School > Planning and content

Contents of the school (program in preparation)

Active learning via practical exercises                        6.5 h

Theory (lectures)                                                      12.5 h

Research question formulation (group discussions)        3 h

Individual "Pet projects" working time                        10 h

Presenting results of individual projects                       4 h

Practical exercices (6.5 h)

Objective: Practice parameter estimation on simple mydata- files

These exercices will be used to provide Matlab and DEBtool training and basics in statistical and numerical methods for those who have an interest in it.

Lectures (12.5 h)

Information and content of the lectures will be published in the Moodle platform. The lectures will summarize the information learned in the tele-course, and then teach how to compose and entry, check the realisms of parameter values, as well as provide ecological background to how parameters are applied in practice for ongoing research projects. Future directions of the theory as well as its historical roots will be decribed.

Group discussions (3 h)

There will be 9 people per discussion group, and 4 discussion groups. Each participant of the practical course is invited to present their topic of research anf highlight how DEB theory will help addressing some of her/his reasearch questions. Each topic will be discussed for 15 min, 3 topics will be presented during a group discusison. The remaining 15 min will be used to address specific or general questions that participants have regarding DEB theory and the course content. 

Individual "AmP projects" (10 h)

Objective: Parameter estimation on the basis of your own mydata- file. Every person will be assisted by the team.

Several participants from DEB2019 and DEB2017 used the work performed in their project as a basis for work they subsequently published in the 2017 and 2019 Special issues on DEB theory.

 Tasks:

  • compose a predict_my_pet file for your pet
  • estimate parameters values using run_my_pet
  • compute over 100 implied properties of your pet
  • compare resulting parameters with those of other animal taxa

 Learning objectives:

 Assessment:

Pet presentation of main findings.

Pet presentations (4 h)

We ask successful participants to present their results briefly; experts giving comments. If time allows we will compare the parameter values and give a short presentation of the findings.

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