Oceanographic Drivers of Bleaching in the GBR: Hazard Maps for 2016-2017

2016 and 2017 hazard maps predicting coral bleaching risk for the Great Barrier Reef using a dynamic temperature threshold. The dataset was created by the Australian Institute of Marine Science under the NESP TWQ 4.2 project, employing a classification tree model trained on aerial survey data. The model achieved over 66% accuracy in classifying reef bleaching conditions based on variables like DHWmax anomaly and water column stratification.

Use Cases

• Predicting coral bleaching risk levels based on dynamic degree heating week thresholds.
• Analyzing the relative importance of oceanographic drivers like DHWmax anomaly and upwelling anomaly for bleaching severity.
• Validating satellite-derived heat stress products against in-situ aerial survey observations.
• Creating spatially explicit hazard maps for reef management and conservation planning.

Strengths

• Model validation reported with over 66% classification accuracy for bleaching conditions.
• Explicit variable importance ranking is provided (e.g., DHWmax anomaly > MHW count anomaly).
• Specific threshold values for severe bleaching are identified (e.g., DHWmax anomaly of 4.4 °C-week).

Limitations

• Dataset is limited to two specific years (2016 and 2017).
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

Australian Ocean Data Network (AODN), Australian Institute of Marine Science (AIMS).

Collection Method

Classification tree prediction model applied to paired aerial bleaching survey data and satellite-derived oceanographic anomalies.

Time Range

2016, 2017

Freshness

Last updated 2026-07-10 16:29:48.975708; freshness should be verified.

Geography

Great Barrier Reef, Australia