Ecological correlates of fish reproductive activity in floodplain rivers: a life-history-based approach
Bibliographic record
Abstract
Reproductive activity of seven species representing three divergent life history strategies was monitored monthly for 2 years in channel and floodplain habitats of the Brazos River, Texas, USA, to evaluate associations between reproductive activity and biotic and abiotic factors predicted by conceptual models to influence reproduction. An information-theoretic approach was used to select best approximating models for each species, and model-averaged estimates of regression coefficients were calculated. Model selection indicated that monthly flow based on the 30-year hydrograph and temperature was strongly supported as factors associated with reproductive activity of all three life history strategies. The timing of reproduction in relation to the long-term hydrograph was related to life history traits. Reproductive activity of species with large adult size and high fecundity was greatest in spring just prior to increasing flows, whereas species with small adult size and extended breeding seasons exhibited greater activity in late spring and summer when mean flow was greatest. Nest-building species with parental care were more abundant in off-channel habitats where floods were less common. Instream flow management would benefit from consideration of flow and habitat requirements needed to support the diverse life history strategies displayed by fishes in river–floodplain systems.
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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 | 0.001 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".