Can antibrowsing defense regulate the spread of woody vegetation in arctic tundra?
Bibliographic record
Abstract
Global climate warming is projected to promote the increase of woody plants, especially shrubs, in arctic tundra. Many factors may affect the extent of this increase, including browsing by mammals. We hypothesize that across the Arctic the effect of browsing will vary because of regional variation in antibrowsing chemical defense. Using birch ( Betula ) as a case study, we propose that browsing is unlikely to retard birch expansion in the region extending eastward from the Lena River in central Siberia across Beringia and the continental tundra of central and eastern Canada where the more effectively defended resin birches predominate. Browsing is more likely to retard birch expansion in tundra west of the Lena to Fennoscandia, Iceland, Greenland and South Baffin Island where the less effectively defended non‐resin birches predominate. Evidence from the literature supports this hypothesis. We further suggest that the effect of warming on the supply of plant‐available nitrogen will not significantly change either this pan‐Arctic pattern of variation in antibrowsing defense or the resultant effect that browsing has on birch expansion in tundra. However, within central and east Beringia warming‐caused increases in plant‐available nitrogen combined with wildfire could initiate amplifying feedback loops that could accelerate shrubification of tundra by the more effectively defended resin birches. This accelerated shrubification of tundra by resin birch, if extensive, could reduce the food supply of caribou causing population declines. We conclude with a brief discussion of modeling methods that show promise in projecting invasion of tundra by woody plants.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".