Regional, watershed, and site-specific environmental influences on fish assemblage structure and function in western Lake Superior tributaries
Bibliographic record
Abstract
The relative importance of regional, watershed, and in-stream environmental factors on fish assemblage structure and function was investigated in western Lake Superior tributaries. We selected 48 second- and third-order watersheds from two hydrogeomorphic regions to examine fish assemblage response to differences in forest fragmentation, watershed storage, and a number of other watershed, riparian, and in-stream habitat conditions. Although a variety of regional, fragmentation, and storage-related factors had significant influences on the fish assemblages, water temperature appeared to be the single most important environmental factor. We found lower water temperatures and troutsculpin assemblages at lower fragmentation sites and higher temperatures and minnowsuckerdarter assemblages as storage increased. Factors related to riparian shading and flow separated brook trout streams from brown trout (Salmo trutta) rainbow trout (Oncorhynchus mykiss) streams. Functionally, fish assemblages at lower fragmentation sites were dominated by cold-water fishes that had low silt tolerance and preferred moderate current speeds, while fishes with higher silt tolerances, warmer temperature preferences, and weaker sustained swimming capabilities were most common at higher storage sites. Our results suggest that site-specific environmental conditions are highly dependent on regional- and watershed-scale characters and that a combination of these factors operates in concert to influence the structure and function of stream fish assemblages.
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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 | 0.001 | 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) | 0.001 | 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".