Foraging geese, vegetation loss and soil degradation in an Arctic salt marsh
Bibliographic record
Abstract
Abstract.The North American mid‐continent population of Lesser snow geese (Chen caerulescens caerulescensL.) has increased by ca. 7% per year, largely as a result of geese feeding on agricultural crops in winter and on migration. We describe the long‐term effects of increasing numbers of geese at an arctic breeding ground (La Pérouse Bay, Manitoba) on intertidal salt‐marsh vegetation. Between 1985 and 1999 goose grubbing caused considerable loss of graminoid vegetation along transects in intertidal marshes. Loss of vegetation led to bare sediment with a plant cover of less than 2%. Changes in vegetation could not be described by simple linear, geometric or exponential functions; most losses occurred between 1988 and 1990 and losses were staggered in time between individual transects, some of which had all vegetation removed. Between 1979 and 1999 the standing crop in July in remaining intact heavily‐grazed swards ofPuccinellia phry‐ganodesandCarex subspathaceafell from 40–60 g m‐2to 20–30 g m‐2. Intense grazing on remaining patches of sward has restricted growth of these clonal forage plants and hypersalinity of bare sediments has precluded re‐establishment of vegetation. Between 1989 and 1993 numbers of faecal droppings in grazed plots reached maximum values of 15–22 droppings m‐2wk‐1. Since then peak values have remained at less than 13 droppings m‐2wk‐1. The loss of vegetation and changes in soil conditions have resulted in the establishment of an alternative stable state (hypersaline bare sediment).
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 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) | 0.001 | 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 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".