Outline

Overview

This intensive field-based course provides practical experience in terrestrial ecology suited to a broad range of careers in ecology, environmental consulting and wildlife management. Students learn a broad range of ecological sampling techniques and develop a detailed understanding of the logical requirements necessary for manipulative ecological field experiments. The field work takes place in native forest and incorporates survey techniques for plants, small mammals and invertebrates and thus provides a good background for ecological consulting work and an introduction into large-scale project management. Students attend a week-long field course and participate in a large-scale research project as well as conducting their own research project. Emphasis is placed on critical thinking in the context of environmental management and technical skills are developed in the area of data handling and analysis, report writing and team work. Invited experts contribute to the lectures and discussions on issues relating to the ecology, conservation and management of Australia's terrestrial flora and fauna.

Unit details and rules

Academic unit	Life and Environmental Sciences Academic Operations
Credit points	6
Prerequisites ?	[12 credit points of BIOL2XXX] or [6 credit points of BIOL2XXX and (MBLG2X72 or GEGE2X01 or GENE2002)]
Corequisites ?	None
Prohibitions ?	BIOL3909 or BIOL2009 or BIOL2909
Assumed knowledge ?	Basic ecological concepts of species and communities, and experimental design and analysis
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Glenda Wardle, glenda.wardle@sydney.edu.au
Lecturer(s)	Clare McArthur, clare.mcarthur@sydney.edu.au
	Rosanne Quinnell, rosanne.quinnell@sydney.edu.au
	Peter Banks, peter.banks@sydney.edu.au
	Glenda Wardle, glenda.wardle@sydney.edu.au
	Thomas Newsome, thomas.newsome@sydney.edu.au
	Aaron Greenville, aaron.greenville@sydney.edu.au

Assessment

The census date for this unit availability is 8 August 2025

Details
Criteria

Type	Description	Weight	Due	Length	Use of AI
In-class quiz	Quiz Pen and paper test with 10 short answer questions	10%	Week 02 Due date: 01 Aug 2025 at 13:00 Closing date: 01 Aug 2025	30 minutes	AI allowed
Outcomes assessed:
Presentation	Sampling project presentation Presentation, held in class on field trip	10%	Week 02 Due date: 01 Aug 2025 at 13:00	5 minutes plus questions	AI allowed
Outcomes assessed:
Experimental design	Sampling project report Report - individual work, write up results from sampling project	20%	Week 05 Due date: 22 Aug 2025 at 23:59	3 pages plus figures, refs, abstract	AI allowed
Outcomes assessed:
Practical skill	Practical skills and data: field skills component -	4%	Week 06 Due date: 29 Aug 2025 at 23:59	-	AI allowed
Outcomes assessed:
Data analysis	Practical skills and data: Data collection, data entry and quality checks Practical skills assessment - ongoing until class data sets are complete	6%	Week 06 Due date: 29 Aug 2025 at 13:00	-	AI allowed
Outcomes assessed:
Experimental design	Major Dungog research report Report, individual work, write up field survey results from class data	50%	Week 09 Due date: 26 Sep 2025 at 23:59 Closing date: 31 Oct 2025	7500 words maximum	AI allowed
Outcomes assessed:

Assessment summary

Detailed information for each assessment can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2021 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name	Mark range	Description
High distinction	85 - 100	Awarded when you demonstrate the learning outcomes for the unit at an exceptional standard, as defined by grade descriptors or exemplars outlined by your faculty or school.
Distinction	75 - 84	Awarded when you demonstrate the learning outcomes for the unit at a very high standard, as defined by grade descriptors or exemplars outlined by your faculty or school.
Credit	65 - 74	Awarded when you demonstrate the learning outcomes for the unit at a good standard, as defined by grade descriptors or exemplars outlined by your faculty or school.
Pass	50 - 64	Awarded when you demonstrate the learning outcomes for the unit at an acceptable standard, as defined by grade descriptors or exemplars outlined by your faculty or school.
Fail	0 - 49	When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see guide to grades.

Use of generative artificial intelligence (AI)

You can use generative AI tools for open assessments. Restrictions on AI use apply to secure, supervised assessments used to confirm if students have met specific learning outcomes.

Refer to the assessment table above to see if AI is allowed, for assessments in this unit and check Canvas for full instructions on assessment tasks and AI use.

If you use AI, you must always acknowledge it. Misusing AI may lead to a breach of the Academic Integrity Policy.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

Deduction of 5% of the maximum mark for each calendar day after the due date.
After ten calendar days late, a mark of zero will be awarded.

Academic integrity

The University expects students to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

Our website provides information on academic integrity and the resources available to all students. This includes advice on how to avoid common breaches of academic integrity. Ensure that you have completed the Academic Honesty Education Module (AHEM) which is mandatory for all commencing coursework students

Penalties for serious breaches can significantly impact your studies and your career after graduation. It is important that you speak with your unit coordinator if you need help with completing assessments.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

Learning support

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

Support for students

The Support for Students Policy reflects the University’s commitment to supporting students in their academic journey and making the University safe for students. It is important that you read and understand this policy so that you are familiar with the range of support services available to you and understand how to engage with them.

