Late Quaternary biomes of Canada and the eastern United States
Bibliographic record
Abstract
Abstract Pollen data have been used to construct biome maps for today, 6000 14 C yr bp and 18,000 14 C yr bp for Canada and the eastern United States. The inferred modern biome distributions agree well with independent reconstructions of North American vegetation prior to European settlement. Some discrepancies between the pollen data and the modern potential vegetation are caused by post‐settlement clearing of the landscape and the consequent increase of herbaceous types in the recent pollen record. Biome distributions at 6000 14 C yr bp reflected the warmer and drier conditions then prevalent in the continental interior, but the overall position of biomes was similar to that of today. The boreal treeline in North America was not significantly north of its present position, in contrast to the 100–200 km shift reported for Siberia. At the last glacial maximum (18,000 14 C yr bp ), steppe and tundra were prevalent in the Midwest and north‐western Canada, and coniferous forests and woodlands grew in eastern North America. The open vegetation at 18,000 14 C yr bp was probably due to drier conditions and/or lower concentrations of atmospheric CO 2 . The composition and physical structure of biomes is not constant over time. Mid‐Holocene biomes were similar in structure to those of today, but shifts in the relative importance of individual plant functional types are large enough that the physical properties of biomes, such as albedo, canopy conductance and surface roughness, are likely to have varied even during the Holocene. Last glacial maximum biomes were structurally different from their modern counterparts. The biome maps therefore may obscure significant vegetational changes in space and time during the late Quaternary. The difference between the highest and next highest affinity scores for each sample measures how strongly affinity scores discriminate among biomes. For many biomes, the difference is not large, and affinity score ties are not uncommon, highlighting the importance of tie‐break procedures when using the biomization method.
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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 | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".