Seasonal and Ontogenic Shifts in Microhabitat Selection by Fishes in the Shallow Waters of the Detroit River, a Large Connecting Channel
Bibliographic record
Abstract
Abstract We examined the relationship between microhabitat variables and fish distributions in a large connecting channel, the Detroit River. Fishes were sampled by boat seine at 60 sites in shallow (<2.5 m) Canadian waters in May, July, and September 2004. Length‐frequency distributions were used to separate species into small‐ and large‐species size categories. Fish–microhabitat associations were examined by applying canonical correspondence analysis separately for each season. Small fishes were often more strongly associated with microhabitat variables than large conspecifics. For example, small centrarchids were more strongly associated with complex macrophytes than large centrarchids in the spring; however, this pattern varied among seasons. We attribute the stronger microhabitat associations of small fishes to predator avoidance. Small‐bodied species also selected habitats that provided protection against predation: The spotfin shiner Cyprinella spiloptera preferred shallow water, and the round goby Neogobius melanostomus preferred coarse substrate. We observed a strong difference in microhabitat preferences between the small and large size categories of a species. Fish size played a greater role than season in determining fish–microhabitat associations. We found that macrophytes with a complex morphological structure were the most important factor in determining fish distributions in all seasons, while depth ranked second or third in importance. Fishes use an array of microhabitats in the Detroit River, and habitat heterogeneity is essential for promoting a diverse fish assemblage.
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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".