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Contents of the school (download program)

Active learning via practical exercises                         6.5h

Theory (lectures)                                                         12.5h

Research question formulation (group discussions)   3h

Individual "Pet projects" working time                         10h

Presenting results of individual projects                       4h

Practical exercices (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 (3h)

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" (11.5 h)

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

 Several participants from DEB2017 used the work performed in their project as a basis for work they subsequently published in the DEB2017 Special issue 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:

•  Create user defined predictions for length, weight, reproduction and/or respiration data with the help of the DEBwiki, DEBtool and AmP websites
• Control parameter estimation by setting options in run_my_pet and/or setting weight coefficients in mydata_my_pet
• Saving results and choosing starting values for parameter estimation by setting options in run_my_pet
• Computing goodness of fit
• Discussing goodness of fit in (biological) context
• Know how to use the AmP ecology module

 Assessment:

 Pet presentation of main findings.

Pet presentations (4h)

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.