Lake Erie beaches: diel variation in fish assemblage structure and implications for monitoring
Bibliographic record
Abstract
Knowledge of temporal variation in nearshore Laurentian Great Lakes fish assemblages is important for understanding species–habitat associations, how abiotic and biotic influences vary temporally, and when sampling should occur. Using spring and fall seining data from Lake Erie beaches, we compared day and night fish assemblages and tested for differences among sampling periods. Beaches were utilized by a diverse collection of Lake Erie basin fishes (one-third of known species). During all sampling periods, catches were dominated by cyprinid species (53–91%), and by invertivores and planktivorous fishes. Diel differences were detected in abundance, species richness and assemblage structure. Multivariate analyses (canonical analysis of principal coordinates) indicated that season had a larger influence on fish assemblage structure than diel period. Given observed temporal variation in assemblage structure, studies of Laurentian Great Lakes beach fishes should be restricted to a single time period (e.g. day-time spring sampling), or adopt sampling designs that permit diel period and season to be included as factors in analyses. Second, the large seasonal variation in assemblage composition combined with higher night species richness indicates that night sampling during both spring and fall would be the most efficient and comprehensive approach for beach fish inventory.
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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) | 0.000 | 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".