Using survivorship curves to estimate age of first reproduction in moose <i>Alces alces</i>
Bibliographic record
Abstract
Age‐specific mortality of large mammals follows a general pattern of high juvenile mortality followed by low adult mortality. I outline a method which models this change in mortality rate to estimate age of maturity in hunted moose Alces alces populations. Kill data indicate that first time reproducers suffer the highest mortality during the hunting season. Cohort analysis of hunter kill data was used to estimate age‐specific female moose numbers and annual survival of cohorts over 18–26 years. Age at maturity was defined as age at the inflection point (highest mortality rate) of a third‐order log‐polynomial of annual survivorship curves. The inflection point demarcates the change in mortality rate between juvenile and adult life stages. Thus, the inflection point represents the greatest moose mortality rate during the hunting season and is likely associated with hunting mortality of inexperienced females accompanied by 6‐month‐old calves. I tested this method by estimating age of first reproduction (inflection point ‐ 0.5 years) and juvenile mortality for 15 Canadian moose populations. Results indicate a wide range of age at maturity (1.7–3.0 years) and percent of juveniles that survive to this age (29–70%). Estimating age at maturity from survivorship curves provides the opportunity to test life‐history theory.
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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 | 0.001 | 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 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".