Late Holocene vegetation and climate change at Moraine Bog, Tiedemann Glacier, southern Coast Mountains, British Columbia
Bibliographic record
Abstract
Moraine Bog lies just outside the outermost lateral moraine of Tiedemann Glacier in the southern Coast Mountains of British Columbia. A sediment core taken from the wetland was analyzed for pollen, magnetic susceptibility, and loss on ignition to reconstruct changes in vegetation and climate during the late Holocene. Vegetation changed little between about 3500 and 2400 14C years BP. A period of local disturbance marked by deposition of a silty clay bed and increases in Alnus pollen, likely reflecting cooler moister conditions, coincides with an extensive Holocene advance of Tiedemann Glacier about 2400 14C years BP. Warm dry conditions between about 1900 and 1500 14C years BP are suggested by peak values of Pseudotsuga pollen and increasing Nuphar sclereids; the latter suggests lowered water levels. This period coincides with a time of drought and increased fire frequency in the southernmost Coast Mountains. About 1300 14C years BP, the forest became more coastal in composition with abundant Tsuga heterophylla and Abies. An increase in Tsuga mertensiana pollen suggests the onset of cool and wet conditions by ca. 500 14C years BP, coincident with the Little Ice Age. The record of inferred climate change at Moraine Bog is broadly synchronous with other paleoclimate records from the Coast Mountains and, at the centennial scale, with records elsewhere in the world.
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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 | 0.001 |
| Science and technology studies | 0.002 | 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) | 0.002 | 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".