MB5340 - Ecological Dynamics: Modelling With Data

[Offered in even-numbered years]

Credit points:	03
Year:	2006
Student Contribution Band:	Band 2
Administered by:

Available to GDipResMeth, GCertResMeth, GDipSc, MAppSc, MSc and PhD students.

This subject examines contemporary techniques for confronting process-based ecological models with data, with a focus on population models. Topics covered include the role of models in the scientific method; stochastic ecological processes and the distributions they generate; fitting models to data; and selecting between competing models. Model fitting and model selection will introduce a diversity of contemporary approaches such as bootstrapping, likelihood, and Bayesian methods. Much of the material will be introduced by examination of case studies from marine, terrestrial, and freshwater systems. Students will be assumed to have some experience with basic calculus, statistics, and population modelling.

Learning Outcomes

• To understand different views of the role of models in ecology, from the perspective of alternative philosophies of science;
• To learn how to fit ecological models to empirical data, using a variety of tools;
• To understand and quantify bias and uncertainty in parameter estimates using a variety of methods, and to incorporate these into model predictions;
• To understand the philosophy and assumptions behind different model selection methods;
• To understand how to inform ecological inferences and management decisions by confronting process- based models with data.

Prerequisites:

MA1000, BS2001, MB3260 or equivalent subjects.

Availabilities
, , Study Period 3
Census Date 27-Jan-2006
Face to face teaching 30-Jan-2006 to 10-Feb-2006
Coord/Lect:	Professor Sean Connolly.
Assessment:	(35%); (65%).
Restrictions:	An enrolment quota applies to this offering.

Note: Minor variations might occur due to the continuous Subject quality improvement process, and in case of minor variation(s) in assessment details, the Subject Outline represents the latest official information.