear model (report) (20) [LO 1,2,3,4]
- Multivariate regression model (report) (20) [LO 1,2]
- Logistic regression model (oral presentation) (30) [LO 1,2,3,5]
- Plant identification practical examination (20) [LO 1,4]
- Data delivery (10) [LO 1,5]
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.
Workload
The expected workload will consist of approximately 130 hours throughout the session including:
- Face-to face component consisting of 70 hours of contact delivered intensively over 2 weeks comprising: daily workshops and other activities such as lectures, practicals and field-trips.
- Approximately 60 hours of self directed study which will include preparation for lectures, presentations and other assessment tasks.
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 expected to attend during these hours. Meaningful engagement in measurement activities is required for all students and will be actively assessed.
Inherent Requirements
This course includes field-based activities.
For more information on field trips please visit: https://students.science.anu.edu.au/program-admin/college-science-field-trips
Requisite and Incompatibility
Prescribed Texts
Not applicable
Assumed Knowledge
ENVS1004 Australia's Environment or EMSC1006 The Blue Planet is strongly recommended.
Fees
Tuition fees are for the academic year indicated at the top of the page.
Commonwealth Support (CSP) Students
If you have been offered a Commonwealth supported place, your fees are set by the Australian Government for each course. At ANU 1 EFTSL is 48 units (normally 8 x 6-unit courses). More information about your student contribution amount for each course at Fees.
- Student Contribution Band:
- 2
- Unit value:
- 6 units
If you are a domestic graduate coursework student with a Domestic Tuition Fee (DTF) place or international student you will be required to pay course tuition fees (see below). Course tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.
Where there is a unit range displayed for this course, not all unit options below may be available.
| Units | EFTSL |
|---|---|
| 6.00 | 0.12500 |
Course fees
- Domestic fee paying students
| Year | Fee |
|---|---|
| 2025 | $4980 |
- International fee paying students
| Year | Fee |
|---|---|
| 2025 | $6720 |
Offerings, Dates and Class Summary Links
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.
Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.
Spring Session
| Class number | Class start date | Last day to enrol | Census date | Class end date | Mode Of Delivery | Class Summary |
|---|---|---|---|---|---|---|
| 9382 | 17 Nov 2025 | 21 Nov 2025 | 21 Nov 2025 | 28 Nov 2025 | In Person | N/A |