Dendroclimatic relationships and possible implications for mountain birch and Scots pine at treeline in northern Sweden through the 21st centuryThis article is a contribution to the series Tree recruitment, growth, and distribution at the circumpolar forest–tundra transition.
Bibliographic record
Abstract
Changing climate in the Arctic is expected to have significant effects on the pattern and distribution of terrestrial vegetation. Species characteristic of specific zones in the mountains of northern Sweden have been shown to migrate up- and down-slope with changes in climate over the Holocene. This study evaluates the potential for Scots pine (Pinus sylvestris L.) to become a treeline dominant at Fennoscandian treelines, replacing mountain birch (Betula pubescens subsp. czerepanovii (Orlova) Hämet-Ahti). Data from paired mountain birch and Scots pine tree-ring chronologies for eight locations in northern Sweden are used to develop climate – tree ring width index (RWI) relationships. Modeled climate–RWI relationships are then used to predict the relative RWI values of the two species under a suite of climate-forcing scenarios using an ensemble of three global climate models. Results indicate that mountain birch and Scots pine RWI are both correlated with summer temperatures, but Scots pine is more likely than mountain birch to be influenced by moisture conditions. Predictions of RWI under future climate conditions indicate that mountain birch is unlikely to be replaced by Scots pine within the next century.
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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 | 0.000 | 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) | 0.001 | 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".