Postglacial vegetation migration facilitated by outposts on proglacial lake islands in eastern North America
Bibliographic record
Abstract
Postglacial vegetation colonization that followed ice retreat and proglacial lakes drainage in north-eastern America occurred rapidly, more rapidly than expected based on the modern dispersal capacities of boreal mixedwood trees. Paleo-islands from proglacial Lake Ojibway in Québec (Canada) were afforested early, before the final drainage of the lake. We hypothesized that these paleo-islands could have acted as outposts of migration and thus, could explain the rapid afforestation of lowlands observed. To determine if postglacial colonization occurred as a south-north front from the southern margin of Lake Ojibway or if islands acted as migration outposts, we estimated the date of first arrival of the main taxa of the current boreal mixedwood forest. We studied southern sites never covered by proglacial Lake Ojibway, sites that were islands within Lake Ojibway, and northern lowland sites that were liberated after the final drainage of proglacial Lake Ojibway. Taxa arrival was estimated as a sharp rise of the pollen percentage or as the occurrence of macro-remains within the sediments of small lakes dated with radiocarbon. Then we compared migration scenarios where colonization occurred gradually from south to north from the southern margin of proglacial Lake Ojibway and where paleo-islands of Lake Ojibway were first colonized through long-distance dispersal, thus becoming sources of seeds readily available to colonize lowland sites after the final drainage of Lake Ojibway. Finally, we compared the migration rates from the scenarios with the current mean dispersal capacities of the studied taxa. The migration rates estimated without taking the paleo-islands into account are too slow to explain the rapid afforestation observed following the final drainage of proglacial Lake Ojibway. Only the migration rates estimated from the scenarios with paleo-islands were comparable to the current mean dispersal capacity of the boreal mixedwood taxa. Thus, paleo-islands acted as stepping stones during postglacial migration, which explains why the lowlands were rapidly colonized. Larger paleo-islands and those located closer to the southern margin of the proglacial Lake were colonized first, in line with the theory of island biogeography.
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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 | 0.001 | 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".