Quantifying habitat‐specific diatom production: A critical assessment using morphological and biogeochemical markers in Antarctic marine and lake sediments
Bibliographic record
Abstract
Reconstructions of historical primary production, and of the algal groups and habitats that contribute to it, are fundamental in studies of climate and environmental change in both marine and freshwater environments. The aims of this study were to critically evaluate morphological and biogeochemical markers of diatom production by direct comparison of diatom marker pigments with absolute diatom biovolume and to partition diatom production between the main habitats (plankton, sea ice, and benthos). Sediments in two cores from the Larsemann Hills, Antarctica, spanning the last 10,000 yr, were analyzed for siliceous microfossils by microscopy and for fossil pigments by high‐performance liquid chromatography. Diatom pigments (diadinoxanthin, diatoxanthin, fucoxanthin) were highly correlated (r2 = 0.557 and 0.358, p < 0.0001) with diatom biovolume in the marine intervals of both cores, but only weakly correlated in the lacustrine sections (r2 = 0.102, p = 0.111; r2 = 0.223, p = 0.001, after correction for temporal autocorrelation), possibly because of frustule dissolution and selective degradation of diadinoxanthin and diatoxanthin. In contrast, fucoxanthin was better preserved. By combining both microfossil and pigment proxies, we obtained a first estimate of diatom production in specific habitats (benthic and planktonic). Benthic diatom production was greatest in the lacustrine core sections, when benthic microbial mats dominated the flora, whereas diatoms were associated mainly with the water column and sea ice during the marine intervals. The combination of both proxies in marine and freshwater environments permits more accurate interpretation of pigment and diatom data in paleo‐ and neoecological research and the partitioning of diatom production between habitats.
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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".