Predicting the temporal response of seagrass meadows to dredging using Dynamic Bayesian Networks
Document Type
Conference Proceeding
Publication Title
21st International Congress on Modelling and Simulation, Gold Coast, Australia
Publisher
The Modelling and Simulation Society of Australia and New Zealand Inc.
School
School of Science / Centre for Marine Ecosystems Research
RAS ID
23377
Abstract
Predicting temporal responses of ecosystems to disturbances associated with industrial activities is critical for their management and conservation. However, prediction of ecosystem responses is challenging due to the complexity and potential non-linearities stemming from interactions between system components and multiple environmental drivers. Prediction is particularly difficult for marine ecosystems due to their often highly variable and complex natures and large uncertainties surrounding their dynamic responses. Consequently, current management of such systems often rely on expert judgement and/or complex quantitative models that consider only a subset of the relevant ecological processes. Hence there exists an urgent need for the development of whole-of-systems predictive models to support decision and policy makers in managing complex marine systems in the context of industry based disturbances...
Access Rights
free_to_read
Comments
Wua, P. P.-Y., Mengersena, K., McMahonbe, K., Kendrickce, G. A., & Caley, M. J. (2015). Predicting the temporal response of seagrass meadows to dredging using Dynamic Bayesian Networks. In Proceedings of the 21st International Congress on Modelling and Simulation, Gold Coast, Australia, 29 Nov to 4 Dec 2015 (pp. 1282-1288). Available here