Linking Habitat Selection and Predation Risk to Spatial Variation in Fitness for Woodland Caribou
Bibliographic record
Abstract
A central assumption underlying niche theory and the study of habitat selection is that selected habitats confer enhanced fitness. Here, we separately measured spatial patterns of both resource selection and predation risk and tested their relationships with a key demographic fitness trait, adult female survival, for a threatened ungulate, woodland caribou (Rangifer tarandus caribou). We used Cox-proportional hazards spatial survival modeling to assess support for various selection- and risk-based estimates of habitat quality using previously developed caribou resource selection functions and wolf predation risk models. Indeed we found positive relationships between the predicted values of a scale-integrated resource selection function and survival, yet subsequently incorporating predation risk greatly improved models further. Predation risk was an additive source of hazard beyond that detected through selection alone, and selection thus shown to be non-ideal. Furthermore, by combining spatially-explicit adult female survival predictions with herd-specific estimates of recruitment in matrix population models, we demographically estimated a fitness landscape for this threatened species.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".