Fish Assemblage Structure in Great Lakes Coastal Wetlands
Bibliographic record
Abstract
PURPOSE: Coastal wetlands in the Great Lakes are important habitats for many fishes. The geographic scale and diversity of land uses in the region result in substantial environmental variation among coastal wetlands. METHODS: Annual surveys were conducted as part of the Great Lakes Coastal Wetland Monitoring Program (GLCWMP) to better understand wetland condition across the basin. Fyke nets were used to sample fish in 1,224 unique monodominant vegetation zones during 2011-2020. RESULTS: A total of 588,709 fish were captured, representing 109 different species. Yellow Perch (Perca flavescens) was the most abundant species in the catch (31%). DISCUSSION AND CONCLUSION: Preliminary results suggested that basin, hydrogeomorphic type, monodominant vegetation type, and sampling year were each associated with variation in fish assemblages. For instance, fish assemblages in the more oligotrophic Lakes Michigan, Huron, and Superior appeared more similar to each other than the more eutrophic Lakes Erie and Ontario. Lacustrine and barrier protected wetlands had similar fish assemblages while riverine wetlands had less variation in community structure than the other wetland types. While we found large amounts of variation in fish assemblage structure in Great Lakes coastal wetlands, we identified patterns that can be used to further define how fish assemblages vary across the Great Lakes basin.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 teacher head, 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".