Cold tolerance varies among invasive populations of the Asian clam (<i>Corbicula fluminea</i>)
Bibliographic record
Abstract
The distribution of the subtropical Asian clam (Corbicula fluminea (O.F. Müller, 1774)), one of the world’s most invasive freshwater molluscs, is reportedly constrained by a lower thermal tolerance limit of 2 °C. Although its occurrence in north temperate regions is typically restricted to artificially heated waterbodies, the species has been found to overwinter in unheated lakes and rivers. In laboratory experiments, we compared the cold tolerance of populations from several geographically distinct sites spanning 35°N to 46°N in eastern North America. Each population contained individuals that fully recovered from 2 months of continuous exposure to near-freezing (1 °C) conditions, contrary to published accounts of C. fluminea’s thermal ecology. Survivorship increased with body size and was enhanced by prior acclimation to a low temperature (10 °C) compared with a higher one (18 °C). When acclimated to 10 °C, clams from northern populations exhibited greater survivorship (55.0% ± 16.1%) than those from southern populations (26.7% ± 19.2%). However, one southern population demonstrated survivorship as great as that of the most tolerant northern population, suggesting that its clams could overwinter in unheated northern waterbodies. Differences among populations indicate either that contemporary evolution has occurred or that developmental plasticity shapes future acclimation responses.
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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 | 0.000 | 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) | 0.001 | 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".