Long-term biodiversity erosion: limited co-existence of the Eurasian zebra mussel and native mussels in a North American river after 25 years
Bibliographic record
Abstract
North American unionid mussel populations have experienced significant mortality due to competition and fouling by the Eurasian zebra mussel Dreissena polymorpha (Pallas, 1771). Habitats whose water chemistry is suboptimal for the zebra mussel could plausibly serve as refugia in which unionids and zebra mussels co-exist. The Richelieu River, invaded by the zebra mussel in the mid-1990s, has a mean calcium concentration (∼18 mg L−1) believed insufficient for supporting a zebra mussel population capable of severely damaging unionids. Using a 25-year dataset, we tested how unionid diversity and abundance have changed along with zebra mussel fouling levels in the river over time. Local unionid populations suffered major declines across sites regardless of their distance from the river’s headwaters, Lake Champlain—a constant source of zebra mussel larvae. Over the past 25 years, unionid diversity and abundance have eroded to a similar extent and followed a similar timeline of population decline as has been observed in invaded calcium-rich habitats. We hypothesize that sustained exposure to zebra mussel fouling and food competition has produced a limited co-existence in which long-term impacts of zebra mussels have accrued.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".