Growth and high‐resolution paleoenvironmental signals of rhodoliths (coralline red algae): A new biogenic archive
Bibliographic record
Abstract
We investigated rhodoliths (coralline red algae) from a subtropical locality in the Gulf of California (Lithothamnium crassiusculum) and a subarctic locality in Newfoundland (Lithothamnium glaciale) for their potential as paleoenvironmental archives using microanalytical geochemical techniques to measure variations in δ18O, Mg, and Ca. Rhodoliths are potentially well suited as recorders of shallow water paleoenvironmental signals because they (1) have worldwide distribution from the tropics to polar regions, (2) are long lived from decades to centuries, and (3) display well‐developed growth bands. Our results indicate that rhodolith growth bands preserve ultrahigh‐resolution records of paleoceanographic‐paleoclimatic change and likely constitute an important new archive for reconstructing the paleoenvironmental history of littoral‐neritic areas in which these algae are found. The δ18O content of individually sampled rhodolith growth bands ranges from −2.4 to −4.6‰ in L. crassiusculum and from −3.2 to −0.3‰ in L. glaciale. In both cases, the range of δ18O values suggests a slightly lower amplitude of variation in sea surface temperature than that actually measured in the ocean at the two study sites. Both L. crassiusculum and L. glaciale show a negative offset from isotopic equilibrium. Electron microprobe analysis of magnesium and calcium in growth bands reveals cyclic variations with values ranging between 7.7–18.5 mol % MgCO3 in L. glaciale and 13.2–22.5 mol % MgCO3 in L. crassiusculum. In addition, electron microprobe element maps highlight individual growth bands, provide a powerful approach to study rhodolith formation, and indicate that the specimens we analyzed have vertical growth rates of 250–450 μm/yr.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".