Recovery of tall cotton–grass following real and simulated feeding by snow geese
Bibliographic record
Abstract
Lesser snow geese Anser caerulescens caeruteseens from the western Canadian Arctic feed on underground parts of tall cotton–grass Eriophorum angustifolium during autumn staging on the coastal plain of the Beaufort Sea in Canada and Alaska. We studied revegetation of sites where cotton–grass had been removed either by human–imprinted snow geese or by hand to simulate snow goose feeding. Aerial cover of cotton–grass at sites (n = 4) exploited by human–imprinted snow geese averaged 60 and 39 Mi lower than in undisturbed control plots during the first and second year after feeding, respectively. Underground biomass of cotton–grass stembases and rhizomes in hand–treated plots was 80 and 62% less than in control plots 2 and 4 yr after removal, respectively (n = 10 yr ‐1 ). Aerial cover and biomass of common non‐forage species such as Carex aquatilis did not increase on treated areas. Removal of cotton‐grass by geese likely reduces forage availability at exploited sites for at least 2–4 yr after feeding but probably does not affect long‐term community composition. Temporal heterogeneity in forage abundance likely contributes to the large spatial requirement of snow geese during staging.
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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 | 0.000 | 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) | 0.000 | 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 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".