Adaptive habitat selection by a single celled alga?
Bibliographic record
Abstract
Faculty and students in the Department of Biology are bound together by a common interest in explaining the diversity of life, the fit between form and function, and the distribution and abundance of organisms. The research reported here shows how habitat selection and adaptive movement influence population dynamics. I first demonstrate by theory why habitat selection should vary with density. I then describe experiments in which I measured per capita population growth rates of the single-celled alga, Chlamydomonas reinhardtii, in separate shaded and unshaded (light) habitats across a range of densities, and used them to predict the number of cells that one should observe in adjacent habitats. Fitness was higher in the light habitat than in the shade. Using these observations, theory predicts that all individuals should occupy the light habitat at low density, but as density increases individuals should increasingly occupy the shade. More generally, individual cells should move to habitats of higher mean fitness (adaptive movement). My experiments on Chlamydomonas demonstrated a rather novel form of adaptive movement that only partially confirmed the predictions. The fitness of cells released in the light habitat in rich environments was not different from that in shade because density was higher in light. Cells released in shade, and those released in poor environments, moved such that there were no differences in density between habitats, even though fitness was usually higher in light. Adaptive movement thus depends not only on the quality of the occupied habitat, but also on mean environmental quality.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".