The importance of the terrestrial weathering feedback for multimillennial coral reef habitat recovery
Bibliographic record
Abstract
Modern‐day coral reefs have well defined environmental envelopes for light, sea surface temperature (SST) and seawater aragonite saturation state (Ω arag ). We examine the changes in global coral reef habitat on multimillennial timescales with regard to SST and Ω arag using a climate model including a three‐dimensional ocean general circulation model, a fully coupled carbon cycle, and six different parameterizations for continental weathering (the UVic Earth System Climate Model). The model is forced with emission scenarios ranging from 1,000 Pg C to 5,000 Pg C total emissions. We find that the long‐term climate change response is independent of the rate at which CO 2 is emitted over the next few centuries. On millennial timescales, the weathering feedback introduces a significant uncertainty even for low emission scenarios. Weathering parameterizations based on atmospheric CO 2 only display a different transient response than weathering parameterizations that are dependent on temperature. Although environmental conditions for SST and Ω arag stay globally hostile for coral reefs for millennia for our high emission scenarios, some weathering parameterizations induce a near‐complete recovery of coral reef habitat to current conditions after 10,000 years, while others result in a collapse of coral reef habitat throughout our simulations. We find that the multimillennial response in sea surface temperature (SST) substantially lags the aragonite saturation recovery in all configurations. This implies that if corals can naturally adapt over millennia by selecting thermally tolerant species to match warmer ocean temperatures, prospects for long‐term recovery of coral reefs are better since Ω arag recovers more quickly than SST.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".