A review of lethal thermal tolerance among freshwater mussels (Bivalvia: Unionida) within the North American faunal region
Bibliographic record
Abstract
Freshwater mussels of the order Unionida are currently one of the most imperiled groups of organisms in the North American faunal region. Accurate risk assessments and development of effective management strategies for remaining populations require knowledge of thermal limits in the face of increasing surface water temperature due to climate change and various anthropogenic factors. We conducted a systematic literature review of unionid mussels (order Unionida, families Margaritiferidae and Unionidae) in the North American faunal region to (1) summarize lethal thermal tolerance data by life stage and taxonomy, (2) discuss ecological and climate change implications of existing lethal tolerance data, and (3) identify needs for future research. We identified lethal tolerance estimates for only 28 of 302 species in the families Unionidae and Margaritiferidae. The mean acute median lethal temperatures were 32.8 °C for glochidia (19 species), 35.0 °C for juveniles (13 species), and 36.3 °C for adults (4 species). Generally, glochidia were less tolerant than juveniles or adults of the same species—but there were several exceptions. Generally, Amblemini had the highest acute and chronic thermal tolerance of all tribes followed by Anodontini, Pleurobemini, Lampsilini, and Quadrilini. Acclimation temperature affected lethal tolerance endpoints in less than half (52 of 145) of comparisons within species. Lethal tolerance data for additional species, combined with a comprehensive database of in situ surface water temperatures, would be useful for modeling the frequency and duration of lethal limit exceedance in North America and identifying populations currently living at or near their upper lethal limits.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".