Post‐weaning survival in kangaroos is high and constant until senescence: Implications for population dynamics
Bibliographic record
Abstract
Large herbivores typically have consistently high prime-aged adult survival and lower, more variable, juvenile, and senescent survival. Many kangaroo populations undergo greater fluctuations in density compared with other large herbivores, but age- and sex-specific survival of kangaroos and their response to environmental variation remain poorly estimated. We used long-term capture-mark-recapture data on 920 individuals to investigate the survival component of eastern grey kangaroo (Macropus giganteus) population dynamics. Forage availability and population density were monitored quarterly and included as predictors of survival in Bayesian Cormack-Jolly-Seber models. Annual survival probabilities were estimated for five age classes: 0 years (juveniles), 1-2 years (subadults), 3-6 years (prime-aged adults), 7-9 years (presenescent adults), and ≥10 years (senescent adults). Survival of juveniles varied widely during our 12-year study, ranging from 0.07 to 0.90 for females and 0.05-0.92 for males. Subadult survival was 0.80-0.93 for females and 0.75-0.85 for males, while that of prime-aged adults was ≥0.94 for females and ≥0.83 for males, despite large fluctuations in forage and density. The survival of presenescent adults spanned 0.86-0.93 for females and 0.60-0.86 for males. Senescent survival was variable, at 0.49-0.90 for females and 0.49-0.80 for males. Male survival was significantly lower than female survival in prime-aged and presenescent adults, but not in other age classes. Although most of the models supported by Watanabe-Akaike Information Criterion selection included at least one environmental covariate, none of these covariates individually had a discernible effect on survival. Temporal variability in overall survival appeared mostly due to changes in the survival of juvenile and senescent kangaroos. Kangaroo survival patterns are similar to those of ungulates, suggesting a strong role of sex-age structure on population dynamics.
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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 | 0.002 |
| 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 | 0.001 |
| 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".