Cultural Forests in Cross Section: Clear-Cuts Reveal 1,100 Years of Bark Harvesting on Vancouver Island, British Columbia
Bibliographic record
Abstract
Culturally modified trees (CMTs) provide tangible evidence of long-term forest use by Indigenous peoples. In Northwest Coast cedar forests, this record rarely spans beyond the last three centuries because older bark-harvest scars have been obscured through taphonomic processes such as natural healing and decay. Thus, archaeological visibility and identification are hindered. Here, I recover chronologies of ancient forest harvesting using a post-impact assessment methodology of targeting old-growth clear-cuts in southern Nuu-chah-nulth territories on the west coast of Vancouver Island, British Columbia, Canada. Bark-peeling scars are identified and dated in cross section by growth-ring patterns of recently logged trees. Approximately half of all bark-peeling scars are “embedded” inside healing lobes, suggesting at least half of all such CMTs are effectively invisible in standing forests. Features in these post-impact surveys predated those discovered in conventional archaeological impact assessments by a mean of almost a century. Additionally, one of the oldest continually used cultural forests ever recorded, dating to AD 908, is found in the Toquaht Nation traditional territory. These findings uncover measurable frequencies of cedar-bark harvesting generations prior to the contact period and reveal the inadequacy of heritage protections for old-growth cedar stands.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 teacher head, 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".