The different strategies of Pinus sylvestris and Larix sibirica to deal with summer drought in a northern Mongolian forest–steppe ecotone suggest a future superiority of pine in a warming climate
Bibliographic record
Abstract
Pinus sylvesteris L. is locally common at the lower forest line to the steppe in Mongolia’s taiga forests, which are otherwise dominated by Larix sibirica Ledeb. The factors responsible for the occurrence of pine patches in the forest–steppe ecotone are insufficiently studied. We analyzed the response of P. sylvestris to summer drought in the western Khentey Mountains, northern Mongolia, by measuring shoot water potentials and exemplary measurements of δ13C signatures, CO2–H2O gas exchange, chlorophyll fluorescence yield, and concentrations of nonstructural carbohydrates. Pine trees growing in the forest–steppe ecotone show conservative water consumption with a sensitive stomatal regulation and relatively constant shoot water potentials under dry conditions. This might be a selective advantage for P. sylvestris against increasing aridity driven by global warming, since the main competitor, L. sibirica, often suffers from drought stress even under the current climate in the study area.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".