Growth phase dependent hydrogen isotopic fractionation in alkenone-producing haptophytes
Bibliographic record
Abstract
Abstract. Recent works have investigated use of the hydrogen isotopic composition of C37 alkenones (δDK37s, lipid biomarkers of certain haptophyte microalgae, as an independent paleosalinity proxy. We discuss herein the factors impeding the success of such an application and identify the potential alternative use of δDK37s measurements as a proxy for non-thermal, physiological stress impacts on the U37K' paleotemperature index. Batch-culture experiments with the haptophyte Emiliania huxleyi (CCMP 1742) were conducted to determine the magnitude and variability of the isotopic contrasts between individual C37 alkenones. Further experiments were conducted with Emiliania huxleyi (CCMP 1742) andGephyrocapsa oceanica (PZ3-1) to determine whether, and to what extent, δDK37s varies between the physiological extremes of nutrient-replete exponential growth and nutrient-depleted senescence. Emiliania huxleyi was observed to exhibit an isotopic contrast between di- and tri-unsaturated C37 alkenones (αK37:3-K37:2≈0.97) that is nearly identical to that reported recently by others for environmental samples. Furthermore, this contrast appears to be constant with growth stage. The consistency of the offset across different growth stages suggests that a single, well-defined value for αK37:3-K37:2 may exist and that its use in an isotope mass-balance will allow accurate determination of δD values for individual alkenones without having to rely on time- and labor-intensive chemical separations. The isotopic fractionation between growth medium and C37 alkenones was observed to increase dramatically upon the onset of nutrient-depletion-induced senescence, suggesting that δDK37s may serve as an objective tool for recognizing and potentially correcting, at least semi-quantitatively, for the effects of nutrient stress on U37K' temperature records.
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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 | 0.000 | 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".