Genomes reveal age and demographic consequence of ultrafast adaptive radiation
Bibliographic record
Abstract
New species typically evolve over several million years. However, rates of speciation and ecological diversification vary by orders of magnitude across the tree of life, with the fastest shown by some adaptive radiations. Eight hundred endemic species of cichlid fishes emerged and formed entire food webs in Lake Victoria and nearby lakes in East Africa. According to Victorias paleolimnological history, five hundred may have arisen within the past 16,700 years, but molecular phylogenies estimated a much older origin. We reconstruct the age and demography of all Lake Victoria region radiations from whole genomes. We show that indeed, in Lake Victoria all trophic guilds diverged <16,700 years ago, corresponding to between 537 and nearly 30000 speciation events per species per million years, the fastest speciation rate in metazoans. Cichlid radiations in lakes Edward, Albert and Kivu too began <20,000 years ago, an order of magnitude faster than previously thought. Evolutionary transitions between trophic levels led to divergence in effective population sizes as predicted by the trophic pyramid of numbers concept and replicated across three parallel food web radiations. Our results demonstrate that classical theory of trophic interactions in ecologically assembled food webs applies equally to food webs that assembled through rapid adaptive radiation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".