Bet‐hedging response to environmental variability, an intraspecific comparison
Bibliographic record
Abstract
A major challenge in ecology is to understand the impact of increased environmental variability on populations and ecosystems. To maximize their fitness in a variable environment, life history theory states that individuals should favor a bet-hedging strategy, involving a reduction of annual breeding performance and an increase in adult survival so that reproduction can be attempted over more years. As a result, evolution toward longer life span is expected to reduce the deleterious effects of extra variability on population growth, and consequently on the trait contributing the most to it (e.g., adult survival in long-lived species). To investigate this, we compared the life histories of two Black-browed Albatross (Thalassarche melanophrys) populations breeding at South Georgia (Atlantic Ocean) and Kerguelen (Indian Ocean), the former in an environment nearly three times more variable climatically (e.g., in sea surface temperature) than the latter. As predicted, individuals from South Georgia (in the more variable environment) showed significantly higher annual adult survival (0.959, SE = 0.003) but lower annual reproductive success (0.285 chick per pair, SE = 0.039) than birds from Kerguelen (survival = 0.925, SE = 0.004; breeding success = 0.694, SE = 0.027). In both populations, climatic conditions affected the breeding success and the survival of inexperienced breeders, whereas the survival of experienced breeders was unaffected. The strength of the climatic impact on survival of inexperienced breeders was very similar between the two populations, but the effect on breeding success was positively related to environmental variability. These results provide rare and compelling evidence to support bet-hedging underlying changes in life history traits as an adaptive response to environmental variability.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.038 | 0.007 |
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; both teacher heads agree on what is shown here.
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".