Extreme events, loss, and grief—an evaluation of the evolving management of climate change threats on the Great Barrier Reef
Bibliographic record
Abstract
Coral reefs across the world have demonstrated an incredible resilience to disturbance, having persisted for over 200 million years withstanding local, short-term shocks such as cyclones and bleaching events, as well as large-scale, long-term global changes such as sea-level fluctuations. However, there are now many persistent and growing threats to the health and productivity of global reef systems such as the Great Barrier Reef (GBR), including water temperature change and subsequent coral bleaching, invasive species, severe weather events, and water quality degradation. Among these, it is widely acknowledged that climate change is the greatest threat to the GBR, with the GBR Marine Park Authority (GBRMPA) releasing a position statement on climate change in 2019, compellingly arguing the urgent need for climate change action for the GBR. For the past two decades, researchers have strongly emphasized the need for vigorous implementation of management strategies that support global reef resilience. This study provides a critical review of the response to this call to action and the barriers and opportunities for implementing transformative resilience actions across a range of social-ecological and natural resource management contexts. Bringing the concepts of environmental grief and resilience thinking together, this study reflects on how back-to-back coral bleaching events in 2016–2017 have changed the framing of GBR management. However, there is more work to be done to ensure that all actors responsible for GBR management accept and embrace change in order to enable transformative resilience, which, for an environment feeling the heat of climate and non-climate pressures, will maintain at least some of their critical environmental, social, and economic values.
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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 | 0.010 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".