The daily resolved temperature dependence and structure of planktonic foraminifera blooms
Bibliographic record
Abstract
Planktonic foraminifera (PF) life cycles are highly sensitive to marine conditions, which are evolving rapidly due to anthropogenic climate change. Even though PF shells in the sedimentary record serve as prominent proxies of past ocean conditions, very little is still known about their life cycles, particularly in oligotrophic environments. Here, we present a full annual record of PF fluxes (> 63 µm) from the oligotrophic Gulf of Aqaba, northern Red Sea, sampled at daily timescales during 2015-2016 using an automated time-series sediment trap. These results are coupled with daily surface chlorophyll-a concentrations, sea surface temperatures (SSTs), particulate organic carbon and bulk fluxes, together with monthly resolved vertical profiles of chlorophyll-a, temperatures and nutrient concentrations. The annual cycle of PF fluxes is controlled by SST changes that drive water column mixing and changes in food availability. PF species flux patterns and succession dynamics vary throughout the year, displaying large variability on previously undocumented daily-weekly timescales, and are not synchronized with lunar periodicity. On daily timescales, spring blooms show a complex structure and interplay between SSTs, chlorophyll-a surface concentrations and PF fluxes. These events deliver about a third of the total annual PF flux over a period of several weeks.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".