Atmospheric pressure requirements of bumblebees (Bombus impatiens) as pollinators of Lunar or Martian greenhouse grown food
Bibliographic record
Abstract
Long-term space exploration missions to the Moon or Mars will require food production facilities to sustain human life. Considering that the atmospheric pressure on the Moon and Mars is much less than that on Earth, scientists have been studying plant production in controlled environments with reduced pressures in order to better understand effects on growth and development. Some plants have been found to successfully grow in environments with pressures as low as 10 kPa. However, candidate species such as tomatoes, tomatillo, squash, pumpkins, melons, sunflower and canola are complicated by the requirement of insect pollinators for successful crop production. Here we show that bumblebees, Bombus impatiens, can function as efficient pollinators in environments with total atmospheric pressures as low as 50 kPa. We found that when bumblebees were exposed to an environment of 50 kPa or higher, they maintained foraging activity levels and a foraging efficiency similar to that exhibited under ambient conditions. However, their activity levels and efficiency were decreased when exposed to an environment lower than 50 kPa. In these experiments, the partial pressure of oxygen was reduced in proportion to the total pressure. When oxygen was returned to an ambient partial pressure of 20kPa at low total pressures, activity improved. Our results demonstrate that bumblebees can function well as pollinators in environments with total atmospheric pressure of 50 kPa or higher, and activity improves at lower levels as long as oxygen levels are adequate. This study is a first step in determining the atmospheric requirements for plant-pollinator interactions in a space station, Moon or Mars greenhouse, which may be essential for long-term space exploration.
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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".