Interannual flow variability in a large subtropical–temperate floodplain: a challenge for fish reproduction
Bibliographic record
Abstract
Fluctuations of temperature and water levels are the two main drivers of aquatic life in river floodplain ecosystems. The large Middle Paraná River floodplain exhibits marked seasons and important interannual hydrological changes. Using a three-factor-based approach (fish reproductive traits, hydroclimatic conditions, and floodplain recruitment patterns), we analyzed how fish life history evolves within this fluctuating environment. We observed that hydroclimatic conditions can be considered through three main interannual variations that prompt the most abundant Paraná species to adopt four different main reproductive strategies: (i) typical periodic strategists are dependent on large spring–summer floods and juveniles strongly predominate in the floodplain when such a condition occurs, (ii) periodic–opportunistic strategists are associated with floods, regardless of their timing, (iii) periodic–equilibrium strategists take advantage of spring–summer floods whatever the intensity and duration, and (iv) equilibrium strategists have low flood dependence and higher stability in temporal fish recruitment. This work brings forth a first synthesis of fish life history in the Middle Paraná River and evidences how important both hydrological and temperature fluctuations are to interpret its complexity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".