Aggregation of nests in an Arctic-breeding shorebird and daily survival rates
Bibliographic record
Abstract
Our current understanding of the factors that influence where birds nest is incomplete, yet such information is important for accurate demographic assessments. To address questions related to spatial distributions of shorebird nests and to evaluate factors that may affect nest distribution in these species, during 2017 and 2019, we studied a small population of semipalmated sandpiper (Calidris pusilla) breeding in the Central Canadian Arctic, near the Karrak Lake Research Station, in Nunavut. The spatial distribution of semipalmated sandpiper nests at this site suggested loose aggregation, with median nearest neighbour distances of 73.8 m and 92.0 m in 2017 and 2019, respectively. Evidence for an influence of nesting distribution on daily survival rate of nests, however, was mixed. Neither nearest neighbour distance nor local nest density had a significant effect on daily nest survival in 2017, but in 2019, the best approximating model included an effect of local nest density, which indicated that nests in areas of high density had reduced survival rates. Contrary to other studies assessing settlement and nest site selection in semipalmated sandpipers, the spatial distribution of nests in this population demonstrates a role for social attraction in an otherwise territorial species and suggests that aggregated nesting can impose a cost on nest survival under certain conditions.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".