The biogeography of aquatic macrophytes in North America since the Last Glacial Maximum
Bibliographic record
Abstract
Abstract AimTo document the post‐glacial migration of the major aquatic macrophytes of North America. LocationNorth America north of Mexico. MethodsAquatic macrophyte pollen were extracted from the North American Pollen Database. The modern pollen distribution was mapped and related to the climate to document the geographical and climatic constraints on these taxa. The fossil pollen were mapped at 2‐ka intervals for the past 21 ka. ResultsNumerous genera were present in ice‐free Alaska during the Last Glacial Maximum, and south of the Laurentide Ice Sheet in the southeast. Those taxa with the widest modern climatic ranges migrated rapidly into ice‐marginal areas, first in the west and then in the east of North America. Subsequent changes in the range and abundance were smaller. Main conclusionsThere were four migration routes of aquatic macrophytes during the late‐glacial and post‐glacial periods: a southward migration from Alaska between 14–13 and ka, a northern migration in the west at the same time into the ice‐free Cordilleran region, and movements east and west of Appalachia as early as 19 ka for some taxa into the lower Mississippi and into the upper Mississippi and Great Lakes by 11 ka. As the Laurentide ice sheet wasted, aquatic taxa with the broadest contemporary temperature tolerances rapidly occupied ice‐marginal environments.
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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 | 0.001 |
| 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".