Keep your feet warm? A cryptic refugium of trees linked to a geothermal spring in an ocean of glaciers
Bibliographic record
Abstract
Up to now, the most widely accepted idea of the periglacial environment is that of treeless ecosystems such as the arctic or the alpine tundra, also called the tabula rasa paradigm. However, several palaeoecological studies have recently challenged this idea, that is, treeless environments in periglacial areas where all organisms would have been exterminated near the glacier formed during the Last Glacial Maximum, notably in the Scandinavian mountains. In the Alps, the issue of glacial refugia of trees remains unanswered. Advances in glacier reconstructions show that ice domes did not cover all upper massifs, but glaciers filled valleys. Here, we used fossils of plant and malacofauna from a travertine formation located in a high mountain region to demonstrate that trees (Pinus, Betula) grew with grasses during the Lateglacial-Holocene transition, while the glacier fronts were 200-300 m lower. The geothermal travertine started to accumulate more than 14,500 years ago, but became progressively more meteogene about 11,500 years ago due to a change in groundwater circulation. With trees, land snails (gastropods) associated to woody or open habitats and aquatic mollusc were also present at the onset of the current interglacial, namely the Holocene. The geothermal spring, due to warm water and soil, probably favoured woody glacial ecosystems. This new finding of early tree growth, combined with other scattered proofs of the tree presence before 11,000 years ago in the western Alps, changes our view of the tree distribution in periglacial environments, supporting the notion of tree refugia on nunataks in an ocean of glaciers. Therefore, the tabula rasa paradigm must be revisited because it has important consequences on the global changes, including postglacial plant migrations and biogeochemical cycles.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".