Acclimatization of Diatom Phaeodactylum Tricornutum to Long-Term Environmental Temperature and Light Intensity Changes
Bibliographic record
Abstract
Diatoms are the dominant primary producers in a number of oceanographic settings that require high-nutrient and turbulent conditions.In addition, diatoms are sensitive indicator of environmental changes and small modifications of environment result in measurable changes in physiological and biochemical parameters.In the present study the model diatom species, Phaeodactylum tricornutum, was culturing for 6 months and the influence of two environmental factors i.e. temperature and light intensity, as the model of greenhouse effect, was tested.Two temperatures i.e. 12°C (low) and 20°C (moderate), and two light intensities i.e. 6µ Em -2 s -1 (low) and 40 µEm -2 s -1 (moderate) were selected.Three main growth phases of diatom cultures were observed.In the first phase (first two weeks) the optical density at 600 nm (OD) of cultures as well as photosynthetic activity measured as Fv/Fm parameter, increased under all experimental conditions.However, in third growth phase i.e. after four months of experiments, the decrease of OD was detected only at a higher temperature.Values of Fv/Fm parameter showed that photosynthetic activity of P. tricornutum was more sensitive to light intensity than to growth temperature and lower photosynthetic activity was detected at moderate light intensity.In the third phase photosynthetic activity was also well correlated with chlorophyll a concentration and the carotenoid content.The obtained results indicated that the growth rate of diatom cultures depends on temperature whereas photosynthetic activity is more sensitive to light intensity.Low temperature as well as low light intensity were found to be better environmental conditions which ensure a sustainable and long-term growth of diatoms.
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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".