Allometry of carbon and nitrogen content and growth rate in a diverse range of coccolithophores
Bibliographic record
Abstract
Abstract As both photoautotrophs and calcifiers, coccolithophores play important roles in ecosystems and biogeochemical cycles. Though some species form blooms in high-latitude waters, low-latitude communities exhibit high diversity and niche diversification. Despite such diversity, our understanding of the clade relies on knowledge of Emiliana huxleyi. To address this, we examine carbon (C) and nitrogen (N) content of strains (n = 9) from the main families of the calcifying Haptophyceae, as well as allometry and cell size frequency across extant species. Coccolithophore cell size is constrained, with ~71% of 159 species smaller than 10 μm in diameter. Growth rates scale with cell biovolume (μ = 1.83 × cell volume−0.19), with an exponent close to metabolic theory. Organic carbon (C) per cell is lower than for other phytoplankton, providing a coccolithophore-specific relationship between cell organic C content and biovolume (pg C cell−1 = 0.30 × cell volume0.70). Organic C to N ratios (~8.3 mol:mol) are similar to other phytoplankton, implying little additional N cost for calcification and efficient retention and recycling of cell N. Our results support observations that coccolithophores are efficient competitors in low-nutrient conditions, able to photosynthesize, calcify and run the routine metabolic machinery necessary without any additional need for N relative to noncalcifying algae.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".