Spatial heterogeneity of primary production as both cause and consequence of foraging patterns of an expanding Greater Snow Goose colony
Bibliographic record
Abstract
In response to spatial heterogeneity of resources, many herbivores move between discrete areas to enhance access to the best foraging areas. Local forage removal by mobile herd-foraging herbivores in turn is likely to produce spatial variability in both plant nutritive quality and quantity. On the tundra of Bylot island, Nunavut, owing to the recent demographic explosion of their population, most greater snow geese move out of their nesting area soon after hatch to rear their young at distant feeding sites. A previous study showed that goslings using these distant sites are generally heavier and larger than those that stay in the colony throughout the brood-rearing period. In this study, we examine the hypothesis that goslings' growth was reduced in the nesting area compared to distant brood-rearing areas because grazing pressure reduced standing crop. In light of the recent expansion in the distribution of geese during brood-rearing, we also investigated if the negative effect of chronic grazing on net above-ground primary production (NAPP) differed between the colony and distant brood-rearing sites. We monitored NAPP, grazing pressure, and intensity of use in the goose colony and in 2 distant brood-rearing areas over a 10-y period by sampling plant biomass inside and outside moveable goose exclosures erected annually and by counting goose feces along transects at the end of the summer. NAPP of graminoids in the nesting area was 40% lower than at the other brood-rearing areas, but the percentage of primary production consumed by geese (28%) did not differ among the 3 sites despite large annual variations. Cumulative feces density revealed that intensity of use of the 2 brood-rearing areas by geese was nearly 2 times higher than at the colony, but the timing of use differed as grazing on the brood-rearing areas occurred only after hatch, unlike the nesting area. We conclude that geese not only respond to spatial heterogeneity in resource availability but also create and sustain it through their foraging behaviour.
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".