Environmental change provokes rapid macromolecular reallocations within the photosynthetic system in a static population of photobionts in the lichen <b><i>Lobaria pulmonaria</i></b>
Bibliographic record
Abstract
Lobaria pulmonaria is an epiphytic lichen that, in south-eastern Canada, inhabits deciduous forests where it must acclimate to large seasonal changes in temperature and in light caused by closing and opening of the leaf canopy. On a seasonal timescale, this acclimation occurs via large shifts in the macromolecular complexes of the photosynthetic system, within a photobiont population that shows no seasonal change in cell numbers. In this study, samples of L. pulmonaria were harvested in February and in May from a natural population near Sackville, New Brunswick, and subjected to two simulated intense seasonal changes: (1) early spring warming, simulated by a shift from high light at 5°C to high light at 16°C (February shift), and (2) late spring canopy closure, simulated by a shift from high light at 16°C to low light at 16°C (May shift). Thallus samples were collected daily throughout each week-long shift. There were no significant changes in photobiont cell population size or in the fraction of cells dividing during either shift. During the first day of the February temperature shift, there were, however, large changes in the pools of chlorophyll, the major light capture molecule in the photobionts, the PsbA (D1) core protein of photosystem II whose turnover is highly responsive to changing light and temperature, and the RbcL major subunit of the carbon-fixing RUBISCO enzyme whose levels correlate strongly with achieved photosynthesis in lichens. A static population of photobionts was therefore able to perform large and rapid macromolecular reallocations to cope with rapid environmental change. No significant changes were seen in the chlorophyll, photosystem II or RUBISCO pools across the May light shift, although seasonal-scale macromolecular reallocation does occur in response to decreased light in the summer.
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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".