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Integrated network models for predicting ecological thresholds: microbial - carbon interactions in coastal marine systems

Citation

McDonald, KS and Turk, V and Mozetic, P and Tinta, T and Malfatti, F and Hannah, DM and Krause, S, Integrated network models for predicting ecological thresholds: microbial - carbon interactions in coastal marine systems, Environmental Modelling and Software, 91 pp. 156-167. ISSN 1364-8152 (2017) [Refereed Article]

Copyright Statement

2017 Elsevier Ltd

DOI: doi:10.1016/j.envsoft.2017.01.017

Abstract

This proof of concept study presents a Bayesian Network (BN) approach that integrates relevant biological and physical-chemical variables across spatial (two water layers) and temporal scales to identify the main contributing microbial mechanisms regulating POC accumulation in the northern Adriatic Sea. Three scenario tests (diatom, nanoflagellate and dinoflagellate blooms) using the BN predicted diatom blooms to produce high chlorophyll a at the water surface while nanoflagellate blooms were predicted to occur also at lower depths (>5m) in the water column and to produce lower chlorophyll a concentrations. A sensitivity analysis using all available data identified the variables with the greatest influence on POC accumulation being the enzymes, which highlights the importance of microbial community interactions. However, the incorporation of experimental and field data changed the sensitivity of the model nodes ≥25% in the BN and therefore, is an important consideration when combining manipulated data sets in data limited conditions.

Item Details

Item Type:Refereed Article
Keywords:biogeochemical cycling, modelling, plankton
Research Division:Biological Sciences
Research Group:Microbiology
Research Field:Microbial ecology
Objective Division:Environmental Management
Objective Group:Coastal and estuarine systems and management
Objective Field:Assessment and management of coastal and estuarine ecosystems
UTAS Author:McDonald, KS (Ms Karlie McDonald)
ID Code:154686
Year Published:2017
Deposited By:Sustainable Marine Research Collaboration
Deposited On:2022-12-21
Last Modified:2023-01-12
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