Documenting ancient plant management in the northwest of North AmericaThis paper was submitted for the Special Issue on Ethnobotany, inspired by the Ethnobotany Symposium organized by Alain Cuerrier, Montréal Botanical Garden, and held in Montréal at the 2006 annual meeting of the Canadian Botanical Association.
Bibliographic record
Abstract
Ethnographic literature documents the pervasiveness of plant-management strategies, such as prescribed burning and other kinds of cultivation, among Northwest Peoples after European contact. In contrast, definitive evidence of precontact plant management has been elusive. Documenting the nature and extent of precontact plant-management strategies has relevance to historians, archaeologists, managers, conservationists, forest ecologists, and First Nations. In this paper, we summarize the various lines of evidence that have been, or could be, used to document ancient cultivation in the northwest of North America. We organize this discussion by the ecological consequences of ancient plant-management practices and their documented or potential visibility in the paleo-, neo-ecological, and archaeological records. Our review demonstrates that while finding evidence of ancient plant management can be difficult, such evidence can be found when innovative research methods are applied. Further, when various independent lines of evidence are compiled, reconstructions of past plant-management strategies are strengthened considerably.
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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 | 0.001 | 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 | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| 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".