Is it safe to nest near conspicuous neighbours? Spatial patterns in predation risk associated with the density of American Golden-Plover nests
Bibliographic record
Abstract
Predation is one of the main factors explaining nesting mortality in most bird species. Birds can avoid nest predation or reduce predation pressure by breeding at higher latitude, showing anti-predator behaviour, selecting nest sites protected from predators, and nesting in association with protective species. American Golden-Plovers (Pluvialis dominica) defend their territory by using various warning and distraction behaviours displayed at varying levels of intensity (hereafter "conspicuous behaviour"), as well as more aggressive behaviours such as aerial attacks, but only in some populations. Such antipredator behaviour has the potential to repel predators and thus benefit the neighbouring nests by decreasing their predation risk. Yet, conspicuous behaviour could also attract predators by signalling the presence of a nest. To test for the existence of a protective effect associated with the conspicuous antipredator behaviour of American Golden-Plovers, we studied the influence of proximity to plover nests on predation risk of artificial nests on Igloolik Island (Nunavut, Canada) in July 2014. We predicted that the predation risk of artificial nests would decrease with proximity to and density of plover nests. We monitored 18 plover nests and set 35 artificial nests at 30, 50, 100, 200, and 500 m from seven of those plover nests. We found that the predation risk of artificial nests increases with the density of active plover nests. We also found a significant negative effect of the distance to the nearest active protector nest on predation risk of artificial nests. Understanding how the composition and structure of shorebird communities generate spatial patterns in predation risks represents a key step to better understand the importance of these species of conservation concern in tundra food webs.
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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 | 0.000 | 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 | 0.000 | 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 teacher head, 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".