The impact of boldness on demographic rates and life‐history outcomes in the wandering albatross
Bibliographic record
Abstract
Differences among individuals within a population are ubiquitous. Those differences are known to affect the entire life cycle with important consequences for all demographic rates and outcomes. One source of among-individual phenotypic variation that has received little attention from a demographic perspective is animal personality, which is defined as consistent and heritable behavioural differences between individuals. While many studies have shown that individual variation in individual personality can generate individual differences in survival and reproductive rates, the impact of personality on all demographic rates and outcomes remains to be assessed empirically. Here, we used a unique, long-term, dataset coupling demography and personality of wandering albatross (Diomedea exulans) in the Crozet Archipelago and a comprehensive analysis based on a suite of approaches (capture-mark-recapture statistical models, Markov chains models and structured matrix population models). We assessed the effect of boldness on annual demographic rates (survival, breeding probability, breeding success), life-history outcomes (life expectancy, lifetime reproductive outcome, occupancy times), and an integrative demographic outcome (population growth rate). We found that boldness had little impact on female demographic rates, but was very likely associated with lower breeding probabilities in males. By integrating the effects of boldness over the entire life cycle, we found that bolder males had slightly lower lifetime reproductive success compared to shyer males. Indeed, bolder males spent a greater proportion of their lifetime as non-breeders, which suggests longer inter-breeding intervals due to higher reproductive allocation. Our results reveal that the link between boldness and demography is more complex than anticipated by the pace-of-life literature and highlight the importance of considering the entire life cycle with a comprehensive approach when assessing the role of personality on individual performance and demography.
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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 | 0.000 | 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".