The University uses email as its primary source of communication with students who need support under the Support for Students Policy. Make sure you check your University email regularly and respond to any communications received from the University.

Learning resources and detailed information about weekly assessment and learning activities can be accessed via Canvas. It is essential that you visit your unit of study Canvas site to ensure you are up to date with all of your tasks.

If you are having difficulties completing your studies, or are feeling unsure about your progress, we are here to help. You can access the support services offered by the University at any time:

Support and Services (including health and wellbeing services, financial support and learning support)
Course planning and administration
Meet with an Academic Adviser

Weekly schedule

WK	Topic	Learning activity
Pre-semester	Introductory lectures	Lecture (3 hr)
Week 02	Field trip: Wangat Lodge near Chichester Dam, past town Dungog, NSW	Field trip (60 hr)
Week 03	Practical	Practical (4 hr)
Week 04	Practical	Practical (4 hr)
Week 05	Practical	Practical (4 hr)
Week 06	Practical	Practical (4 hr)

Attendance and class requirements

Students are required to attend the field trip and the practical classes unless a prior arrangement has been made for clashes with other units of study.

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Required readings

No required text book.

A printed practical manual will be made available at the start of the Block teaching mode. This will contain all required reading. Additional reading lists will be made available to assist with report writing.

Students are required to attend the field trip and the practical classes unless a prior arrangement has been made for clashes with other units of study.

Learning outcomes

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

Outcomes
Graduate qualities

At the completion of this unit, you should be able to:

LO1. understand the scientific methods needed for field ecology
LO2. conduct ecological surveys of flora and fauna in forests
LO3. analyse and interpret ecological data sets
LO4. communicate scientific findings in reports and in oral presentations
LO5. work effectively in teams and contribute to complex tasks relevant to real world employment.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1	Depth of disciplinary expertise Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.
GQ2	Critical thinking and problem solving Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.
GQ3	Oral and written communication Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.
GQ4	Information and digital literacy Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.
GQ5	Inventiveness Generating novel ideas and solutions.
GQ6	Cultural competence Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.
GQ7	Interdisciplinary effectiveness Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.
GQ8	Integrated professional, ethical, and personal identity An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.
GQ9	Influence Engaging others in a process, idea or vision.

Outcome map

Learning outcomes	Graduate qualities
Learning outcomes

Responding to student feedback

This section outlines changes made to this unit following staff and student reviews.

Feedback from previous students has been highly positive for the unit. An extra lecture on sampling designs has been offered to assist students who lacked some of the assumed knowledge. We have also streamlined practical classes to provide more time to undertake the statistical analyses of data for students who have not taken the recommended classes to gain assumed knowledge in this area. Staff work individually with students to explain the statistical methods, where needed and recommend additional reading to deepen understanding of data management and analysis for ecological studies.

Additional information

The Expression Of Interest Form is located on this Canvas Page along with other relevant fieldwork information. Fieldwork Units in SOLES: School of Life and Environmental Sciences - Student Portal

Fieldwork Units in SOLES - Field trip dates, How to apply and EOI procedure

Additional costs

A fee $600 fee to cover accommodation, meals and travel for the field trip.

Site visit guidelines

• Detailed information about the risk assessments for the field trip will be available on Canvas site. • Q-fever: Completion of online zoonosis awareness module is mandatory, and all students also are recommended to have had Q-fever vaccination prior to attending this UoS.

Work, health and safety

Completion of the Canvas module “Zoonosis Awareness” is compulsory.

We are governed by the Work Health and Safety Act 2011, Work Health and Safety Regulation 2011 and Codes of Practice. Penalties for non-compliance have increased. Everyone has a responsibility for health and safety at work. The University’s Work Health and Safety policy explains the responsibilities and expectations of workers and others, and the procedures for managing WHS risks associated with University activities.
General laboratory safety rules

No eating or drinking is allowed in any laboratory under any circumstances
A laboratory coat and closed-toe shoes are mandatory
Follow safety instructions in your manual and posted in laboratories
In case of fire, follow instructions posted outside the laboratory door
First aid kits, eye wash and fire extinguishers are located in or immediately outside each laboratory
As a precautionary measure, it is recommended that you have a current tetanus immunisation. This can be obtained from University Health Service: unihealth.usyd.edu.au/

Field work risk assessments are made available prior to the field trip.

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Additional costs

Site visit guidelines

Work, health and safety

Disclaimer

On this page

Useful links

BIOL3009: Terrestrial Field Ecology

Intensive July - August, 2025 [Block mode] - Camperdown/Darlington, Sydney

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Additional costs

Site visit guidelines

Work, health and safety

Disclaimer

On this page

Useful links