Comparison of methods for revegetation of vehicle tracks in High Arctic tundra on Svalbard
Bibliographic record
Abstract
Natural regeneration after anthropogenic disturbance is slow in the tundra biome, but assisted regeneration can help speed up this process. A tracked off-road vehicle damaged a High Arctic dwarf shrub heath in Svalbard in May 2009, drastically reducing the vegetation cover, soil seed banks, and incoming seed rain. We assisted regeneration the following year using six different revegetation treatments and monitored their effects one month, and one and eight years after their application. By 2018, all treatments still had lower vegetation cover and limited species composition than the undamaged reference vegetation. The fertiliser treatment was the most effective in restoring vegetation cover (71% vegetation cover, of which 62% were bryophytes and 38% were vascular plant species). Compared to the reference plots (98% vegetation cover, of which 32% were bryophytes and 66% were vascular plant species), the composition of the disturbed vegetation was still far from regenerated to its original state nine years after the tracks were made. The slow regrowth demonstrated in this study underlines the importance of avoiding the disturbance of fragile tundra and implementing and upholding regulations that restrict or ban such disturbances.
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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 | 0.001 | 0.001 |
| 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 | 0.000 |
| 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 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".