Spatial heterogeneity and genetic variation in the copepod Neocalanus cristatus along two transects in the North Pacific sampled by the Continuous Plankton Recorder
Bibliographic record
Abstract
We present a macrogeographic study of spatial heterogeneity in an important subarctic Pacific copepod and describe the first genetic analysis of population structure using Continuous Plankton Recorder (CPR) samples. Samples of Neocalanus cristatus were collected at a constant depth of ∼7 m from two CPR tow-routes, (i) an east–west ∼6500-km transect from Vancouver Island, Canada to Hokkaido Island, Japan, and (ii) a north–south transect of ∼2250 km from Anchorage, Alaska to Tacoma, Washington. Analysis of these samples revealed three features of the biology of N. cristatus. First, N. cristatus undergoes small-scale diel vertical migration that is larger among stages CV–adult (3–6 times more abundant at 7 m at night), than stages CI–CIV (only 2–4 times higher at night). Secondly, while there were no regions where N. cristatus did not appear, each transect sampled a few large-scale macrogeographic patches. Thirdly, an analysis of molecular variation, using a partial sequence of the N. cristatus cytochrome oxidase I gene, revealed that 7.3% (P < 0.0001) of the total genetic variation among N. cristatus sampled from macrogeographic patches by the CPR could be explained by spatial heterogeneity. We suggest that spatial heterogeneity at macrogeographic scales may be important in plankton evolution.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".