Early afforestation on islands of proglacial Lake Ojibway as evidence of post-glacial migration outposts
Bibliographic record
Abstract
At the end of the last glacial period in the northern hemisphere, meltwater from receding ice sheets accumulated into large proglacial lakes, potentially limiting postglacial afforestation. We explored whether former islands of proglacial Lake Ojibway (Canada) (hilltops in the current landscape) could have acted as migration outposts and thus accelerated the postglacial migration. We extracted sediments from two small lakes located on “paleo-islands” and used XRF to detect changes in soil erosion and vegetation biomass. We also used plant macro-remains and wood charcoal to determine if (and which) tree species colonized the sites and to detect local fire events. Organic sediment accumulation started around 9657 and 9947 cal. yr BP at Lakes Perché and Despériers, respectively, before the level of Lake Ojibway started to decrease and liberate parts of the studied landscape ca 9400 cal. yr BP. Lithogenic elements (Ti, K, Sr, Fe, Zr, and Rb) decreased between the beginning of organic sediment accumulation and 8800–8700 cal. yr BP, indicating reduced soil erosion, possibly due to soil stabilization by vegetation. Then, the S/Ti ratio, a proxy of organic matter increased around 8800 and 8400 cal. yr BP. The earliest tree macro-remains ( Larix laricina and Pinus spp.) were found between 9850 and 9500 cal. yr BP. Local fires were detected around 9820 and 8362 cal. yr BP. Early afforestation occurred on the islands of Lake Ojibway, 200 and 450 years before its level started to decrease, confirming that some islands acted as migratory outposts accelerating postglacial migration.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".