Changing climate, vegetation, and fire disturbance in a sub-boreal pine-dominated forest, British Columbia, Canada
Bibliographic record
Abstract
Holocene climate, vegetation, and fire history were reconstructed using pollen, molluscs, and charcoal from two lake sediment records (Scum and Norma lakes) collected from the Chilcotin Plateau, British Columbia, Canada. In the late-glacial period, cold steppe prevailed and fire was limited. Artemisia steppe expanded in the earliest Holocene as climate warmed and conditions became dry, with shallow basins drying out. High-frequency surface fires maintained the steppe. An increase in Pinus after 10 200 cal BP signals moistening and the establishment of Pinus ponderosa P. & C. Lawson and Pinus contorta Dougl. ex Loud. stands, with surface fires in the former and higher severity fires in the latter. Cooling around 8500 cal BP favored P. contorta, and a crown fire regime likely prevailed, with intermittent surface fires. Shallow basins began to fill with water. In the mid-Holocene, basins filled further and Picea increased slightly in abundance. Fire frequency decreased, though severity increased. In the last three millennia, modern P. contorta dominated forests were established, with mixed-severity fire disturbance. Considering the future, the results of this study align well with ecosystem climate niche simulations, indicating that non-arboreal and open-forest communities may again prevail widely on the plateau, together with surface fires. Land managers need to develop strategies to manage the upcoming transformation.
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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 | 0.002 | 0.000 |
| Open science | 0.001 | 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".