Ecological variation in South American geophagine cichlids arose during an early burst of adaptive morphological and functional evolution
Bibliographic record
Abstract
Diversity and disparity are unequally distributed both phylogenetically and geographically. This uneven distribution may be owing to differences in diversification rates between clades resulting from processes such as adaptive radiation. We examined the rate and distribution of evolution in feeding biomechanics in the extremely diverse and continentally distributed South American geophagine cichlids. Evolutionary patterns in multivariate functional morphospace were examined using a phylomorphospace approach, disparity-through-time analyses and by comparing Brownian motion (BM) and adaptive peak evolutionary models using maximum likelihood. The most species-rich and functionally disparate clade (CAS) expanded more efficiently in morphospace and evolved more rapidly compared with both BM expectations and its sister clade (GGD). Members of the CAS clade also exhibited an early burst in functional evolution that corresponds to the development of modern ecological roles and may have been related to the colonization of a novel adaptive peak characterized by fast oral jaw mechanics. Furthermore, reduced ecological opportunity following this early burst may have restricted functional evolution in the GGD clade, which is less species-rich and more ecologically specialized. Patterns of evolution in ecologically important functional traits are consistent with a pattern of adaptive radiation within the most diverse clade of Geophagini.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".