Diversity of nitrogen isotopes and protein status in caribou: implications for monitoring northern ungulates
Bibliographic record
Abstract
Nutritional condition is an important determinant of productivity and survival in caribou (Rangifer tarandus). We used samples of excreta (n = 1,150) to estimate diet composition from microhistology and 2 isotopic proxies of protein status for 2 ecotypes of caribou in 4 herds in late winter (2006–2008). Isotopes of nitrogen (δ15N in parts per thousand [%0]) from excreta samples (urea, diet, and body N) were used to estimate indexes of protein status: the proportion of urea N derived from body N (p-UN) and the difference between the δ15N of the body and urinary urea (Δbody-urea). We examined dietary and terrain characteristics, δ15N, p-UN, and Δbody-urea by ecotype, herd, year, and foraging site. Multiple regression and an information-theoretic approach were used to evaluate correlates of protein status at each foraging site. The dietary and terrain characteristics of foraging sites did not vary by ecotype or herd (P > 0.108); diets were dominated by lichens (68% α 14.1% SD). The δ15N of urea, diet, body N, p-UN, and Δbody-urea varied among foraging sites within each herd (P < 0.001). Although highly variable, the δ15N of urinary urea was typically low (−4.68%0 α 2.67% SD). Dietary N also had low δ15N (−4.18%0 α 0.92%0 SD), whereas body N was generally heavier in 15N (2.20%0 α 1.56%0 SD) than urinary urea or the diet. Both measures of protein status were similarly diverse between ecotypes and among herds, which limited their applicability to monitor protein status at the population level. Although we observed limitations to interpreting estimates of p-UN from highly vagile ungulates, the Δbody-urea may prove to be a useful index of protein status at smaller spatial and temporal scales. Indeed, a portion of the observed variance (r2 = 0.26) in Δbody-urea at each foraging site was explained by the proportion of shrubs in the winter diet. There remains potential in using δ15N in excreta as a noninvasive tool for evaluating protein status in northern ungulates; however, considerable analytical and sampling challenges remain for applying these isotopic approaches at large scales.
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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 | 0.000 | 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".