Hypoxic refuges, predator–prey interactions and habitat selection by fishes
Bibliographic record
Abstract
Localized hypoxic habitats were created in Delta Marsh, Manitoba, Canada to determine the potential of regions of moderate hypoxia to act as refuges for forage fishes from piscine predators. Minnow traps and giving-up density (GUD) plates (plexiglas plates covered with trout crumble and fine gravel) were used to assess habitat use and perceived habitat quality for forage fishes, respectively, while passive integrated transponder tags provided data on habitat use by predator species to assess the level of predation risk. Data were collected both before and after a hypoxia manipulation (2-3 mg l(-1) dissolved oxygen, DO) to create a before-after control-effect style experiment. Fathead minnows Pimephales promelas were more abundant and consumed more food from GUD plates in hypoxic bays after the DO manipulation, indicating hypoxic locations were perceived as higher quality, lower-risk habitats. The frequency of predator visits was not consistently affected. The duration of visits, and therefore the total time spent in these habitats, however, was significantly shorter. These predator data, combined with the prey information, are consistent with the hypothesis that hypoxic regions function as predator refuges. The refuge effect is not the result of predator exclusion, however; instead predators are rendered less capable of foraging and pose less of a threat in hypoxic locations.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".