Estuarine Modelling
Using expert driven approaches to model changes in benthic biodiversity through time
Tidal Research is developing modelling tools to inform the management of upstream stressors on estuarine ecosystems. Project partners include the National Institute of Water and Atmospheric Research (NIWA) and the Hawkes Bay Regional Council.
The objective of this project is to explore whether expert driven multiple stressor relationships can be used to predict changes in benthic biodiversity through time. We are using long-term monitoring data on key stressors (suspended sediment, mud, metals, nutrients), from locations such as the Ahuriri estuary within the Hawkes Bay (where annual monitoring data exists from 2006 to 2022), to predict changes in benthic macrofaunal diversity through time. These outputs will be compared to benthic biodiversity measured from long term macrofaunal core sampling. We will also explore whether climatic variables (SOI) not considered in the expert model can help to explain differences between the modelled predictions and the actual data.
These outputs will help to determine whether the expert driven modelling approach can be used to make useful time series predictions and inform management decisions. Run a scenario of interest to explore how temporal variability in stressor interactions may impact estuarine ecosystems.
Utilising modelling to inform estuarine decision-making
Management of estuary values and aspirations: an extension of the Estuarine Bayes Net Model.
Tidal Research joins the researchers from the University of Auckland, University of Waikato and University of Otago on a Sustainable Seas project which investigates the utilising Bayesian network modelling to inform estuarine decision making. The project aimed to expand on existing estuarine Bayesian Network models through a participatory process with coastal communities so that their values, aspirations and concerns could be incorporated into estuarine management.
The project contributes towards the Sustainable Seas National Science Challenge project Improved decision-making using an ecosystem-based management (EBM) approach.
Background
Probabilistic Bayesian Network models have been identified as key tools to inform management decision making by the Sustainable Seas National Science Challenge. Importantly, the ability for Bayesian Network models to be co-developed through participatory processes with communities/stakeholders demonstrated the value of using decision support tools to help align the understanding of marine management decisions and values and aspirations of different groups.
This project expands on the Estuarine Bayesian Network model commissioned by the Parliamentary Commission for the Environment that explored the effect of human-induced stressors on biological, physical and chemical processes and the overall condition of an estuary to further incorporate additional estuarine stressors/tidal flushing, marine heatwaves, and the values of coastal communities.
Project status
July 2024 - Project complete. Report and two-page summary published on the Sustainable Seas Challenge website (see below).
Outputs
Hewitt J. E., Bulmer R., Savage C., Ellis J., Thomson T., Flowers G. (2024). Management for estuary values and aspirations: An extension of the Estuaries Bayes Net Model. Sustainable Seas National Science Challenge.
