Interpopulational variation in the cold tolerance of a broadly distributed marine copepod
Bibliographic record
Abstract
Latitudinal trends in cold tolerance have been observed in many terrestrial ectotherms, but few studies have investigated interpopulational variation in the cold physiology of marine invertebrates. Here, the intertidal copepod Tigriopus californicus was used as a model system to study how local adaptation influences the cold tolerance of a broadly distributed marine crustacean. Among five populations spanning 18° in latitude, the following three metrics were used to compare cold tolerance: the temperature of chill-coma onset, the chill-coma recovery time and post-freezing recovery. In comparison to copepods from warmer southern latitudes, animals from northern populations exhibited lower chill-coma onset temperatures, shorter chill-coma recovery times and faster post-freezing recovery rates. Importantly, all three metrics showed a consistent latitudinal trend, suggesting that any single metric could be used equivalently in future studies investigating latitudinal variation in cold tolerance. Our results agree with previous studies showing that populations within a single species can display strong local adaptation to spatially varying climatic conditions. Thus, accounting for local adaptation in bioclimate models will be useful for understanding how broadly distributed species like T. californicus will respond to anthropogenic climate change.
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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 | 0.001 | 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".