MB5340 - Ecological Dynamics: Modelling With Data

[Offered in odd-numbered years]

Credit points:	03
Year:	2015
Student Contribution Band:	Band 2
Administered by:	College of Marine & Environmental Sciences

Available to Graduate Diploma of Research Methods, Graduate Certificate of Research Methods, Graduate Diploma of Science, Master of Applied Science, Graduate Certificate of Development Practice, Graduate Diploma of Development Practice, Master of Science and Master of Development Practice.

This subject introduces students to contemporary techniques for confronting bespoke, process-based ecological models with data, using the statistical software program R. 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, Monte Carlo simulation, likelihood, and information-theoretic and Bayesian methods. Much of the material will be introduced using case studies from marine, terrestrial, and freshwater systems.

Learning Outcomes

• critically evaluate different views of the role of models in ecology, from the perspective of alternative philosophies of science;
• formulate algorithms to confront ecological models with empirical data, applying a variety of contemporary tools;
• analyze bias and uncertainty in parameter estimates, and to critically interpret model fits and predictions with these in mind;
• reflect on the philosophy and assumptions behind different model selection methods, and to draw conclusions from the application of those methods accordingly;
• make informed ecological inferences and management decisions by confronting bespoke, process-based models with data.

Assumed Knowledge:	Students will be assumed to have some experience with basic calculus, statistics, ecology, and programming in S-plus or R. For those lacking background in one or more of those areas, material will be made available for students to complete prior to commencement of the subject. Some experience with ecological modelling (e.g., MB5260 or similar) is desirable
Prerequisites:	MB5260 AND BS5001

Availabilities
Townsville, Block, Study Period 7
Census Date 09-Jul-2015
Face to face teaching 13-Jul-2015 to 24-Jul-2015
Coord/Lect:	Professor Sean Connolly.
Contact hours:	65 hours - lectures, tutorials, computer practicals
Assessment:	tutorial attendance and participation (10%); assignments (75%); practical scripts (15%).
Special Assessment Requirements:	Students are expected to have completed the Introduction to R tutorial, the maths/stats reviews, and the first assigned reading from the text, prior to commencement of face-to-face teaching
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.