Using stable carbon (δ<sup>13</sup>C) and nitrogen (δ<sup>15</sup>N) isotopes to infer trophic relationships among black and grizzly bears in the upper Columbia River basin, British Columbia
Bibliographic record
Abstract
Ecological segregation of species is difficult to determine using conventional dietary analysis techniques. However, stable-isotope analysis may provide a convenient means of establishing trophic segregation of species and of groups of animals within a species in the same area. We measured stable carbon (δ 13 C) and nitrogen (δ 15 N) isotope values in hair of black bears (Ursus americanus) and grizzly bears (Ursus arctos) inhabiting the upper Columbia River basin in southeastern British Columbia, together with samples of potential foods ranging from plant material through invertebrates and ungulate meat. We found extensive overlap in both δ 15 N and δ 13 C values of hair from male grizzly bears and black bears of both sexes. Female grizzly bears, however, had lower δ 15 N values in their hair than the other groups of bears, indicating either less animal protein in their diet or a reliance on foods more depleted in 15 N, possibly related to altitude. Our isotopic model generally confirmed a herbivorous diet for both bear species (a mean estimated plant contribution of 91%). Bears showing the highest δ 15 N values were those captured because they posed a management problem. We suggest that the slope of the relationship between tissue δ 15 N and δ 13 C values might provide a convenient means of evaluating the occurrence of consumption of animal protein in populations, regardless of local isotopic end-points for dietary samples. We examined three black bear cubs from dens and found them to be about a trophic level higher than adult females, reflecting their dependence on mother's milk, a result generally confirmed by an analysis of eight mother-cub pairs from Minnesota. Our study demonstrates how stable-isotope analysis of bear tissue can be used to monitor the feeding habits of populations, as well as provide dietary histories that may reveal dietary specializations among individuals.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".