An isotopic approach to measuring nitrogen balance in caribou
Bibliographic record
Abstract
Abstract Nutritional restrictions in winter may reduce the availability of protein for reproduction and survival in northern ungulates. We refined a technique that uses recently voided excreta on snow to assess protein status in wild caribou (Rangifer tarandus) in late winter. Our study was the first application of this non‐invasive, isotopic approach to assess protein status of wild caribou by determining dietary and endogenous contributions of nitrogen (N) to urinary urea. We used isotopic ratios of N (δ15N) in urine and fecal samples to estimate the proportion of urea N derived from body N (p‐UN) in pregnant, adult females of the Chisana Herd, a small population that ranged across the Alaska‐Yukon border. We took advantage of a predator‐exclosure project to examine N status of penned caribou in April 2006. Lichens were the primary forage (>40%) consumed by caribou in the pen and δ15N of fiber tracked the major forages in their diets. The δ15N of urinary urea for females in the pen was depleted relative (−1.3 ± 1.0 parts per thousand [‰], ${\bar {x}}\pm {\rm SD}$ ) to the δ15N of body N (2.7 ± 0.7‰). A similar proportion of animals in the exclosure lost core body mass (excluding estimates of fetal and uterine tissues; 55%) and body protein (estimated by isotope ratios; 54%). This non‐invasive technique could be applied at various spatial and temporal scales to assess trends in protein status of free‐ranging populations of northern ungulates. Intra‐ and inter‐annual estimates of protein status could help managers monitor effects of foraging conditions on nutritional constraints in ungulates, increase the efficiency and efficacy of management actions, and help prepare stakeholders for potential changes in population trends. © 2010 The Wildlife Society.
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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 | 0.001 |
| 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 | 0.000 |
| 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".