Habitat alteration by geese at a large arctic goose colony: consequences for lemmings and voles
Bibliographic record
Abstract
Heavy grazing by Ross’s geese ( Chen rossi (Cassin, 1861)) and lesser snow geese ( Chen caerulescens (L., 1758)) has resulted in substantial habitat alteration in some parts of the Arctic. However, the influence of these habitat alterations on other animals is poorly understood. We therefore examined how habitat alteration by geese influenced small-mammal (lemmings and voles) abundance at the large goose colony near Karrak Lake, Nunavut, by comparing small-mammal abundance and aboveground biomass of plants inside and outside the colony. Heavy grazing by geese resulted in virtually complete removal of graminoid plants (grasses and sedges) in lowland areas in the colony, which in turn was associated with a reduction in small-mammal abundance of about one order of magnitude compared with that in lowland areas outside the colony. Aboveground biomass of plants in upland areas in the colony was also reduced compared with that in upland areas outside the colony, although this reduction was less pronounced than that in lowland areas in the colony. Moreover, this reduction was not associated with a reduction in small-mammal abundance. There was, thus, a strong negative correlation between habitat alteration by geese and distribution and abundance of small mammals at this colony.
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 | 0.001 | 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".