Do hyperabundant Arctic-nesting geese pose a problem for sympatric species?
Bibliographic record
Abstract
Arctic-breeding geese are at record high population levels and are causing significant changes to some of their breeding and staging habitats. These changes could influence sympatric wildlife, but the nature and strength of these effects are unknown. Here, we review the interactions between geese and sympatric species and propose future research that could help to fill important knowledge gaps. We suggest that geese may be indirectly affecting other species through changes to nesting habitat, prey availability, and predator–prey interactions. Many ground-nesting Arctic birds prefer vegetated wet tundra habitats that offer concealed nest sites; areas also heavily used by breeding and staging geese. Where goose foraging exceeds the capacity of the plants to regenerate, habitats have shorter graminoids and more exposed substrate, potentially reducing the availability of concealed nest sites for other birds. Studies have documented local reductions in the abundance of these concealed-nesting species, such as shorebirds. Despite the nutrient enrichment contributed by goose feces, habitats heavily altered by geese have also been shown to host a reduced diversity and abundance of some invertebrate groups. In contrast, generalist predators show positive functional and numerical responses to the presence of breeding geese. Therefore, the risk of predation for alternative or incidental prey (e.g., lemmings or small bird nests) is likely elevated within or near breeding colonies. Studies have demonstrated a reduced abundance of small mammals in areas heavily used by geese, but it is unknown whether this is related to shared predators or habitat alteration. Sympatric wildlife could be further affected through higher stress-levels, altered body condition, or other physiological effects, but there is currently no evidence to demonstrate such impacts. Few studies have explored the potential effects of geese at larger spatial scales, but we suggest that hyperabundant geese could result in regional declines in the abundance and diversity of shorebirds and passerines. We recommend coordinated studies across multiple regions to quantify nesting habitat, arthropod communities, and predator–prey interactions in response to nearby goose colonies. To align with current multispecies approaches to conservation, adequate knowledge of the potential effects of hyperabundant goose populations on other wildlife should be a priority.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 | 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) | 0.007 | 0.007 |
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; both teacher heads agree on what is shown here.
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".