Not putting all their eggs in one basket: bet-hedging despite extraordinary annual reproductive output of desert tortoises
Bibliographic record
Abstract
Bet-hedging theory makes the counter-intuitive prediction that, if juvenile survival is low and unpredictable, organisms should consistently reduce short-term reproductive output to minimize the risk of reproductive failure in the long-term. We investigated the long-term reproductive output of an Agassiz's desert tortoise (Gopherus agassizii) population and conformance to a bet-hedging strategy of reproduction in an unpredictable but comparatively productive environment. Most females reproduced every year, even during periods of low precipitation and poor germination of food plants, and the mean percentage of reproducing females did not differ significantly on an annual basis. Although mean annual egg production (clutch size × clutch frequency) differed significantly among years, mean clutch size and mean clutch frequency remained relatively constant. During an El Niño year, mean annual egg production and mean annual clutch frequency were the highest ever reported for this species. Annual egg production was positively influenced by maternal body size but clutch size and clutch frequency were not. Our long-term results confirm earlier conclusions based on short-term research that desert tortoises have a bet-hedging strategy of producing small clutches almost every year. The risk of long-term reproductive failure is minimized in unpredictable environments, both through time by annually producing multiple small clutches over a long reproductive lifespan, even in years of low resource availability, and through space by depositing multiple annual clutches in different locations. The extraordinary annual reproductive output of this population appears to be the result of a typically high but unpredictable biomass of annual food plants at the site relative to tortoise habitat in dryer regions. Under the comparatively productive but unpredictable conditions, tortoises conform to predictions of a bet-hedging strategy of reproduction with relatively small but consistent clutch sizes.
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 | 0.002 | 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) | 0.000 | 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".