Late snow melt moderates herbivore disturbance of the Arctic tundra
Bibliographic record
Abstract
ABSTRACT Resilience of tundra vegetation to disturbance by herbivores can be low and lead to ecosystem state shifts. Pink-footed geese Anser brachyrhynchus are the most numerous herbivore on Svalbard and disturb vegetation when foraging for below-ground plant biomass (grubbing). We assessed grubbing extent (occurrence of vegetation disturbance) and intensity (proportion of vegetation disturbed) in 2006/07/08 when goose numbers were approximately 56,000 and in 2013 when they increased to approximately 81,000. Despite a 36% increase in population size, in 2013 the grubbing extent at pre-breeding sites was similar to that in 2007/08 but grubbing intensity was lower. Extensive snow cover in 2013 probably dispersed geese over larger areas in search of snow-free patches for feeding, thereby reducing grubbing intensity. At the largest known breeding site, both grubbing extent and intensity increased with more geese. Birds preferentially fed close to nests in previously grubbed wet habitat, probably aiding nest defence and permitting feeding on plants that were easier to remove from the soil. A greater impact on tundra vegetation may occur at nesting areas if the breeding population continues to grow. However, timing of snowmelt appears key in moderating the impact of disturbance on tundra vegetation since it controls spatial distributions of feeding geese.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".