Compound Extreme Events Induce Rapid Mortality in a Tropical Sea Urchin
Bibliographic record
Abstract
The frequency, magnitude, and duration of marine heatwaves and deoxygenation events are increasing globally. Recent research suggests that their co-occurrence is more common than previously thought and that their combination can have rapid, dire biological impacts. We used the sea urchin Echinometra lucunter to determine whether mortality occurs faster when deoxygenation events are combined with extreme heating (compound events), compared to deoxygenation events alone. We also tested whether prior exposure to local heatwave conditions accentuates the impacts of compound events. Animals were first exposed for five days to either ambient temperature (28 °C) or a warmer temperature that met the minimum criteria for a local heatwave (30.5 °C). Animals were then exposed to hypoxia, defined as oxygen levels 35% below their average critical oxygen limit, combined with ambient or extreme field temperatures (28 °C, 32 °C). Subsets of animals were removed from the hypoxic treatments every 3 hours for 24 hours to determine how long they could survive. Prior exposure to heatwave conditions did not help or hinder survival under hypoxic conditions, and animals exposed to hypoxia under ambient temperatures experienced little mortality. However, when hypoxia was coupled with extreme temperatures (32 °C), 55% of the animals died within 24 hours. On the reefs at our Panama study site, we found that extreme hypoxic conditions only ever occurred during marine heatwave events, with four compound events occurring in 2018. These results show that short durations (∼1 day) of compound events can be catastrophic and that increases in their duration will severely threaten sea urchin populations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.001 | 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".