Diet Overlaps between the Sexes in Breeding American Oystercatchers
Bibliographic record
Abstract
Sexual dimorphism in bill size can lead to sex-specific foraging strategies. All 12 extant species of oystercatchers (Haematopus spp.) have sexually dimorphic bills, and most oystercatcher species show intersexual niche partitioning in diet, where males and females eat different prey species in different proportions. Intersexual niche partitioning in diet has not been examined in American Oystercatchers (Haematopus palliatus). This study tested for intersexual niche partitioning in diet in a population of American Oystercatchers breeding on two barrier islands in coastal Virginia, U.S.A. in 2022 and 2023. Diet composition, prey size selection, and foraging areas were compared between the sexes (n = 31 males and n = 28 females). Unlike other oystercatcher species, male and female American Oystercatcher diets overlapped by 99%. Both sexes took similar-sized prey across the seven prey species and shared use of 59% of feeding areas. Previous studies on other oystercatcher species may have found intersexual niche partitioning in diet because of highly competitive environments due to high population density or low prey availability. In contrast, the present study in the Virginia barrier islands that found diet overlap between the sexes may be due to a low competitive environment from low breeding densities and sufficient prey abundance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".