Effects of Simulated Grazing in Ungrazed Wet Sedge Tundra in the High Arctic
Bibliographic record
Abstract
Wet sedge tundra communities in the High Arctic are valuable sources of forage for several resident and migratory herbivores; however, the effects of grazing on these systems have been rarely studied. We simulated grazing in two wet sedge meadows at a site on Ellesmere Island that has not been affected by grazing. Over two summers, we clipped plots at four different frequencies and removed litter to assess effects on aboveground net primary production, availability of soil nitrogen, shoot concentrations of carbon and nitrogen, and soil temperature and moisture regimes. Available soil nitrate and ammonium were highest in plots with intermediate clipping frequencies. Shoot nitrogen concentrations were also greater at intermediate clipping frequencies in two of the four species studied. Aboveground net primary production decreased after clipping, regardless of frequency. Litter removal resulted in slightly increased soil moisture, but had no effect on aboveground net primary production. Soil temperature was not affected by any of our treatments. These results suggest that nitrogen cycling is stimulated by intermediate frequencies of simulated grazing, but clipping decreased aboveground net primary production in ungrazed high arctic wet sedge tundra.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".