Paleovegetation Reconstruction from Soil Phytoliths of a Ceremonial Site Complex at Maok-Skoistch on the Red Deer River, Alberta, Canada
Bibliographic record
Abstract
Maok-skoistch (Nitsitapii for Sacred Red Rock Place) is in the dry mixed grasslands of southwestern Alberta. It sits on a horseshoe bend of the Red Deer River approximately 40 kilometers from its confluence with the South Saskatchewan River. This area contains numerous stone constructions associated with First Nations groups and their ancestors. The purpose of this study is to investigate the paleovegetation of this area to understand local and regional environmental changes. A secondary purpose is to try to detect human influence on paleovegetation. I used phytoliths extracted from two sediment columns and the modern surface as a vegetational and environmental proxy. A sediment column extracted from a depression, or slough, on the upland prairie begins circa 5700 cal BP and provides data on the regional paleovegetation. A second column from a wooded riparian coulee in the river valley (a micro-environment) begins circa 3440 cal BP and records local vegetational changes. There is little available literature on phytoliths of the Canadian Prairies, to say nothing of the micro-environments within the region such as riparian coulees. I created a morphotype reference collection from the available relevant literature on grassland and forest phytolith assemblages. I detail how I developed a phytolith extraction protocol tailored to the sampled sediments, including the pitfalls I encountered. This section may be of use to those who have not extracted phytoliths before. I used environmental index formulae to investigate paleovegetational dynamics. I used Principal Components Analysis to find similar assemblages and to compare them to modern surface assemblages. The paleovegetation at the upland slough conforms to the synoptic record of environmental changes. I found the river valley coulee paleovegetation responds most strongly to local conditions. Soil moisture appears to be the strongest factor in paleovegetational changes. Interestingly, the coulee record may be responsive to precipitation and glacial meltwater changes in the Rockies where the Red Deer River begins. The phytolith knowledge base in the Canadian Prairies is not robust enough yet to achieve the resolution necessary to detect human influences on paleovegetation. I outline some ideas and avenues for future research to remedy this situation.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".