The ecomorphological diversity of Amazonian stream fishes is constrained by phylogenetic relationships
Bibliographic record
Abstract
Phylogenetic history and environmental conditions determine the trait diversity of species pools. Stream fishes have diversified into a wide range of body and oral shapes that allow a similarly wide range of functional traits, but that can be determined by habitat type and taxon. Herein, we analyzed 16 ecomorphological traits of nearly 400 fishes inhabiting streams distributed across the Brazilian Amazon to (i) describe the main axes of ecomorphological variation of Amazonian stream fishes; (ii) quantify the proportion of the potential combination of traits that is displayed by the regional pool of species; (iii) evaluate the distribution of different taxonomic groups in those axes; (iii) determine the overall contributions of the taxonomic groups to regional ecomorphological diversity. Our results show that Amazonian stream fishes concentrate around multiple combinations of traits defined by five axes of ecomorphological variation. The benthic-nektonic axis segregates fishes with upper-positioned eyes and wide mouth gapes from fishes with lower-positioned eyes and narrow mouth gapes related to narrower body shapes. Benthic fishes further differ in three groups of species depending on ecomorphological traits coupling different strategies for feeding and swimming. Taxonomic order and family constrained species position along these axes of variation and consequently determined their contribution to overall ecomorphological variation. Overall, we show that five axes related to habitat and food partitioning explain most of the ecomorphological diversity of Amazonian stream fishes, but taxonomic identity determines species suite of traits.
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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 | 0.001 |
| 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) | 0.002 | 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".