ReefState model predictions

Created 23/06/2025

Updated 23/06/2025

ReefState (version 3.0) utilises a Bayesian Network modelling framework to integrate lower-level submodels of future warming, coral damage, coral recovery, coral adaptation, and algal herbivory, into a continuous causal chain. The integrated model allows prediction of ecological endpoints that reflect important management concerns, namely coral cover and composition. The purpose of the ReefState model is to investigate the long-term implications on coral reef resilience of projected increases in the frequency and intensity of coral bleaching events. And more specifically, how successful management outcomes (viz. water quality, fishing pressure, and no take zones) might interact to benefit coral reefs during the period of climate warming that is expected in the coming decades. Details pertaining to the rationale, development and application of the individual submodels and integrating framework can be found within the refereed journal articles:Wooldridge S, Berkelmans R, Done TJ, Jones RN, Marshall P (2005). Precursors for resilience in coral communities in a warming climate: a belief network approach. Marine Ecology Progress Series 295:157-169.Wooldridge S, Done TJ (2004). Learning to predict large-scale coral bleaching from past events: A Bayesian approach using remotely sensed data, in-situ data, and environmental proxies. Coral Reefs 23: 96-108.

Files and APIs

Additional Info

Field Value
Title ReefState model predictions
Language eng
Licence Not Specified
Landing Page https://data.gov.au/data/dataset/18292f96-397f-48f4-8a1f-7db1fa66d426
Contact Point
Australian Ocean Data Network
adc@aims.gov.au
Reference Period 20/04/2023
Geospatial Coverage Australia
Data Portal Australian Oceans Data Network

Data Source

This dataset was originally found on Australian Oceans Data Network "ReefState model predictions". Please visit the source to access the original metadata of the dataset:
https://catalogue.aodn.org.au/geonetwork/srv/eng/csw/dataset/reefstate-model-predictions1