Large-scale dieback of mangroves in Australia’s Gulf of Carpentaria: a severe ecosystem response, coincidental with an unusually extreme weather event
Bibliographic record
Abstract
This study records and documents the most severe and notable instance ever reported of sudden and widespread dieback of mangrove vegetation. Between late 2015 and early 2016, extensive areas of mangrove tidal wetland vegetation died back along 1000 km of the shoreline of Australia’s remote Gulf of Carpentaria. The cause is not fully explained, but the timing was coincident with an extreme weather event; notably one of high temperatures and low precipitation lacking storm winds. The dieback was severe and widespread, affecting more than 7400 ha or 6% of mangrove vegetation in the affected area from Roper River estuary in the Northern Territory, east to Karumba in Queensland. At the time, there was an unusually lengthy period of severe drought conditions, unprecedented high temperatures and a temporary drop in sea level. Although consequential moisture stress appears to have contributed to the cause, this occurrence was further coincidental with heat-stressed coral bleaching. This article describes the effect and diagnostic features of this severe dieback event in the Gulf, and considers potential causal factors.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".