RAPID SYMPATRY EXPLAINS GREATER COLOR PATTERN DIVERGENCE IN HIGH LATITUDE BIRDS
Bibliographic record
Abstract
Latitudinal variation in patterns of evolution has fascinated biologists for over a century, but our understanding of latitudinal differences in evolutionary processes-such as selection and drift-remains limited. Here, we test for, and find, accelerated evolution of color patterns in bird taxa that breed at higher latitudes compared with those breeding in the tropics, analyzing data from seven diverse avian families. Most important, we show that the extent of overlap of species' breeding ranges (degree of sympatry) explains the elevated rate of color pattern evolution at higher latitudes. We suggest that the dynamic shifts in breeding ranges that accompanied climatic changes during the last 3 million years (Milankovitch Oscillations) resulted in more rapid and more frequent secondary contact at high latitudes. We argue that sympatry among diverging clades causes greater divergence of color traits in birds at higher latitudes through sexual, social, or ecological character displacement that accelerate rates of evolution, and through the selective elimination of weakly differentiated lineages that hybridize and fuse in sympatry (differential fusion).
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".