Macroevolutionary analyses indicate that repeated adaptive shifts towards predatory diets affect functional diversity in Neotropical cichlids
Bibliographic record
Abstract
Abstract During adaptive radiation, diversification within clades is limited by adaptation to the available ecological niches, and this may drive patterns of both trait and species diversity. However, adaptation to disparate niches may result in varied impacts on the timing, pattern and rate of morphological evolution. In this study, we examined the relationship between feeding ecology and functional diversification across a diverse clade of freshwater fishes, the Neotropical cichlids. Species dietary niches were ordinated via multivariate analysis of stomach content data. We investigated changes in the rate and pattern of morphological diversification associated with feeding, including dietary niche and degree of dietary specialization. A major division in dietary niche space was observed between predators that consume fish and macroinvertebrates vs. other groups with diets dominated by small invertebrates, detritus or vegetation. These trophic niches were strongly associated with groupings defined by functional morphospace. Clades within the piscivore/macroinvertivore group rarely transitioned to other dietary niches. Comparatively, high dietary specialization enhanced functional diversification, driving the evolution of more extreme morphologies. Divergent patterns of trophic diversification among Neotropical cichlids appear to derive from different performance demands in regional abiotic and biotic environments associated with biogeographical history.
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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) | 0.001 | 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".