Cumulative and interannual effects of reproduction in eastern grey kangaroos
Bibliographic record
Abstract
Reproduction can reduce energy allocation to other life-history traits such as survival and growth. Resource constraints give rise to (co)variation in life-history traits and to heterogeneity in energy acquisition and allocation. At each reproductive opportunity, females face a choice between allocation to current reproduction or to maintenance. Many studies compare reproductive trade-offs between two consecutive years, but few account for the cumulative effects of reproduction over multiple years, a crucial factor in understanding life-history evolution in long-lived iteroparous species. We compared short- (interannual) and long-term (cumulative) reproductive trade-offs with a 14-year capture-mark-recapture study of eastern grey kangaroos, where females can have substantial skeletal growth for several years after maturation. We used a multivariate approach to compare how interannual and multi-annual cumulative reproduction affected growth (n = 378 measurements), mass change (n = 376 measurements) and subsequent reproduction (n = 388 measurements), and to quantify (co)variation between these traits among individuals (n = 107) and years (n = 14). Interannually, young females that reproduced experienced decreased skeletal growth compared to young females that did not reproduce. Reproductive females of all ages experienced reduced mass gain and weaning probability in the following year. The cumulative effects of multiple reproductions included decreased skeletal growth, mass gain and weaning probability in the following year. These effects increased with age and reproductive rate. We found positive trait correlations between mass change, leg growth and subsequent reproduction among individuals and years, though weaker at the cumulative than interannual level. Females experience dynamic interannual and cumulative trade-offs. Our analyses of cumulative costs of reproduction revealed long-term trade-offs as well as cumulative costs that were not apparent when estimating interannual costs. Trait correlations suggested heterogeneity in growth and reproduction among females. Years of increased growth were followed by years of increased reproduction, and years of poor growth were followed by years of poor reproduction. Our exploration of both interannual and cumulative costs of reproduction underscores the need to account for long-term reproductive histories to better understand reproductive trade-offs in long-lived iteroparous 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 | 0.000 | 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 | 0.000 | 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".