Sustainable Agriculture: Nutritional Benefits of Wheat–Soybean and Maize–Sunflower Associations for Hibernation and Reproduction of Endangered Common Hamsters
Bibliographic record
Abstract
Farmland species face many threats, including habitat loss and malnutrition during key periods of their life cycle. This is aggravated in conventionally managed monocultures, leading to nutrient deficiencies that impair the survival and reproduction of farmland wildlife. For instance, protein deficiencies in wheat or vitamin B3 deficiency in maize reduce by up to 87% the reproductive success of the critically endangered common hamster (Cricetus cricetus), a flagship species of European farmlands. It is urgent to identify and implement agricultural practices that can overcome these deficiencies and help restoring hamsters’ reproductive success. As part of a conservation program to diversify farming habitats in collaboration with farmers, we tested whether associations between wheat or maize and three supplemental crops (soybean, sunflower and fodder radish) supported hamsters’ performance during hibernation and reproduction. We observed that maize–sunflower, maize–radish and wheat–soybean associations minimized hamsters’ body mass loss during hibernation. The wheat–soybean association led to the highest reproductive success (N = 2 litters of 4.5 ± 0.7 pups with a 100% survival rate to weaning), followed by maize–sunflower and maize–radish. These crop associations offer promising opportunities to overcome nutritional deficiencies caused by cereal monocultures. Their agronomic potential should promote their implementation on a large scale and benefit farmland biodiversity beyond the common hamster.
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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 | 0.000 |
| 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) | 0.001 | 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".