Increased plant biomass in a High Arctic heath community from 1981 to 2008
Bibliographic record
Abstract
The Canadian High Arctic has been warming for several decades. Over this period, tundra plant communities have been influenced by regional climate change, as well as other disturbances. At a site on Ellesmere Island, Nunavut, Canada, we measured biomass and composition changes in a heath community over 13 years using a point-intercept method in permanent plots (1995-2007) and over 27 years using a biomass harvest comparison (1981-2008). Results from both methods indicate that the community became more productive over time, suggesting that this ecosystem is currently in transition. Bryophyte and evergreen shrub abundances increased, while deciduous shrub, forb, graminoid, and lichen cover did not change. Species diversity also remained unchanged. Because of the greater evergreen shrub cover, canopy height increased. From 1995 to 2007, mean annual temperature and growing season length increased at the site. Maximum thaw depth increased, while soil water content did not change. We attribute the increased productivity of this community to regional warming over the past 30-50 years. This study provides the first plot-based evidence for the recent pan-Arctic increase in tundra productivity detected by satellite-based remote-sensing and repeat-photography studies. These types of ground-level observations are critical tools for detecting and projecting long-term community-level 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".