Comparative life‐history strategies in three <scp>Lebiasinidae</scp> (<scp>Characiformes</scp>) in a <scp>Rio Negro</scp> tributary, <scp>Brazilian Amazon</scp>
Bibliographic record
Abstract
Reproductive traits co-evolve and form successful life-history strategies adapted to the biology and environment of a particular taxon, maximizing offspring and species survival chances, therefore studies investigating differences in adaptive traits across different environments can enhance our understanding of the natural selection process and evolution. Herein, we address whether the reproductive strategies of phylogenetically closely related fishes are influenced by habitat predictability, using three species of the Lebiasinidae family as models. The predominance of larger and mature individuals during the flood season, with high waters characterized by smaller immature individuals, suggests a seasonal reproductive strategy for Nannostomus trifasciatus. Copella callolepis, which inhabits both habitats, also showed a single reproductive peak. However, compared to N. trifasciatus, this species displayed late spawning, restricted to the flood season, as indicated by the higher abundance of larger and mature individuals during this period and the presence of smaller (juveniles) and spawned individuals in the following season. The reproductive tactics observed in N. marginatus differed significantly from the single reproductive peak of the other species, as two reproductive peaks were observed: one during the flood season and another during the low water season. In conclusion, our study demonstrates that the environment strongly influences reproductive strategies for lebiasinids. N. marginatus, restricted to small water bodies, exhibited an opportunistic reproductive strategy, whereas the species inhabiting main rivers, N. trifasciatus and C. callolepis, exhibited a more seasonal strategy.
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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 | 0.000 |
| 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".