Contrasting climate- and land-use-driven tree encroachment patterns of subarctic tundra in northern Norway and the Kola PeninsulaThis article is a contribution to the series Tree recruitment, growth, and distribution at the circumpolar forest–tundra transition.
Bibliographic record
Abstract
High-latitude regions are experiencing substantial climate change, and the forest–tundra transition is assumed to sensitively track these changes through advancing treeline and increased tundra encroachment. However, herbivores may influence these responses. The present study addresses, through analyses of age structures, growth characteristics, and climate correspondence, how mountain birch (Betula pubescens Ehrh. ssp. czerepanovii (Orlova) Hämet-Ahti) treelines and sapling cohorts beyond the treeline have responded to the last decade’s warming in six North European subarctic areas with different climate and grazing characters. The results show different response patterns among areas representing advancing, stationary, and possibly retreating treelines. Recruitment was abundant over the last decades in all areas except one, with predominantly arctic conditions, where both tree and sapling cohorts were old. Areas with high annual precipitation show advancing birch populations characterized by young individuals and partly overlapping tree and sapling age distributions. Areas in reindeer herding districts show stationary or retreating birch populations characterized by nonoverlapping age distributions and low sapling survival. Recruitment patterns beyond the treeline generally corresponded with non-growing-season climate variables, mainly precipitation, indicating the importance of a protecting snow cover. The results highlight the important interplay between abiotic and biotic control over tundra encroachment and treeline dynamics and the importance of multisite studies when addressing responses to warming.
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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 | 0.001 | 0.000 |
| 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".