The Conservation Planning for a Changing Coastal Zone project team, Owen, Ben and Amélie, are making good progress towards finalising the prototype scenario-Bayesian networks method as a decision support tool for GBR managers. Owen, from Bayesian Intelligence, was contracted to complete the BN and apply them spatially. He will be presenting the overall project with a bit more focus on his work and tell us how BNs work and fit in the project to conduct the cumulative impact assessment of coastal development scenarios and their marine consequences.

When: Monday 10th November 13:00 – 14:00
Where: GBRMPA Conference Room 1, Townsville

photoAbstract: The cumulative impacts of coastal development and associated activities are placing multiple stressors on the Great Barrier Reef (GBR), causing declines in abundances of some species and degradation of marine ecosystems. Cumulative impact assessment has proven difficult because we cannot determine exactly what development will occur in the future or the response of GBR’s species and ecosystems to multiple stressors. Complete information needed to truly assess cumulative impacts will never be available, but decisions need to be made now. This project applies Bayesian networks (BNs) and Geographic Information Systems (GIS) to tackle the difficulties in this task. BNs are effective tools for modelling complex systems using experts’ knowledge, where quantitative data are either incomplete or uncertain. We develop BNs for a select suite of better-known species (seagrass, dugongs, and benthic-grazer reef fish) to model the effects on them of multiple pressures. The BNs are applied to spatially-explicit scenarios of marine uses and impacts based on previously modeled land-use scenarios that depict plausible development futures for the GBR coastal zone over the next 20 years. The scenarios generate the GIS inputs for the BN. This approach provides a large-scale planning and decision-support tool for managers and policy-makers to explore and minimise the impacts of coastal development.

Bio: Dr Owen Woodberry is a Senior Consultant with Bayesian Intelligence, a Melbourne-based company. Bayesian Intelligence specialises in Bayesian network development, data mining, and training. Owen has worked with Bayesian networks for over a decade, leading several projects and assisting in the development of ecological Bayesian networks and models for environmental research and management. He has a PhD in computer science from Monash University, focused on developing agent-based models to explore open questions in evolutionary biology.

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