Impacts of the Eurasian round goby (<i>Neogobius melanostomus</i>) on benthic communities in the upper St. Lawrence River
Bibliographic record
Abstract
An invasive benthivorous fish, the Eurasian round goby ( Neogobius melanostomus ) is abundant throughout the lower Great Lakes – St. Lawrence River system. We examined the round goby’s potential to alter benthic communities on cobble substrates in the upper St. Lawrence River. During the summers of 2008 and 2009, macroinvertebrates and benthic algae were sampled across sites with varying goby densities. Archived data from various sites in 2004–2006 (prior to invasion) were available for comparison. Macroinvertebrate community composition varied significantly among samples grouped into categories based on goby density and time since invasion. Macroinvertebrate diversity and dominance by large-bodied taxa declined with increasing goby density. Surprisingly, dreissenid biomass did not vary consistently with goby density, in contrast to studies in the Great Lakes. The biomass of all non-dreissenid taxa was negatively correlated with increasing goby density across sites and over time at three of four sites. Negative effects were most pronounced on the biomass of gastropods. Benthic algal biomass increased with goby density across sites, suggesting a trophic cascade driven by the impacts of gobies on gastropods and other algivores. Our study highlights the potential ecosystem impacts of an expanding goby population in a large 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 | 0.000 |
| 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 | 0.001 |
| 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".