Bibliographic record
Abstract
We examined the role of trophic interactions in structuring a high arctic tundra community characterized by a large breeding colony of greater snow geese (Chen caerulescens atlantica). According to the exploitation ecosystem hypothesis of Oksanen et al. (1981), food chains are controlled by top-down interactions. However, because the arctic primary productivity is low, herbivore populations are too small to support functional predator populations and these communities should thus be dominated by the plant/ herbivore trophic-level interaction. Since 1990, we have been monitoring annual abundance and productivity of geese, the impact of goose grazing, predator abundance (mostly arctic foxes, Alopex lagopus) and the abundance of lemmings, the other significant herbivore in this community, on Bylot Island, Nunavut, Canada. Goose grazing consistently removed a significant proportion of the standing crop (∼40%) in tundra wetlands every year. Grazing changed plant community composition and reduced the production of grasses and sedges to a low-level equilibrium compared to the situation where the presence of geese had been removed. Lemming cyclic fluctuations were strong and affected fox reproduction. Fox predation on goose eggs was severe and generated marked annual variation in goose productivity. Predation intensity on geese was closely related to the lemming cycle, a consequence of an indirect interaction between lemming and geese via shared predators. We conclude that, contrary to the exploitation ecosystem hypothesis, both the plant/herbivore and predator/prey interactions are significant in this arctic community.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".