Hobart

Seminar Abstract

Friday 6 March 2009, 10.00am (Tas time)
CSIRO Auditorium, Hobart

Grace Chiu
Department of Statistics and Actuarial Science
University of Waterloo
Ontario, Canada

Statistical Inference for Food Webs, Part I: Bayesian Melding

Quantifying various aspects of dependence within a food web or ecological network has largely been descriptive or deterministic. Existing schemes that attempt to assess reliability of such quantification are often non-statistical in nature. This talk focuses on understanding ecological networks in the context of mass balance (as opposed to identifying trophic compartments). Our statistical inferential approach employs Bayesian melding, and embodies the traditional deterministic views on network relations; yet, it is developed for the estimation of physical quantities and assessment of the estimation, both from a statistical perspective. The practical advantage of incorporating natural measurement variability into deterministic beliefs about the relationships among measurements is a more honest representation of the true state of nature, and the ability to formally assess balance before data are passed on to later stages of an ecological network analysis (ENA). We also find that general Bayesian inference for ENA can yield new ecological insight that may not be available through standard classical inference.

Seminar Recording

[back]

Location:
CSIRO = Marine Laboratories Auditorium, Castray Esplanade, Hobart

For further information, or to schedule a seminar, contact:
To schedule a seminar, contact:
Clothilde Langlais, (Oceanographic seminars) CSIRO Marine and Atmospheric Research (03) 6232 5399
Natalie Kelly, (Biology/Modelling seminars) CSIRO Marine and Atmospheric Research 0438 452 483
Jillian Enraght-Moony, (seminar administrator) CSIRO Marine and Atmospheric Research (03) 6232 5320
Communications Manager, Antarctic Climate and Ecosystems CRC (03) 6226 2265
Margaret Hazelwood, Institute of Antarctic and Southern Ocean Studies (IASOS) University of Tasmania (03) 6226 2971

Last updated 8/12/09