Plant–Environment Interactions in the Low Arctic Torngat Mountains of Labrador
Bibliographic record
Abstract
Abstract The eastern Canadian Subarctic and Arctic are experiencing significant environmental change with widespread implications for the people, plants, and animals living there. In this study, we integrate 10 years of research at the Nakvak Brook watershed in Torngat Mountains National Park of Canada, northern Labrador, to assess the sensitivity of ecological and geomorphological systems to regional climate warming. A time series of the Normalized Difference Vegetation Index indicates that the area has undergone a significant greening trend over the past four decades. Analyses of shrub cross sections suggest that greening has been caused by a combination of rapid establishment and growth that began in the late 1990’s and coincided with warmer growing season temperatures. Recent (2010–2015) vegetation change has been subtle and heavily moderated by soil moisture status. Plant canopy height is greater in wet areas and has an insulating effect on ground surface temperatures during the winter, a consequence of snow trapping by shrub canopies. Observations of subsurface conditions indicate that the study site is best characterized as having discontinuous near-surface permafrost. The importance of subsurface conditions for above-ground vegetation depends on the geomorphological context, with plants in wet areas underlain by fine materials being the most likely to be growth-limited by permafrost, thus being potential hot-spots for future change. With the expectation of sustained climate change, loss of adjacent sea ice, and proximity to the forest-tundra ecotone, it is likely that the Torngat Mountains will continue to be an area of rapid environmental change in the coming decades.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".