Stable isotopic niche predicts fitness of prey in a wolf-deer system
Bibliographic record
Abstract
Interindividual variation in niche presents a potentially central object on which natural selection can act. This may have important evolutionary implications because habitat use governs a suite of selective forces encountered by foragers. In a free-living native black-tailed deer, Odocoileus hemionus, population from coastal British Columbia, we used stable isotope analysis to identify individual variation in foraging niche and investigated its relationship to fitness. Using an intragenerational comparison of surviving and nonsurviving O. hemionus over 2 years of predation by wolves, Canis lupus, we detected resource-specific fitness. Individuals with isotopic signatures that suggested they foraged primarily in cedar (Thuja plicata)-dominated and low-elevation hemlock (Tsuga heterophylla)-dominated forest stands were more likely to be killed by C. lupus. High-quality forage in T. plicata stands, as indexed by protein content, may be involved in maintaining this foraging phenotype. Moreover, nonsurvivors diverged more than survivors from median isotopic signatures, suggesting selection against foraging specialization. Stable isotope analysis provides a novel opportunity to integrate ecological and selective landscapes in order to identify underlying ecological mechanisms of selection and provide insight into the maintenance of variability.
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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 | 0.002 | 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".