Native freshwater species get out of the way: Prussian carp (<i>Carassius gibelio</i>) impacts both fish and benthic invertebrate communities in North America
Bibliographic record
Abstract
) are one of the most noxious non-native species in Eurasia. Recently, Prussian carp, a non-native freshwater fish species, were genetically confirmed in Alberta, Canada and have been rapidly expanding their range in North America since establishment. Given their rapid range expansion, there is an increasing need to determine how Prussian carp may impact native species. We assessed the severity of the Prussian carp invasion by (i) determining their impact on fish communities, (ii) assessing their impact on benthic invertebrate communities, (iii) evaluating if Prussian carp alter abiotic conditions, and (iv) identifying where we find higher abundances of Prussian carp. When Prussian carp were established, we found significant changes to the fish community. Correspondingly, the degree of impact to benthic invertebrate communities was related to the stage of invasion (none, early or recent), where changes in fish communities were significantly concordant with changes in benthic invertebrate communities. Finally, we found that higher abundances of Prussian carp were significantly associated with lower abundances of a majority of native fish species. Altogether, using three lines of evidence, we determine that Prussian carp can have wide-ranging impacts on freshwater ecosystems in North America, pressing the need for management intervention.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".