Data from: Subtle individual variation in indeterminate growth leads to major variation in survival and lifetime reproductive output in a long-lived reptile
Bibliographic record
Abstract
1. The consequences of individual variation in life-history traits have been well studied due to their importance in evolutionary ecology. However, a trait that has received little empirical attention is the rate of indeterminate growth. In long-lived ectotherms, subtle variation in growth after maturity could have major effects over the animals’ lifetimes. 2. These effects are difficult to measure due to the challenges involved in reliably estimating individual variation in the face of environmental stochasticity, and the need to account for trade-offs among growth, reproduction and survival. However, modelling advances have made such analysis possible if long-term high-quality data sets are available. 3. We used an integrated state-space modelling framework to reveal relationships between indeterminate growth, reproduction and survival in a population of North American snapping turtles (Chelydra serpentina) using a 41-year data set for 298 adult females. 4. A hierarchical version of the von Bertalanffy model fitted to data on carapace lengths showed substantial individual variation in growth trajectories, and hierarchical models fitted to clutch-mass data and recapture histories showed that reproductive output and survival probability increased with size. Integration of these models revealed no detectable trade-offs – i.e., individual growth parameters were not correlated with size-specific survival or reproduction rates, and individual variation in reproductive output did not affect the size-specific survival rate. Consequently, individual variation in growth parameters was estimated to result in > 2-fold variation in post-maturity life expectancy and > 4-fold variation in expected lifetime reproductive output. 5. These results illustrate that indeterminate growth can have major fitness consequences in long-lived species. We suggest that the individual variation in growth rates reflects variation in environments experienced during development or later life. An understanding of this variation may be essential for predicting the population dynamics of long-lived species under threat and identifying the most important environments to protect.
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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 | 0.002 | 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 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| 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 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".