Longitudinal variability in lateral hydrologic connectivity shapes fish occurrence in temporary floodplain ponds
Bibliographic record
Abstract
Dynamic flow regimes maintain critical connections between main channel and adjacent floodplain habitats that provide fish access to shelter, foraging, and spawning opportunities. Our study advances the understanding of these processes by exploring the importance of coupled longitudinal–lateral connectivity for determining species occurrence in headwater streams of the Amazon. Using a multispecies occupancy model, we revealed a clear pattern of species addition in the downstream direction in temporary floodplain ponds, associated with changes in the pool of potential colonists present in the channel and with increasing lateral hydrologic connectivity. Species that are more tolerant of stagnant waters and those able to disperse in shallow habitats (e.g., Anablepsoides micropus) occurred frequently in ponds along the entire longitudinal extent, whereas those species preferring lotic habitats were present only in the most downstream sites. We also observed increasing similarity of pond and channel communities with distance downstream. This study provides insights on the spatial structuring of tropical fish communities in response to flood-induced hydrologic connectivity and further highlights the vulnerability of floodplain fishes to modification in flooding regimes.
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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 | 0.000 | 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".