IDEM 288

The Demography of Aging across the Tree of Life

From individual level data over comparative analyses to population modelling

Course coordinators:  Ralf Schaible and Alexander Scheuerlein

Start:   6 November 2013
End:   20 December 2013
Location:  MPI Rostock

Annette Baudisch
Hal Caswell
Fernando Colchero
Dalia Conde
Jutta Gampe
Owen Jones
Eelke Jongejans
Boris Kramer
Ralf Schaible
Alexander Scheuerlein
Meir Sussmann
James Vaupel

Course description:
Research on aging is currently receiving considerable attention with a multitude of studies on humans and model organisms. Much of the underlying rationale for these studies relies on the evolutionary theories developed in the 1950s, 60s and 70s. These theories predict that evolution will lead to monotonically increasing mortality rates and decreasing fertility rates after the age of maturity. Yet, a preliminary overview across species shows an astonishing diversity of patterns across multicellular organisms. The aim of the course is threefold:

1. Provide an overview of current research topics:
a. Research on non-humans informs the formulation of evolutionary theories of aging, which help us understand the dynamics of human demographic rates
b. Social insect models as a prime example of programmed short and extremely long lifespan
c. Current research in the laboratory: interesting models that cannot be observed in their natural environments
d. Comparative life history and scaling laws.

2.Introduce relevant databases (DATLife database, COMPADRE Plant Matrix database and COMADRE animal matrix database) and provide scholars with a toolbox comprising the necessary conceptual, mathematical and programming skills to perform comparative demographic analyses on

3. Demonstrate the viability of the scientific discipline “Comparative Demography”
a. Once we understand the evolution of demographic rates across the tree of life we infer demographic rates for data-deficient species.
b. This is essential for the imputation of Conservation measures and, in general, for population management.

This course will run for seven weeks with normally eight classroom hours every week.  During each week the classroom hours will be held on Wednesday afternoon (two hours; 15:00-17:00), Thursday morning (four hours; 9:00 – 13:00) and Friday morning (two hours; 11:00 – 13:00).  The classroom hours will consists of a mix of lectures and practical exercises.

Detailed schedule:
Week 1: Lecture week
Wed 6 Nov.:  James Vaupel: What we do not understand about the evolution of
aging: Current research questions
Thu 7 Nov.: Annette Baudisch: Adaptive and non-adaptive theories of aging: Background, criticisms, directions
Thu 7 Nov.:  Alexander Scheuerlein: DATLife database
Fri 8 Nov.: Alexander Scheuerlein: COMPADRE Plant matrix database and COMADRE Animal matrix database

Week 2: Lecture week
Wed 13 Nov.: Ralf Schaible: Current approaches to study aging in the laboratory
Thu 14 Nov.: Boris Kramer: Ant demography: long-lived queens and short-lived
Thu 14 Nov.: Meir Sussmann: Research on model species. Molecular basis on aging:      What has been found, how can it be used, what is still unknown.

Week 3: Lecture and exercises week
Lecturer-in-charge: Hal Caswell
Species introduction to matrix population models: From individual data to population modelling
Data required:
COMPADRE Plant matrix database and COMADRE Animal matrix database
Environmental variables
Wed 20 Nov.: Lecture (2 hours)
Thu 21 Nov.: Practical exercises (4 hours)
Fri 22 Nov.: Discussion of results (2 hours)

Week 4: Lecture and exercises week
Wed 27 Nov.: Dalia Conde: Applying comparative life history
Lecturer-in-charge (Thursday/Friday): Fernando Colchero
Bayesian methods in animal demography:
Individual based datasets with incomplete histories
Integrating growth and mortality data from mark-recapture studies
Data required:
individual-based mortality / growth data
Thu 28 Nov.: Lecture and practical exercises (4 hours)
Fri 29 Nov.: Practical exercises and discussion of results (4 hours)

Week 5: Lecture and exercises week
Lecturer-in-charge: Jutta Gampe
General survival analysis: Which methods to use if standard models fail?
Fitting models where proportional hazard assumption is not met.
Data required:
Individual  or population level data
Mortality / fertility data from DATLife
Wed 4 Dec.: Lecture (2 hours)
Thu 5 Dec.: Practical exercises (4 hours)
Fri 6 Dec.: Discussion of results (2 hours)

Week 6: Lecture and exercises week
Lecturer-in-charge: Eelke Jongejans
Integral population projection models
Use in forecasting / management / conservation
Data required:
Individual based mortality-fertility – growth data
Wed 11 Dec.: Lecture (2 hours)
Thu 12 Dec.: Practical exercises (4 hours)
Fri 13 Dec.: Discussion of results (2 hours)

Week 7: Lecture and exercises week
Lecturer-in-charge (Wednesday and Thursday): Owen Jones
Comparative analyses: Inference using standard and Bayesian methods
Phylogenetic informed analyses: Current hot topics and methods
Data required:
Mortality fertility data from DATLife; matrix data from COMPADRE Plant matrix database and COMADRE Animal matrix database
Data required:
Individual based mortality-fertility – growth data
Wed 18 Dec.: Lecture (2 hours)
Thu 19 Dec.: Practical exercises & discussion of results (4 hours)
Fri 20 Dec.: Discussion of results (2 hours)

Course prerequisite:
A basic knowledge of R is a course prerequisite.

An acceptable solution to all assignments and exercises serves as the examination for this course.

Reading materials will be provided during the course.

How to apply:
For application instructions please visit the applications page