Watershed, reach, and riparian influences on stream fish assemblages in the Northern Lakes and Forest Ecoregion, U.S.A.
Bibliographic record
Abstract
We analyzed data from 79 watersheds in an undegraded U.S. ecoregion to identify key environmental factors that explained stream fish assemblage patterns and to evaluate the relative influence of environmental factors operating at different spatial scales. A few key factors from the watershed, reach, and riparian scale explained a significant amount of the variance in fish attributes. Three environmentfish associations were evident. Top carnivores and intolerant cold-water fishes were associated with relatively narrow, deep, high-gradient, cold streams with strong groundwater inputs. Tolerant cyprinids occurred in small streams with low groundwater input, low dissolved oxygen, and abundant macrophytes. A diverse assemblage (Cyprinidae, Catostomidae, Centrarchidae, Percidae) existed in warm, wide streams in watersheds dominated by lacustrine sand and gravel geology and abundant wetlands and lakes. Overall, reach-scale variables directly explained the most, watershed-scale variables less, and riparian-scale variables the least variation in fish attributes. Watershed and riparian variables had indirect connections with fishes through their direct influence on reach variables. In conjunction with findings from more degraded regions, we conclude that the relative influence of reach-scale variables on fishes are greatest in undegraded areas and that direct effects of watershed-scale variables are increasingly important as human modifications of the landscape increase.
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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".