Increases in graminoids after three decades of change in the High Arctic
Bibliographic record
Abstract
Climate change portends serious implications for Arctic vegetation. Understanding these effects is likely to be enhanced with long-term observations from permanent plots. I evaluated three decades of change in tundra vegetation from 80 permanent plots on south-eastern Victoria Island, Nunavut, Canada. I compared baseline (1991 and 1992) and contemporary (2019 and 2022) periods in the cover and frequency of graminoids, mosses and common species of forbs, shrubs and lichens. I found substantial shifts in cover of several species and growth forms—an increase in graminoids, decreases in Dryas integrifolia, Polygonum viviparum and Saxifraga oppositifolia, and marginally significant declines in mosses and Cassiope tetragona, but no detectable changes in other groups. The decline in Dryas integrifolia was more pronounced at lower elevations and was noticeable as patches of apparent mortality, inside the plots and elsewhere. The shifts in species abundance were not significantly correlated with each other, nor with changes in soil depth. These changes, manifest as communities with more abundant graminoids, are consistent with expected climate change effects in colder regions of the Arctic. Repeated observations of permanent plots can aid in detecting and understanding long-term ecological change.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".