Changes in C uptake in populations of <i>Chlamydomonas reinhardtii</i> selected at high CO<sub>2</sub>
Bibliographic record
Abstract
Estimates of the effect of increased global atmospheric CO(2) levels on oceanic primary productivity depend on the physiological responses of contemporary phytoplankton populations. However, microalgal populations will possibly adapt to rising CO(2) levels in such a way that they become genetically different from contemporary populations. The unknown properties of these future populations introduce an undefined error into predictions of C pool dynamics, especially the presence and size of the biological C pump. To address the bias in predictions introduced by evolution, we measured the kinetics of CO(2) uptake in populations of Chlamydomonas reinhardtii that had been selected for growth at high CO(2) for 1000 generations. Following selection at high CO(2), the populations were unable to induce high-affinity CO(2) uptake, and one line had a lower rate of net CO(2) uptake. We attribute this to conditionally neutral mutations in genes affecting the C concentrating mechanism (CCM). Lower affinity CO(2) uptake, in addition to smaller population sizes, results in a significant reduction in net CO(2) uptake of about 38% relative to contemporary populations under the same conditions. This shows how predictions about the properties of communities in the future can be influenced by the effect of natural selection.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".