Distinguishing prehistoric human influence on late-Holocene forests in southern Ontario, Canada
Bibliographic record
Abstract
The influence of Native Americans on late-Holocene forests of North America remains a contentious issue, as it is unclear whether vegetation transitions inferred from pollen records are a product of prehistoric human disturbance. In southern Ontario, the adoption of maize agriculture coincides with neoglacial cooling, so distinguishing the relative roles of prehistoric people and climatic change in shaping forest composition requires that pollen records be interpreted in a regional context. In this study, we objectively identify pollen records from the southern Ontario region which exhibit periods of significant pre-European anthropogenic disturbance in the context of the archeological record. This enables a comparison of pollen records shaped primarily by climatic cooling with those disturbed by prehistoric human forest clearance. Our results suggest that regional-scale late-Holocene cooling resulted in a gradual and synchronous shift from deciduous to boreal taxa. However, forest clearance by Native Americans resulted in a secondary succession characterized by the replacement of late-successional beech-maple forest with ruderal species, grasses and poplar, followed by mid-successional oak and white pine. This transition consistently coincides in space and time with an increase in archeological records of human occupation. The method we have developed here to distinguish significant prehistoric human impacts could be applied to pollen records in other regions, or on a continental scale.
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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 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".