Subject to approval of the Head of School.

BIOL471

Timetable Note

Each of the six seminars will run for two hours. Proposed topics are listed below.

Tutorial number and topic
0  Course orientation meeting                                              Tadeu (July 15)
1  Overview of community ecology and projects                     Tadeu (July 23)
2  Biodiversity: Key concepts, dimensions and theories           Julian (July 30)
3  Indirect facilitation                                                           Mads (August 06)
4  The role of environmental heterogeneity and complexity     Mads (August 13)
5  Traits-based community ecology                                       Julian (August 20)
6  Metacommunity ecology                                                   Tadeu (September 10)

Course Coordinator / Lecturer

Tadeu Siqueira

Lecturers

Mads Thomsen and Jonathan Tonkin

Guest Lecturer

Professor Julian Olden, visiting Erskine Fellow (University of Washington)

Assessment

Talking points - 10% (mandatory)
By 9 am the morning of each seminar, you must submit (via Learn) a brief critical assessment for each paper in the readings. At a minimum, this should be three points:  
• At least one strength.  
• At least one untested assumption or design flaw in the study that undermines the conclusions.  
• At least one new question that arises from their results.
During each seminar, you should ‘self-evaluate’ by comparing your own assessment to the assessment highlighted and discussed by the other students and the lecturer.

Project outline – 5%  
To ensure you think of a research project topic early and get early feedback, you will be required to submit an outline of your project by the end of the fourth week of the course.

Research project – 45%  
In science, a key skill is the ability to analyse a new dataset and write a research paper. The major in-term assessment is to analyse novel community data and write a scientific paper following the format of a Research article in Ecology (no more than ~5000 words in length, including tables, figure legends, abstract, and references). Several datasets are available to choose from - but different novel community data may alternatively (after consultation with the lecturers) be identified and analysed by motivated students. More details will be given in class and can be found on the course Learn page.

Examination - 40%
This will be a 24-hr take-home exam that will be submitted online. Date and time will be confirmed in consultation with the class. You will write a peer review of ONE out of three provided scientific papers, outlining the paper’s strengths and weaknesses.

Textbooks / Resources

Reference Material
There is no textbook for this course. You will be assigned a series of readings from the scientific literature. The readings will be listed on Learn by the lecturers at least one week before the seminar. Students are expected to have read the material and submit their Talking points sheets, and to be prepared to discuss the papers by the start of each seminar.

Course links

Learn Site
Course Outline

Notes

Feedback from 2019 course survey (62% response; 5 out of 8)
1. Materials provided helped me understand what was required to succeed in this course 3.4
2. The organisation of this course helped me learn 3.6
3. Workload was appropriate to the level of the course   3.8                                                
4. Assessments were appropriate for the course   3.2                                                          
5. Where I sought feedback on my assessments, I found it helpful  3.2                                  

The following issues were raised in written feedback by students as part of the course survey.

Positive features
- The two paper seminar format was good for critically analyzing and pulling apart papers.
- For the seminars I believe the workload was appropriate.

Negative features (Action/response indicated below)
- I would have appreciated a more detailed handout for the assignment.
o We have added information about the Research Project to the course handouts. We have also added information about the Research Project to both the Course orienteering meeting and the first seminar. Finally, we encourage students to setup meetings with the teachers to discuss specific issues related to their completion of the Research Project.
- Weekly having different tutors might be useful in undergraduate courses, however it felt disjointed for a post grad class, and I didn't feel a strong undercurrent/theme from the course due to this.
o Community ecology is a complex research field with a bewildering number of theories and frameworks and this level of complexity can be confusing and intimidating for new graduate students. We have changed the first class to focus on this topic to better prepare the student for what he/she will encounter in the course and future graduate studies.  We have also reduced the number of teachers from 4 to 3 to facilitate better student-teacher interactions. Finally, we now include discussions in the seminars about how the different topics link to each other.
- Would have appreciated just a sentence on each of the strengths and weakness weekly assignment, to inform on how my interpretation was going, doesn't have to be marked, but a tiny bit of feedback would have been appreciated.
o We discuss, in detail, strengths and weakness of research papers in the seminars and expect students to actively participate in the seminar. We therefore expect each student to cross-check her/his own comment with comments raised in the class discussion (i.e., we expect students to self-evaluate his/hers own comments and bring up, in class, issues related to lack of understanding). We also encourage students to take initiative and setup meetings with teachers for more specific evaluations of his/hers understanding of the seminar discussions.

The course is constantly being refined and updated, and students should see the benefits of this.  Note that basic skills in data analysis, data management, graphical data analysis, statistical tests, and usage of Excel and statistical software (like r) is expected. These skills are essential to complete the Research Project.

Indicative Fees

* All fees are inclusive of NZ GST or any equivalent overseas tax, and do not include any programme level discount or additional course-related expenses.