Growth, Chl <i>a</i> content, photosynthesis, and elemental composition in polar and temperate microalgae
Bibliographic record
Abstract
Abstract Polar microalgae live under extreme environmental conditions: permanently low temperatures (−1.7°C to +5°C) and extreme variations in irradiance and day length. These conditions may have led to various specific adaptations allowing Arctic phytoplankton to become specialists under these conditions. The goal of this study is to derive, for polar microalgae, empirical relationships between key physiological parameters (growth rate, photosynthesis–irradiance curve parameters, Chl a : C, and N : C ratios) and growth temperature and irradiance in nutrient replete cultures. Ecophysiological characteristics of polar and temperate microalgae were also compared in order to highlight some strategies that are specific to the polar environment. Most of the polar species are psychrophilic. Polar microalgae have low light‐saturated growth rates (μm) and very low light saturation parameters for growth (KE) but similar initial slopes of their growth–irradiance curve (αµ = μm/KE). Low temperatures probably account for low μm and KE in polar species. The C : Chl a ratios (θ) of polar species are similar to those of temperate species although they have much lower growth rates, which implies major differences in energy allocation. Polar microalgae also exhibit very unique photosynthetic properties [low light saturation parameters for photosynthesis (EK), low maximum photosynthetic rates ( ), decreasing and decreasing initial slope of the photosynthesis vs. irradiance curve (α*) with increasing irradiance] and have lower C : N ratios than their temperate cousins, which may be related to a much higher protein content. Some of the implications of these findings in terms of adaptation/acclimation to the environment in which polar species evolve are discussed.
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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) | 0.000 | 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".