Migration, movements, and survival in a partially migratory elk ( <i>Cervus canadensis</i> ) population
Bibliographic record
Abstract
Abstract Migration provides an adaptive strategy to improve fitness by allowing individuals to exploit gradients of resources and changes in predation risk. In recent decades, the extent and prevalence of migration has declined in numerous ungulate species including many populations of elk ( Cervus canadensis ). Resident elk are often more closely associated with human activity, are more readily involved in agricultural conflicts and may contribute to overgrazing on some ranges. We evaluated migratory trends, survival rates, and causes of mortality in a partially migratory elk population in southeastern British Columbia, Canada, and compared these parameters with data from a 1982–1996 study from the same area. Analysis of 201 animal‐years ( n = 78 collared cow elk) between 2016 and 2022 showed a ratio of 52% migratory to 48% resident elk, similar to what was found during the 1982–1996 study (55% migratory to 45% resident; n = 40 cows). Among the migrants, 55% were standard migrants (traveling moderate to longer distances and changing little in elevation), 35% elevational, and 10% mixed/atypical. We detected a 14% yearly switching rate between migratory and resident strategies. We recorded 30 mortalities: 47% from human causes, predominantly elk‐vehicle/train collisions (33% of mortalities), apparent starvation/old age (17%), and predation (17%). Notably, while mortality from natural causes was similar between strategies, human‐caused mortality was nearly twice as high in resident elk. Signs of nutritional stress and lower pregnancy rates indicated potential forage limitations. Migrants had higher average survival rates (0.90) compared to residents (0.83), a shift from the 1982–1996 study that recorded higher resident survival rates (0.98), the same migrant survival rate (0.90), and fewer elk‐vehicle/train collisions. Cow elk in our study made fewer and shorter movements into upper mountain tributaries and greater use of mine properties than observed during the 1982–1996 study. Wildlife managers should consider opportunities to enhance elk forage within traditional high‐elevation summer ranges and mitigations to reduce elk‐vehicle/train collisions. Further research is needed to quantify reproductive success, monitor calf survival, and determine relative forage quality among summering areas between migratory strategies, and determine winter ranges of long‐distant migrants.
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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 | 0.000 |
| 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".