Resource partitioning among five species of waterfowl (<i>Anas</i> spp.) at an autumn migratory stopover: combining stable isotope and mercury biomarkers
Bibliographic record
Abstract
The Saskatchewan River Delta (SRD) is North America’s largest inland delta and an important stopover site for waterfowl in the Central Flyway. However, little is known about their basic feeding ecology at this site and how species segregate or overlap in resource use. We used stable carbon (δ13C) and nitrogen (δ15N) isotopes and mercury concentrations ([Hg]) in liver tissue to trace use of local nutrient sources by five waterfowl species and tested for differences in diets among species, sexes, and age groups. Macrophytes were the dominant food source for Northern Pintail (Anas acuta L., 1758) and American Wigeon (Anas americana Gmelin, 1789) with median proportions of 0.86 and 0.98, respectively. There was also evidence of partitioning of resources, as Blue-winged Teal (Anas discors L., 1766) and Green-winged Teal (Anas carolinensis Gmelin, 1789) consumed invertebrates, as did a subset of Mallards (Anas platyrhynchos L., 1758), suggesting that these birds might minimize competition for resources during the short staging period in the SRD when waterfowl densities are high. Other isotopes or tracers, such as [Hg] that varied among sources (0.03–0.20 μg·g–1 dry mass) and waterfowl species (0.22–3.19 μg·g–1 dry mass), can be used for further refining dietary estimates.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".