Ecosystem change and stability over multiple decades in the Swedish subarctic: complex processes and multiple drivers
Bibliographic record
Abstract
The subarctic environment of northernmost Sweden has changed over the past century, particularly elements of climate and cryosphere. This paper presents a unique geo-referenced record of environmental and ecosystem observations from the area since 1913. Abiotic changes have been substantial. Vegetation changes include not only increases in growth and range extension but also counterintuitive decreases, and stability: all three possible responses. Changes in species composition within the major plant communities have ranged between almost no changes to almost a 50 per cent increase in the number of species. Changes in plant species abundance also vary with particularly large increases in trees and shrubs (up to 600%). There has been an increase in abundance of aspen and large changes in other plant communities responding to wetland area increases resulting from permafrost thaw. Populations of herbivores have responded to varying management practices and climate regimes, particularly changing snow conditions. While it is difficult to generalize and scale-up the site-specific changes in ecosystems, this very site-specificity, combined with projections of change, is of immediate relevance to local stakeholders who need to adapt to new opportunities and to respond to challenges. Furthermore, the relatively small area and its unique datasets are a microcosm of the complexity of Arctic landscapes in transition that remains to be documented.
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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 | 0.001 | 0.002 |
| 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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".