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A Bayesian inference approach to account for multiple sources of uncertainty in a macroalgae based integrated multi-trophic aquaculture model

Citation

Hadley, S and Jones, E and Johnson, C and Wild-Allen, K and Macleod, C, A Bayesian inference approach to account for multiple sources of uncertainty in a macroalgae based integrated multi-trophic aquaculture model, Environmental Modelling and Software, 78 pp. 120-133. ISSN 1364-8152 (2016) [Refereed Article]

Copyright Statement

Copyright 2016 Elsevier Ltd.

DOI: doi:10.1016/j.envsoft.2015.12.020

Abstract

A Bayesian inference method was employed to quantify uncertainty in an Integrated Multi-Trophic Aquaculture (IMTA) model. A deterministic model was reformulated as a Bayesian Hierarchical Model (BHM) with uncertainty in the parameters accounted for using "prior" distributions and unresolved time varying processes modelled using auto-regressive processes. Observations of kelp grown in 3 seeding densities around salmon pens were assimilated using a Sequential Monte Carlo method implemented within the LibBi package. This resulted in a considerable reduction in the variability in model output for both the observed and unobserved state variables. A reduction in variance between the prior and posterior was observed for a subset of model parameters which varied with seeding density. Kullback eLiebler (KL) divergence method showed the reduction in variability of the state and parameters was approximately 90%. A low to medium seeding density results in the most efficient removal of excess nutrients in this simple system.

Item Details

Item Type:Refereed Article
Keywords:Bayesian inference, macroalgae, IMTA, Sequential Monte Carlo, particle filter, aquaculture
Research Division:Biological Sciences
Research Group:Ecology
Research Field:Marine and Estuarine Ecology (incl. Marine Ichthyology)
Objective Division:Environment
Objective Group:Ecosystem Assessment and Management
Objective Field:Ecosystem Assessment and Management of Marine Environments
Author:Hadley, S (Mr Scott Hadley)
Author:Johnson, C (Professor Craig Johnson)
Author:Macleod, C (Associate Professor Catriona MacLeod)
ID Code:108107
Year Published:2016
Deposited By:Sustainable Marine Research Collaboration
Deposited On:2016-04-06
Last Modified:2016-12-06
Downloads:0

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