Comparing Adaptive Radiations Across Space, Time, and Taxa
Bibliographic record
Abstract
Adaptive radiation plays a fundamental role in our understanding of the evolutionary process. However, the concept has provoked strong and differing opinions concerning its definition and nature among researchers studying a wide diversity of systems. Here, we take a broad view of what constitutes an adaptive radiation, and seek to find commonalities among disparate examples, ranging from plants to invertebrate and vertebrate animals, and remote islands to lakes and continents, to better understand processes shared across adaptive radiations. We surveyed many groups to evaluate factors considered important in a large variety of species radiations. In each of these studies, ecological opportunity of some form is identified as a prerequisite for adaptive radiation. However, evolvability, which can be enhanced by hybridization between distantly related species, may play a role in seeding entire radiations. Within radiations, the processes that lead to speciation depend largely on (1) whether the primary drivers of ecological shifts are (a) external to the membership of the radiation itself (mostly divergent or disruptive ecological selection) or (b) due to competition within the radiation membership (interactions among members) subsequent to reproductive isolation in similar environments, and (2) the extent and timing of admixture. These differences translate into different patterns of species accumulation and subsequent patterns of diversity across an adaptive radiation. Adaptive radiations occur in an extraordinary diversity of different ways, and continue to provide rich data for a better understanding of the diversification of life.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".