Parallelism in adaptive radiations of experimental<i>Escherichia coli</i>populations
Bibliographic record
Abstract
Adaptive radiations are major contributors to species diversity. Although the underlying mechanisms of adaptive radiations, specialization and trade-offs, are relatively well understood, the tempo and repeatability of adaptive radiations remain elusive. Ecological specialization can occur through the expansion into novel niches or through partitioning of an existing niche. To test how the mode of resource specialization affects the tempo and repeatability of adaptive radiations, we selected replicate bacterial populations in environments that promoted the evolution of diversity either through niche expansion or through niche partitioning, and in a third low-quality single-resource environment, in which diversity was not expected to evolve. Colony size diversity evolved equally fast in environments that provided ecological opportunities regardless of the mode of resource specialization. In the low-quality environments, diversity did not consistently evolve. We observed the largest fitness improvement in the low-quality environment and the smallest the glucose-limited environment. We did not observe a change in the rate of evolutionary change in either trait or environment, suggesting that the pool of beneficial mutations was not exhausted. Overall, the mode of resource specialization did not affect the tempo or repeatability of adaptive radiations. These results demonstrate the limitations of eco-evolutionary feedbacks to affect evolutionary outcomes.
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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".