Foraging ecology and time budgets of non-breeding shorebirds in coastal Cuba
Bibliographic record
Abstract
Abstract: During the non-breeding season, shorebirds, a large and important group of wetland vertebrates, divide their time between foraging, resting and maintenance activities. We examined factors affecting time budgets, foraging techniques and rates, and spacing patterns of 14 to 92 individuals each of 10 shorebird species spending the non-breeding season in Cayo Guillermo, Cuba. We hypothesized that all species would spend the majority of their time foraging. Time spent foraging ranged from 20–85% of total time and was significantly negatively related to average body size. Apparent aggression (e.g. chasing or being chased) occurred in < 10% of individuals in all species and was not related to maximum counts of conspecifics. Aggression was most common in the black-necked stilt but did not vary in frequency as a function of activity. Vigilance varied in occurrence from 0–53% of individuals, but the frequency was not related to maximum counts. Intraspecific distances were generally greater between foraging than non-foraging birds. For most species interspecific distances were similar to intraspecific distances during foraging but greater than intraspecific differences during non-foraging, suggesting some overlap in foraging habitat and niche partitioning during non-foraging. Shorebirds that used primarily tactile techniques foraged closer together than primarily visual foragers. Low rates of aggression, as an index of potential competition, suggest that species-specific energy requirements rather than competitive interactions are the main determinants of foraging behaviour on these tropical non-breeding grounds.
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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 | 0.000 |
| 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) | 0.001 | 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".