Temporal Sources of Deuterium (δD) Variability in Waterfowl Feathers Across a Prairie-to-Boreal Gradient
Bibliographic record
Abstract
The use of hydrogen isotopes to delineate origins of migratory birds relies on predictable relationships between levels of deuterium (δD) in tissue and those predicted from long-term precipitation (δDp). Variance in deuterium associated with the year of interest, the long-term isotopic database, and in feathers (δDf) of waterbirds occupying small wetlands is an issue confronting isotopic comparisons. We examined the factors that influence isotopic variation among feathers of known-origin Mallards (Anas platyrhynchos) from breeding locations in north-central North America. We evaluated temporal variability in δDf values at two spatial scales. At scales >500 km, annual differences accounted for 0–45% of variation in δDf values of feathers from the North American Boreal Forest, Peace Lowlands, Aspen Parkland, and Prairie ecoregions; annual variability was greatest in the Aspen Parkland. At scales <50 km, differences among and within years contributed similarly and together accounted for 93–95% of variation in δDf values of Mallard broods at two Canadian prairie sites. Variability in δDf among Mallards from one small wetland complex in prairie Canada was best explained by variability in δDp values that represented the period of feather synthesis through the beginning of the previous growing season >12 months earlier. These annual and seasonal shifts in δDf values may help to explain why assigning origins of wetland birds on the basis of deuterium levels can be more uncertain at finer spatial scales, particularly in regions of complex wetland hydrology.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".