Holocene vegetation history and fire regimes of <i>Pseudotsuga menziesii</i> forests in the Gulf Islands National Park Reserve, southwestern British Columbia, Canada
Bibliographic record
Abstract
Abstract Pollen analysis of a 9.03-m-long lake sediment core from Pender Island on the south coast of British Columbia was used to reconstruct the island's vegetation history over the last 10,000 years. The early Holocene was characterized by open mixed woodlands with abundant Pseudotsuga menziesii and a diverse understory including Salix and Rosaceae shrubs and Pteridium aquilinum ferns. The establishment of Quercus garryana savanna-woodland with P. menziesii and Acer macrophyllum followed deposition of the Mazama tephra until ~ 5500 cal yr BP, when these communities gave way to modern mixed P. menziesii forest. Charcoal analyses of the uppermost sediments revealed low charcoal accumulation over the last 1300 years with a mean fire return interval (mFRI) of 88 years. Fires were more frequent (mFRI = 50 yr) during the Medieval Climate Anomaly (MCA) with warm, dry conditions facilitating a higher fire frequency than during the Little Ice Age, when fires were infrequent. Given the projected warming for the next 50–100 years, land managers considering the reintroduction of fire to the Gulf Islands National Park Reserve may want to consider using the mFRI of the MCA as a baseline reference in prescribed burning strategies.
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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 | 0.000 |
| 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".