Long-term assessment of ichthyoplankton in a large North American river system reveals changes in fish community dynamics
Bibliographic record
Abstract
Larval fishes are sensitive to abiotic conditions and provide a direct measure of spawning success. The St. Clair – Detroit River System, a Laurentian Great Lakes connecting channel with a history of environmental degradation, has undergone improvements in habitat and water quality since the 1970s. We compared 2006–2015 ichthyoplankton community data with those collected prior to remediation efforts (1977–1978) to identify patterns in spatial and temporal variability. Both assemblages exhibited a predictable phenology, with taxa from the subfamily Coregoninae dominant in early spring followed by families Osmeridae, Percidae, and Moronidae (May–June) and Cyprinidae and Clupeidae (June–August). While higher densities of larval fish were found in the Detroit River, greater taxa richness and Shannon diversity were observed in the St. Clair River. System wide, 14 new taxa were observed in the 2000s study period. In addition, relative densities of two nonnative species, alewife (Alosa pseudoharengus) and rainbow smelt (Osmerus mordax), declined since the 1970s. Increased larval fish richness and decreased densities of nonnative taxa in the 2000s are consistent with improvements to environmental conditions.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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 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".