Competition both drives and impedes diversification in a model adaptive radiation
Bibliographic record
Abstract
Competitors are known to be important in governing the outcome of evolutionary diversification during an adaptive radiation, but the precise mechanisms by which they exert their effects remain elusive. Using the model adaptive radiation of Pseudomonas fluorescens, we show experimentally that the effect of competition on diversification of a focal lineage depends on both the strength of competition and the ability of the competitors to diversify. We provide evidence that the extent of diversification in the absence of interspecific competitors depends on the strength of resource competition. We also show that the presence of competitors can actually increase diversity by increasing interspecific resource competition. Competitors that themselves are able to diversify prevent diversification of the focal lineage by removing otherwise available ecological opportunities. These results suggest that the progress of an adaptive radiation depends ultimately on the strength of resource competition, an effect that can be exaggerated or impeded by the presence of competitors.
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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".