Is diet segregation between dabbling ducks due to food partitioning? A review of seasonal patterns in the <scp>W</scp>estern <scp>P</scp>alearctic
Bibliographic record
Abstract
Abstract Within the paradigm of resource‐limited competition‐structured communities, dabbling ducks (Anas spp.) have been used as a textbook example of how morphological differences, notably bill lamellar density and body length, may allow sympatric species to partition food and hence coexist. We reviewed all accessible diet studies from the Western Palearctic for three closely related dabbling duck species, mallard (Anas platyrhynchos), pintail (A. acuta) and teal (A. crecca), and present a comprehensive list of the food items (invertebrates, seeds, vegetative parts of plants) ingested. To assess the circumannual perspective of niche separation, we evaluated size distribution of ingested seeds among seasons and duck species. There was a significant difference among duck species in mean size and mass of ingested seeds, as well as in diet composition, with the largest seeds consumed by the largest species (mallard) with the coarsest bill filter apparatus (lamellae), and the smallest seeds by the smallest species (teal) with the finest bill lamellae. However, no effect of season was found, suggesting consistent diet segregation among species throughout the annual cycle of ducks and over large geographical areas. We argue that the patterns of food size separation between the three species are compatible with the idea of coexistence under interspecific competition.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".