Vulnerability to predation may affect species distribution: plovers with broader arctic breeding range nest in safer habitat
Bibliographic record
Abstract
Lower vulnerability to predation should increase the capacity of prey populations to maintain positive population growth rate in regions characterized by high predation pressure. Some arctic-nesting shorebirds nest almost exclusively in areas where predation pressure is regularly released. The few species that can breed within the entire distribution range of the Arctic Fox, the main nest predator in the arctic tundra, are supposedly less sensitive to predation. However, empirical data supporting this hypothesis are scarce and mechanisms driving interspecific variation in vulnerability to nest predation are poorly documented. We monitored nest success of two arctic-nesting shorebirds with contrasting breeding distribution and nesting habitat. We found that (i) when co-existing at the same breeding site, the widely distributed Ringed Plovers nesting along stony shores showed a higher nest survival rate than the Golden Plovers nesting in mesic tundra, and (ii) such differences in nest survival were at least partly driven by the nesting habitat type per se, with lower predation risk in stony shores than in adjacent mesic tundra. We suggest that the use of safer nesting habitat by some shorebird species can contribute to maintaining viable breeding populations over a broader distribution range.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".