Spatio-temporal changes in littoral fish community structure along the St. Lawrence River (Québec, Canada) following round goby (Neogobius melanostomus) invasion
Bibliographic record
Abstract
The round goby (Neogobius melanostomus), a small Ponto-Caspian bottom-dwelling fish species, was first observed in the St. Lawrence River in 1997. After twenty years, it is now considered as one of the most successful invaders of the St. Lawrence River. Despite the elevated abundances observed throughout the river, little is known about its impacts on the littoral/mid-shore fish community. In this study, we used a large dataset obtained from an annual standardized fish survey held in the St. Lawrence River to analyze the impacts of round goby on littoral native fish community and native predator assemblages within five distinct segments of the river characterized by different round goby abundances. Throughout the system, the round goby negatively impacted the abundances of tessellated darter (Etheostoma olmstedi) likely as a consequence of competitive exclusion. In contrast, the small pelagic/demersal brook silverside (Labidesthes sicculus) and emerald shiner (Notropis \natherinoides) increased in abundance. Indirect food web effects, such as predation pressure relaxation, are suspected. Native predator abundances exhibited contrasting trends in the different sectors analyzed, with the exception of smallmouth bass (Micropterus dolomieu) abundances that increased in all fluvial lakes. We hypothesize that trophic relationships between littoral fish and native predators are influencing the outcomes of the round goby invasion of the St. Lawrence River.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".