Summer elk calf survival in a partially migratory population
Bibliographic record
Abstract
Abstract Decomposing variation in juvenile recruitment is a key component of understanding population dynamics for partially migratory ungulates. We investigated reproductive parameters of adult female elk (Cervus canadensis) with calves at heel, and survivorship, cause‐specific mortality, and intrinsic and extrinsic factors affecting risk of mortality for calves in a partially migratory elk population from 2013–2016 in Alberta, Canada. Elk calves born to resident mothers had 45% lower survivorship on average compared to migrant calves (0.24 vs. 0.69) and nearly twice the mortality rate (0.37 vs. 0.19) from bears (Ursus spp.), the dominant source of mortality. Contrary to our predictions, we found that increasing levels of maternal ingesta‐free body fat were associated with increasing risk of calf mortality, indicating predation may have overwhelmed nutritional effects. We found no evidence that timing of calf birth or birth weight differed between migratory tactics or influenced mortality risk. We found that as percentage of cut forest increased, risk of calf mortality marginally decreased, which benefited migrant elk that were exposed to more clear‐cuts compared to residents. Exposure to bear predation risk was unimportant during the hiding phase (≤10 days after birth) for either migratory tactic, presumably because neonatal hiding behavior reduced vulnerability. In contrast, bear predation risk was important for mortality risk after 10 days in age, especially for resident elk calves, which were exposed to higher bear predation risk compared to migrants. We conclude that relative differences in bear predation between migratory tactics are contributing to the dynamics of partial migration in this population through additive effects on calf mortality. Thus, wildlife managers should anticipate that recovering grizzly bear (U. arctos) populations may substantially lower elk recruitment through effects on summer calf survival, especially in areas with diverse carnivore assemblages.
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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 | 0.000 |
| 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) | 0.001 | 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".