A short spring before a long jump: the ecological challenge to the steppe tortoise (<i>Testudo horsfieldi</i>)
Bibliographic record
Abstract
The steppe tortoise (Testudo horsfieldi) is probably the most widespread and abundant of all living terrestrial tortoises, but paradoxically, this chelonian as been studied only superficially. Steppe tortoise populations are declining rapidly as a result of massive harvesting for the pet trade and extensive disruption of their habitat by intensive agriculture. Thus, it is urgent to acquire accurate information on major life-history traits. Our 5-year field study at the Djeiron Ecocenter in the Republic of Uzbekistan indicates that steppe tortoises usually remain buried in one place for over 9 months, which helps them cope with the extreme environmental conditions that occur in summer, fall, and winter. After emerging in late winter, steppe tortoises have less than 3 months in spring to forage to obtain the fuel needed for growth and reproduction, and replenish the body reserves necessary for the subsequent 9 months of total starvation. The mating period occurred between the end of March and mid-April and the egg-laying period from the end of April to mid-June. Using radio-tracking and focal sampling, we measured the time devoted to different activities by males and females. During the mating period, males allocated a large proportion of their daily activity to sexual behaviours, whereas females' sexual activity tended to be cryptic. However, males devoted less time to feeding and resting than did females. During the postmating period, both males and females spent much time foraging. The strong sexual divergences indicate that each sex copes differently with the extreme continental climate. The seasonal and interannual changes in body mass indicate complex interactions between climatic conditions, activity budget, and body reserves.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".